34355 ROLLING BACK MALARIA THE WORLD BANK GLOBAL STRATEGY & BOOSTER PROGRAM ROLLING BACK MALARIA THE WORLD BANK GLOBAL STRATEGY & BOOSTER PROGRAM ROLLING BACK MALARIA THE WORLD BANK GLOBAL STRATEGY & BOOSTER PROGRAM Washington, DC © 2005 The International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org E-mail: feedback@worldbank.org All rights reserved 1 2 3 4 08 07 06 05 The findings, interpretations, and conclusions expressed herein are those of the author(s) and do not necessarily reflect the views of the Executive Directors of the International Bank for Reconstruction and Development / The World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work. 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All other queries on rights and licenses, including subsidiary rights, should be addressed to the Office of the Publisher, The World Bank, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522-2422; e-mail: pubrights@worldbank.org. ISBN-10: 0-8213-6199-6 ISBN-13: 978-0-8213-6199-3 e-ISBN-10: 0-8213-6200-3 DOI: 10.1596/978-0-8213-6199-3 Library of Congress Cataloging-in-Publication Data has been applied for. Cover photo: Suprotik Basu, World Bank Contents Foreword ix Acknowledgments xi Abbreviations and Acronyms xv Executive Summary 3 1 Introduction 11 2 Rationale for a Renewed World Bank Effort on Malaria 13 2.1 Malaria Impairs Economic Growth and Human Development 14 2.2 Malaria Is Preventable and Curable, with Good Returns on Investment 15 2.3 Success Is Possible on a Large Scale 16 2.4 There is a Wide Gap between Knowing and Doing 18 2.5 The World Bank Has Underused its Comparative Advantage in Malaria Control 24 2.6 Clients and Partners Demand a Stronger World Bank Effort 34 3 Priorities and Business Model 37 4 Program of Action 43 4.1 The Program and Deliverables 43 4.2 The International Finance Corporation and the Private Sector in Malaria Control 45 4.3 Cooperation with the Global Fund and Other Major Partners in Malaria Control 50 5 The Malaria Task Force 53 5.1 Objectives 53 5.2 Oversight 54 5.3 Staffing: Secretariat and Regional Clusters 54 5.4 Financing the Malaria Task Force 54 6 Results-Based Monitoring and Evaluation 57 6.1 Results Framework 57 6.2 Steps to a Results-Based Monitoring and Evaluation System 58 6.3 RBM Technical Strategies and Indicators of Population Coverage 59 Appendix 1 Outline of the Monitoring and Evaluation Framework 61 A1.1 Support to Countries 61 A1.2 Support to Regional/Global Partnerships and Collective Efforts 63 A1.3 Strengthening of Bank's Capacity to Contribute Effectively to Malaria Control 64 v vi Rolling Back Malaria Appendix 2 Malarial Case Notification and Coverage with Key Interventions 67 Notes on Available Information 67 Data Tables 1 Malarial Case Notification: Malaria Notifications for the Most Recent Year Information Received 70 2 Malarial Case Notification: Standardized Malaria Notifications and Notification Rates per 1,000, since 1990 80 3 Percentage of Households That Have at Least One Mosquito Net, by Background Characteristics 96 4 Percentage of Households That Have at Least One Insecticide-treated Mosquito Net, by Background Characteristics 100 5 Percentage of Children under Five Years Old That Slept under a Mosquito Net during the Night Preceding the Survey, by Background Characteristics 104 6 Percentage of Children under Five Years Old That Slept under an Insecticide-treated Mosquito Net during the Night Preceding the Survey, by Background Characteristics 110 7 Percentage of Pregnant Women That Slept under a Mosquito Net during the Night Preceding the Survey, by Background Characteristics 116 8 Percentage of Pregnant Women That Slept under an Insecticide-treated Mosquito Net during the Night Preceding the Survey, by Background Characteristics 118 9 Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Once during Pregnancy (Community Level, Prevention or Treatment), by Background Characteristics 120 10 Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Twice during Pregnancy (Community Level, Prevention or Treatment), by Background Characteristics 120 11 Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Once during an Antenatal Visit, by Background Characteristics 122 12 Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Twice during an Antenatal Visit, by Background Characteristics 122 13 Percentage of Children under Five Years Old with Reported Fever in the Two Weeks Prior to the Survey, by Background Characteristics 124 14 Percentage of Febrile Children under Five Years Old That Received Treatment with Chloroquine, by Background Characteristics 132 15 Percentage of Febrile Children under Five Years Old That Received Treatment with Sulfadoxine Pyrimethamine (SP), by Background Characteristics 136 Contents vii 16 Percentage of Febrile Children under Five Years Old That Received Treatment with Any Antimalarial, by Background Characteristics 140 17 Summary of Antimalarial Drug Efficacy Results, Expressed as Treatment Failure 144 Appendix 3 Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam 157 Appendix 4 Strategic Communications 171 Appendix 5 High-Impact Partnerships: Private Sector and Civil Society 175 Appendix 6 Impact of Malaria on Schoolchildren and the Education Sector 179 Notes 181 References 183 Tables, Figures, and Boxes Box 1 Malaria and Selected MDGs 4 Figure 2.1 Profile in Contrasts: The Persistent Burden of Malaria in Africa 17 Table 2.1 Ownership of Insecticide-treated Bed Nets in Malawi, by Income Group 19 Figure 2.2 Access to Antimalarial Treatment 20 Figure 2.3 The Increasing Costs of Commodities for Malaria Control 24 Box 2.1 Putting the Bank's Comparative Advantage to Work: Assisting Countries to Develop Strategies for Financing Treatment with ACTs 25 Figure 2.4 Effectiveness of PRSPs in Addressing Malaria 29 Figure 2.5 Malaria Control Efforts Have Not Benefited from Increased Health Spending in Ghana 33 Table 3.1 The Booster Program for Malaria Control: Matrix of Options for Financing and Instruments 41 Table 4.1 The Booster Program for Malaria: Deliverables 46 Table 5.1 Potential Staffing and Distribution of the Malaria Task Force 55 Foreword Malaria afflicts millions in low- and middle-income countries. For centuries, it has impaired economic growth, child development, learning, health, and productivity on a large scale. The World Bank has worked to reduce the bur- den of malaria, together with many partner agencies. In 1998 the Bank cofounded, with the World Health Organization (WHO), the United Nations Children's Fund (UNICEF), and the United Nations Development Program (UNDP), the global Roll Back Malaria (RBM) Partnership to coordinate and enhance the global fight against malaria. There has been some success, but the pace of work was slower than desired and the scale was less than expected. The world now faces additional challenges, not the least of which is the emergence of drug-resistant forms of malaria. Despite the challenges, there are great opportunities to be explored. We have access to more effective technologies to prevent and cure malaria. Countries are renewing efforts to control the disease, and there is a global consensus that more needs to be done, urgently, on a large scale and in a sustainable way. This report translates our corporate commitment into increased efforts to control malaria. It lays the basis for a Booster Program for Malaria Con- trol, through which the Bank will make an important contribution to malaria control in the years ahead. We will undertake this effort in support of country-led programs and in partnership with community service organ- izations, specialized agencies, and financiers of malaria control at all levels. Consistent with the new Global Strategic Plan of the Roll Back Malaria Partnership, the Bank's work will combine measures to increase coverage of malaria-specific interventions with effective service delivery, broader health-system development, and capacity building across multiple sectors. A multidisciplinary Malaria Task Force prepared this report, together with the Program of Action. The Task Force included staff from across the World Bank Group, with much appreciated contributions from the Interna- tional Finance Corporation. Consultations with country officials helped to shape the results-based and client-oriented approach in this strategy. Many peer reviewers, colleagues in the Roll Back Malaria Partnership Secretariat, and an External Consultative Group provided critical reviews and helpful suggestions. The Roll Back Malaria Department of the WHO provided data ix x Rolling Back Malaria on malaria case notification and coverage with key interventions. We thank all contributors for their time and inputs. Looking to the future, a steering committee of vice presidents in opera- tional and corporate units will provide guidance and support for its imple- mentation. Regional and country teams will lead the implementation of the proposed Booster Program for Malaria Control in a way that is responsive to country needs. We will monitor progress, evaluate impacts, and learn from experiences. Working with multiple partners, the proposed program will boost malaria control, foster economic growth, and accelerate progress toward the Millennium Development Goals, which are central to the Bank's overall mission of reducing poverty. Jean-Louis Sarbib Senior Vice President Human Development Network World Bank Acknowledgments This Global Strategy and Program of Action was prepared with guidance from Jean-Louis Sarbib (Senior Vice President, Human Development Net- work) and substantial contributions from the senior leadership, managers, and staff of the World Bank Group, including Gobind Nankani (Vice Pres- ident, Africa Region), Praful Patel (Vice President, South Asia Region), Jacques Baudouy (Director, Health, Nutrition, and Population), Kei Kawa- bata (Sector Manager, Health, Nutrition, and Population), and Ok Pannen- borg (Senior Health Adviser, Africa Region). Davidson Gwatkin and Keith Hansen made helpful contributions. Members of the Human Development Network Council provided informal advice prior to the Decision Meeting in December 2004. Olusoji Adeyi managed the work program and led the Malaria Task Force. The Malaria Task Force Alexandre Abrantes Sector Manager, AFTH2 Anabela Abreu Sector Manager, SASHD F. Ayo Akala Public Health Specialist, MNSHD Chantal Andriamilamina Investment Officer, IFC Lawrence Barat Consultant Enis Baris Senior Health Specialist, ECSHD Donald Bundy Lead Education Specialist, HDNED Gilles Dussault Senior Health Specialist, WBIHD John Garrison Senior Communications Officer, EXTIA Phil Hay Communications Advisor, HDNOP Stevan Jackson Communications Associate, HDNOP Eva Jarawan Lead Health Specialist, AFTH3 Monique Mrazek Young Professional, IFC Egbe Osifo Sector Manager, WBIHD Mead Over Lead Economist (Health), DECRG Maryse Pierre-Louis Lead Health Specialist, AFTH2 Agnes Soucat Lead Economist, AFTHD Jean Jacques de St. Antoine Lead Operations Officer, AFTH1 xi xii Rolling Back Malaria Yolanda Tayler Lead Specialist, Procurement/Health, OPCPR Denise Vaillancourt Senior Evaluation Officer, OEDSG Secretariat Olusoji Adeyi Coordinator, Global Partnerships for Communicable Diseases, HDNHE Yvette Atkins Program Assistant, HDNHE Suprotik Basu Public Health Specialist, HDNHE (seconded from RBM Secretariat) Pablo Gottret Senior Economist, HDNHE Samantha Naidoo Health Specialist (YP), HDNHE Andreas Seiter Global Pharmaceuticals Industry Fellow, HDNHE Disclaimer: Peer reviewers and members of the External Consultative Group bear no responsibility for the contents of this Global Strategy and Program of Action. Peer Reviewers Internal Benjamin Loevinsohn Senior Public Health Specialist, SASHD Gebre Okubagzhi Senior Health Specialist, AFTH3 Mead Over Lead Economist, DECRG Susan Stout Manager, Results Secretariat Christopher Walker Lead Health Specialist, AFTH1 External Dean Jamison Chair, Institute of Medicine Board on Global Health Adetokunbo Lucas Adjunct Professor, Harvard University. Formerly Director, UNDP/World Bank/ WHO Special Program for Research and Training in Tropical Diseases Acknowledgments xiii Innocent Nyaruhirira Minister of State for HIV/AIDS and Other Epidemics, Rwanda Richard Steketee Formerly Chief, Malaria Branch, United States Centers for Disease Control and Prevention External Consultative Group George Amofah Chair, RBM Partnership Board and Director, Public Health Division, Ghana Health Service James Banda RBM Partnership Secretariat Dennis Carroll USAID Awa Coll-Seck RBM Executive Secretary (former Minister of Health, Senegal) Don de Savigny Swiss Tropical Institute Laurie Garrett Council on Foreign Relations Melville George WHO Representative, Ghana Salim Habayeb WHO Representative, India Chris Hentschel Medicines for Malaria Venture James Herrington United Nations Foundation Gerhard Hesse Bayer Environmental Science Fatoumata Nafo-Traore WHO, Geneva (former Minister of Health, Mali) Frank Nyonator Ghana Health Service Nosa Orobaton John Snow Inc., Uganda Regina Rabinovich Bill and Melinda Gates Foundation Jeffrey Sachs Columbia University Alec Soucy Results Canada Awash Teklehaimonot Columbia University Susan Zimicki Academy for Educational Development The staff of the Office of the Publisher contributed to the quality of this document, especially Dana Vorisek. Abbreviations and Acronyms AAA Analytic and advisory services ACT Artemisinin-based combination therapy CAS Country assistance strategy CDD Community-driven development CSO Civil society organization CQ Chloroquine DALY Disability-adjusted life year DEC Development Economics Vice Presidency DHS Demographic and Health Surveys EMCP Enhanced Malaria Control Project FTE Full-time equivalent GDP Gross domestic product GNP Gross national product GFATM Global Fund to Fight AIDS, Tuberculosis and Malaria HAMSET HIV/AIDS, Malaria, STDs, and TB Control Project HIPC Initiative Highly Indebted Poor Country Initiative IDA International Development Association IFC International Finance Corporation IRS Indoor residual spraying ITN Insecticide-treated bed net LICUS Low Income Countries Under Stress LLIN Long-lasting insecticidal nets M&E Monitoring and evaluation MACEPA Malaria Control and Evaluation Project in Africa MAP Multi-country HIV/AIDS Program MDGs Millennium Development Goals MICS Multiple Indicator Cluster Surveys MTEF Medium-Term Expenditure Framework NGO Nongovernmental organization NMCP National Malaria Control Program PRSC Poverty Reduction Support Credit PRSP (I-PRSP) Poverty Reduction Strategy Paper (Interim Poverty Reduction Strategy Paper) RBM Roll Back Malaria Partnership SP Sulfadoxine pyrimethamine SWAp Sectorwide approach UNDP United Nations Development Program UNICEF United Nations Children's Fund xv xvi Rolling Back Malaria USAID U.S. Agency for International Development VPU Vice presidential unit WHO World Health Organization WHO AFRO World Health Organization Regional Office for Africa WPRO WHO Office for the Western Pacific Executive Summary Introduction This Global Strategy and Booster Program is a significant upgrade of the World Bank's support for malaria control, with emphasis on closing the gap between knowing and doing. It provides the basis for a new Booster Pro- gram for Malaria Control, which is designed to accelerate malaria control and progress toward the Millennium Development Goals (MDGs, box 1). The World Health Organization estimates that there are more than 1.1 million deaths per year from malaria, mostly among children less than five years old (WHO 2002).1 The disease is preventable and curable with available technologies. However, in the absence of strong and sustained malaria control efforts, coverage with effective interventions is low, partic- ularly among the poor. At least 85 percent of deaths from malaria occur in Africa, 8 percent in Southeast Asia, 5 percent in the Eastern Mediterranean region, 1 percent in the Western Pacific, and 0.1 percent in the Americas (Arrow, Panosian, and Gelband 2004). Globally, there are more than 500 million cases of malaria per year; a recent study put the number of cases from a particularly severe form of the malaria parasite, Plasmodium falci- parum, at 515 million in 2002 alone (Snow et al. 2005). Rationale The Global Strategy and Booster Program responds to the inadequacy of global efforts to control malaria and the modesty of the Bank's current efforts relative to its potential. The Bank was a key contributor to recent successes in malaria control, including those in Brazil, Eritrea, parts of 3 4 Rolling Back Malaria Box 1: Malaria and Selected MDGs Goal 2: Achieving universal primary education · Malaria is a leading source of illnesses and absenteeism in school-age children and teach- ers. It adversely affects education by impeding school enrollment, attendance, cognition, and learning. Goal 4: Reducing child mortality · Malaria is a leading cause of child mortality in endemic areas. Goal 5: Improving maternal health · Malaria causes anemia in pregnant women and low birth weight. Goal 6: The combating of HIV/AIDS, malaria, and other diseases · Malaria morbidity and mortality are increasing in Africa. Goal 8: Developing a global partnership for development, including as a target the provision of access to affordable essential drugs · There is a lack of access to affordable essential drugs for malaria. India, and Vietnam. It cofounded and supports the global RBM Partner- ship.2 However, the Bank's efforts have been severely understaffed and underfunded, in terms of both funds committed to malaria control at the country level and the internal budget for the Bank's Malaria Team--a budget that declined during much of the period since RBM was founded in 1998. On balance, the Bank's activities were very useful, but not sufficient for success on a larger scale. The rationale for a stronger World Bank effort includes the following: · Malaria impairs economic growth and human development in many of the World Bank's client countries, particularly in Sub-Saharan Africa. · The disease is preventable, curable, and controllable on a large scale, with good returns on investment. · Malaria control has positive externalities and is a global public good. · At the regional and global levels, there is a wide gap between what is fea- sible and the current level of effort. Despite successes in a few countries, measurable progress in malaria control is well below the 60 percent cov- erage target set by countries and development agencies for 2005 in terms of coverage with preventive and curative interventions.3 Executive Summary 5 · The Bank has the capacity to do a lot more than it has in malaria control, including financing, policy advice, and implementation support. · Clients, partner agencies, independent observers, civil society organiza- tions, and potential cofinanciers are requesting that the Bank play a more decisive role in malaria control. There is much unmet demand for the Bank's financing and advisory services. At the macroeconomic level, annual economic growth in malarious coun- tries between 1965 and 1990 averaged 0.4 percent of gross domestic prod- uct (GDP) per capita, compared with 2.3 percent in the rest of the world, after controlling for the other standard growth determinants used in macro- economic models (Sachs and Malaney 2002). These analyses do not consti- tute proof that malaria is a cause of low incomes and poor aggregate growth, but that the disease must be considered a legitimate contributor (Arrow, Panosian, and Gelband 2004). At the microeconomic level, estimates of the "total" (direct plus indirect) costs of malaria vary: 0.75 percent of gross national product (GNP) in Pakistan (Khan 1966); 7 percent of household income in Malawi (Ettling et al. 1994); 9­18 percent of annual income for small farmers in Kenya, and 7­13 percent in Nigeria (Leighton and Foster 1993). One multicountry study attempted an Africa-wide estimate of total costs of malaria based on extrapolations from case studies of areas in Burk- ina Faso, Chad, the Democratic Republic of Congo, and Rwanda. The totals reported translated to 0.6 percent of total Sub-Saharan African GDP (Shephard et al. 1991). Malaria control gives good value for money. In Vietnam, at a cost to the government of about US$11 (1998 costs) for a clinic visit plus drugs to treat an episode, the direct costs saved were about US$9.5 million, which is about twice the amount spent on malaria control each year. To this is added about US$14 million in reduced out-of-pocket health care costs to households (Laxminarayan 2004). In Brazil, compared to what would have happened in the absence of the malaria control program, nearly 2 million cases of malaria and 231,000 deaths were prevented. The overall cost-effectiveness was US$2,672 per life saved, or US$69 per disability-adjusted life year (DALY),4 which compares favorably to many other disease control interventions (Akhavan et al. 1999). Other sources indicate that insecticide treatment of existing mosquito nets costs US$4­10 per DALY saved, providing nets and retreatment costs US$19­85 per DALY saved, and intermittent presump- tive treatment of pregnant women through existing prenatal services costs US$4­29 per DALY saved (Goodman, Coleman, and Mills 1999). 6 Rolling Back Malaria Priorities and Business Model The Bank's priority is enabling countries to achieve and sustain large-scale impact in malaria control. More specifically, the Bank will support countries to develop and implement programs to (i) cost-effectively reduce morbidity, productivity losses in multiple sectors, and mortality due to malaria, partic- ularly among the poor and vulnerable subgroups such as children and preg- nant women; and (ii) address the challenges of regional and global public goods. The Bank will achieve the stated priorities through a new business model that combines an emphasis on outcomes with flexibility in approaches and lending instruments.5 Products and services will be tailored to different client segments in a way that meets their needs and maximizes the institution's comparative advantages. This approach is consistent with the new Global Strategic Plan of RBM (RBM 2004a). The Bank participated actively in the formulation of that strategy. The Booster Program for Malaria Control In the short to medium term, a new Booster Program for Malaria Control will provide increased financing and technical support to accelerate pro- gram design and implementation, increase coverage, and improve outcomes more rapidly than in the recent past. The Booster Program for Malaria Control will be global in scope and consist initially of an intensive effort over a five-year period. It may include one or more Horizontal Adaptable Programs6 at the global or regional level, covering many countries, with emphasis on country ownership, measurable outcomes, and rigorous appli- cation of epidemiology. While the immediate objectives are fixed--increas- ing coverage, improving outcomes, and building capacity--the means will be flexible. The financial commitment is subject to consideration by the Board of Executive Directors of the World Bank. The new business model and the Booster Program for Malaria Control take into account lessons learned from successful malaria programs and expe- riences from the Multi-country HIV/AIDS Program (MAP). They consti- tute a substantial departure from the Bank's previous approach to malaria control. There is a need for decisive action on a large scale in order to achieve impact. Experience of the past five years shows that a pledge of com- mitment, such as that made by the Bank in Abuja in 2000, with neither a Executive Summary 7 clearly funded program for malaria control nor the internal budget to ensure that the Bank's malaria team can function effectively, does not lead to success on a large scale. A different and more robust approach is needed for success. Drawing on lessons of the past five years, Bank management is designing a program for Board approval to ensure that the Bank responds to country demands with flexibility and speed. On the basis of initial demand from clients, the working assumption is that a total commitment of US$500 mil- lion to US$1 billion is feasible over the next five years. The Bank will mobi- lize financial and technical resources from within and outside the institu- tion, including the public and private sectors, to stimulate the production of commodities such as insecticide-treated bed nets (ITNs) and antimalarial drugs; lower taxes and tariffs on such commodities; improve and maintain long-term commitment to malaria control by governments and civil society groups; and build public-private partnerships for program design, manage- ment, and evaluation. Several key partners have expressed interest in a col- laborative and stronger effort. The International Finance Corporation (IFC), which has a particularly strong comparative advantage in working with the private sector, will play an important role in this enhanced effort by the World Bank Group. Significant cofinancing will be leveraged by a demonstration of the Bank's own commitment up front, together with the emphasis on measurable results. Crucially, the Bank's approach will be proactive while respecting and supporting country leadership and ownership. It will complement the Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM), WHO, United Nations Children's Fund (UNICEF), the Bill and Melinda Gates Founda- tion, and others in ensuring sufficient financing as well as technical and implementation support for effective malaria control. Henceforth, malaria control will be mainstreamed into the Poverty Reduction Strategies and large sector-development programs that emphasize outcomes. The high cov- erage rates achieved in most countries would be sustained through combina- tions of domestic financing, programmatic operations, and budget support on a case-by-case basis. High coverage with preventive interventions will decrease the burden of disease and the pressures on health services. Countries will have three main options for accessing more funds and technical support from the Bank. These options, which are not mutually exclusive, are outlined below. 8 Rolling Back Malaria · Enhancing PRSCs and health SWAps to support malaria control. In this option, the Booster Program for Malaria Control will be used to enhance Poverty Reduction Support Credits (PRSCs) and sectorwide approaches (SWAps) for health to include stronger malaria control programs, with additional financing when required, technical support, and results-based monitoring and evaluation. The recently approved PRSC for Rwanda is a useful example. It includes technically sound malaria control activities within the health sector plan of work, including the monitoring and eval- uation matrix and the Medium-Term Expenditure Framework (MTEF). Beyond the health sector, PRSCs provide opportunities for cross-sectoral work on malaria through, for example, the education, agriculture, envi- ronment, and transport sectors. · Malaria Control Projects at the country or subregional level. Based on coun- try requests, the Booster Program for Malaria Control will support Malaria Control Projects, as in the successful examples of Brazil, Eritrea, India, and Vietnam. Project design and objectives will depend on the local context in terms of government policy, disease burden and distribution, the nature of the vector (the mosquito), and local manage- ment capacity. Countries may choose to use community-driven devel- opment (CDD) approaches, depending on the context. These Malaria Control Projects will supplement, not disrupt, systemic health sector development programs. Strengthening the health infrastructure will facilitate malaria control and help to sustain the gains to be achieved under the Booster Program for Malaria Control. For Low Income Countries Under Stress (LICUS) and postconflict countries, special implementation arrangements may include more extensive contracting of civil society organizations (CSOs) for service delivery, combined with technical and operational support from agencies such as WHO and UNICEF. · Combined HIV, Tuberculosis, and Malaria Control Projects. Another option is to develop and implement operations covering HIV, tuberculosis, and malaria, such as those in Eritrea and Angola. In this option, the Booster Program for Malaria Control will support broader operations covering several disease control objectives in a way that is consistent with medium- to long-term sectoral and multisectoral development. Implementation of the Booster Program implies an increase in the deliv- erables to be planned and achieved by Bank regional vice presidencies, Executive Summary 9 country units, and sector units working on malaria control from fiscal 2006 onwards. The Booster Program will support operations at the subregional and country levels. Depending on specific contexts, the operations will include proactive engagement of CSOs and the private sector to the extent that is compatible with their comparative advantages. Such engagement may include contracting or financing of activities to be undertaken by CSOs and the private sector. In order to promote sustainability and mitigate the risks of distortions, the Booster Program will supplement programmatic approaches such as health SWAps and PRSCs. The Bank would seek cofi- nancing or performance-based buydowns from partners, including but not limited to foundations and multinational corporations. The Malaria Task Force and Steering Committee The Malaria Task Force is a Bank-wide group drawn from corporate units, networks, operational vice presidential units (VPUs), and the IFC. It will support the Bank's country and regional teams to (i) increase rapidly the scale and impact of the Bank's support for malaria control at the country level and (ii) improve the institutional knowledge base regarding the eco- nomics of malaria at the household, sectoral, and macro levels, and channel that knowledge into the Bank's work on poverty reduction. A high-level Steering Committee will provide institutional oversight and guidance. The Steering Committee will include the Senior Vice President and Head of the Human Development Network; the Regional Vice Presidents for Africa, South Asia, East Asia and the Pacific; the Vice President for Operations Pol- icy and Country Services; and the Senior Vice President and Chief Econo- mist. The Poverty Reduction and Economic Management Network will provide guidance on the integration of malaria control into Poverty Reduc- tion and Strategy Papers (PRSPs). Subject to satisfactory performance and resource availability, the Bank will continue its highly selective support for partnerships working on product development and applied research that are relevant to malaria control. By the end of the fifth year of the Booster Program for Malaria Control, most of the eligible countries are expected to have achieved significant increases in coverage of essential interventions. CHAPTER 1 Introduction The purpose of this Global Strategy and Booster Program is to translate the World Bank's corporate commitment into a serious effort to close the gap between knowing and doing in malaria control. Implementation of the Global Strategy and Booster Program will increase rapidly the scale and impact of the Bank's support for malaria control at the country level, with a view to reducing the burden of economic loss, impaired development, pre- ventable illnesses, and deaths due to malaria. This effort will facilitate the achievement of results at the country, regional, and global levels, consistent with the emerging themes of the International Development Association (IDA), including achievement of the Millennium Development Goals (MDGs), collaboration with relevant partners, results measurement, and attention to communicable diseases: "IDA will continue its work to combat these diseases and mitigate their effects, both at the country level through disease-specific interventions and support for health systems strengthening, and across countries through regional projects, as well as through support for international initiatives" (IDA 2005). Following this introduction, the rationale for a major World Bank effort on malaria control is outlined in section 2. Section 3 presents the priorities and business model for the future. This is followed by the Program of Action in section 4, which includes the options in financing and instruments for assisting the countries. Section 5 is on the Malaria Task Force, a Bank- wide group that will be charged with implementation of the Global Strat- egy and Booster Program. Finally, section 6 presents a results-based moni- toring and evaluation framework and draft plan. The appendices provide details and context for much of the foregoing discussions. 11 12 Rolling Back Malaria The Global Strategy and Booster Program has a dual audience. The pri- mary audience is internal. It includes the corporate, regional, country, and sector units with direct or indirect responsibilities for, or influence on, the Bank's support for malaria control. This internal audience will find the Global Strategy and Booster Program useful in the following ways: placing the malaria control agenda within the broader efforts of poverty reduction, health, and economic development; defining the unmet needs at the coun- try, regional, and global levels; and assisting countries to develop and imple- ment effective programs. The secondary audience is external, including country clients (represented by ministries of finance, planning, economic development and health, malaria control programs, research institutions, the commercial and private sectors, civil society groups, and so forth); mem- bers of the RBM Partnership,7 including regional and country officers in the major multilateral and bilateral organizations and local and international nongovernmental organizations; and financiers of health and malaria con- trol programs. These external clients and partner agencies will find the Global Strategy and Booster Program useful in better understanding the World Bank's work on malaria. This will enable more effective collaboration among the Bank and other institutions in malaria control. CHAPTER 2 Rationale for a Renewed World Bank Effort on Malaria The Global Strategy and Booster Program is a response to the inadequacy of efforts to control malaria and the inadequacy of the Bank's current efforts relative to its potential. The Bank was a key contributor to recent successes in malaria control, including those in Brazil, Eritrea, parts of India, and Vietnam. It cofounded and supports the global Roll Back Malaria Partner- ship. However, the institution's efforts have been severely understaffed and underfunded, in terms of both funds committed to malaria control at the country level and the internal budget for the Bank's Malaria Team--a budget that declined during much of the period since 1998.8 On balance, the Bank's activities were useful but not sufficient for success on a larger scale. A stronger World Bank effort for malaria is needed on the following grounds: · Malaria impairs economic growth and human development in many of the World Bank's client countries, particularly in Sub-Saharan Africa. · Malaria is preventable, curable, and controllable on a large scale, with good returns on investment. · Malaria control has positive externalities and is a global public good. · At the regional and global levels, there is a wide gap between what is fea- sible and the current level of effort. Despite successes in a few countries, measurable progress in malaria control is well below the 60 percent cov- erage targets set by countries and development agencies for 2005 in terms of coverage with preventive and curative interventions.9 13 14 Rolling Back Malaria · The Bank has the capacity to do a lot more than it has in malaria control, including financing, policy advice, and implementation support. · Clients, partner agencies, independent observers, civil society organiza- tions, and potential cofinanciers are requesting that the Bank play a more decisive role in malaria control. There is much unmet demand for the Bank's financing and advisory services. 2.1 Malaria Impairs Economic Growth and Human Development Malaria impairs economic development and health in many of the World Bank's client countries, particularly in Sub-Saharan Africa (Chima, Good- man, and Mills 2003; Ettling et al. 1994; Ettling and Shepard 1991; Shep- ard et al. 1991). For many low-income countries, malaria control is essen- tial for progress toward achieving the MDGs, which the Bank has adopted as a corporate priority. The link between malaria and economic develop- ment is bidirectional; impaired health from malaria restrains economic development, whereas economic development, by improving living condi- tions and access to both effective prevention and treatment, reduces the ill- nesses from malaria. Malaria potentially affects both the volume and the productivity of inputs. At the macroeconomic level, annual economic growth in malarious coun- tries between 1965 and 1990 averaged 0.4 percent of GDP per capita, com- pared with 2.3 percent in the rest of the world, after controlling for the other standard growth determinants used in macroeconomic models (Sachs and Malaney 2002). This analysis does not constitute proof that malaria is a cause of low incomes and poor aggregate growth, but that the disease must be considered a legitimate contributor to these failings (Arrow, Panosian, and Gelband 2004). At the microeconomic level, estimates of the total (direct plus indirect) costs of malaria vary: 0.75 percent of GNP in Pakistan (Khan 1966); 7 percent of household income in Malawi (Ettling et al. 1994); 9­18 percent of annual income for small farmers in Kenya, and 7­13 per- cent in Nigeria (Leighton and Foster 1993). One multicountry study attempted an Africa-wide estimate of total costs of malaria based on extrap- olations from case studies of areas in Burkina Faso, Chad, the Democratic Republic of Congo, and Rwanda. The totals reported translated to 0.6 per- cent of total Sub-Saharan GDP (Shephard et al. 1991). Rationale for a Renewed World Bank Effort on Malaria 15 2.2 Malaria is Preventable and Curable, with Good Returns on Investment There is no accurate count of the global toll of illnesses and deaths from malaria. This is due to multiple factors, including weaknesses in data col- lection and reporting systems, inaccurate diagnoses that may result in over- or underreporting and, for many people in malaria-endemic areas, lack of access to skilled workers who can make accurate diagnoses. WHO esti- mated that there were 1,124,000 deaths due directly to malaria in 2002, of which about 970,000 were in Africa (WHO 2002). Globally, there are more than 500 million cases of malaria per year; a recent study put the number of cases from a particularly severe form of the malaria parasite, Plasmodium fal- ciparum, at 515 million in 2002 alone (Snow et al. 2005). The disease is preventable and easy to cure with available technologies. RBM and WHO support an evidence-based consensus on a combination of preventive and curative measures that include integrated vector manage- ment--insecticide-treated bed nets (ITNs) and curtains, indoor residual (house) spraying with WHO-approved insecticides where the pattern of transmission makes such measures appropriate, environmental modifications to eliminate breeding sites of mosquitoes, and biological control (e.g., bacte- ria, fungi, nematodes, copepods, and larvicidal fish); intermittent preventive treatment in pregnancy; and prompt treatment with effective drugs (RBM 2004a, WHO 2004b, WHO 2004c). In each context, the priorities and appropriate combination of interventions will depend on factors such as the epidemiology of malaria, the type and behavior of the mosquito, local cus- toms and preferences, the susceptibility of the malaria parasite to different drugs, feasibility of the logistics required, the quantity and quality of human resources for malaria control, and affordability. A full documentation of these factors is beyond the immediate scope of this strategy but is available from specialized texts, journals, project reports, and the website of WHO (http://www.who.int). Effective malaria control is complex and challenging. In the absence of strong and sustained malaria control efforts, coverage with effective interventions is low, particularly among the poor in most of the affected countries. Estimates suggest that malaria accounts for up to 40 per- cent of all public expenditures on health and 20­50 percent of hospital admissions in many settings (WHO and UNICEF 2003). In 1954 the Pan American Sanitary Conference adopted a continental plan to eradicate malaria from the Americas. In 1955 this plan was extended 16 Rolling Back Malaria to the world by the World Health Assembly. In 1956, the Sixth Expert Committee formulated a strategy for eradicating malaria (WHO 1957). The goal of malaria eradication was understood by the committee as a prob- lem of economic and political development, as much as of public health (Packard 1998). Malaria was eliminated in Europe, North America, and parts of other continents through deliberate programs of mosquito control and clinical treatment, as well as through generally improved social and liv- ing conditions (see figure 2.1). The commitment and persistence behind eradication10 efforts elsewhere were never applied in Africa's highly endemic areas (Breman, Egan, and Keutsch 2001). Taking into account lessons learned during the eradication campaigns, in 1969 the World Health Assembly reaffirmed that eradication was the ultimate goal but stated that, in regions where eradication was not yet feasible, control11 of malaria should be encouraged and may be a necessary and valid step toward that goal (WHO 1969). The recent efforts to control malaria fall short of agreed goals in Africa. Today, at least 85 percent of deaths from malaria occur in Africa, 8 percent in Southeast Asia, 5 percent in the Eastern Mediterranean region, 1 percent in the Western Pacific, and 0.1 percent in the Americas. The poor bear a disproportionate burden of malaria; while the average total cost burden of malaria was 7.2 percent of household income, the total cost burden for very poor households was much higher at a potentially catastrophic 32 percent of annual income in Malawi (Ettling et al. 1994). Despite the fact that Africa bears the largest share of the malaria burden, the problem is not exclusive to Africa. For example, parts of Southeast Asia bear high burdens of the dis- ease. In addition, Southeast Asia has been the epicenter of drug-resistant malaria (Arrow, Panosian, and Gelband 2004). These drug-resistant forms later spread elsewhere. Consequently, good malaria control in Southeast Asia and other places with similar patterns of malaria would benefit not only residents of these regions but, by reducing the emergence of drug-resistant forms of malaria, would benefit Africa as well. 2.3 Success is Possible on a Large Scale Although large-scale successes in malaria control have been rare in the low- and middle-income countries, the World Bank was a key player in recent large-scale successes, as in Brazil, Eritrea, several states in India, and Viet- Rationale for a Renewed World Bank Effort on Malaria 17 Figure 2.1: Profile in Contrasts: The Persistent Burden of Malaria in Africa Deaths due to malaria: annual mortality rates since 1900 250 200 150 population 100 100,000 Per 50 0 1900 1930 1950 1970 1990 1997 World minus Sub-Saharan Africa World Sub-Saharan Africa Source: WHO 1999. nam (see appendix 3 for details). In Vietnam, at a cost to the government of about US$11 (1998 costs) for a clinic visit plus drugs to treat an episode, the direct costs saved were about US$9.5 million, which is about twice the amount spent on malaria control each year. To this is added about US$14 million in reduced out-of-pocket health care costs to households (Laxmi- narayan 2004). In Brazil, compared to what would have happened in the absence of the malaria control program, nearly 2 million cases of malaria and 231,000 deaths were prevented. The overall cost-effectiveness was US$2,672 per life saved or US$69 per disability-adjusted life year (DALY), which compares favorably with many other disease control interventions (Akhavan et al. 1999). Other sources indicate that insecticide treatment of existing mosquito nets costs US$4­10 per DALY saved, providing nets and retreatment costs US$19­85 per DALY saved, and intermittent presump- tive treatment of pregnant women through existing prenatal services costs US$4­29 per DALY saved (Goodman, Coleman, and Mills 1999). The Bank responded to requests for malaria-specific investment projects in some countries, such as in Eritrea and India. This combination of coun- try commitment with Bank support has resulted in measurable success. For example, through the US$40 million IDA credit for the HIV/AIDS, Malaria, STDs, and TB Control Project (HAMSET) in Eritrea, with tech- 18 Rolling Back Malaria nical support from and partnership with the U.S. Agency for International Development (USAID), Eritrea has reduced malaria morbidity and mortal- ity for four consecutive years and has seen the use of ITNs rise from 20 per- cent in 2000 to 58.5 percent in 2002. India's Enhanced Malaria Control Project, which the Bank supports, started in 1997. Reported cases of malaria declined by 93.3 percent, 80.8 percent, and 40.6 percent for the states of Maharashtra, Gujarat, and Rajasthan, respectively, from 1997 to 2002.12 Key factors in these success stories include a results-oriented approach; local leadership and good management capacity; explicit prioritization of malaria control by the government; levels of financing that were sufficient to achieve impact; evidence-based decision making to align interventions with the local patterns and causes of disease transmission; flexibility in the mech- anism of Bank support; effective systems for delivering commodities; and proactive Task Teams from the Bank. These factors may be adapted for use elsewhere, and are taken into account in the new business model, priorities, and program of action. 2.4 There is a Wide Gap between Knowing and Doing The use of ITNs has major effects on malaria and child mortality. When ITN coverage is over 60 percent, there may be up to a 20 percent reduction in all-cause mortality among children under five years of age, a 50 percent reduction in clinical malaria episodes, and widespread uptake confers pro- tection on nonusers over time. When ITN coverage in Tanzanian infants increased from 10 to more than 50 percent, child survival increased by 27 percent and anemia decreased by 63 percent (Lengeler 2001). Despite the efforts and successes in a few countries, measurable progress in malaria control is well below the 60 percent coverage targets set by coun- tries and development agencies for 2005 in terms of coverage with preven- tive and curative interventions. This is particularly true in Africa, where malaria control efforts remain patchy in most of the severely affected coun- tries. In many of them, there are indications of a real or potential increase in the burden of malaria, partly due to increases in drug-resistant forms of the malaria parasite. In Ghana, for example, "malaria continues to be a lead- ing cause of morbidity and mortality. There are high levels of chloroquine resistance in the country, resulting in a change in drug policy to more expensive drugs. Coupled with the low coverage of ITNs, a major issue will Rationale for a Renewed World Bank Effort on Malaria 19 be the need to subsidize both the cost of ITNs and the drug to make them more affordable to government and to the people" (Ghana Ministry of Health and Health Partners 2004). According to the report of the External Evaluation of Roll Back Malaria (Malaria Consortium 2002): "Due to inadequacies in the systems available for monitoring and evaluation (M&E), it is not possible to know with any certainty how the malaria burden has changed during the first three years of RBM. However, anecdotal evidence and the strong consensus among experts suggest that, at the very least, the malaria burden has not decreased. What is more likely, and believed to be the case by those involved, is that malaria has got[ten] somewhat worse during this period." While current data on coverage with RBM-endorsed interventions are sparse, the most recent official data from WHO indicate that, in many malaria-endemic countries, national coverage with key interventions is well below agreed tar- gets of 60 percent for 2005 (WHO and UNICEF 2005) and the poor have much less access to effective interventions than others (table 2.1 and figure 2.2). At the same time, high coverage rates in some districts signal what can be achieved in a relatively short period when programs are based on prior- ity interventions and use a results-based approach.13 Treatment, when prompt and effective, is associated with improved out- comes, even in very poor settings. For example, teaching mothers to pro- vide prompt chloroquine treatment for fevers at home resulted in a 40 per- cent reduction in under-five mortality in Tigray, Ethiopia (Kidane and Morrow 2000). However, the poor also have less access to any treatment, as shown in figure 2.2, not to mention effective treatment. The challenge of drug-resistant malaria One of the reasons for the resurgence and increased burden of malaria is the development of resistance to traditional first-line antimalarial treatments such as chloroquine (CQ) and sulfadoxine pyrimethamine (SP, or Fansidar) Table 2.1: Ownership of Insecticide-Treated Bed Nets in Malawi, by Income Group BED NET OWNERSHIP BOTTOM 28% TOP 35% % of households with at least one bed net 5.1 25.6 % of households with at least one ITN 0.9 5.4 Source: Gwatkin 2004. 20 Rolling Back Malaria Figure 2.2: Access to Antimalarial Treatment 90 80 five 70 treatment under 60 50 40 children of antimalarial 30 20 10 Percent receiving 0 Guinea- Cameroon Côte Niger Senegal Congo, Gambia Chad Burundi Rwanda Bissau d`Ivoire Dem. Rep. of Richest 20% Poorest 20% Source: Worrall, Basu, and Hanson 2003. by Plasmodium falciparum, the parasite that causes a severe form of malaria. Faced with increasing resistance to these first-line treatments, countries are revising their antimalarial drug policies and exploring alternative treatment options. Experience in some areas of Southeast Asia has shown combination therapy containing artemisinin-based drugs, so-called artemisinin-based combination therapy (ACT), to be successful in treating and reversing the spread of drug-resistant malaria. Based on such evidence, WHO has revised its guidance to countries to promote the use of ACT when a new drug pol- icy is required. There is a dual crisis in responding to drug-resistant malaria. First, at US$1­2 per course of treatment, ACTs are 10­20 times as expensive as the failed or failing chloroquine. Second, there is a potential biomedical crisis. Since the artemisinin-based drugs are the only first-line antimalarial drugs appropriate for widespread use that still work against chloroquine-resistant malaria parasites, malaria's toll could rise even higher if resistance to artemisinin were allowed to spread. The challenge is thus twofold: to facil- itate the widespread use of artemisinins where appropriate while preserving their effectiveness for as long as possible. Arrow, Panosian, and Gelband (2004) asserted that preserving the effectiveness of ACTs means delaying the development of resistance, which creates a benefit for all--"a global public good." In July 2004, the Institute of Medicine (of the National Acad- emies in the United States) published a report recommending a sustained global ACT subsidy, in which artemisinins are coformulated with other Rationale for a Renewed World Bank Effort on Malaria 21 antimalarials, as the most economically and biomedically sound means to meet this dual challenge. Without external funding, neither governments nor consumers, who bear most of the cost, can afford ACTs at current prices. The Institute of Medicine report identified the International Devel- opment Association (IDA) of the World Bank Group as a potential financier of an estimated annual subsidy of US$300­500 million (Arrow, Panosian, and Gelband 2004). As of March 2005, the Bank was examining the "global public good" rationale for a high-level subsidy through a study financed by the RBM Secretariat as part of the work program of RBM's Finance and Resource Working Group. Global estimates of financing needs International estimates provide a range of what may be needed to achieve the Abuja Targets and MDGs, with the caveat that many estimates are based on epidemiological scenarios rather than scenarios that take account of con- straints on implementation. Country-specific estimates of financing require- ments are required to obtain a more robust picture. Furthermore, since the financial burden of malaria control falls mostly on the household level in Africa, the manner in which malaria control funding should be targeted remains a topic for debate (Jowett, Miller, and Mnzava 2000; WHO 2002). Estimates of the financing needs for worldwide malaria control vary, but all estimates indicate that more money is needed, even after taking into account grants from the GFATM, which had committed a total of US$904.5 million as of December 2004 (in two-year grants, up to mid- 2006). The rising cost of treatment has added to what was already a difficult financial situation. In 2004, the Copenhagen Consensus estimated that US$1­3 billion per year is needed to halve deaths from malaria worldwide by 2010 (Mills and Shillcutt 2004). In 2000, The Abuja Declaration called for the allocation of new resources of at least US$1 billion per year, from African countries and their development partners, to halve malaria morbid- ity and mortality in Sub-Saharan Africa by 2010. Addressing both disease-specific interventions and health system support The financial constraint remains an urgent and key factor, but not the only key factor, holding back malaria control in most countries. As with broader 22 Rolling Back Malaria health and development issues, additional financing is likely to make a dif- ference when combined with sound policies, good governance, effective implementation arrangements that suit the local context (World Bank 2002; World Bank 2004a), technical rigor, better use of existing human resources, and the concurrent improvement of human resource capacity in the coun- tries (Chen et al. 2004). Weak health systems need to be improved, both for sustainability and to ensure that a more proactive effort to control malaria does not distort the health system. Efforts to enhance PRSCs and SWAps for malaria control will take account of systemic constraints in the use and development of human resources, drug procurement and management, planning and budgeting, and monitoring and evaluation. Immunization campaigns and maternal and child health services provide opportunities for integration of malaria control into routine health services. However, health system constraints alone justify neither inaction nor a continuation of the inadequate level of the Bank's commitment to malaria control. There is evidence that, in disease control and public health, major interventions have worked on a large scale even in poor settings with grind- ing poverty and weak health systems (Levine et al. 2004). At the same time, there is evidence that a persistent failure to achieve improvements in health outcomes could lead to a backlash against broader efforts to reform the health system, as in Zambia, where "continued deterioration of health con- ditions during the mid-1990s was a key factor in the Government's 1998 back-pedaling on the reform agenda" (World Bank 2003b, p. 10), along with local perceptions that there was too much emphasis on process and too little on content. It is crucial to address the content, not only the process, of programmatic operations in order to achieve measurable improvements in health outcomes. An effective approach needs to be more robust than a mutually exclusive framework of either health system strengthening versus disease control pro- grams, or horizontal versus vertical programs. The Booster Program would support an effective combination of both as appropriate. Malaria control may be thought of as a diagonal program that needs elements of horizontal and vertical approaches, with the balance dependent on the context. Growing pressures on scarce resources The pressures on governments to finance treatment for malaria increased dramatically from 2004 to 2005 due to drug resistance and the emergence Rationale for a Renewed World Bank Effort on Malaria 23 of new preventive technologies. Increased resistance of the malaria parasite to long-standing treatment has forced countries to shift first-line treatment for malaria from drugs that cost US$0.05­0.10 per treatment course (such as CQ and SP [Fansidar]) to ACTs that cost up to US$2 per treatment course. Funds available to clients, including those from the GFATM, are insufficient to maintain treatment coverage. Clients have requested sub- stantial financing from the Bank, not only to purchase the drugs, but also to increase the capacity of health systems to cope with the increased demands on service delivery. The costs of prevention are increasing as well. ITNs are clearly effective in preventing malaria when deployed on a significant scale. A key bottleneck to increasing net use, however, is that nets have to be retreated with insec- ticide every six months in order to maintain their effectiveness. In Sub- Saharan Africa of the average 13 percent of the population covered by ITNs, retreatment rates were generally under 4 percent (WHO and UNICEF 2003). In response to this problem, WHO prompted the indus- try to develop long-lasting insecticidal nets (LLINs), which are ready-to- use, factory-pretreated nets that require no further treatment during their expected lifespan of four to five years. According to the WHO, "this tech- nology obviates the need for re-treatment (unlike conventional ITNs, LLINs resist washing) and reduces both human exposure (at any given time, most of the insecticide is hidden and not bioavailable) and the risk of envi- ronmental contamination" (WHO 2004a). This development, however, comes at an increased upfront price: about US$6, compared to approxi- mately US$3 for a conventional ITN (see figure 2.3), though the costs over time may be lower than a conventional ITN given that retreatment costs would not be incurred by users of LLINs. The GFATM is currently the major financier of ACTs. However, the short term of GFATM grants (two years in a first instance, with a possibil- ity of extension to five years) puts vulnerable countries, governments, and populations in a precarious position should funds not be available beyond two years. Furthermore, manufacturers of ITNs and ACTs have been either unwilling or unable to produce sufficient quantities of either com- modity, largely as a result of the uncertain financial landscape for malaria control and the absence of predictable, large-scale demand. Although the GFATM has approved some grants for this purpose, the way they are dis- bursed means that the process is too slow and too fragmented to give firms reassurance, leading to more calls for a commitment from an organization 24 Rolling Back Malaria Figure 2.3: The Increasing Costs of Commodities for Malaria Control Unit cost increases for malaria prevention and treatment 7 6 5 4 US$ 3 2 1998 (unit cost) 1 2004 (unit cost) 0 Treatment Prevention Source: RBM 2004b. such as the World Bank to address the issue through complementary financing, and a centralized global purchasing body to coordinate the orders (Economist 2004). The Bank Group has a combination of compara- tive advantages, including a medium- to long-term financial horizon, pro- curement expertise, experience with innovative financing instruments, and international credibility among pharmaceutical manufacturers to work with governments, the private sector, CSOs, and multiple agencies (see box 2.1). The Bank's Malaria Team has received requests from clients and inde- pendent agencies to engage more strongly in helping countries meet the need for effective treatment of malaria. 2.5 The World Bank Has Underused its Comparative Advantage in Malaria Control There are publicly available reports and perceptions that the Bank (i) has not kept its promise on malaria control; (ii) was aloof from the needs and operational realities of those who implement malaria control programs at the country level; and (iii) was insufficiently focused on outcomes in terms of reducing the burden of illness, productivity losses, and preventable deaths. Many of these reports and perceptions have merit. Rationale for a Renewed World Bank Effort on Malaria 25 Box 2.1: Putting the Bank's Comparative Advantage to Work: Assisting Countries to Develop Strategies for Financing Treatment with ACTs Many countries in the Bank's Africa Region are facing a combination of finance-related issues around the shift in first-line treatment to ACTs, including but not limited to the inadequacy of current funds for ACTs and concerns in client governments about financial sustainability given growth projections. Planning and budgeting officials are skeptical about epidemiologically driven cost estimates, while program-based cost projections remain unclear. In response, the Bank and USAID, through the "Partners for Health Reform Plus Project," are now working together in Tanzania and the Democratic Republic of Congo to address their respective concerns around a shift to ACTs. The studies will address both incremental resource requirements and gains in health outcomes. The findings will help to inform min- istries of health and finance about the potential for increased expenditures and the benefits such expenditures would buy in the short and medium term. In the Democratic Republic of Congo, this work will inform directly the preparation of the proposed Health Rehabilitation Project, which will support malaria control and help close the gap between available financing and what is required for impact. It may also assist the coun- try team in its efforts to secure project cofinancing, by articulating clearly what outcomes an increased investment might purchase. In Tanzania, this work will inform the discussions with Ministries of Health and Finance on whether or not the new first-line treatment should be supported, given the medium- to long- term financial implications. The proposed work could help inform Ministry of Health decisions on intrasectoral allocations with evidence on the cost-effectiveness of ACT expenditures, given the burden of disease and the longer-term affordability of financing such costs. Since September 2004, this type of assistance has been requested by Benin, Burkina Faso, Kenya, Rwanda, and Senegal. While many more requests are expected, the Bank's capacity to respond to this demand has already been exceeded due to the inadequacy of current internal budgets. The World Bank is capable of doing a lot more than it has on malaria control. Much of the Bank's comparative advantage in malaria control lies in the combination of its cross-sectoral capacity in analytical work, advisory services, financing, operational support, and convening power across multi- ple sectors that contribute to or benefit from malaria control. The Bank has strategic access to, and support for, the following: · Country-led and country-owned processes for developing Poverty Reduction Strategies, Medium-Term Expenditure Frameworks, and debt relief agreements under the Highly Indebted Poor Country Initiative (HIPC Initiative) 26 Rolling Back Malaria · Planning and budgeting at the country level, with attention to opera- tional constraints and linkages to expected outcomes · Coformulation of sector-wide approaches and budget support to address systemic constraints within sectors (particularly health), and across mul- tiple sectors · Financing or cofinancing (as in the successful efforts in Brazil, Eritrea, India, and Vietnam). External evaluation of Roll Back Malaria and implications for the World Bank In 2002, the RBM Partnership underwent an External Evaluation as a requirement for continued funding from the British government's Depart- ment for International Development and Development Grant Facility financing from the Bank.14 In summary, the evaluation concluded that while the RBM Partnership had made impressive gains in global advocacy, it had not succeeded in making large-scale impacts at the country level in terms of reducing morbidity and mortality from malaria (Malaria Consor- tium 2002). The evaluation team found that the Bank could be playing a more active role to fulfill its responsibility in RBM. The evaluation team identified a tension between two views: whereas many in the RBM Partnership argued that funding was a major problem holding back malaria control, the World Bank argued that money was not the rate-limiting factor. The Bank cited as rate-limiting factors limited absorptive capacity and poor prioritization of malaria control, as evidenced by significant unspent monies at the close of many IDA-financed operations. The RBM evaluation team cited difficulties experienced by the Bank's clients in navigating and understanding SWAps, Poverty Reduction and Strategy Papers (PRSPs), and HIPC debt relief financing modalities, as well as confusion in the Partnership about whose responsibility it was to channel funds from these existing opportunities to malaria control efforts (the country, the Bank, other RBM partners, or another?). The evaluation team noted that "the Bank's presumed compara- tive advantage in development policies, sector-wide planning and budgeting was inaccessible to the broader RBM partnership" due to the complexity of its processes, and due to many partners' lack of familiarity with those processes. The reported impression of the Bank among other partners was Rationale for a Renewed World Bank Effort on Malaria 27 that "it talks the talk, but does not deliver in practice on the ground" (Malaria Consortium 2002). The Bank's financing of malaria control At the Abuja Summit in April 2000, the Bank, along with heads of state and senior government officials from 44 of the 50 malaria-endemic countries in Africa, pledged to (i) halve the malaria burden in Africa by 2010 and (ii) achieve by 2005 a coverage of 60 percent with key malaria control inter- ventions.15 The Bank stated the following before signing the declaration: We would like to significantly increase the resources needed to address malaria through World Bank financing. We estimate that we now have re- allocated somewhere between US$100­150 million for RBM activities in our Africa Region health portfolio, a healthy amount already available for malaria at the country level. However, we can do much more. We estimate that we can finance an additional US$300­500 million for RBM action across Africa and we hope that the RBM Partnership and the African Leadership will be instrumental in specifically creating a demand for the World Bank operations in this direction. The resources can be deployed to increase the fight against malaria, but there has to be an explicit, coun- try-driven, country-owned, and country prioritization in order to win that fight. There should be more common objectives between the Ministers of Finance and Health. The presence here of so many Heads of State sends a promising signal that a regional effort is urgent, yet viable. Since 2000, total Bank commitments in all regions are about US$100­150 million in earmarked funds for malaria control. These include only health sector investment credits and grants, as well as commitments through broad programmatic operations such as SWAps. Total World Bank support for malaria control was higher, due to financing through debt relief, multisec- toral operations such as PRSCs, Emergency Recovery Credits, and Social Funds. However, it is difficult to quantify exactly how many of these com- mitments went to malaria control, since these operations have not tracked details of disease-specific inputs. Investments in health sector development activities, such as training of nurses and management training at the country and district levels, have not been included. These investments contribute to the capacity of health systems to undertake effective malaria control. 28 Rolling Back Malaria Enhancing PRSPs, PRSCs, and health SWAps to achieve measurable results in malaria control coverage and health outcomes Malaria control would benefit from the application of key principles under- lying the Poverty Reduction Strategy Initiative--ownership, results focus, multisectoral perspectives, and country-led partnership. The Bank could support countries to apply these principles. However, this potential has yet to be realized in many malaria-endemic countries. For example, analyses of PRSPs and Interim Poverty Reduction and Strategy Papers (I-PRSPs) of 27 countries in Sub-Saharan Africa showed that inclusion of malaria in PRSPs is generally low. While 81 percent of PRSPs and I-PRSPs include data on child health indicators, only 37 percent further the analysis to specify the determinants of child health. As a result, the discussion on malaria, which is a major contributing factor to under-five mortality, typically does not include country-specific, quantitative, or, where necessary, costed informa- tion on the problems due to malaria. It rarely includes strategies and actions to achieve malaria control targets. Figure 2.4 and its accompanying table show a categorical distribution of PRSPs and I-PRSPs according to how well they addressed specific items. The analytical base and results focus of the PRSPs are weak in relation to malaria control. These findings are con- sistent with those from a recent evaluation that was done by the Bank's Operations Evaluation Department and indicate a major opportunity for each eligible country to integrate malaria control into its PRSP, given the role that the PRSP plays in development planning and assistance (World Bank, 2004b). With reference to Sub-Saharan Africa, Bank support for this approach would be consistent with the principles addressed in Improving Health, Nutrition, and Population Outcomes in Sub-Saharan Africa (World Bank 2004c). There is a need to combine PRSCs and health SWAps with an emphasis on measurable outcomes Budget support through PRSCs, as well as programmatic operations in the form of basket funding and health SWAps, has the potential to sustain medium- to long-term gains in malaria control and the broader health sys- tem. However, they have not been consistently applied in ways that enable rapid improvements in coverage while improving systems to ensure sustain- ability. An important question is whether these are problems of concept, design, execution, or some combination of the three. Rationale for a Renewed World Bank Effort on Malaria 29 Figure 2.4: Effectiveness of PRSPs in Addressing Malaria 90 80 70 60 None 50 Weak Percent 40 Average 30 Strong 20 10 0 goals indicators health indicators analysis actions strategies relationship determinants child health of of health control Medium-termShort-term child child on Malaria-poverty Malaria-health Malaria Data Specification Medium-term DATA ON MEDIUM- CHILD DETERMINANTS TERM CHILD MALARIA- MALARIA- MALARIA HEALTH OF CHILD HEALTH HEALTH POVERTY CONTROL MEDIUM- SHORT-TERM PERCENT INDICATORS HEALTH INDICATOR RELATIONSHIP ANALYSIS STRATEGIES TERM GOALS ACTIONS None 0 15 7 19 78 30 41 78 Weak 7 33 4 30 7 30 11 11 Average 11 15 4 15 4 30 19 4 Strong 81 37 85 37 11 11 30 7 Total: Avg + Strong 93 52 89 52 15 41 48 11 Source: Pande, Adeyi, and Basu 2004. 30 Rolling Back Malaria For example, the Operations Evaluation Department's report on the Zambia Health Sector Support Project (IDA Credit 003239) noted that while progress was made on the reforms and harmonization agendas, "there is no clear evidence that the overall quality of, and access to, a national pack- age of essential health services had improved" (World Bank 2003a). The Implementation Completion Report for the project noted that there was "no evidence to suggest that the project had any measurable impact on the health status of the Zambian population," and the case fatality rate for malaria in children (45 deaths per 1,000 cases) was higher than projected (25 deaths per 1,000 cases). Furthermore, there was a local perception of "too much emphasis on process and not enough on achieving visible results on the ground." Drug shortages were common, especially in the urban health centers (World Bank 2003b). According to the Implementation Completion Report, this project was designed as a SWAp, one of the first of its kind in the social sectors in Africa; hence, the findings reflect in part the challenges of a pioneering effort, in addition to local complexities. Lessons were learned about sustained com- mitment, good governance, fiduciary issues, strengthening of procurement capacity, and human resource development. Other lessons learned included: (i) the need to engage with technical personnel who are implementing reforms; and (ii) the perils of a lack of baseline indicators and a system for monitoring progress toward goals, which, along with an inadequate mech- anism for tracking sector expenditures, seriously undermined effective implementation of a sector-program approach. In such instances, the appro- priate strategy would be a phased transition toward sector-wide manage- ment that supports capacity building in key areas and protects high-priority public health interventions while introducing over time SWAp processes such as annual reviews and pooled support for districts. An important lesson is the need to address concurrently the policy, process, and technical issues, including short-term improvements in coverage and health outcomes, while working toward medium- to long-term improve- ments across the health system. Therefore, it is prudent to (i) maximize use of PRSCs and health SWAps whenever possible, by enhancing them to address malaria control explicitly, and (ii) undertake a more intensive malaria control program to ensure major gains in coverage with effective interven- tions, thereby maximizing health and economic gains as rapidly as possible. This effort will facilitate the achievement of results at the country, regional, and global levels, consistent with the emerging themes of the Rationale for a Renewed World Bank Effort on Malaria 31 IDA, including achievement of the MDGs, collaboration with relevant part- ners, results measurement, and attention to communicable diseases: "IDA will continue its work to combat these diseases and mitigate their effects, both at the country level through disease-specific interventions and support for health systems strengthening, and across countries through regional projects, as well as through support for international ini- tiatives" (IDA 2005, p. 13). There are promising developments in integrating strong malaria control efforts within budget support and health SWAps. For example, the Poverty Reduction Support Credit and Grant to the Republic of Rwanda (World Bank 2004d) includes the following malaria-specific measures: · "Use of ITNs by pregnant women will increase from 10 percent in 2003 to 30 percent by 2006, and the percent of children under five covered will increase from 18 percent to 40 percent." This is one of the three primary coverage indicators chosen for the health sector. · "Block grants will be transferred to districts by the Ministry of Health, using agreed performance-based criteria related to malaria control and other high-impact health care services." Furthermore, key actions on malaria include the following (World Bank 2004d): · By end 2004: "Publish policy on antimalarial drug (ACT) and ITN pric- ing and subsidy scheme." · By November 2005: "(i) Ensure that 35 percent of districts have trained promoters in malaria prevention and case management. (ii) Ensure that budget reflects the purchase of any higher cost treatment to be provided at subsidized prices, ensuring that cost to consumers is maintained at cur- rent or lower levels according to the RBM Plan." · By November 2006: "(i) Design and test malaria epidemic early warning system. (ii) Ensure that budget reflects cost of purchasing new high cost antimalarial drugs, ensuring cost to consumers is maintained at current or lower levels according to RBM Plan." 32 Rolling Back Malaria The new Malawi Health SWAp provides an opportunity to integrate malaria control within a broader approach to health sector development. The Joint Program of Work (2004­2010) for the SWAp recognized malaria as "the leading cause of outpatient visits (30 percent)" (Government of Malawi, 2004). However, there was no mention of malaria among the 42 indicators in the SWAp indicator matrix. This raises questions about the technical rigor and strategic relevance of the contents around which donors are harmonizing processes, given the Zambian experience. Malaria Control Programs have found it difficult to navigate the changing landscape of development assistance at the country level One reason for difficulties with development assistance, as given by some RBM partners at the country level, is poor access to health sector resources by National Malaria Control Programs (NMCPs). There is a lack of guid- ance on how NMCPs might operate in a decentralized planning and budg- eting environment. More specifically, it was determined that the combina- tion of increased health sector support and low malaria control coverage is partly due to weak linkages among disease control programs, health sector plans of work, and associated funding. There is evidence that malaria con- trol activities in countries using SWAps or budget support remain generally supported by small projects and have been below the threshold where impact on disease transmission is possible, leaving many to question what tangible outcomes the health system investment is buying. In Ghana, for instance, despite donor harmonization in the sector, an increased Ministry of Health budget, and a growing percentage of that budget being spent at the district level, malaria incidence is on the rise (figure 2.5). This raises concerns, which have been confirmed by operational experiences, that the malaria control program has limited engagement in and ownership of the overall Ministry of Health budget and, therefore, of IDA funds which are channeled through a SWAp (through the Second Health Sector Support Project, US$90 million). According to an external review of the achieve- ments in implementing the 2002 Program of Work, malaria remained the leading cause of morbidity and mortality in the country, accounting for 40 percent of all outpatient contacts and 25 percent of all under-five mortality (Government of Ghana 2003). Rationale for a Renewed World Bank Effort on Malaria 33 Figure 2.5: Malaria Control Efforts Have Not Benefited from Increased Health Spending in Ghana Estimated Malaria Cases 148 146 104 2,884,631 2,925,513 1,967,575 2000 2001 2002 Number of cases Cases/1,000 pop. Estimated Health Sector Plan of Work Budget 206 189 167 2000 2001 2002 US$ millions Source: Government of Ghana, Ministry of Health 2003. 34 Rolling Back Malaria Expanding ownership of malaria control to district level in Senegal In Senegal, key roadblocks to more widespread implementation of RBM activities include weak and spotty implementation of district-level activities and the overly centralized structure of the NMCP. Dialogue between the central program and the provincial and district health directors has been relatively weak, as has been ownership at the district level of key malaria control activities. In August 2004, at the request of the NMCP and the Bank, the RBM Secretariat provided the NMCP with US$60,000 to carry out a process by which the central NMCP staff spread out across the coun- try to discuss with each district the activities and performance targets needed to reduce morbidity and mortality from malaria. This process has been completed and the agreed-upon activities have been integrated into the overall health sector plan of work, to avoid duplicate planning and budg- eting for malaria control activities. Sector-wide or budget support to dis- tricts would automatically support malaria control activities through sup- port of the more technically robust district plans. Critical now to success will be funding flows to the district level, as well as the availability of com- modities. The latter will be increasingly difficult given the impending increase in the cost of malaria treatment (for ACTs). 2.6 Clients and Partners Demand a Stronger World Bank Effort The Bank's clients in malaria control include not only ministries of finance, which are the prime institutional counterpart for Bank-country relations, but also multiple stakeholders that either play key roles in effective malaria control or are affected by the Bank's work in this area. These stakeholders include the line ministries such as health, education, agriculture, environ- ment, and infrastructure; malaria control programs; maternal and child health programs; CSOs; and the private sector. Tacit knowledge acquired in the past five years indicated that while engagement with the ministry of finance was necessary, it was not sufficient to ensure effective Bank support for malaria control. Recent consultations with stakeholders pointed to les- sons learned and also indicated areas in which the Bank should improve its work on malaria control. During the annual joint Malaria Control/Integrated Management of Childhood Illnesses Program Managers meeting in Maputo, Mozambique, Rationale for a Renewed World Bank Effort on Malaria 35 in September 2004, the WHO Regional Office for Africa (WHO AFRO) gave Bank representatives the opportunity to discuss the Bank's perfor- mance in malaria control. In addition to participating in plenary discussions, Bank representatives asked NMCP managers to provide feedback on the Bank's role in malaria control by filling out a short, self-administered ques- tionnaire, the results of which were considered in the development of the new Strategy and Program of Action. Since this was a convenience sample, the findings are only illustrative of a range of issues to be considered and cannot be gen- eralized beyond the sample. The findings raise many questions to be addressed on a country-by-country basis and provide the Bank with an interim idea of how its work on malaria is perceived by one of the key client constituencies in malaria control--technical experts and program managers responsible for malaria control in client countries. Thirteen client countries were consulted on the status of work at the country level, NMCP managers' successes and perceived challenges in working with the Bank on malaria, recent achievements in malaria control, their unmet needs and expectations, and how the Bank might respond to those needs. Separate discussions with officials from many of the countries included their experiences with and perceptions of the Bank's approach to malaria control, including policy dialogue, program design, financing, implementation support, lending instruments, cross-cutting health system constraints and efforts to address them, and suggestions for the future. Nine of the 13 clients (69 percent) responded that the Bank provided financing for malaria control in their countries. Interestingly, for two major health sector support programs implemented through SWAps, program managers claimed either that they were "not sure" of Bank financing for malaria or that there was "no financing" for malaria. The limited knowledge and ownership of malaria financing by the program managers, as evidenced by their responses, is a major issue, regardless of the level of financing. Of the countries using health SWAps (71 percent of the countries sampled), 90 percent of the program managers attended the planning meetings, though their levels of participation varied from simply attending to active partici- pation through involvement in the planning, presentation, and reviews of progress. The Bank scored highest in its active involvement in policy discussions on malaria control in client countries, with 8 of 13 (62 percent) responding positively. The Bank's lowest performance rating (with 100 percent of clients assigning a "very poor" rating) was in response to a question about 36 Rolling Back Malaria the simplicity of procedures to help malaria control programs access World Bank funds. In addition to this issue, the two other questions on which the Bank scored very poorly both involve the limited engagement of the Bank with non-governmental organizations (NGOs) and civil society groups, and the formal or informal commercial private sector work on malaria control in client countries. (Regarding NGO engagement, 92 percent scored the Bank a "poor" or "very poor" rating, with the Democratic Republic of Congo being a key exception, scoring the Bank "excellent" on this question. Regarding private sector engagement, 75 percent scored the Bank a "poor" or "very poor" rating.) Given that the majority of malaria cases in endemic areas (as in most of Sub-Saharan Africa) are prevented and treated in the nonpublic sector, the low ratings on this front are troubling. While the results of the questionnaire do not provide the Bank with a positive scorecard overall, the clients do not want to see the Bank disengage; 100 percent of the respondents would like the Bank to "do more than it is doing today." In response to an open-ended question, NMCP managers' most common requests for how the Bank might better support malaria con- trol in the future centered around the following: · Increased financing (through direct support to malaria control programs, through SWAp/budget support, and through both), particularly long- term financing for commodities such as ACTs · Support for economic analyses relating to malaria control · Sharing of best practices across countries · Simplification of disbursement to support programs. CHAPTER 3 Priorities and Business Model The Bank's priority is to enable countries to achieve and sustain large-scale impact in malaria control. More specifically, the Bank will support countries to develop and implement programs to (i) cost-effectively reduce morbidity, productivity losses in multiple sectors, and mortality due to malaria, partic- ularly among the poor and vulnerable subgroups such as children and preg- nant women, and (ii) address challenges of regional and global public goods. The Bank will achieve the stated priorities through a business model that combines an emphasis on outcomes with flexibility in approaches and lending instruments.16 Products and services will be tailored to different client seg- ments in a way that meets their needs and maximizes the institution's com- parative advantages. This approach is consistent with the new Global Strategic Plan of the Roll Back Malaria Partnership (RBM 2004). The Bank participated actively in the formulation of that strategy. In the short to medium term, a new Booster Program for Malaria Con- trol, outlined in table 3.1, will provide increased financing and technical support to accelerate program design and implementation, increase cover- age, and improve outcomes more rapidly than in the recent past. The Booster Program for Malaria Control will be global in scope and consist ini- tially of an intensive effort over a five-year period. It may include one or more Horizontal Adaptable Programs17 at the global or regional level and will cover many countries, with emphasis on country ownership, measura- ble outcomes, and rigorous application of epidemiology. While the imme- diate objectives are fixed--increasing coverage, improving outcomes, and building capacity--the means will be flexible. The business model and the Booster Program take into account lessons learned from successful malaria programs in several countries, and also constitute a substantial departure 37 38 Rolling Back Malaria from the Bank's previous approach to malaria control. There is a need for decisive action on a large scale in order to achieve impact. Crucially, the Bank's approach will be proactive while respecting and supporting country leadership and ownership. Experience of the past five years shows that a pledge of commitment, such as that made by the Bank in Abuja in 2000, with neither a clearly funded program for malaria control nor the internal budget to ensure that the Bank's malaria team can function effectively, does not lead to success on a large scale. A different and more robust approach is needed for success. Drawing on lessons of the past five years, Bank management is designing a program for Board approval to ensure that the Bank responds to country demands with flexibility and speed. On the basis of initial demand from clients, the working assumption is that a total commitment of US$500 mil- lion to US$1 billion is feasible over the next five years. The Bank will mobi- lize financial and technical resources from within and outside the institu- tion, including the public and private sectors, to: stimulate the production of commodities such as ITNs and antimalarial drugs; lower taxes and tariffs on such commodities; improve and maintain a long-term commitment to malaria control by governments and civil society groups; and build public- private partnerships for program design, management, and evaluation. Sev- eral key partners have expressed interest in a collaborative and stronger effort. The International Finance Corporation (IFC), which has a particu- larly strong comparative advantage in working with the private sector, will play an important role in this enhanced effort by the World Bank Group. Subject to satisfactory performance and resource availability, the Bank will continue its highly selective support for partnerships working on product development and applied research that are relevant to malaria control. Henceforth, malaria control will be mainstreamed into the Poverty Reduction Strategies and large sector-development programs that empha- size outcomes. The high coverage rates achieved in most countries will be sustained through combinations of domestic financing, programmatic oper- ations, and budget support on a case-by-case basis. High coverage with pre- ventive interventions will decrease the burden of disease and the pressures on health services. Approaches and instruments will depend on what is needed in each con- text. This combination of an emphasis on outcomes with flexibility of approaches and instruments will make the Booster Program relevant and adaptable to a variety of countries in each region, taking into account dif- Priorities and Business Model 39 ferences in their institutional capacities, risk profiles (which vary from post- conflict to stable), resource needs, relative strength of the public and private sectors, and the pattern of malaria in each setting. For Sub-Saharan Africa, which bears the highest burden of malaria, the approach is consistent with the Strategic Framework for Assistance to Africa in its recognition of the need for adaptability to a client typology continuum. The Framework states that "the array of instruments appropriate for a given country will vary with the country's capacity and performance" (World Bank 2004e, p. 85). The Booster Program is adaptable to postconflict settings, Low Income Coun- tries Under Stress (LICUS), middle performers, and high performers. The business model puts emphasis on results, system indicators, and high-impact partnerships with a predictable resource flow. Countries will have three main options for accessing more funds and technical support from the Bank. These options, which are not mutually exclusive, are outlined below. · Enhancing PRSCs and health SWAps to support malaria control. In this option, the Booster Program for Malaria Control will be used to enhance health SWAps and PRSCs, with additional financing when required, to include stronger malaria control programs, technical support, and results-based monitoring and evaluation. The recently approved PRSC for Rwanda is a useful example. It includes technically sound malaria con- trol activities within the health sector plan of work, including the moni- toring and evaluation matrix and the Medium-Term Expenditure Frame- work (MTEF). Beyond the health sector, PRSCs provide opportunities for cross-sectoral work on malaria through, for example, the education, agriculture, environment, and transport sectors. · Malaria Control Projects at the country or subregional level. Based on coun- try requests, the Booster Program for Malaria Control will support Malaria Control Projects, as in the successful examples of Brazil, India, and Vietnam. Project design and objectives will depend on the local con- text in terms of government policy, disease burden and distribution, the nature of the vector (the mosquito), and local management capacity. Countries may choose to use community-driven development (CDD) approaches, depending on the context. These Malaria Control Projects will supplement, not disrupt, systemic development programs for the health sector. Strengthening the health infrastructure will facilitate malaria control and help to sustain the gains to be achieved under the 40 Rolling Back Malaria Booster Program for Malaria Control. The success of the Onchocercia- sis Control Program, as well as the ongoing lessons from the Bank's work on HIV/AIDS, will be applied to the challenge of addressing system- wide needs while improving coverage and outcomes in the short to medium term. In this option, the Booster Program for Malaria Control will support investment operations that are consistent with broader sec- toral frameworks in each context. For LICUS and postconflict countries, special implementation arrangements may include more extensive con- tracting of CSOs for service delivery, combined with technical and oper- ational support from agencies such as WHO and UNICEF. · Combined HIV, Tuberculosis, and Malaria Control Projects. Another option is to develop and implement operations covering HIV, tuberculosis, and malaria, such as those in Angola and Eritrea. In this option, the Booster Program for Malaria Control will support broader operations covering several disease control objectives in a way that is consistent with medium- to long-term sectoral and multisectoral development. By the end of the fifth year of the Booster Program, most eligible coun- tries are expected to have achieved significant increases in coverage of essential interventions, in line with targets set by client countries and the global Roll Back Malaria Partnership for 2010. Priorities and Business Model 41 Table 3.1: The Booster Program for Malaria Control: Matrix of Options for Financing and Instruments KEY FEATURES OF THE PROGRAM · May include one or more Horizontal Adaptable Programs at the global or regional level, covering many countries · Can combine with cofinancing from other sources (foundations, bilateral agencies) and country-by-country partnerships with the GFATM · Can use grants or performance-based buydowns (converting credits into grants and providing incentives to achieve results) · Linked to a Malaria Control Advisory Service, to be funded through grants (foundations, multilateral and bilater- al agencies) · Addresses the global public good financing and supply issue to expand access to malaria-related commodities (namely, the new ACTs and long-lasting ITNs). OPTIONS FOR IMPLEMENTATION Main requirements Implications for Bank operations (These are not mutually exclusive.) Enhancing PRSCs and health SWAps Emphasis on measurable Increased operating budget (Bank to support malaria control results Budget) Malaria Control Projects Increased and more Untied Trust Funds · At country level predictable flow of funds Commitment from country directors · At subregional level for malaria control Incentives for team leaders to focus Combined HIV, TB, and Malaria Control Increased technical support on results and be flexible in Projects Clients have choices in the approaches type of instrument that they can use to access support from the World Bank CROSS-CUTTING ISSUES · More proactive and effective collaboration with CSOs · Better utilization of country capacity, concurrent with development of human resources · User-friendly tools and operational support for country-based planning and budgeting · The roles of major partners: leveraging financing, coordination and technical resources from partners such as the RBM Secretariat, Bill and Melinda Gates Foundation (which finances the Malaria Control and Evaluation Project in Africa [MACEPA]), GFATM, UN Foundation, WHO, large multinational corporations, and others IMPLICATIONS FOR BANK OPERATIONS · Increased operating budget and untied trust funds to enable effective Bank support · A Bank-wide Malaria Task Force to prepare and spearhead execution of the Global Strategy and Booster Program · Emphasis on measurable results, with flexibility in approaches, depending on client preferences and contexts · Internal coding and tracking: Bank will know how much it is committing to malaria control · Review of programmatic operations related to the health sector and their effects on malaria control: What is the evidence? · Strategic communications: The Bank will be more active in shaping global discussions and in disseminating its approach and success stories. CHAPTER 4 Program of Action The Booster Program will be an umbrella program for intensified work, including analytical and advisory services, lending, and grants. Table 4.1 is an indicative schedule of deliverables and major activities by fiscal year. 4.1 The Program and Deliverables Implementation of the Booster Program implies an increase in the deliver- ables to be planned and achieved by regional vice presidentail units (VPUs), country units, and sector units that are working on malaria control from fis- cal 2006 onwards. The Program would support operations at the subre- gional and country levels. Depending on specific contexts, the operations would include proactive engagement of CSOs and the private sector to the extent that it is compatible with their comparative advantages. Such engage- ment could include contracting and/or financing of activities to be under- taken by CSOs and the private sector. In order to promote sustainability and mitigate the risks of distortions, this Program will supplement and be con- current and synergistic with programmatic approaches such as health SWAps and PRSCs. Contingent upon the commitment of IDA resources for the Booster Program, the Bank will seek cofinancing or performance-based buydowns from partners, including but not limited to foundations and multinational corporations. The program document for the Booster Program will address, among other things: (i) operational aspects of complementarity with the GFATM, of which there is an emerging example in Angola; (ii) procurement of com- modities for malaria prevention and treatment; (iii) technical support for teams with primary responsibilities for work at the country level, particu- 43 44 Rolling Back Malaria larly to overcome implementation bottlenecks; and (iv) better utilization and improvement of local capacity for implementation. The program doc- ument will include guidelines and sample terms of reference for speedy application at the country level, with considerable room for country teams to customize it to local contexts, given the importance of local adaptation and flexibility for successful malaria control. Furthermore, it will make explicit the linkages with other major providers of development assistance for health, namely, the GFATM. Under Phase I of the Booster Program, which began in fiscal 2005, the Bank-wide Malaria Task Force, with guidance from a high-level Steering Committee, started developing operational guidelines and discussing arrangements with strategic partners to enhance programmatic operations so that they are better designed and supported to achieve more rapid progress in malaria control. The Malaria Task Force will also undertake or commission analytical work, jointly with economists in the Development Economics (DEC) and regional VPUs, to improve the knowledge base for the economics of malaria control, such as what the medium- to long-term economic implications would be for clients should they undertake more intensive efforts to control malaria and the optimal deployment of treatment given increasing rates of drug resistance and the costs of new treatments. Concurrent efforts to develop a learning program on malaria control for World Bank staff and a strategic communications program aimed at internal and external audiences will increase both clients' and Bank counterparts' understanding of the Bank's new Global Strategy and Booster Program. During Phase II (fiscal 2006­7), contingent upon Board approval in fis- cal 2006 of the Booster Program, the emphasis will be on the application of the operational guidelines and arrangements developed in fiscal 2005 to: (i) enhance programmatic operations to achieve rapid progress in malaria con- trol and (ii) support project preparation and implementation at the country and subregional levels, including malaria-specific operations, where appro- priate. By the end of Phase II, at least five countries will have enhanced their programmatic operations by increasing significantly their financial resources or strengthening technical support for malaria control. Such financial increases will be on budget and reflected in MTEFs as appropri- ate. In addition to strengthened malaria control under programmatic oper- ations, given existing client demands, the Task Force will support country and regional teams to deliver at least 10 Malaria Control Projects (or MDG-related communicable disease control projects) at the country or Program of Action 45 subregional level by the end of fiscal 2007. All country or subregional oper- ations will be managed by regional VPUs. Other key activities in Phase II will include the completion and applica- tion of analytical work on the economics of malaria control, further devel- opment and application of tools and support mechanisms to enable country and program teams to do their work effectively, including Web-based resources, and a Malaria Advisory Service. Phase III (fiscal 2008) will include lending (programmatic and disease-specific if required), analytical, and advisory services, as well as an evaluation of the Booster Program. The Booster Program will be adjusted in line with country needs and corporate priorities, or phased out as required. Deliverables The timeline and deliverables are indicative (see table 4.1). The execution of this program will be responsive to the needs of clients, with emphasis on results and concurrent improvement of country capacity for implementa- tion. It will be flexible, rather than sequential and rigid. This combination of emphasis on outcomes with flexibility in approaches and lending instru- ments will make the Booster Program relevant and adaptable to a variety of countries in every region, including LICUS and postconflict countries. The program will be results-driven, with the goals of increasing malaria inter- vention coverage, reducing illness, minimizing productivity loss, and decreasing deaths attributable to malaria. 4.2 The International Finance Corporation and the Private Sector in Malaria Control The private sector is essential for the supply, distribution, and sale of inputs needed for tackling malaria, such as drugs and ITNs, as well as in the deliv- ery of related services. However, until now, the private sector has been con- strained in many of these activities. The market for these needed goods is often unpredictable and difficult to forecast. Although needs are high, the ability of poor households to pay for these goods and services is limited. Current public financing arrangements are limited and not dependable, and even donor-supported aid offers only short-term predictability. The Global Strategy and Booster Program will play an important role in stimulating 46 Rolling Back Malaria Table 4.1: The Booster Program for Malaria Control: Deliverables DELIVERABLES COMMENTS 1 Phase I: Fiscal Year 2005 (start-up phase) 1.1 Global Strategy and Booster Program, Completion date: April 2005. which provides the basis for future actions. 1.2 Booster Program for Malaria Control. For preparation in fiscal 2005 and early fiscal 2006, followed by presentation to the Board of Directors in fiscal 2006. Potential sources of cofinancing or performance-based buydowns include major foundations and multinational corporations. Further exploration of such cofinancing is contingent upon World Bank commitment to a stronger effort to control malaria. The program document will address operational aspects of complementarity with GFATM (example from Angola), procurement of commodities, support for Teams with primary responsibilities for work at the country level, and better utilization and improvement of local capacity for implementation. It will address collaboration with WHO, UNICEF, and other key partners such as foundations and multinational corporations. The program document will include guidelines and sample terms of reference for speedy application at the country level, with considerable room for country teams to adapt guidelines to local contexts. 1.3 Development of practical guidelines for Task To be done jointly with RBM Secretariat and Teams on (i) assisting countries to enhance PRSCs subregional networks as appropriate. or health SWAps to strengthen malaria control; (ii) programming incremental resources from the HIPC initiative; (iii) ensuring complementarity among the Booster Program, health SWAps, and PRSCs; (iv) developing malaria-responsive PRSPs; and (v) developing malaria-responsive Country Assistance Strategies (CASs) as part of results- based CASs. 1.4 Report of first phase of analytic and advisory Ongoing, jointly with USAID. services (AAA) on the operational and budgetary implications of policy shifts to artemisinin-based combination therapies in selected countries. Program of Action 47 Table 4.1: The Booster Program for Malaria Control: Deliverables (continued) DELIVERABLES COMMENTS 1.5 Formulation of a learning program on malaria control for World Bank staff. Concurrently, five learning sessions for Bank staff on important aspects of malaria control. 1.6 Formulation and implementation of the first To address both internal and external communication stages of a Communication Strategy. needs. 1.7 Development of procurement guidelines for Jointly with OPCPR and RBM Partnership Secretariat. malaria commodities. 2 Phase II: Fiscal Years 2006­7 2.1 At least five countries have enhanced programmatic Jointly with WHO, MACEPA, Roll Back Malaria (RBM) operations, increased significantly their financial Partnership Secretariat and subregional networks. resources to and strengthened technical support for Intense country support (for example, attendance at malaria control from funds already committed all joint sector review meetings, technical assistance under PRSCs, other multisectoral operations, or between reviews) combined with cofinancing or per- health SWAps. All increases within budget and formance-based buydowns of parts of credits spent reflected in MTEF as appropriate. on malaria control. Additional financing will meet the incremental resources needed for effective malaria control. 2.2 Preparation of at least 10 Malaria Control Jointly with WHO, MACEPA, Regional Collaboration Projects (investment operations) at the country or Center in Ouagadougou, RBM Partnership Secretariat, subregional level, depending on the combination and subregional networks. Intense country support of client demands, feasibility, and pattern of combined with cofinancing or performance-based disease. buydowns of parts of credits spent on malaria control. The number of operations will depend upon client (Includes malaria-specific operations wherever demand. appropriate.) 2.3 Implementation of learning program for Bank Jointly with the World Bank Institute and the Global staff. Development Learning Network. Continuation of learning sessions for Bank staff on important aspects of malaria control, with emphasis on operational effectiveness. 2.4 Report of AAA on modalities to engage the Jointly with Africa Region (ongoing private-public formal and informal private sector, given the partnerships work) and IFC. importance of such engagement in reaching and sustaining coverage. Commissioning of applied research on Jointly with technical and academic partners. Findings epidemiology, service delivery, and quality of care. to be applied to ongoing and planned operations as part of broader monitoring and evaluation (M&E). 48 Rolling Back Malaria Table 4.1: The Booster Program for Malaria Control: Deliverables (continued) DELIVERABLES COMMENTS 2.5 Web-based directory of technical and managerial Jointly with RBM Secretariat, WHO, MACEPA, and resources for malaria control programs. others as appropriate. 2.6 Continued implementation of the first stages To address both internal and external communication of a communication strategy. needs. 3 Phase III: Fiscal Year 2008 3.1 Preparation of 20 country-specific or subregional Subject to Board approval of a Booster Program and Malaria Control Projects (cumulative total of client demand. investment operations) under the Booster Program. To be managed by regional VPUs, with incremental operating budget from one or more of Bank budget, trust funds, or credit lines. The Bank-wide Malaria Task Force will support country teams. 3.2 A cumulative total of at least 10 countries have Jointly with WHO, MACEPA, RBM Secretariat, and enhanced programmatic operations, increased RBM subregional networks. Intense country support significantly their financial resources to and (for example, attendance at all joint sector reviews) strengthened technical support for malaria control combined with cofinancing or malaria-related debt from funds already committed under PRSCs, other buydowns (for example, ACT or ITN investments) will multisectoral operations, or health SWAps. All be employed to improve the incentive system for increases within budget and reflected in MTEF clients to use Bank monies for malaria control. Addi- as appropriate. tional financing would help mitigate the increasing costs of malaria control. 3.3 Malaria control is mainstreamed into the major Regional VPUs will be responsible for this. development instruments in all malaria-endemic countries (all CASs, PRSPs) beginning in fiscal 2006. The Malaria Task Force will provide support. 3.4 Continued implementation of the Communication To address both internal and external communication Strategy. needs. 3.5 Malaria Advisory Service established and Jointly with WHO, MACEPA, RBM Secretariat, and one operational. or more foundations. 3.6 Evaluation. Operations Evaluation Department or external evalua- tion team (or both). Program of Action 49 wider involvement of the private sector by providing more predictability and stability to the market. The IFC could potentially finance private companies involved in a num- ber of activities, such as manufacturing of drugs, nets, and diagnostics, and drug distribution. To date the private sector has not sufficiently engaged in these activities to meet demand. There are several roles the Bank could undertake with proposed financing that could facilitate involvement of the private sector. The draft business plan of the Roll Back Malaria Initiative calls for "stimulating development, manufacturing and widespread distribu- tion of long-lasting insecticidal nets" and sets out a useful framework within which the private sector and potentially the IFC could engage. Several of these roles are more broadly applicable: · Advance purchase contracts for drugs, nets, diagnostics, or other inputs with a medium-term duration (seven years or longer): Guaranteed markets would give manufacturers incentive to invest · Buydowns of drugs, nets, diagnostics, and so forth: Buydowns would close the gap between ability to pay and demand · Grant funding to cover first loss or a Debt Service Reserve Account: If the IFC were to finance a local producer directly or through a financial interme- diary, grant funding could potentially cover a first loss or support a Debt Service Reserve Account. For a private company, activities that the Bank may support to increase the attractiveness of investment, and the market more generally, include: · Loan buydowns and other mechanisms to lower the cost of capital · Improved transparency and streamlining of regulatory frameworks: Currently these serve as a major barrier to entry in a number of countries. Improv- ing transparency and streamlining regulatory frameworks would benefit a company's bottom line and enhance the incentive to supply a given market · Efforts to lower taxes and tariffs: Taxes and tariffs may introduce unfair barriers to entry and discourage market entry. If some of the initiatives above are undertaken and the right market con- ditions exist, the IFC could then undertake the following: 50 Rolling Back Malaria · Identify and finance private sector partners to fill these gaps · Use trust fund money to identify manufacturers, distributors, and others essential to achieving overall goals. Though they require further consideration, other products the IFC could offer for small enterprises and NGOs for which the transaction costs of doing business with the IFC are too high include: · Fund or line of credit for small manufacturers and distributors · Loan guarantees to back local banks' financing of small companies · New grassroots initiative that provides a mixture of grants and small loans to small companies and NGOs. 4.3 Cooperation with the Global Fund and Other Major Partners in Malaria Control The Bank's work will continue to be done with country leadership and in collaboration with major partners. The RBM partnership provides the global mechanism for interagency collaboration in malaria control. The Bank will be proactive in seeking major sources of cofinancing for country- led operations, including but not limited to the GFATM, major bilateral and multilateral organizations, the Bill and Melinda Gates Foundation, the United Nations Foundation, and large corporations. In all partnerships, the Bank will emphasize an orientation toward measurable outcomes at the country level, and collective actions to utilize and improve local capacity for sustainable programs. The GFATM "only finances programs when it is assured that its assis- tance does not replace or reduce other sources of funding, either those for the fight against AIDS, tuberculosis and malaria or those that support pub- lic health more broadly. The GFATM actively seeks to complement the finance of other donors and to use its own grants to catalyze additional investments by donors and by recipients themselves."18 The Bank will work closely with the GFATM to increase synergies and avoid overlaps and gaps, while keeping in mind the GFATM's mandate as an additional source of financing and the Bank's comparative advantage in development economics, Program of Action 51 financing, system-wide development, capacity building, and implementa- tion support. For some countries, over the short term, the Booster Program and Task Force may place more emphasis on analytical and advisory services and the removal of implementation bottlenecks and less emphasis on increased lending, given existing GFATM commitments. Other countries face short- term financial constraints or long-term uncertainties; IDA resources are needed in these contexts. The deployment of ACTs is one area in which the importance of collaboration between the Bank's Booster Program and the GFATM is evident. Currently, clients have concerns regarding the sustain- ability of short-term health sector investments (through increased drug financing) without both medium- to long-term guarantees of financing or returns (economic and health) and the establishment of a timeframe over which greater investments will be required. Other challenges include stim- ulating local production capacity for commodities used in malaria control, reducing market and demand uncertainties for drug companies, and com- pleting procurement in a timely manner. CHAPTER 5 The Malaria Task Force 5.1 Objectives The Malaria Task Force is a Bank-wide group drawn from corporate units, networks, operational VPUs, and the IFC. It will support the Bank's coun- try and regional teams to do the following: · Increase rapidly the scale and impact of the Bank's support for malaria control at the country level, with the aim of reducing the burdens of pre- ventable illness and deaths due to malaria over both the short and medium term · Improve the institutional knowledge base regarding (i) the economic effects of malaria at the household, sectoral, and macro levels, and the implications of these effects for the Bank's work on poverty reduction, and (ii) the effects of subsidies for antimalarial drugs and ITNs on house- holds, service providers, and program managers · Mainstream malaria control into PRSPs and into the Bank's lending and nonlending services. This Task Force will support the execution (by country and regional units) of the Global Strategy and Booster Program to enable countries to make more rapid progress in malaria control. The Task Force will have a lifespan of five years, after which it will be dissolved or modified on the basis of progress made and corporate needs. It will be nimble and results-ori- ented, with a small bureaucratic footprint and cross-sectoral membership from regional and corporate units. 53 54 Rolling Back Malaria 5.2 Oversight A Steering Committee will provide institutional oversight and guidance. The Steering Committee will include the Senior Vice President and Head of the Human Development Network, the Regional Vice Presidents for Africa, South Asia, East Asia, and the Pacific, the Vice President for Oper- ations Policy and Country Services, and the Senior Vice-President and Chief Economist. The Poverty Reduction and Economic Management Network will provide guidance on the integration of malaria control into PRSPs. 5.3 Staffing: Secretariat and Regional Clusters The Malaria Task Force will have a small secretariat in the Health, Nutri- tion and Population Unit of the Human Development Network Hub (HDNHE) and a substantial presence in the regional VPUs, with member- ship from corporate units and multiple sectors in the Bank. Apart from those in the secretariat, the Malaria Task Force members will remain in their home units within the Bank. No new full-time staff members will be recruited for the Secretariat, whereas Task Force Members will either be providing cross support or be seconded. The only exceptions are (i) a full- time Public Health Specialist on secondment from the Roll Back Malaria Secretariat in Geneva and (ii) one Young Professional (YP) and one Assis- tant in the Task Force Secretariat. At the discretion of each regional VPU, full-time specialists could be recruited over time. Regional clusters: The Malaria Task Force will operate mainly through regional clusters that may include senior specialists, economists, operations officers, and external relations officers. The size and configuration of the cluster will depend on the needs of each region and decisions made by the respective regional VPUs. Table 5.1 shows a possible staffing and distribution of the Task Force. 5.4 Financing the Malaria Task Force One of the main lessons from Bank experience is that major commitments such as those outlined in this document require sustained financing from the The Malaria Task Force 55 regular Bank budget and trust funds. For example, both the highly success- ful Onchocerciasis Control Program (see http://www.worldbank.org/afr/ gper/) and the ongoing work on HIV/AIDS in Africa (see http://www. worldbank.org/afr/aids/actafrica.htm) had unstinting support from senior management and regular financing, at a level of US$1.5 to US$3 million per year. There is a need for equally strong senior management commitment to the Malaria Task Force, commensurate with the size of the problem and the level of effort that is required to tackle it. Budget allocation from the regular Bank budget would make it possible to leverage additional resources from partner institutions. Regional VPUs and Country Units would need to allo- cate funds for project preparation on a country-by-country basis in addition to this budget. Funding should be consistent with the decisions around the increases in deliverables agreed to by RVPs, country units, and sector units. Table 5.1: Potential Staffing and Distribution of the Malaria Task Force LOCATION FULL-TIME EQUIVALENT (FTE) Secretariat (in HDNHE) Coordinator 0.4 (Bank staff) Public Health Specialist 1.0 (Secondee from RBM Secretariat) Operations Officer 0.5 (Bank staff) Health Economist or Specialist 1.0 (Bank staff, YP) Communications Specialist 0.5 (Bank staff, from HDNVP) Task Force Assistant 1.0 (Bank staff) Regional and corporate clusters Africa (to be determined by Africa VPU, and will take into account lessons learned through the Onchocerciasis Control Program and ACTafrica) · Regional Focal Point 1 (Bank staff) · Regional Implementation Specialists 1.5 (Bank staff) · Task Team Leaders 8 × 0.25 = 2.0 (Bank staff) · Task Force Assistant 1.0 (Bank staff) · External Relations Officer 0.5 (Bank staff) South Asia 4 × 0.25 =1.0 (Bank staff) East Asia and Pacific 2 × 0.25 = 0.5 (Bank staff) Latin America and the Caribbean 2 × 0.25 = 0.5 (Bank staff) Development Economics 2 × 0.25 = 0.5 (Bank staff) Operations Policy and Country Services 1 × 0.25 = 0.25 (Bank staff) World Bank Institute 1 × 0.25 = 0.25 (Bank staff) CHAPTER 6 Results-Based Monitoring and Evaluation 6.1 Results Framework The Bank's Global Strategy and Booster Program is focused on impact in countries, with links to selected MDGs: · Reduction of all-cause child (under five) mortality (MDG 4) · Improvement of maternal health (MDG 5) · Reduction of malaria-specific morbidity and mortality (MDG 6) · Reduction of productivity losses attributable to malaria (MDG 6) · Reduction of illness and absenteeism in school-age children and mitiga- tion of other impediments to learning caused by malaria (MDG 2). The Strategy and Program of Action are thus designed to be results- driven and to strengthen the country capacity for monitoring and evalua- tion. In this regard it is responsive to key recommendations of an inde- pendent evaluation of the World Bank's approach to global programs, which called for greater emphasis on outcome and impact evaluation (World Bank 2004f). A results framework has been developed as the basis for a monitor- ing and evaluation system. It is conceived around the three main thrusts of the Program: (i) to improve the quality and intensity of the Bank's (lending and nonlending) assistance to its client countries; (ii) to improve the quality and intensity of the Bank's contribution to regional and global partnerships, in line with its comparative advantage; and (iii) to strengthen the Bank's internal capacity to rise to the challenges of (i) and (ii). 57 58 Rolling Back Malaria These three thrusts are complementary and build upon one another. For this reason, results frameworks for each have been developed, and each framework presents a results chain of inputs, outputs, outcomes, and impacts. The impacts and outcomes of the Bank's strengthened capacity are inputs to the results chain of the other two thrusts (support to countries and improved partnerships). They are presented in this section. 6.2 Steps to a Results-Based Monitoring and Evaluation System The review, clarification, and confirmation of these results chains are an important first step in building a viable M&E system for tracking the per- formance and impact of the Bank's Global Strategy and Booster Program. These results require the understanding and full engagement of all staff and managers involved in implementing and overseeing Program implementa- tion. The final articulation of results will also benefit from the understand- ing and input of those standing to benefit from the Bank's improved and intensified support--client countries and partners. Once the results are fully defined and agreed, a number of other key steps will need to be taken to establish a viable M&E system. They include: · Selection of key performance indicators to monitor outcomes · Establishment of baseline data on indicators, including the collection of data and documentation of sources · Quantification of targets · Definition of modes and frequency of data collection, analysis, and reporting for each input, output, and outcome indicator (monitoring), and the instruments for analysis and reporting · Definition of the types, timing, and levels of evaluations · Definition of how the findings will be disseminated and utilized in deci- sion making and incorporated into improved performance (for example, through reports to the Steering Committee and subsequent decision making) · Definition of roles and responsibilities for carrying out the various tasks of the M&E plan and for its overall coordination. Results-Based Monitoring and Evaluation 59 In addition to developing a system for monitoring and evaluating the Bank's performance, the support to countries to improve their own M&E systems for malaria (in the context of health M&E systems) will be critical. Among many other advantages, decentralized, results-based, in-country M&E will help key actors and contributors to the fight against malaria take the following steps: · Articulate their goals in various catchment areas based on challenges, opportunities, and baseline data · Monitor their performance and improve their effectiveness as a conse- quence of the above articulation · Build a local knowledge base and credibility that will, together, strengthen analysis of the malaria problem and its appropriate prioritiza- tion in cross-sectoral development strategies such as PRSPs, as well as mobilize additional funding · Set the stage for the design of results-based (or performance-based) dis- bursements in the context of the Bank's lending support and possibly, as well, in the context of technical and financial support of other partners. A detailed outline of the monitoring and evaluation framework is pro- vided in appendix 1. 6.3 RBM Technical Strategies and Indicators of Population Coverage The Roll Back Malaria Partnership Monitoring and Evaluation Reference Working Group has defined the core set of program indicators to monitor programs. For ease of use, technical rigor, and comparability in measuring outcomes, these indicators will guide clients and Bank task teams in the Booster Program. They will be modified and adapted to each context as necessary. Vector control via ITNs 1. Proportion of households with at least one ITN. 2. Proportion of children under five years old who slept under an ITN the previous night. 60 Rolling Back Malaria Prompt access to effective treatment 3. Proportion of children under five years old with fever in the last two weeks who received antimalarial treatment according to national pol- icy within 24 hours from onset of fever. Prevention and control of malaria in pregnant women 4. Proportion of pregnant women who slept under an ITN the previous night. 5. Proportion of women who received intermittent preventive treatment for malaria during their last pregnancy. Proposed measurement tools Nationally representative, population-based sample surveys are the princi- pal measurement tools required to collect the necessary data for construct- ing all five core RBM indicators for population coverage. Many different forms of these surveys are currently being routinely implemented; however, few of these surveys collect data on malaria-specific issues. Two large survey efforts that do currently collect data on malaria are the Demographic and Health Surveys (DHS) and the Multiple Indicator Cluster Surveys. In addition to these ongoing survey efforts, the RBM partners have developed a standard Management Information System (MIS) package for assessing the key household coverage indicators. This includes a core ques- tionnaire and data tabulation plan, as well as related materials for organiz- ing and conducting fieldwork. This stand-alone survey is designed to be implemented in a similar manner to the DHS, producing nationally repre- sentative, population-based data from which all five core RBM outcome indicators of population coverage can be constructed. The MIS will also produce a wide range of data for in-depth assessment of the malaria situa- tion within countries. It is designed to be shorter, less expensive, and quicker to implement than many of the more comprehensive national sur- vey efforts. Where appropriate, surveys and other monitoring and evalua- tion modalities of this sort will form a core component of operations under the Booster Program. APPENDIX 1 Outline of the Monitoring and Evaluation Framework A1.1 Support to Countries RESULTS CHAIN EXPECTED RESULTS Impact Reduction of all-cause child (under five) mortality (MDG 4) Improvement of maternal health (MDG 5) Reduction of malaria-specific morbidity and mortality (MDG 6) Reduction of productivity losses attributable to malaria Reduction of illness and absenteeism in school-age children and mitigation of other impediments to learning caused by malaria (MDG 2) Outcome Improved coverage, access, and utilization of technically sound and cost-effective program interventions for (i) prevention and (ii) treatment at community and facility levels, as appropriate Data-driven and evidence-based strategic management and decision making Output Good disease surveillance to track trends and ability to detect and respond promptly to epidemics Operational research (epidemiology and economics of malaria) to provide knowledge on (i) the cost-effectiveness of interventions in the country and (ii) resource flows, including malaria modules within national health accounts, household expenditures, public and private sector expenditures Viable M&E system (with baseline data, indicators, targets, staffing, capacity at all levels of program activity) that enables (i) data-driven/evidence-based decision making; (ii) the delineation and monitoring of accountabilities; and (iii) information of the public at large M&E system to be in line with technically sound consensus of the M&E reference Group of the RBM Partnership, including (i) vector control, (ii) prompt access to effective treatment for vulnerable populations, and (iii) prevention and control of malaria in pregnant women. 61 62 Rolling Back Malaria Strong leadership and commitment at all levels of government and among relevant sectors for high priority, intensified efforts to control malaria: · PRSPs and CASs have well-justified, prioritized, and sound strategies for fighting malaria with explicit goals and targets that fit country goals and strategies · Full integration of malaria control into national planning/budgeting frameworks (MTEFs and development plans) (and used as an instrument for donor coordination and collaboration) · Appropriate linkages with other sectors Technically sound, well-targeted, and well-implemented malaria program thanks to: · Technical knowledge and support · National capacity and trained personnel · Adequate and flexible/decentralized financing to accommodate needs of front-line implementers · Partnerships with other sectors and civil society; private sector in line with comparative advantages (underpinned by analytic work on capacity and comparative advantages) · Adequate infrastructure Inputs Lending and Grant Assistance (increase in funding for malaria programs) *see also matrix · Health sector and PRSC lending on Bank capacity · Board approval of the Booster Program building ­ Country-specific programs effective in at least 10 eligible countries by fiscal 2006­7 ­ 20 eligible countries (cumulative total) by fiscal 2008 · Mobilization of financing under other health lending instruments (PRSCs and SWAps) and reflected on MTEF ­ at least 5 countries by fiscal 2006­7 ­ at least 10 countries (cumulative) by fiscal 2008 · Other development sector lending · Malaria components in other, selected priority development sectors (number retrofitted, number incorporated into new projects) ­ Education ­ Agriculture ­ Infrastructure ­ Water ­ Environment ­ Other · Malaria addressed in CDD and other cross-cutting lending (e.g., public sector service delivery) (number retrofitted, number incorporated into new projects) Outline of the Monitoring and Evaluation Framework 63 Nonlending assistance and analytic and advisory services · Technical assistance/joint analytic work to: · Establish/complete baseline for malaria program, establish targets, and set up M&E system and plan · Elevate and justify its importance in PRSPs (burden of disease and its implica- tions for social and economic development and poverty reduction prospects) · Assessment of capacity and institutional/organizational frameworks for greater efficiencies and productive partnerships (government, central and decentralized; civil society; private sector [formal and informal]) A1.2 Support to Regional/Global Partnerships and Collective Efforts RESULTS CHAIN EXPECTED RESULTS Ultimate impact Reduction of all-cause child (under five) mortality (MDG 4) Improvement of maternal health (MDG 5) Reduction of malaria-specific morbidity and mortality (MDG 6) Reduction of productivity losses attributable to malaria Reduction of illness and absenteeism in school-age children and mitigation of other impediments to learning caused by malaria (MDG 2) Short-term impact Minimization of wasteful overlaps and gaps among partners by proactive focus on Bank's comparative advantage, including: · Evaluative and operational research · Medium- to long-term financing horizon · Cross-sectoral work · Budgeting/planning frameworks and fit with overall macroeconomic growth agenda · Selective support for product development and applied research · Convening power Improved coherence and evidence base of the Bank's and other partners' strategies and packages of assistance to countries through the development and dissemination of the Bank's knowledge and experience (macroeconomics, system-wide approach, cross-sectoral perspective, evaluations, operational research, and so forth) Outcome Improved (and well-earned) appreciation of the Bank's contribution to global malaria control efforts 64 Rolling Back Malaria Improved knowledge to inform evidence-based decision making and support (thanks to research on epidemiology, economics, development effectiveness of malaria). Improved knowledge base/continual update of approaches/strategies based on emerging best practices/technologies Shared information systems that enable coordination among agencies In coordination with other partners, subsidized antimalarial drugs available to any eligible purchaser from malaria-endemic countries in order to ensure universal access and to crowd out monotherapy Outputs High-impact operational research on epidemiology and economics of malaria, service delivery, and program management Evaluative research on development effectiveness of malaria control Inputs Implementation of strategic communications strategy to shape the global discussion around issues related to the Bank's comparative advantage among RBM partners. This will include dissemination of the Bank's strategy and program of action, progress toward meeting targets, implementation bottlenecks, research findings and implications, and so forth (See also the matrix on strengthened Bank capacity.) A1.3 Strengthening of Bank's Capacity to Contribute Effectively to Malaria Control (Achievement of this objective is an input into results chains for Support to Countries and Support to Global Efforts.) RESULTS CHAIN EXPECTED RESULTS Impact Improved quality and development effectiveness of the Bank's work on malaria Expanded scope, coverage, and intensity of Bank assistance on malaria Greater flexibility and client orientation Outcome Increase in the responsiveness of PRSPs and CASs to malaria control in malaria-endemic countries, measured by the consideration of the relationship between malaria and pov- erty, country strategies for malaria control, medium-term goals, and short-term actions Strong Bank leadership through the establishment of a high-level Steering Committee and commitment of World Bank country directors responsible for malaria-endemic coun- tries in the Bank, as evidenced by: · High priority accorded to malaria work · Intensified advocacy for malaria control in the context of PRSPs, country dialogue, and sector dialogues Outline of the Monitoring and Evaluation Framework 65 Output Bank strategy and program of action on malaria: available and being implemented M&E plan and system for M&E of its support to countries functional and in line with technically sound consensus of the M&E Reference Group of the RBM Partnership. These include (i) vector control, (ii) prompt access to effective treatment for vulnerable populations, and (iii) prevention and control of malaria in pregnant women. Guideline(s) to staff on assisting countries to develop malaria-responsive PRSPs and the preparation of malaria-responsive CASs, PRSCs, and SWAps in malaria-endemic countries Learning Strategy for the Bank produced Five learning sessions for Bank staff on important aspects of malaria control with emphasis on operational effectiveness (pending learning strategy) Board approval of new lending facility: Booster Program for Malaria Control (and effectiveness of country interventions--see country-level support) AAA work program including: · Effects of subsidies for antimalarial drugs and insecticide-treated nets on households, service providers, and program managers · Macroeconomic effects of increased expenditures for malaria control · Modalities to engage the formal and informal private sector · Web-based directory of technical and managerial resources for malaria control programs · Applied research on epidemiology, service delivery, and quality of care Multidisciplinary Malaria Advisory Service established and operational (jointly with WHO, MACEPA, RBM Secretariat, and other partners as appropriate and feasible) Development and implementation of a strategic communications program, including: · Documentation and dissemination of best practices and portfolio reviews of the Bank's (improved/expanded) performance Inputs Human resources--recruitment, training, mobilization of internal expertise for: · Lending and nonlending assistance to countries · Malaria task force · Steering committee Financial resources: · Administrative budget · Untied Trust Funds APPENDIX 2 Malarial Case Notification and Coverage with Key Interventions (Courtesy of RBM Department of WHO) Source: RBM Global Malaria Database: accessed February 7, 2005. Available online at: http://www.who.int/globalatlas/autologin/malaria_login.asp Notes on Available Information Reported epidemiological burden of malaria. This burden includes the annual malaria cases and deaths notified in Health Information Systems (HIS), recorded separately for laboratory-confirmed, clinically diagnosed, and imported cases as far as data were reported to WHO. Also, the total number of slides and rapid diagnostic tests taken (of which a part would have resulted in a confirmed case) are presented, if countries recorded and reported this information. Malaria case and death notifications are pre- sented for all countries thought to have malaria transmission and that reported at least one case of malaria to WHO that was not reported to have been imported from outside the country. Malaria cases clinically diagnosed denotes, for countries with very little or no reported laboratory confirmation of malaria cases, such as in most of Sub-Saharan Africa, clinically diagnosed malaria cases. For countries with routine laboratory confirmation of malaria diagnosis, this denotes probable or suspected malaria cases, and in the case of Pakistan, all patients with fever. For countries in the Pacific and selected countries in eastern Asia, clinically diagnosed cases denotes the number of suspected malaria cases minus the number of patients tested for malaria. These 67 68 Rolling Back Malaria probable cases do not include suspected malaria patients who test nega- tive during laboratory confirmation. Probable or clinically diagnosed severe cases denotes, for areas reporting only clinically diagnosed cases, clinically diagnosed patients requiring hospi- talization for signs or symptoms of severe malaria and receiving anti- malarial treatment. Probable or clinically diagnosed deaths denotes, for areas reporting only clini- cally diagnosed malaria cases, deaths among patients diagnosed with probable severe malaria. Parasitologically confirmed cases denotes, for areas performing laboratory con- firmation of malaria diagnosis, all patients with signs or symptoms of malaria and laboratory-confirmed diagnosis who received antimalarial treatment. Plasmodium falciparum or mixed denotes those cases laboratory-diagnosed as due to infection with Plasmodium falciparum or a mix of Plasmodia species including falciparum. Plasmodium vivax denotes those cases laboratory-diagnosed as due to infec- tion with Plasmodium vivax. Parasitologically confirmed severe cases denotes, among laboratory-diagnosed cases, the number requiring hospitalization for signs or symptoms of severe malaria and receiving antimalarial treatment. Parasitologically confirmed deaths denotes deaths among patients with a labo- ratory-confirmed diagnosis of severe malaria. Imported cases denotes malaria cases where the infection was acquired out- side the country in which it was diagnosed, implying that the origin could be traced to a known malarious area. The case notification rate is a standardized rate, per 1,000 persons per year, calculated against national population sizes in each calendar year as esti- mated by the UN Population Division. Standardized rates are derived from the rate of reported case notifications, based on an appreciation of what proportion of cases are laboratory confirmed. For countries where none of the reported cases were confirmed (as in most of Sub-Saharan Africa), the rate was based on probable/clinically diagnosed cases. For Malarial Case Notification and Coverage with Key Interventions 69 countries where all cases are laboratory confirmed, the rate was based on parasitologically confirmed cases minus imported cases. For the few countries where some cases were laboratory confirmed ("Some" in col- umn 5, for Somalia, Sudan, Afghanistan, and Yemen), the standardized rate was based on the sum of the mutually exclusive reported categories "Probable/clinically diagnosed" and "Parasitologically confirmed." Source of data: WHO annual reporting forms, country presentations, reports, and publications. Estimated coverage of the key RBM interventions according to the core indicators recommended by the RBM Monitoring & Evaluation Reference Group. These indicators include:19 · The percentage of households possessing at least one mosquito net, and possessing at least one ITN · The percentage of children under five years old and of pregnant women who slept under a net or an ITN during the night before a survey · The percentage (for African countries) of febrile children under five years old who received treatment with any antimalarial, with chloro- quine, and with SP. Each outcome is reported as the national estimate, where applicable and available, disaggregated by the background characteristics urban/rural and male/female. The treatment with antimalarials of febrile children is reported only for African countries, because outside Africa malaria makes up only a very small proportion of fevers reported in surveys. Africa-centered reporting possibly results in a misleadingly low coverage of antimalarial treatment; results may also be misleading because children under five are the only group consid- ered in this evaluation of the coverage of antimalarial treatment. Also, for African countries only, the period prevalence of fevers for children under five in the two weeks preceding a survey is reported as an indicator of the burden of malaria on African health systems. Source of data: Reports from household surveys, including DHS and Multiple Indicator Cluster Surveys (MICS) or cluster-sampled subnational surveys. Only surveys with appropriate documentation of dates of field work, sampling design, and sample sizes were included. 70 Rolling Back Malaria Data Table 1: Malarial Case Notification: Malaria Notifications for the Most Recent Year Information Received AFRICA STANDARDIZED MALARIA NOTIFICATIONS PROBABLE/CLINICALLY DIAGNOSED POPULATION RATE CONFIRMED YEAR (THOUSANDS) CASES PER 1,000 STATUS DEATHS SLIDES/RDTS CASES SEVERE DEATHS COUNTRY 1 2 3 4 5 6 7 8 9 10 Central Africa Cameroon 1998 14,458 664,413 45.96 NR 664,413 CAR 2003 3,865 95,644 24.75 NR Chad 2001 8,103 386,197 47.66 NR 1,001 386,197 19,463 Congo, Rep. of 1998 3,244 17,122 5.28 NR 17,122 Congo, Dem. Rep. of 2003 52,771 4,386,638 83.13 NR 16,498 4,386,638 16,498 Equatorial Guinea 1995 401 12,530 31.25 NR 12,530 Gabon 1998 1,202 80,247 66.78 NR 80,247 Sao Tome and Principe 2003 161 63,199 393.53 NR 63,199 East Africa Burundi 2002 6,602 1,808,588 273.96 NR 330 1,808,588 330 Comoros 2001 726 3,718 5.12 NR 16 3,718 820 16 Djibouti 2003 703 5,036 7.17 All Eritrea 2003 4,141 72,023 17.39 NR 78 72,023 78 Ethiopia 2003 70,678 565,273 8.00 All 1,210,868 Kenya 2002 31,540 124,197 3.94 NR 135 12,491 124,197 9,584 135 Rwanda 2003 8,387 856,233 102.09 Some 856,233 94,990 1,045 Somalia 2003 9,890 23,349 2.36 Some 10 12,578 15,778 44 Sudan 2003 33,610 3,084,320 91.77 Some 2,479 1,998,367 105,813 2,479 Uganda 2003 25,827 12,343,411 477.93 NR 8,450 12,343,411 8,450 UR Tanzania 2003 36,977 10,712,526 289.71 Some 14,156 3,116,332 10,712,526 521,019 14,156 Northern Africa Algeria 2002 31,266 52 <0.01 All 0 Egypt 2003 71,931 0 <0.01 All 0 1,041,767 Morocco 2003 30,566 4 <0.01 All 405,800 Notes: Please refer to explanatory notes for regional tabulations. NR = None Reported RDTs = Rapid Diagnostic Tests Pf/mixed = the number of reported Plasmodium falciparum or mixed cases Pv = the number of reported Plasmodium vivax cases Malarial Case Notification and Coverage with Key Interventions 71 NOTIFIED MALARIA CASES AND DEATHS DESCRIPTION LABORATORY CONFIRMED INVESTIGATIONS CASES PF/MIXED (%) PV SEVERE DEATHS IMPORTED (%) 11 12 13 14 15 16 17 18 5,036 565,273 395,964 70.0 158,115 411,069 7,571 7,571 100.0 10 1,085,853 1,509,236 307 188 61.2 116 0 255 83.1 45 44 97.8 1 45 100.0 73 62 84.9 69 94.5 72 Rolling Back Malaria Data Table 1, continued AFRICA, continued STANDARDIZED MALARIA NOTIFICATIONS PROBABLE/CLINICALLY DIAGNOSED POPULATION RATE CONFIRMED YEAR (THOUSANDS) CASES PER 1,000 STATUS DEATHS SLIDES/RDTS CASES SEVERE DEATHS COUNTRY 1 2 3 4 5 6 7 8 9 10 Southern Africa Angola 2002 13,184 1,409,328 106.90 NR 11,344 1,409,328 11,344 Botswana 2003 1,785 22,418 12.56 Some 10 22,418 Madagascar 2003 17,404 2,114,400 121.49 NR 759 2,114,400 10,359 759 Malawi 2002 11,871 2,853,317 240.36 NR 6,993 4,216,059 157,862 9,579 Mauritius 2002 1,210 22 0.02 NR 22 Mozambique 2003 18,863 5,087,865 269.72 NR 3,569 5,087,865 3,569 Namibia 2003 1,987 444,081 223.44 NR 1,095 444,081 20,968 1,095 South Africa 2003 45,026 13,446 0.30 NR 141 13,446 141 Swaziland 2003 1,077 36,664 34.03 NR 36,664 977 Zambia 2001 10,570 2,010,185 190.18 NR 5,763 2,010,185 162,709 5,763 Zimbabwe 2002 12,835 1,252,668 97.60 NR 626 599,416 626 Western Africa Benin 2001 6,387 779,041 121.98 NR 670 779,041 32,008 670 Burkina Faso 2002 12,624 1,451,125 114.95 NR 4,417 1,451,125 73,017 4,417 Cape Verde 2000 436 143 0.33 NR 143 Côte d'Ivoire 2001 16,098 400,402 24.87 NR 422 400,402 40,375 422 Gambia, The 1999 1,273 127,899 100.47 NR 127,899 Ghana 2003 20,922 3,552,869 169.81 Some 3,245 3,552,869 478,960 3,245 Guinea 2000 8,117 889,089 109.53 NR 441 889,089 14,933 441 Guinea-Bissau 2002 1,449 194,976 134.57 NR 780 194,976 66,703 780 Liberia 1998 2,580 777,754 301.51 NR 777,754 Mali 2003 13,007 809,428 62.23 NR 1,309 809,428 1,309 Mauritania 2002 2,807 167,423 59.64 NR 100 167,423 7,312 100 Niger 2002 11,544 681,707 59.05 NR 1,096 681,707 4,777 1,096 Nigeria 2003 124,009 2,608,479 21.03 NR 5,343 2,608,479 5,343 Senegal 2000 9,393 1,120,094 119.25 NR 1,337 1,120,094 36,860 1,337 Sierra Leone 1999 4,294 409,670 95.41 NR 409,670 Togo 2001 4,686 431,826 92.15 NR 791 431,826 12,904 791 Notes: Please refer to explanatory notes for regional tabulations. NR = None Reported RDTs = Rapid Diagnostic Tests Pf/mixed = the number of reported Plasmodium falciparum or mixed cases Pv = the number of reported Plasmodium vivax cases Malarial Case Notification and Coverage with Key Interventions 73 NOTIFIED MALARIA CASES AND DEATHS DESCRIPTION LABORATORY CONFIRMED INVESTIGATIONS CASES PF/MIXED (%) PV SEVERE DEATHS IMPORTED (%) 11 12 13 14 15 16 17 18 1,811 478,960 74 Rolling Back Malaria Data Table 1, continued ASIA STANDARDIZED MALARIA NOTIFICATIONS PROBABLE/CLINICALLY DIAGNOSED POPULATION RATE CONFIRMED YEAR (THOUSANDS) CASES PER 1,000 STATUS DEATHS SLIDES/RDTS CASES SEVERE DEATHS COUNTRY 1 2 3 4 5 6 7 8 9 10 Central Asia & Trans-Caucasus Armenia 2003 3,061 8 <0.01 All 0 Azerbaijan 2003 8,370 480 0.06 All 0 Georgia 2003 5,126 308 0.06 All 0 Kyrgyzstan 2003 5,138 465 0.09 All 0 Tajikistan 2003 6,245 5,428 0.87 All 0 Turkmenistan 2002 4,794 15 <0.01 All 0 Uzbekistan 2003 26,093 33 <0.01 All 0 Eastern Mediterranean Afghanistan 2003 23,897 591,441 24.75 Some 224,662 Iran 2003 68,920 17,060 0.25 All 1,358,262 0 Iraq 2003 25,175 303 0.01 All 0 581,938 0 0 Oman 2003 2,851 6 <0.01 All Pakistan 2003 153,578 122,560 0.80 All 29 4,145,290 3,985,915 29 Saudi Arabia 2003 24,217 596 0.02 All 0 819,869 Syrian Arab Republic 2003 17,800 2 <0.01 All Turkey 2003 71,325 9,182 0.13 All 0 United Arab Emirates 2003 2,995 0 <0.01 All 42,601 Yemen 2003 20,010 265,023 13.24 Some 29 414,919 214,212 South-East Asia Bangladesh 2003 146,736 56,879 0.39 All 574 434,723 434,723 1,250 Bhutan 2003 2,257 3,806 1.69 All 15 61,246 237 Korea, DPR 2003 22,664 16,538 0.73 All 0 32,083 46,251 0 0 India 2003 1,065,462 1,781,336 1.67 All 990 98,154,977 Indonesia 2002 217,131 220,073 1.01 All 197 1,298,194 1,355,714 Myanmar 2003 49,485 716,100 14.47 Some 2,476 849,517 539,929 Nepal 2003 25,164 9,394 0.37 All 3 195,376 56,640 Sri Lanka 2003 19,065 10,510 0.55 All 2 1,192,259 Thailand 2003 62,833 35,076 0.56 All 325 3,259,607 Timor Leste 2003 778 31,819 40.89 All 8 50,815 100,000 100 Notes: Please refer to explanatory notes for regional tabulations. NR = None Reported RDTs = Rapid Diagnostic Tests Pf/mixed = the number of reported Plasmodium falciparum or mixed cases Pv = the number of reported Plasmodium vivax cases Malarial Case Notification and Coverage with Key Interventions 75 NOTIFIED MALARIA CASES AND DEATHS DESCRIPTION LABORATORY CONFIRMED INVESTIGATIONS CASES PF/MIXED (%) PV SEVERE DEATHS IMPORTED (%) 11 12 13 14 15 16 17 18 29 4 13.8 0 21 72.4 482 0 0.0 0 2 0.4 316 2 0.6 0 8 2.5 468 1 0.2 0 3 0.6 5,428 250 4.6 0 0 0.0 18 0 0.0 0 3 16.7 74 0 0.0 0 41 55.4 366,779 44,243 12.1 322,536 23,562 4,475 19.0 18,818 131 6,502 27.6 307 0 0.0 307 0 0 4 1.3 740 299 40.4 734 99.2 125,152 39,944 31.9 85,240 14 2,592 2.1 1,724 1,234 71.6 462 0 1,128 65.4 24 13 54.2 10 22 91.7 9,222 12 0.1 0 40 0.4 1,796 405 22.6 1,796 100.0 50,811 48,741 95.9 29 56,879 42,012 73.9 14,867 10,332 574 3,806 1,681 44.2 2,126 1,621 15 16,538 0 0.0 16,538 0 0 1,781,336 845,173 47.4 936,163 990 220,073 71,202 32.4 148,871 197 176,171 139,315 79.1 74,833 12,962 2,476 9,394 1,218 13.0 8,177 3 10,510 1,273 12.1 9,237 2 37,355 19,024 50.9 18,295 325 2,279 6.1 31,819 17,370 54.6 14,449 409 8 76 Rolling Back Malaria Data Table 1, continued ASIA, continued STANDARDIZED MALARIA NOTIFICATIONS PROBABLE/CLINICALLY DIAGNOSED POPULATION RATE CONFIRMED YEAR (THOUSANDS) CASES PER 1,000 STATUS DEATHS SLIDES/RDTS CASES SEVERE DEATHS COUNTRY 1 2 3 4 5 6 7 8 9 10 Western Pacific Cambodia 2003 14,144 71,258 5.04 All 492 160,326 4,936 China 2002 1,294,867 25,520 0.02 All 42 Lao PDR 2003 5,657 18,894 3.34 All 187 256,534 Malaysia 2003 24,425 5,477 0.22 All 21 Papua New Guinea 2003 5,711 70,226 12.30 All 537 1,729,697 17,590 537 Philippines 2003 79,999 43,644 0.55 All Korea, Rep. of 2003 47,700 1,107 0.02 All 0 Solomon Islands 2003 477 90,606 189.94 All 71 297,897 71 Vanuatu 2003 212 15,240 71.90 All 0 Vietnam 2003 81,377 37,416 0.46 All 50 2,738,600 12,694 423 4 Notes: Please refer to explanatory notes for regional tabulations. NR = None Reported RDTs = Rapid Diagnostic Tests Pf/mixed = the number of reported Plasmodium falciparum or mixed cases Pv = the number of reported Plasmodium vivax cases Malarial Case Notification and Coverage with Key Interventions 77 NOTIFIED MALARIA CASES AND DEATHS DESCRIPTION LABORATORY CONFIRMED INVESTIGATIONS CASES PF/MIXED (%) PV SEVERE DEATHS IMPORTED (%) 11 12 13 14 15 16 17 18 71,258 63,739 89.4 492 25,520 5,937 23.3 42 18,894 17,878 94.6 1,016 187 6,338 2,884 45.5 3,127 421 21 861 13.6 70,226 55,638 79.2 43,644 1,107 0 0.0 1,107 0 0 90,606 64,302 71.0 26,304 15,240 8,406 55.2 0 37,416 29,435 78.7 46 78 Rolling Back Malaria Data Table 1, continued THE AMERICAS STANDARDIZED MALARIA NOTIFICATIONS PROBABLE/CLINICALLY DIAGNOSED POPULATION RATE CONFIRMED YEAR (THOUSANDS) CASES PER 1,000 STATUS DEATHS SLIDES/RDTS CASES SEVERE DEATHS COUNTRY 1 2 3 4 5 6 7 8 9 10 Central America & Caribbean Belize 2002 251 928 3.70 All 0 15,480 Costa Rica 2003 4,173 718 0.17 All 0 9,622 Dominican Republic 2003 8,745 1,296 0.15 All 16 391,216 El Salvador 2003 6,515 85 0.01 All 102,053 Guatemala 2003 12,347 31,127 2.52 All 0 156,227 Haiti 2003 8,326 9,837 1.18 All 16 51,067 Honduras 2003 6,941 10,122 1.46 All 0 90,575 Mexico 2003 103,457 4,289 0.04 All 0 1,577,647 Nicaragua 2003 5,466 6,812 1.25 All 0 449,839 Panama 2003 3,120 13,365 4.28 All 3 333,622 South America Argentina 2003 38,428 122 0.00 All 0 3,977 Bolivia 2003 8,808 20,343 2.31 All 2 158,299 Brazil 2003 178,470 379,551 2.13 All 30 1,474,656 Colombia 2003 44,222 164,722 3.72 All 24 520,980 Ecuador 2003 13,003 52,065 4.00 All 0 433,244 French Guiana 2003 178 3,823 21.49 All 0 46,548 Guyana 2003 765 27,627 36.09 All 185,877 Paraguay 2003 5,878 1,392 0.24 All 0 126,582 Peru 2003 27,167 143,686 5.29 All 34 1,426,410 Suriname 2003 436 14,657 33.65 All 70,670 Venezuela 2003 25,699 31,719 1.23 All 346,586 Notes: Please refer to explanatory notes for regional tabulations. NR = None Reported RDTs = Rapid Diagnostic Tests Pf/mixed = the number of reported Plasmodium falciparum or mixed cases Pv = the number of reported Plasmodium vivax cases Malarial Case Notification and Coverage with Key Interventions 79 NOTIFIED MALARIA CASES AND DEATHS DESCRIPTION LABORATORY CONFIRMED INVESTIGATIONS CASES PF/MIXED (%) PV SEVERE DEATHS IMPORTED (%) 11 12 13 14 15 16 17 18 928 0 0.0 928 0 718 14 1.9 704 0 1,296 1,034 79.8 4 16 85 2 2.4 83 31,127 1,310 4.2 29,817 5 0 9,837 9,837 100.0 0 16 10,122 323 3.2 9,799 0 4,289 17 0.4 4,272 0 6,812 1,245 18.3 5,567 0 13,365 627 4.7 3,873 3 122 0 0.0 122 0 20,343 793 3.9 17,319 2 379,551 81,343 21.4 297,962 10,719 30 164,722 69,238 42.0 95,484 24 52,065 10,724 20.6 41,341 0 3,823 3,166 82.8 657 0 27,627 12,970 46.9 14,654 1,392 3 0.2 1,389 0 143,686 30,045 20.9 113,538 34 14,657 13,043 89.0 1,614 31,719 5,562 17.5 26,111 80 Rolling Back Malaria Data Table 2: Malarial Case Notification: Standardized Malaria Notifications and Notification Rates per 1,000, since 1990 AFRICA 1990 1991 1992 1993 1994 1995 1996 1997 Central Africa Cameroon 869,048 787,796 664,413 478,693 189,066 784,321 931,311 787,796 74.5 65.6 53.8 37.7 14.5 58.5 67.7 55.8 CAR 174,436 125,038 89,930 82,072 82,057 100,962 95,259 99,718 59.3 41.4 29.0 25.8 25.1 30.1 27.7 28.4 Chad 212,554 246,410 229,444 234,869 278,225 293,564 278,048 343,186 36.5 41.1 37.2 37.0 42.6 43.6 40.1 47.9 Congo, Rep. of 32,428 32,391 21,121 15,504 35,957 28,008 14,000 9,491 13.0 12.6 7.9 5.6 12.7 9.5 4.6 3.0 Congo, Dem Rep. of 198,064 4.4 Equatorial Guinea 25,552 22,598 25,100 17,867 14,827 12,530 72.3 62.5 67.7 46.9 37.9 31.3 Gabon 57,450 80,247 100,629 70,928 82,245 54,849 74,310 57,450 60.3 81.6 99.2 67.8 76.3 49.4 65.2 49.0 São Tomé and Principe 51,938 47,074 47,757 396.3 350.1 346.2 East Africa Burundi 92,870 568,938 773,539 828,429 831,481 932,794 974,226 670,857 16.6 99.4 132.9 140.4 139.3 154.9 160.8 110.3 Comoros 12,012 13,860 15,707 15,509 20.9 23.4 25.8 24.7 Djibouti 3,237 7,338 7,468 4,166 6,140 5,982 6,105 4,314 6.1 13.5 13.6 7.5 11.0 10.5 10.5 7.1 Eritrea 81,183 129,908 25.3 39.7 Ethiopia 206,262 305,616 358,469 412,609 478,411 509,804 4.0 5.7 6.4 7.2 8.1 8.4 Kenya 6,103,447 4,343,190 3,777,022 228.9 158.6 134.5 Rwanda 1,282,012 1,331,494 1,373,247 733,203 371,550 1,391,931 1,145,759 1,331,494 189.2 204.7 226.7 131.7 71.2 271.0 213.0 226.0 Somalia 3,049 0.4 Sudan 7,508,704 6,947,787 9,326,944 9,867,778 8,562,205 6,347,143 4,595,092 4,065,460 301.2 272.5 357.3 368.9 312.3 226.1 159.9 138.3 Uganda 2,446,659 1,470,662 2,191,277 1,431,068 2,317,840 132.1 77.0 111.3 70.6 107.9 Tanzania 10,715,736 8,715,736 7,681,524 8,777,340 7,976,590 2,438,040 4,969,273 1,131,655 411.1 322.9 274.7 303.2 266.6 79.0 156.6 34.8 Malarial Case Notification and Coverage with Key Interventions 81 1998 1999 2000 2001 2002 2003 664,413 46.0 105,664 127,964 89,614 140,742 95,644 29.5 35.0 24.1 37.3 24.7 395,205 392,815 369,263 386,197 53.5 51.5 47.0 47.7 17,122 5.3 141,353 1,508,042 964,623 2,199,247 2,640,168 4,386,638 3.0 31.7 19.9 44.2 51.6 83.1 80,247 66.8 46,026 37,026 43,488 55,630 66,619 63,199 325.1 254.9 291.9 364.1 425.2 393.5 687,301 1,936,584 3,057,239 2,855,868 1,808,588 112.4 313.9 487.9 445.4 274.0 3,844 9,793 9,618 3,718 5.8 14.3 13.6 5.1 5,920 6,140 4,667 4,312 5,021 5,036 9.5 9.5 7.0 6.3 7.2 7.2 255,150 147,062 119,155 125,746 75,386 72,023 73.6 41.0 32.1 32.7 18.9 17.4 604,960 647,919 383,382 400,371 427,831 565,273 9.7 10.1 5.8 6.0 6.2 8.0 80,718 122,792 74,194 132,590 124,197 2.7 4.1 2.4 4.3 3.9 1,279,581 906,552 915,916 856,233 195.1 125.7 118.6 102.1 9,055 10,364 10,364 96,922 23,349 1.1 1.2 1.1 10.2 2.4 5,062,000 4,215,308 4,332,827 3,985,702 3,056,400 3,084,320 168.4 137.1 137.8 124.0 93.0 91.8 2,845,811 3,070,800 3,552,859 5,622,934 7,216,411 12,343,411 128.6 134.8 151.3 232.1 288.6 477.9 30,504,654 423,967 7,489,890 10,712,526 915.1 12.4 206.5 289.7 82 Rolling Back Malaria Data Table 2, continued AFRICA, continued 1990 1991 1992 1993 1994 1995 1996 1997 Northern Africa Algeria 152 229 106 84 206 107 221 197 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 Egypt 75 24 16 17 495 313 23 4 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 Morocco 837 494 405 198 158 166 53 76 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 Southern Africa Angola 243,673 1,143,701 782,988 722,981 667,376 156,603 893,232 26.1 119.0 79.0 70.6 63.2 14.4 78.0 Botswana 10,750 14,364 4,995 55,331 29,591 17,599 80,004 101,887 7.9 10.3 3.5 37.6 19.6 11.4 50.4 62.6 Madagascar 196,358 14.2 Malawi 3,870,904 7,590,313 4,686,201 4,736,974 6,164,666 6,183,290 2,761,269 409.3 774.8 475.5 477.4 613.6 603.5 263.0 Mauritius 54 48 66 54 65 46 82 65 0.1 <0.1 0.1 <0.1 0.1 <0.1 0.1 0.1 Mozambique 12,794 0.8 Namibia 380,530 401,519 275,442 345,177 390,601 245.2 251.3 167.3 203.4 223.2 South Africa 6,822 4,693 2,872 13,285 10,289 8,750 27,035 23,121 0.2 0.1 0.1 0.3 0.3 0.2 0.6 0.5 Swaziland 13,749 38,875 23,754 14.6 40.5 24.2 Zambia 1,933,696 2,340,994 2,953,692 3,514,000 3,514,000 2,742,118 3,215,866 235.8 277.5 340.6 394.5 384.5 292.6 335.0 Zimbabwe 662,613 581,168 420,137 877,734 324,188 761,791 1,696,192 1,849,383 63.3 54.0 38.1 77.9 28.2 64.9 142.0 152.2 Malarial Case Notification and Coverage with Key Interventions 83 1998 1999 2000 2001 2002 2003 256 701 63 53 52 <0.1 <0.1 <0.1 <0.1 <0.1 0 0 0 0 0 0 0 0 0 0 0 0 68 17 3 0 20 4 <0.1 <0.1 <0.1 0 <0.1 <0.1 1,169,028 1,471,993 1,635,884 1,385,597 1,409,328 99.6 122.2 132.1 108.5 106.9 59,696 72,640 71,403 48,237 28,858 22,418 35.9 42.8 41.4 27.6 16.3 12.6 1,141,474 1,383,239 1,429,491 1,543,130 2,114,400 73.6 86.6 87.0 91.2 121.5 2,985,659 4,193,145 3,774,982 2,955,627 2,853,317 276.6 378.1 332.0 254.2 240.4 0 0 0 0 22 0 0 0 0 <0.1 194,024 2,336,640 3,278,525 3,978,397 4,458,589 5,087,865 11.3 133.4 183.6 218.6 240.5 269.7 353,110 429,571 519,113 537,115 442,527 444,081 196.0 232.1 274.2 278.3 225.6 223.4 26,445 51,444 64,622 26,506 15,649 13,446 0.6 1.2 1.5 0.6 0.3 0.3 4,410 30,420 45,581 19,799 14,863 36,664 4.4 29.6 43.6 18.7 13.9 34.0 3,399,630 2,992,203 1,139,489 2,010,185 338.5 292.1 109.4 190.2 1,719,960 1,804,479 1,533,960 1,609,296 1,252,668 139.3 144.2 121.3 126.2 97.6 84 Rolling Back Malaria Data Table 2, continued AFRICA, continued 1990 1991 1992 1993 1994 1995 1996 1997 Western Africa Benin 92,870 118,796 290,868 403,327 546,827 579,300 623,396 670,857 20.0 24.7 58.5 78.5 103.0 105.9 110.9 116.2 Burkina Faso 496,513 448,917 420,186 502,275 472,355 501,020 582,658 672,752 55.7 48.9 44.5 51.6 47.2 48.6 54.9 61.6 Cape Verde 69 80 38 44 21 127 77 20 0.2 0.2 0.1 0.1 0.1 0.3 0.2 <0.1 Côte d'Ivoire 511,916 466,895 553,875 421,043 755,812 1,109,011 983,089 40.9 36.2 41.7 30.8 52.6 75.5 65.6 Gambia, The 222,538 215,414 188,035 299,824 135,909 266,189 325,555 237.7 221.9 187.0 278.3 121.9 230.8 272.9 Ghana 1,438,713 1,372,771 1,446,947 1,697,109 1,672,709 1,928,316 2,189,860 2,227,762 94.2 87.4 89.5 102.1 98.0 110.1 122.1 121.4 Guinea 21,762 17,718 607,560 600,317 772,731 802,210 3.6 2.8 85.6 82.0 102.8 104.3 Guinea-Bissau 81,835 64,123 56,073 158,748 197,386 6,457 10,632 80.5 61.2 51.8 142.0 165.9 5.3 8.4 Liberia 430,085 534,559 362,774 239,998 826,151 209.1 258.2 170.4 107.2 344.9 Mali 248,904 282,256 280,562 295,737 263,100 95,357 29,818 384,907 27.5 30.4 29.4 30.2 26.1 9.2 2.8 35.2 Mauritania 26,903 42,112 45,687 43,892 156,080 214,478 181,204 189,571 13.3 20.3 21.4 20.1 69.7 93.3 76.7 78.1 Niger 1,162,824 808,968 865,976 726,666 806,204 778,175 1,162,824 978,855 152.0 102.3 106.0 86.0 92.3 86.1 124.4 101.2 Nigeria 1,116,992 909,656 1,219,348 981,943 1,175,004 1,133,926 1,149,435 1,148,542 13.0 10.3 13.4 10.4 12.1 11.4 11.2 10.9 Senegal 450,071 628,773 861,276 55.3 75.4 98.5 Sierra Leone 9,636 16,851 5,865 7,192 209,312 2.4 4.1 1.4 1.8 50.5 Togo 810,509 780,825 634,166 561,328 328,488 297,326 352,334 366,672 234.6 220.9 175.7 152.4 87.2 76.9 88.3 88.8 Malarial Case Notification and Coverage with Key Interventions 85 1998 1999 2000 2001 2002 2003 650,025 709,348 707,408 779,041 109.9 116.9 113.7 122.0 721,480 867,866 1,032,886 1,203,640 1,451,125 64.2 75.1 86.8 98.2 114.9 41 29 143 0.1 0.1 0.3 1,491,943 400,402 94.3 24.9 127,899 100.5 1,745,214 2,895,079 3,349,528 3,383,025 2,830,784 3,552,869 93.0 151.0 171.0 168.9 138.3 169.8 817,949 807,895 889,089 104.3 101.2 109.5 2,113 197,454 246,316 202,379 194,976 1.6 148.6 180.2 143.9 134.6 777,754 301.5 12,234 530,197 546,634 612,895 723,077 809,428 1.1 45.8 45.9 50.0 57.3 62.2 168,131 253,513 259,093 243,942 167,423 67.3 98.7 98.0 89.5 59.6 872,925 815,895 646,757 606,802 681,707 87.2 78.7 60.2 54.5 59.1 2,122,663 1,965,486 2,476,608 2,253,519 2,605,381 2,608,479 19.5 17.6 21.6 19.1 21.5 21.0 948,823 1,145,112 1,120,094 105.9 124.9 119.3 249,744 409,670 59.4 95.4 368,472 412,619 398,103 431,826 86.1 93.3 87.3 92.1 86 Rolling Back Malaria Data Table 2, continued ASIA 1990 1991 1992 1993 1994 1995 1996 1997 Central Asia & Trans-Caucasus Armenia 0 0 0 0 1 0 149 567 0 0 0 0 <0.1 0 <0.1 0.2 Azerbaijan 24 113 27 23 667 2,840 13,135 9,911 <0.1 <0.1 <0.1 <0.1 0.1 0.4 1.7 1.2 Georgia 0 0 0 0 0 0 3 0 0 0 0 0 0 0 <0.1 0 Kyrgyzstan 0 0 0 0 0 0 1 0 0 0 0 0 0 0 <0.1 0 Tajikistan 175 294 404 619 2,411 6,103 16,561 29,794 <0.1 0.1 0.1 0.1 0.4 1.1 2.8 5.1 Turkmenistan 0 13 5 1 1 0 3 4 0 <0.1 <0.1 <0.1 <0.1 0 <0.1 <0.1 Uzbekistan 3 1 0 0 0 0 0 0 <0.1 <0.1 0 0 0 0 0 0 Eastern Mediterranean Afghanistan 317,479 297,605 88,302 303,955 202,767 23.0 20.3 4.8 15.3 10.0 Iran 77,470 96,340 76,971 64,581 51,089 67,532 56,362 38,684 1.4 1.7 1.3 1.1 0.8 1.1 0.9 0.6 Iraq 3,924 1,764 5,752 49,863 98,243 98,705 49,840 13,959 0.2 0.1 0.3 2.6 5.0 4.9 2.4 0.7 Oman 32,720 19,274 14,827 16,873 7,083 1,164 603 129 17.7 10.0 7.4 8.1 3.3 0.5 0.3 0.1 Pakistan 79,689 66,586 99,015 92,634 108,586 109,792 98,035 77,480 0.7 0.6 0.8 0.8 0.9 0.9 0.8 0.6 Saudi Arabia 15,666 9,962 19,623 18,380 10,032 15,662 15,221 17,692 0.9 0.6 1.1 1.0 0.5 0.8 0.8 0.9 Syrian Arab Republic 107 54 456 966 583 582 280 83 <0.1 <0.1 <0.1 0.1 <0.1 <0.1 <0.1 <0.1 Turkey 8,675 12,213 18,665 47,206 84,321 81,754 60,634 35,376 0.2 0.2 0.3 0.8 1.4 1.3 0.9 0.5 United Arab Emirates 3,514 3,457 3,605 3,735 3,335 8 2,863 1 1.7 1.6 1.6 1.6 1.4 <0.1 1.1 <0.1 Yemen 11,384 12,717 29,320 31,262 37,201 500,000 416,246 1,394,495 1.0 1.0 2.2 2.3 2.6 33.1 26.5 85.6 Malarial Case Notification and Coverage with Key Interventions 87 1998 1999 2000 2001 2002 2003 542 329 56 31 16 8 0.2 0.1 <0.1 <0.1 <0.1 <0.1 5,175 2,311 1,526 1,054 505 480 0.6 0.3 0.2 0.1 0.1 0.1 14 35 244 437 473 308 <0.1 <0.1 <0.1 0.1 0.1 0.1 5 0 7 15 2,712 465 <0.1 0 <0.1 <0.1 0.5 0.1 19,351 13,493 19,064 11,387 6,160 5,428 3.2 2.2 3.1 1.9 1.0 0.9 115 10 18 5 15 <0.1 <0.1 <0.1 <0.1 <0.1 0 7 46 9 11 33 0 <0.1 <0.1 <0.1 <0.1 <0.1 288,070 395,581 203,911 364,243 590,176 591,441 14.0 18.9 9.5 16.5 25.7 24.7 32,951 23,110 19,716 8,895 9,122 17,060 0.5 0.4 0.3 0.1 0.1 0.2 9,684 4,143 1,860 1,265 952 303 0.4 0.2 0.1 0.1 <0.1 <0.1 116 30 6 2 6 6 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 73,516 91,774 82,526 104,003 101,761 122,560 0.5 0.7 0.6 0.7 0.7 0.8 36,139 10,099 4,736 1,614 1,226 596 1.7 0.5 0.2 0.1 0.1 <0.1 14 5 6 63 15 2 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 36,780 20,908 11,381 10,758 10,184 9,182 0.6 0.3 0.2 0.2 0.1 0.1 0 0 0 0 0 0 0 0 0 0 0 0 2,781,640 1,394,495 187,159 265,023 159.7 77.4 9.7 13.2 88 Rolling Back Malaria Data Table 2, continued ASIA, continued 1990 1991 1992 1993 1994 1995 1996 1997 South-East Asia Bangladesh 53,875 63,578 115,660 125,402 166,564 152,729 100,864 68,594 0.5 0.6 1.0 1.1 1.4 1.2 0.8 0.5 Bhutan 9,497 22,126 28,900 28,116 39,852 23,188 15,696 9,029 5.6 12.8 16.6 15.9 22.3 12.8 8.5 4.8 Korea, DPR India 2,018,783 2,117,460 2,125,826 2,207,431 2,511,453 2,988,231 3,035,588 2,660,057 2.4 2.5 2.4 2.5 2.7 3.2 3.2 2.8 Indonesia 171,908 132,412 103,277 136,367 145,920 123,226 179,878 161,285 0.9 0.7 0.5 0.7 0.8 0.6 0.9 0.8 Maldives 16 27 25 29 16 17 9 10 0.1 0.1 0.1 0.1 0.1 0.1 <0.1 <0.1 Myanmar 989,042 939,257 789,672 702,239 701,043 656,547 664,507 568,262 24.4 22.8 18.8 16.5 16.2 14.9 14.8 12.5 Nepal 22,856 29,135 23,234 16,380 9,442 9,718 6,628 8,957 1.2 1.5 1.2 0.8 0.5 0.5 0.3 0.4 Sri Lanka 287,384 400,263 399,349 327,020 273,434 142,294 184,319 218,550 17.1 23.5 23.2 18.8 15.5 8.0 10.3 12.1 Thailand 273,880 198,383 168,370 115,220 102,119 82,743 87,622 97,540 5.0 3.6 3.0 2.0 1.8 1.4 1.5 1.7 Timor Leste Western Pacific Cambodia 123,796 102,930 93,595 98,956 74,190 76,923 74,883 85,661 12.7 10.2 9.0 9.2 6.7 6.7 6.3 7.0 China 89,000 83,000 74,000 59,000 62,000 47,118 33,382 26,800 0.1 0.1 0.1 <0.1 0.1 <0.1 <0.1 <0.1 Lao PDR 22,044 41,048 39,904 41,556 53,707 52,021 51,544 54,133 5.3 9.7 9.2 9.3 11.7 11.1 10.7 11.0 Malaysia 50,500 39,189 36,853 39,890 58,958 59,208 52,060 26,651 2.8 2.1 2.0 2.1 3.0 2.9 2.5 1.2 Papua New Guinea 104,900 86,500 86,500 66,797 65,000 99,000 71,013 38,105 25.5 20.5 19.9 15.0 14.2 21.1 14.7 7.7 Philippines 86,200 86,400 95,778 64,944 61,959 56,852 40,545 42,005 1.4 1.4 1.5 1.0 0.9 0.8 0.6 0.6 Republic of Korea 0 0 0 1 20 107 396 1,724 0 0 0 <0.1 <0.1 <0.1 <0.1 <0.1 Malarial Case Notification and Coverage with Key Interventions 89 1998 1999 2000 2001 2002 2003 60,023 63,738 55,599 55,646 55,646 56,879 0.5 0.5 0.4 0.4 0.4 0.4 7,693 12,237 5,935 5,982 6,511 3,806 3.9 6.1 2.9 2.8 3.0 1.7 1,085 7,980 73,742 115,615 98,852 16,538 <0.1 0.4 3.3 5.2 4.4 0.7 2,222,748 2,284,713 2,031,790 2,085,484 1,842,019 1,781,336 2.3 2.3 2.0 2.0 1.8 1.7 160,282 245,612 267,592 220,073 0.8 1.2 1.2 1.0 25 20 0 0 0 0 0.1 0.1 0 0 0 0 548,066 591,826 592,354 661,463 721,739 716,100 11.9 12.6 12.5 13.7 14.8 14.5 8,498 8,959 7,616 6,408 12,786 9,394 0.4 0.4 0.3 0.3 0.5 0.4 211,691 264,549 210,039 66,522 41,411 10,510 11.6 14.3 11.3 3.5 2.2 0.6 131,055 125,379 81,692 63,528 45,240 35,076 2.2 2.1 1.3 1.0 0.7 0.6 10,332 49,836 63,440 26,651 31,819 13.8 71.0 89.2 36.1 40.9 58,874 64,679 62,439 53,601 46,902 71,258 4.7 5.0 4.7 4.0 3.4 5.0 27,090 26,797 18,620 26,945 25,520 <0.1 <0.1 <0.1 <0.1 <0.1 41,039 28,096 40,023 26,932 21,384 18,894 8.1 5.4 7.6 5.0 3.9 3.3 13,491 11,106 12,705 12,780 11,019 5,477 0.6 0.5 0.6 0.5 0.5 0.2 20,900 18,564 81,192 89,819 79,822 70,226 4.1 3.6 15.2 16.4 14.3 12.3 50,709 37,061 36,596 34,787 37,005 43,644 0.7 0.5 0.5 0.5 0.5 0.5 3,992 3,621 4,142 2,488 1,763 1,107 0.1 0.1 0.1 0.1 <0.1 <0.1 90 Rolling Back Malaria Data Table 2, continued ASIA, continued 1990 1991 1992 1993 1994 1995 1996 1997 Western Pacific, continued Solomon Islands 116,500 141,400 153,359 126,123 131,687 118,521 84,795 68,125 365.7 429.9 451.5 359.6 363.6 316.9 219.7 171.0 Vanuatu 28,805 19,466 12,842 11,483 5,765 11,954 5,740 6,103 192.7 126.7 81.3 70.6 34.4 69.4 32.4 33.5 Vietnam 123,796 187,994 225,928 156,069 140,120 100,116 76,356 65,859 1.9 2.8 3.3 2.2 2.0 1.4 1.0 0.9 Malarial Case Notification and Coverage with Key Interventions 91 1998 1999 2000 2001 2002 2003 72,808 63,169 67,884 76,417 74,865 90,606 177.2 149.1 155.4 169.8 161.5 189.9 6,181 5,180 6,422 7,647 14,339 15,240 33.1 27.0 32.6 37.9 69.3 71.9 72,091 64,679 62,442 53,601 46,902 37,416 0.9 0.8 0.8 0.7 0.6 0.5 92 Rolling Back Malaria Data Table 2, continued THE AMERICAS 1990 1991 1992 1993 1994 1995 1996 1997 Central America & Caribbean Belize 3,033 3,317 5,341 8,586 9,957 9,413 6,605 4,014 16.3 17.4 27.2 42.5 47.9 44.1 30.2 17.9 Costa Rica 1,151 3,273 6,951 5,033 4,445 4,515 5,480 4,712 0.4 1.0 2.2 1.5 1.3 1.3 1.5 1.3 Dominican Republic 356 377 698 987 1,670 1,808 1,414 816 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.1 El Salvador 9,269 5,933 4,539 3,887 2,803 3,362 5,888 2,719 1.8 1.1 0.9 0.7 0.5 0.6 1.0 0.5 Guatemala 41,711 57,829 57,560 41,868 22,057 24,178 20,268 32,099 4.8 6.4 6.2 4.4 2.3 2.4 2.0 3.0 Haiti 4,806 25,511 13,457 853 23,140 18,877 0.7 3.6 1.9 0.1 3.1 2.5 Honduras 53,095 73,352 70,838 44,513 52,110 59,446 74,487 65,863 10.9 14.6 13.7 8.4 9.5 10.5 12.8 11.0 Mexico 44,513 26,565 16,170 15,793 12,864 7,316 6,293 5,046 0.5 0.3 0.2 0.2 0.1 0.1 0.1 0.1 Nicaragua 35,785 27,653 26,866 44,037 41,490 69,444 75,606 42,819 9.4 7.0 6.6 10.6 9.7 15.7 16.6 9.1 Panama 381 1,115 727 481 684 730 476 505 0.2 0.5 0.3 0.2 0.3 0.3 0.2 0.2 South America Argentina 1,660 803 643 758 948 1,065 2,048 592 0.1 <0.1 <0.1 <0.1 <0.1 <0.1 0.1 <0.1 Bolivia 19,680 19,031 24,486 27,475 34,749 46,911 64,012 51,478 3.0 2.8 3.5 3.8 4.8 6.3 8.4 6.6 Brazil 560,396 614,431 609,860 466,190 564,406 565,727 455,194 392,976 3.8 4.1 4.0 3.0 3.6 3.5 2.8 2.4 Colombia 99,489 184,156 184,023 129,377 127,218 187,082 135,923 180,898 2.8 5.2 5.1 3.5 3.4 4.9 3.5 4.5 Ecuador 71,670 59,400 41,089 46,859 30,006 18,128 11,882 16,365 7.0 5.7 3.8 4.3 2.7 1.6 1.0 1.4 French Guiana 5,909 3,573 4,072 3,974 4,241 4,711 4,724 3,195 50.8 29.5 32.4 30.6 31.6 34.0 32.9 21.5 Guyana 22,681 42,204 39,702 33,172 39,566 59,311 32,103 31.0 57.8 54.3 45.2 53.6 80.0 42.9 Malarial Case Notification and Coverage with Key Interventions 93 1998 1999 2000 2001 2002 2003 2,614 1,850 1,486 1,097 928 11.4 7.9 6.2 4.5 3.7 5,148 3,998 1,879 1,363 1,021 718 1.4 1.0 0.5 0.3 0.2 0.2 2,006 3,589 1,215 1,038 1,296 1,296 0.2 0.4 0.1 0.1 0.2 0.1 1,182 1,230 745 362 117 85 0.2 0.2 0.1 0.1 <0.1 <0.1 47,689 45,098 53,311 35,824 35,540 31,127 4.4 4.1 4.7 3.1 3.0 2.5 34,449 1,196 16,897 9,837 9,837 4.4 0.2 2.1 1.2 1.2 42,979 46,740 35,122 24,023 17,223 10,122 7.0 7.4 5.4 3.6 2.5 1.5 14,451 6,402 7,390 4,831 4,289 4,289 0.2 0.1 0.1 <0.1 <0.1 <0.1 33,903 38,676 24,014 10,482 7,466 6,812 7.0 7.8 4.7 2.0 1.4 1.2 1,039 936 1,036 928 2,244 13,365 0.4 0.3 0.4 0.3 0.7 4.3 339 222 440 215 215 122 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 73,913 50,037 31,468 15,765 14,276 20,343 9.3 6.1 3.8 1.9 1.7 2.3 471,892 609,594 610,878 388,658 349,873 379,551 2.8 3.6 3.6 2.2 2.0 2.1 185,455 66,845 107,616 206,195 195,719 164,722 4.6 1.6 2.6 4.8 4.5 3.7 43,696 87,620 98,598 108,903 86,757 52,065 3.6 7.2 7.9 8.6 6.8 4.0 3,462 5,307 3,708 3,823 3,661 3,823 22.5 33.3 22.6 22.6 21.1 21.5 41,200 27,283 24,018 27,122 21,895 27,627 54.8 36.1 31.7 35.6 28.7 36.1 94 Rolling Back Malaria Data Table 2, continued THE AMERICAS, continued 1990 1991 1992 1993 1994 1995 1996 1997 South America, continued Paraguay 2,912 2,983 1,289 436 583 898 637 567 0.7 0.7 0.3 0.1 0.1 0.2 0.1 0.1 Peru 28,882 33,705 54,922 95,222 122,039 192,629 208,132 183,740 1.3 1.5 2.4 4.1 5.2 8.1 8.6 7.4 Suriname 1,608 1,490 1,404 4,704 6,606 16,649 11,323 4.0 3.7 3.5 11.5 16.1 40.4 27.3 Venezuela 46,910 43,454 21,416 12,539 13,727 16,371 18,858 22,400 2.4 2.2 1.0 0.6 0.6 0.7 0.8 1.0 Malarial Case Notification and Coverage with Key Interventions 95 1998 1999 2000 2001 2002 2003 2,091 9,947 6,853 2,710 2,778 1,392 0.4 1.9 1.3 0.5 0.5 0.2 247,004 166,579 69,726 79,473 85,742 143,686 9.8 6.5 2.7 3.0 3.2 5.3 12,412 13,939 13,132 17,074 13,091 14,657 29.7 33.1 30.9 39.8 30.3 33.7 21,862 19,086 29,736 29,491 29,491 31,719 0.9 0.8 1.2 1.2 1.2 1.2 96 Rolling Back Malaria Data Table 3: Percentage of Households That Have at Least One Mosquito Net, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Benin 2002 PSI 2002 1 district 12.0 2001 DHS 2001 national 40.2 PSI 2001 subnational 58.0 RBM 2000 3 health zones 47.4 Burkina Faso 2003 DHS 2003 national 40.4 Cameroon 2001 PSI 2001 3 provinces 15.0 Chad 2000 RBM 2001 5 districts 68.2 Congo, Dem Rep. of 2003 PSI 2003 1 district 27.9 Eritrea 2003 MoH 2003 3 zobas 91.2 2002 DHS 2002 national 33.8 Ethiopia 2001 RBM 2001 14 districts 16.2 2000 DHS 2000 national 1.1 Ghana 2003 DHS 2003 national 17.6 Kenya 2003 DHS 2003 national 21.8 2001 PSI 2000 6 regions 37.0 RBM 2001 4 districts 29.7 Madagascar 2001 PSI 2001 1 district 60.8 Malawi 2004 MoH 2004 national 42.9 2000 DHS 2000 national 13.1 IMCI 2000 5 districts 18.2 1998 PSI 1998 1 district 22.2 Mali 2003 NetMark 2003 5 areas 72.8 2001 DHS 2001 national 54.4 Mauritania 2004 DHS 2003­04 national 56.0 2001 DHS 2000­01 national 55.6 Mozambique 2000 NetMark 2000 5 areas 26.5 Namibia 2000 DHS 2000 national 13.1 Nigeria 2003 DHS 2003 national 11.8 2000 NetMark 2000 5 areas 12.0 Rwanda 2001 PSI 2001 11.1 2000 DHS 2000 national 6.6 1997 PSI 1997 3 areas 3.2 Senegal 2000 NetMark 2000 5 areas 33.6 Togo 2000 RBM 2000 3 districts 30.5 Malarial Case Notification and Coverage with Key Interventions 97 RESIDENCE WEALTH QUINTILE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- 48.9 35.0 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 46.4 38.8 34.1 39.7 37.3 38.6 51.5 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 28.3 37.3 -- -- -- -- -- -- -- -- -- -- -- -- 3.1 0.6 -- -- -- -- -- 9.9 24.2 27.9 23.6 17.1 12.1 11.4 37.6 16.6 11.2 11.4 14.0 24.4 39.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 63.3 39.3 -- -- -- -- -- 32.1 10.1 -- -- -- -- -- -- -- -- -- -- -- -- 28.0 14.0 -- -- -- -- -- 81.0 67.3 -- -- -- -- -- 57.7 53.4 -- -- -- -- -- 42.5 66.2 -- -- -- -- -- 39.9 66.8 -- -- -- -- -- 34.0 21.5 -- -- -- -- -- 10.9 14.5 -- -- -- -- -- 5.4 15.5 23.0 15.5 10.8 8.0 3.3 13.3 11.2 -- -- -- -- -- 56.0 4.3 -- -- -- -- -- 29.7 2.9 -- -- -- -- -- -- -- -- -- -- -- -- 28.8 36.8 -- -- -- -- -- -- -- -- -- -- -- -- 98 Rolling Back Malaria Data Table 3, continued AFRICA, continued COUNTRY YEAR SOURCE SCALE TOTAL Uganda 2003 Fapohunda BM 2003 6 districts 30.0 Gertrude N. 2004 1 district 43.7 2002 Spencer et al. 2004 1 district 78.2 2001 DHS 2000­01 national 12.8 MoH 2001 (RBM Baseline survey) 4 districts 17.6 2000 CMS 2000 district 22.4 NetMark 2000 5 areas 34.0 PSI 2000 4 provinces 22.4 1999 Nuwaha F. 1999 1 district 55.0 Tanzania 2001 NSO 2001 national 37.1 2000 Nathan R. et al. 2004 2 districts 73.0 PSI 2000 4 areas 51.1 1999 DHS 1999 national 30.3 1998 PSI 1998 4 areas 32.0 1997 Nathan R. et al. 2004 2 districts 37.0 Zambia 2002 DHS 2002­03 national 27.2 2000 NetMark 2000 5 areas 26.5 Zimbabwe 1999 DHS 1999 national 10.2 ASIA COUNTRY YEAR SOURCE SCALE TOTAL Afghanistan 2002 MoH 2002 50 districts 10.8 Cambodia 2000 DHS 2000 national 82.0 Lao PDR 2001 PSI 2001 2 provinces 96.9 Myanmar 2001 PSI 2001 1 state 50.0 Nepal 2003 MoH 2003 8 districts 73.0 Timor Leste 2004 MoH 2005 national 36.0 THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Bolivia 2002 PSI 2002 1 province 92.4 2001 PSI 2001a 1 province 94.4 PSI 2001b 1 province 95.6 Colombia 2000 DHS 2000 national 31.0 Nicaragua 2001 DHS 2001 national 42.1 Malarial Case Notification and Coverage with Key Interventions 99 RESIDENCE WEALTH QUINTILE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 32.9 9.2 -- -- -- -- -- -- -- -- -- -- -- -- 45.5 16.5 -- -- -- -- -- 47.4 24.9 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 67.4 27.9 -- -- -- -- -- -- -- 54.0 64.0 74.0 83.0 92.0 -- -- -- -- -- -- -- 57.1 20.8 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 20.0 29.0 32.0 45.0 63.0 34.9 23.3 -- -- -- -- -- 34.9 20.8 -- -- -- -- -- 16.5 6.3 -- -- -- -- -- RESIDENCE URBAN RURAL -- -- 91.5 80.3 -- -- -- -- -- -- -- -- RESIDENCE URBAN RURAL -- -- -- -- -- -- 30.6 32.1 45.6 37.0 100 Rolling Back Malaria Data Table 4: Percentage of Households That Have at Least One Insecticide-treated Mosquito Net, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Benin 2002 PSI 2002 1 district 2.1 2001 PSI 2001 subnational 26.7 RBM 2000 3 health zones 5.4 Burkina Faso 2003 DHS 2003 national 4.6 2001 RBM 2000 district 17.4 Chad 2000 RBM 2001 5 districts 5.4 Congo 2003 PSI 2003 1 district 2.4 Eritrea 2003 MoH 2003 3 zobas 71.0 Ethiopia 2000 DHS 2000 national 0.2 Ghana 2003 DHS 2003 national 3.2 2001 RBM 2001 5 districts 12.2 Guinea 2001 RBM 2001 4 districts 7.0 Kenya 2003 DHS 2003 national 5.9 Malawi 2004 MoH 2004 national 33.8 2000 DHS 2000 national 4.9 IMCI 2000 5 districts 7.0 1998 PSI 1998 1 district 0.4 Mali 2003 RBM 2003 district 25.1 Mauritania 2004 DHS 2003­04 national 0.6 Mozambique 2000 NetMark 2000 5 areas 7.2 Nigeria 2003 DHS 2003 national 2.2 2000 NetMark 2000 5 areas 0.1 Senegal 2000 NetMark 2000 5 areas 11.0 Uganda 2003 Gertrude N. 2004 1 district 11.5 2002 Spencer et al. 2004 1 district 75.6 2001 MoH 2001 (RBM Baseline survey) 4 districts 1.7 2000 NetMark 2000 5 areas 3.8 1999 Nuwaha F. 1999 1 district 6.8 Tanzania 1999 DHS 1999 national 1.3 1998 PSI 1998 4 areas 6.0 Zambia 2002 DHS 2002­03 national 13.6 2001 RBM 2001 10 districts 1.6 Zambia 2000 NetMark 2000 5 areas 9.3 Malarial Case Notification and Coverage with Key Interventions 101 RESIDENCE WEALTH QUINTILE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 12.0 2.7 1.5 1.7 2.2 3.6 13.1 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 0.4 0.1 -- -- -- -- -- 2.3 4.0 7.1 2.1 2.0 2.2 3.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 10.6 4.4 2.5 2.6 4.2 5.6 11.7 52.3 30.4 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 0.6 0.0 -- -- -- -- -- -- -- -- -- -- -- -- 0.5 0.6 -- -- -- -- -- 9.3 5.8 -- -- -- -- -- 1.0 2.9 4.5 1.3 2.4 2.1 1.0 0.3 0.0 -- -- -- -- -- 10.0 11.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 6.7 1.8 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 16.1 12.4 -- -- -- -- -- -- -- -- -- -- -- -- 9.4 9.2 -- -- -- -- -- 102 Rolling Back Malaria Data Table 4, continued ASIA COUNTRY YEAR SOURCE SCALE TOTAL Afghanistan 2002 MoH 2002 50 districts 4.8 Lao PDR 2001 PSI 2001 2 provinces 63.8 THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Bolivia 2001 PSI 2001b 1 province 13.4 Colombia 2000 DHS 2000 national 2.8 Malarial Case Notification and Coverage with Key Interventions 103 RESIDENCE URBAN RURAL - - 2.5 3.7 104 Rolling Back Malaria Data Table 5: Percentage of Children under Five Years Old That Slept under a Mosquito Net during the Night Preceding the Survey, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Angola 2001 MICS 2001 national 10.2 Benin 2002 PSI 2002 subnational 46.2 2001 DHS 2001 national 32.0 1999 MICS 1999 national 38.7 Burkina Faso 2003 DHS 2003 national 19.8 Burundi 2000 MICS 2000 national 2.6 Cameroon 2001 PSI 2001 3 provinces 6.2 2000 MICS 2000 national 11.3 Central African Republic 2000 MICS 2000 national 30.9 Chad 2000 MICS 2000 national 26.9 RBM 2001 5 districts 43.3 Comoros 2000 MICS 2000 national 36.4 Côte d'Ivoire 2000 MICS 2000 national 9.6 Congo, Dem. Rep. of 2001 MICS 2001 national 11.8 Equatorial Guinea 2000 MICS 2000 national 15.4 Eritrea 2003 MoH 2003 3 zobas 81.0 2002 DHS 2002 national 12.1 Ethiopia 2001 RBM 2001 14 districts 17.1 Gabon 2000 DHS 2000 national 8.7 Gambia, The 2000 MICS 2000 national 42.1 Ghana 2003 DHS 2003 national 14.7 2001 RBM 2001 5 districts 27.0 Guinea 2001 RBM 2001 4 districts 27.2 Guinea-Bissau 2000 MICS 2000 national 67.0 Kenya 2003 DHS 2003 national 14.5 2001 PSI 2000 6 regions 31.2 RBM 2001 4 districts 15.1 2000 MICS 2000 national 16.4 Madagascar 2001 PSI 2001 1 district 54.7 2000 MICS 2000 national 30.3 Malawi 2004 MoH 2004 national 38.0 2000 DHS 2000 national 7.6 Malawi 2000 IMCI 2000 5 districts 8.6 1998 PSI 1998 1 district 58.0 Malarial Case Notification and Coverage with Key Interventions 105 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 9.5 10.9 10.9 8.6 7.1 5.7 5.4 11.1 20.2 -- -- -- -- -- -- -- -- -- 31.7 32.3 42.9 26.8 -- -- -- -- -- -- -- 48.0 32.2 -- -- -- -- -- 19.6 20.0 22.8 19.3 22.3 19.4 17.1 16.0 26.4 2.7 2.6 27.6 0.7 0.2 0.7 0.8 1.9 8.8 -- -- -- -- -- -- -- -- -- 11.4 11.3 17.6 8.7 7.3 9.8 8.9 14.5 18.6 31.0 30.8 48.2 19.8 18.6 16.7 23.1 41.4 58.8 26.6 27.2 57.5 18.6 22.5 13.6 19.5 32.1 50.3 -- -- -- -- -- -- -- -- -- 37.3 35.5 56.8 31.1 23.4 25.6 32.8 40.9 60.6 9.7 9.4 11.9 7.9 7.0 8.0 12.9 11.0 9.8 11.9 11.7 15.0 10.3 7.1 14.0 9.7 9.6 18.6 16.7 14.0 29.8 9.9 7.3 8.6 22.8 16.3 26.8 -- -- -- -- -- -- -- -- -- 11.8 12.4 14.3 11.0 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 7.5 14.4 -- -- -- -- -- 43.1 41.0 35.7 45.9 44.5 46.1 44.5 37.8 32.9 -- -- 9.0 17.5 16.8 17.1 16.0 11.2 9.6 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 67.2 66.7 74.9 63.5 60.5 63.4 66.8 71.4 74.7 14.9 14.2 32.6 10.7 6.4 7.0 11.4 18.3 35.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 15.7 17.1 34.9 10.2 6.8 8.6 9.2 19.2 42.5 -- -- -- -- -- -- -- -- -- 30.1 30.5 31.7 29.9 27.9 38.0 30.3 23.0 31.6 -- -- 57.5 34.1 -- -- -- -- -- -- -- 20.8 5.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 60.0 53.0 -- -- -- -- -- 106 Rolling Back Malaria Data Table 5, continued AFRICA, continued COUNTRY YEAR SOURCE SCALE TOTAL Mali 2003 NetMark 2003 5 areas 52.7 Mauritania 2004 DHS 2003­4 national 30.8 Mozambique 2000 NetMark 2000 5 areas 12.5 Namibia 2000 DHS 2000 national 6.7 Niger 2000 MICS 2000 national 16.6 Nigeria 2003 DHS 2003 national 5.9 2000 NetMark 2000 5 areas 8.8 Rwanda 2001 PSI 2001 2000 DHS 2000 national 5.6 MICS 2000 national 6.0 São Tomé and Principe 2000 MICS 2000 national 42.5 Senegal 2000 MICS 2000 national 15.2 NetMark 2000 5 areas 17.7 Sierra Leone 2000 MICS 2000 national 15.2 Somalia 1999 MICS 1999 national 15.6 Sudan 2000 MICS 2000 national 23.1 Swaziland 2000 MICS 2000 national 0.2 Togo 2000 MICS 2000 national 14.8 RBM 2000 3 districts 22.7 Uganda 2003 CMS 2003a 2 districts 1.0 CMS 2003b 4 districts 1.0 Fapohunda BM 2003 6 districts 22.0 GTZ 2001 3 districts 1.0 2001 DHS 2000­01 national 7.3 MoH 2001 (RBM Baseline survey) 4 districts 11.8 2000 NetMark 2000 5 areas 24.7 Tanzania 1999 DHS 1999 national 20.7 Zambia 2002 DHS 2002­03 national 16.3 2001 RBM 2001 10 districts 13.2 2000 NetMark 2000 5 areas 11.9 1999 MICS 1999 national 6.0 Zimbabwe 1999 DHS 1999 national 3.0 Malarial Case Notification and Coverage with Key Interventions 107 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- -- -- 30.6 31.0 25.7 34.5 -- -- -- -- -- -- -- 17.1 9.8 -- -- -- -- -- -- -- 5.0 7.5 -- -- -- -- -- 17.2 16.0 35.8 13.7 12.9 7.8 15.5 14.0 32.5 6.3 5.6 3.6 7.0 -- -- -- -- -- -- 9.9 8.2 -- -- -- -- -- 47.3 -- -- 50.0 45.7 -- -- -- - -- -- 26.9 1.7 -- -- -- -- -- 5.6 6.4 27.8 2.2 0.5 0.9 0.8 9.7 37.7 41.8 42.4 60.4 27.1 31.4 14.8 25.9 25.5 47.6 14.6 15.9 13.3 16.3 15.5 20.4 15.7 11.4 11.7 -- -- 13.7 19.9 -- -- -- -- -- 16.1 14.3 12.6 16.1 15.6 15.7 14.9 15.4 14.4 15.9 15.3 18.7 16.3 -- -- -- -- -- 23.1 23.1 25.8 20.6 18.1 23.0 27.4 23.6 23.1 0.2 0.2 0.2 0.2 0.2 0.1 0.1 0.0 0.5 15.4 14.1 18.5 13.3 11.3 11.8 13.1 16.1 26.2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 21.1 5.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 34.3 18.3 -- -- -- -- -- -- -- 47.9 13.0 -- -- -- -- -- 16.5 16.1 21.9 13.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 19.3 7.2 -- -- -- -- -- 6.1 5.9 8.5 4.7 3.9 3.0 4.8 7.2 11.5 -- -- -- -- -- -- -- -- -- 108 Rolling Back Malaria Data Table 5, continued ASIA COUNTRY YEAR SOURCE SCALE TOTAL Azerbaijan 2000 MICS 2000 national 12.4 Indonesia 2000 MICS 2000 national 32.0 Iraq 2000 MICS 2000 national 7.4 Lao PDR 2001 PSI 2001 2 provinces 98.3 2000 National Health Survey 2002 national 82.3 Tajikistan 2000 MICS 2000 national 5.9 Timor Leste 2002 MICS 2002 national 47.5 Vietnam 2000 MICS 2000 national 95.9 THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Bolivia 2001 PSI 2001a 1 province 97.1 Colombia 2000 DHS 2000 national 23.9 Guatemala 1999 MICS national 6.4 Guyana 2000 MICS 2000 national -- Suriname 2000 MICS 2000 national 76.6 Malarial Case Notification and Coverage with Key Interventions 109 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 12.8 12.0 6.5 18.1 17.1 19.7 8.9 5.4 4.7 32.0 32.2 23.3 37.5 -- -- -- -- -- 7.3 7.5 6.9 8.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 82.8 81.9 96.9 77.9 72.9 82.2 83.2 86.4 91.1 5.6 6.1 6.1 5.8 2.9 6.8 7.3 6.5 6.0 48.1 46.8 74.6 39.3 26.1 33.2 46.3 58.6 77.1 95.5 96.2 93.7 96.4 92.4 98.6 98.7 99.0 92.7 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- -- -- -- 23.2 25.6 -- -- -- -- -- -- 5.6 19.1 -- -- -- -- 68.7 65.8 -- -- -- -- -- -- 75.4 77.9 -- -- -- 0.0 50.0 58.1 74.9 110 Rolling Back Malaria Data Table 6: Percentage of Children Under Five Years Old That Slept under an Insecticide-treated Mosquito Net during the Night Preceding the Survey, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Angola 2001 MICS 2001 national 2.3 Benin 2003 AIMI/Benin 2003 3 districts 47.0 2001 DHS 2001 national 7.4 RBM 2000 3 health zones 4.4 1999 MICS 1999 national 5.0 Burkina Faso 2003 DHS 2003 national 1.6 2001 RBM 2000 district 12.4 Burundi 2000 MICS 2000 national 1.3 Cameroon 2000 MICS 2000 national 1.3 Central African Republic 2000 MICS 2000 national 1.5 Chad 2000 MICS 2000 national 0.6 RBM 2001 5 districts 2.9 Comoros 2000 MICS 2000 national 9.3 Côte d'Ivoire 2000 MICS 2000 national 1.1 Congo, Dem. Rep. of 2001 MICS 2001 national 0.7 Equatorial Guinea 2000 MICS 2000 national 0.7 Eritrea 2003 MoH 2003 3 zobas 63.0 2002 DHS 2002 national 4.2 Gambia, The 2000 MICS 2000 national 14.7 Ghana 2003 DHS 2003 national 3.5 2001 RBM 2001 5 districts 9.1 Guinea 2001 RBM 2001 4 districts 0.5 Guinea-Bissau 2000 MICS 2000 national 7.4 Kenya 2003 DHS 2003 national 4.6 2001 RBM 2001 4 districts 4.5 2000 MICS 2000 national 2.9 Madagascar 2000 MICS 2000 national 0.2 Malawi 2004 MoH 2004 national 35.5 2000 DHS 2000 national 2.5 Mali 2003 NetMark 2003 5 areas 17.7 RBM 2003 district 8.4 Mauritania 2004 DHS 2003­04 national 2.1 Mozambique 2000 NetMark 2000 5 areas 3.5 Niger 2000 MICS 2000 national 1.0 Nigeria 2003 DHS 2003 national 1.2 2000 NetMark 2000 5 areas 0.1 Rwanda 2000 DHS 2000 national 4.3 MICS 2000 national 5.0 Malarial Case Notification and Coverage with Key Interventions 111 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 2.3 2.3 2.9 0.9 0.8 0.8 0.8 3.8 4.7 -- -- -- -- -- -- -- -- -- 7.0 7.8 13.5 4.4 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 4.3 0.7 -- -- -- -- -- 1.4 1.9 5.2 1.1 1.1 0.4 0.6 1.5 6.0 -- -- -- -- -- -- -- -- -- 1.4 1.2 14.8 0.2 0.0 0.7 0.2 0.5 4.7 1.3 1.4 2.7 0.8 0.5 0.1 1.1 2.5 3.1 1.3 1.8 2.1 1.2 0.6 1.3 1.1 2.0 2.7 0.6 0.6 1.3 0.4 0.4 0.4 0.0 0.2 2.1 -- -- -- -- -- -- -- -- -- 9.3 9.3 16.8 7.4 5.0 6.0 7.1 9.2 19.9 1.2 1.1 1.9 0.6 0.3 1.0 1.6 1.2 2.1 0.7 0.8 2.1 0.1 0.0 0.1 0.2 0.4 3.1 0.9 0.6 3.2 0.2 0.0 0.2 1.9 0.6 3.1 -- -- -- -- -- -- -- -- -- 4.3 4.1 4.8 4.0 -- -- -- -- -- 14.4 15.2 7.2 19.4 17.6 20.7 13.9 10.8 7.4 -- -- 3.5 3.5 6.2 1.6 1.9 2.6 5.0 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 7.9 7.1 19.0 2.5 2.2 2.7 4.1 9.3 23.0 5.1 4.1 9.8 3.5 1.2 2.2 4.9 4.8 12.0 -- -- -- -- -- -- -- -- -- 3.0 2.8 3.9 2.6 2.0 2.7 2.5 3.2 4.2 0.2 0.2 0.8 0.2 0.2 0.2 0.3 0.2 0.3 -- -- 50.1 32.2 -- -- -- -- -- -- -- 10.6 1.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 2.5 1.7 2.4 1.9 -- -- -- -- -- -- -- 4.6 2.9 -- -- -- -- -- 0.9 1.1 4.0 0.5 0.3 0.3 0.5 0.1 3.7 1.1 1.2 0.6 1.4 -- -- -- -- -- -- -- 0.2 0.0 -- -- -- -- -- -- -- 20.8 1.3 -- -- -- -- -- 4.8 5.3 23.9 1.7 0.3 0.6 0.5 8.4 31.9 112 Rolling Back Malaria Data Table 6, continued AFRICA, continued COUNTRY YEAR SOURCE SCALE TOTAL São Tomé and Principe 2000 MICS 2000 national 22.8 Senegal 2000 MICS 2000 national 1.7 NetMark 2000 5 areas 5.7 Sierra Leone 2000 MICS 2000 national 1.5 Somalia 1999 MICS 1999 national 0.3 Sudan 2000 MICS 2000 national 0.4 Swaziland 2000 MICS 2000 national 0.1 Togo 2000 MICS 2000 national 2.0 Uganda 2003 Fapohunda BM 2003 6 districts 4.0 2001 DHS 2000­01 national 0.2 MoH 2001 (RBM Baseline survey) 4 districts 2.0 2000 NetMark 2000 5 areas 3.1 Tanzania 1999 DHS 1999 national 2.1 Zambia 2002 DHS 2002­03 national 6.5 2001 RBM 2001 10 districts 10.2 2000 NetMark 2000 5 areas 4.1 1999 MICS 1999 national 1.1 ASIA COUNTRY YEAR SOURCE SCALE TOTAL Azerbaijan 2000 MICS 2000 national 1.4 Indonesia 2000 MICS 2000 national 0.1 Iraq 2000 MICS 2000 national 0.0 Lao PDR 2000 National Health Survey 2002 national 14.6 Tajikistan 2000 MICS 2000 national 1.9 Timor Leste 2002 MICS 2002 national 3.9 Vietnam 2000 MICS 2000 national 15.8 Malarial Case Notification and Coverage with Key Interventions 113 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 20.8 23.4 32.4 14.4 9.3 7.9 12.8 12.2 26.1 1.7 1.6 1.5 1.7 0.7 2.4 2.0 1.5 1.3 -- -- 4.9 6.2 -- -- -- -- -- 1.7 1.3 3.9 0.7 0.2 0.3 0.6 2.0 5.3 0.3 0.5 0.4 0.6 -- -- -- -- -- 0.4 0.5 0.7 0.2 0.1 0.3 0.5 0.5 0.9 0.1 0.1 0.2 0.1 0.1 0.1 0.0 0.0 0.3 2.3 1.6 3.7 1.4 0.9 0.3 1.3 2.4 7.1 -- -- -- -- -- -- -- -- -- -- -- 0.9 0.2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 5.5 1.5 -- -- -- -- -- -- -- 4.8 1.3 -- -- -- -- -- 6.4 6.6 8.1 5.8 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 6.1 2.8 -- -- -- -- -- 1.3 0.8 1.6 0.8 0.2 0.4 1.0 1.1 2.9 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 1.5 1.3 0.9 1.9 2.0 1.8 1.6 0.3 0.8 0.1 0.1 0.0 0.1 -- -- -- -- -- 0.0 0.0 0.0 0.0 -- -- -- -- -- 14.5 14.6 10.9 15.3 10.8 17.7 14.2 15.8 15.2 1.6 2.3 1.1 2.1 0.9 3.1 2.5 1.8 0.8 4.0 3.9 8.8 2.5 0.9 1.7 4.1 8.0 5.7 14.4 17.3 3.8 18.6 27.3 15.1 11.0 11.6 4.1 114 Rolling Back Malaria Data Table 6, continued THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Bolivia 2001 PSI 2001a 1 province 15.3 Colombia 2000 DHS 2000 national 2.8 Guatemala 1999 MICS national 1.2 Guyana 2000 MICS 2000 national -- Suriname 2000 MICS 2000 national 2.7 Malarial Case Notification and Coverage with Key Interventions 115 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- -- -- -- 2.5 3.7 -- -- -- -- -- -- 1.2 1.5 -- -- -- -- 8.1 5.6 -- -- -- -- -- -- 2.1 3.3 -- -- -- -- 6.5 3.1 116 Rolling Back Malaria Data Table 7: Percentage of Pregnant Women That Slept under a Mosquito Net during the Night Preceding the Survey, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Benin 2001 DHS 2001 national 33.2 RBM 2000 3 health zones 36.9 Burkina Faso 2003 DHS 2003 national 24.0 Cameroon 2001 PSI 2001 3 provinces 5.0 Chad 2000 RBM 2001 5 districts 45.5 Eritrea 2002 DHS 2002 national 6.6 Ethiopia 2001 RBM 2001 14 districts 4.7 Ghana 2003 DHS 2003 national 9.5 2001 RBM 2001 5 districts 21.6 Guinea 2001 RBM 2001 4 districts 25.5 Kenya 2003 DHS 2003 national 13.1 2001 PSI 2000 6 regions 23.1 Madagascar 2001 PSI 2001 1 district 53.3 Malawi 2004 MoH 2004 national 34.1 Mali 2003 NetMark 2003 5 areas 49.1 Mauritania 2004 DHS 2003­04 national 31.2 Mozambique 2000 NetMark 2000 5 areas 18.8 Nigeria 2003 DHS 2003 national 5.4 2000 NetMark 2000 5 areas 7.4 Senegal 2000 NetMark 2000 5 areas 21.4 Uganda 2001 DHS 2000­01 national 6.6 2000 NetMark 2000 5 areas 20.8 Zambia 2002 DHS 2002­03 national 17.4 2000 NetMark 2000 5 areas 4.1 ASIA COUNTRY YEAR SOURCE SCALE TOTAL Lao PDR 2001 PSI 2001 2 provinces 96.0 Malarial Case Notification and Coverage with Key Interventions 117 RESIDENCE WEALTH QUINTILE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 39.0 30.5 -- -- -- -- -- -- -- -- -- -- -- -- 24.6 23.9 29.2 25.7 29.7 21.0 26.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 7.4 5.5 5.2 8.7 7.0 -- -- -- -- -- -- -- 5.6 11.5 11.9 8.4 11.7 8.3 4.9 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 25.7 9.9 5.7 6.4 8.6 17.4 27.5 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 54.4 31.8 -- -- -- -- -- -- -- -- -- -- -- -- 27.2 34.6 -- -- -- -- -- -- -- -- -- -- -- -- 3.2 6.2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 118 Rolling Back Malaria Data Table 8: Percentage of Pregnant Women That Slept under an Insecticide-treated Mosquito Net during the Night Preceding the Survey, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Benin 2001 RBM 2000 3 health zones 3.8 Burkina Faso 2003 DHS 2003 national 2.6 2001 RBM 2000 district 10.0 Chad 2000 RBM 2001 5 districts 7.2 Eritrea 2002 DHS 2002 national 2.9 Ghana 2003 DHS 2003 national 2.7 2001 RBM 2001 5 districts 7.8 Guinea 2001 RBM 2001 4 districts 2.7 Kenya 2003 DHS 2003 national 4.4 Malawi 2004 MoH 2004 national 31.4 Mali 2003 NetMark 2003 5 areas 19.6 RBM 2003 district 19.0 Mozambique 2000 NetMark 2000 5 areas 5.6 Nigeria 2003 DHS 2003 national 1.3 2000 NetMark 2000 5 areas -- Senegal 2000 NetMark 2000 5 areas 6.0 Uganda 2001 DHS 2000­01 national 0.5 MoH 2001 (RBM Baseline survey) 4 districts 2.3 2000 NetMark 2000 5 areas 1.5 Zambia 2002 DHS 2002­03 national 7.9 2000 NetMark 2000 5 areas 1.4 THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Bolivia 2001 PSI 2001a 1 province 17.8 Malarial Case Notification and Coverage with Key Interventions 119 RESIDENCE WEALTH QUINTILE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- 6.1 2.1 0.6 0.7 2.7 1.5 8.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 3.4 2.3 0.8 3.8 5.5 1.6 3.2 4.7 2.8 1.0 1.9 3.0 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 4.8 4.3 1.7 2.2 6.5 6.3 5.9 49.1 29.0 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 0.4 1.6 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 120 Rolling Back Malaria Data Table 9: Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Once during Pregnancy (Community Level, Prevention or Treatment), by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Benin 2001 DHS 2001 national 6.2 Ghana 2003 DHS 2003 national 1.0 Kenya 2003 DHS 2003 national 12.5 Malawi 2004 MoH 2004 national 77.7 2000 DHS 2000 national 67.5 Mauritania 2004 DHS 2003­04 national 0.5 Nigeria 2003 DHS 2003 national 2.4 Rwanda 2000 DHS 2000 national 0.1 Zambia 2002 DHS 2002­03 national 0.5 Benin 2001 DHS 2001 national 6.2 Ghana 2003 DHS 2003 national 1.0 Kenya 2003 DHS 2003 national 12.5 Malawi 2004 MoH 2004 national 77.7 2000 DHS 2000 national 67.5 Mauritania 2004 DHS 2003­04 national 0.5 Nigeria 2003 DHS 2003 national 2.4 Rwanda 2000 DHS 2000 national 0.1 Zambia 2002 DHS 2002­03 national 0.5 Data Table 10: Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Twice during Pregnancy (Community Level, Prevention or Treatment), by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Malawi 2004 MoH 2004 national 46.8 2000 DHS 2000 national 29.3 Malarial Case Notification and Coverage with Key Interventions 121 RESIDENCE WEALTH QUINTILE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 4.2 7.2 -- -- -- -- -- 0.9 1.1 1.3 0.7 1.0 0.9 1.4 13.1 12.4 12.6 11.8 13.8 11.9 12.5 88.9 75.4 -- -- -- -- -- -- -- -- -- -- -- -- 0.9 0.2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 0.8 0.4 -- -- -- -- -- 4.2 7.2 -- -- -- -- -- 0.9 1.1 1.3 0.7 1.0 0.9 1.4 13.1 12.4 12.6 11.8 13.8 11.9 12.5 88.9 75.4 -- -- -- -- -- -- -- -- -- -- -- -- 0.9 0.2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 0.8 0.4 -- -- -- -- -- RESIDENCE URBAN RURAL 57.2 44.7 -- -- 122 Rolling Back Malaria Data Table 11: Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Once during an Antenatal Visit, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Mauritania 2004 DHS 2003­04 national 0.3 Nigeria 2003 DHS 2003 national 1.0 Data Table 12: Pregnant Women Receiving Sulfadoxine Pyrimethamine (SP) at Least Twice during an Antenatal Visit, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Ghana 2003 DHS 2003 national 0.8 Kenya 2003 DHS 2003 national 3.9 Uganda 2001 MoH 2002 17 districts 33.0 Malarial Case Notification and Coverage with Key Interventions 123 RESIDENCE URBAN RURAL 0.7 -- 2.0 0.6 RESIDENCE WEALTH QUINTILE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 0.6 0.9 0.7 0.7 1.0 0.6 1.1 4.2 3.9 3.0 4.7 4.7 3.4 3.9 -- -- -- -- -- -- -- 124 Rolling Back Malaria Data Table 13: Percentage of Children under Five Years Old with Reported Fever in the Two Weeks Prior to the Survey, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Angola 2001 MICS 2001 national 25.0 Benin 2001 DHS 2001 national 41.0 1999 MICS 1999 national 15.0 Botswana 1988 DHS 1988 national 3.9 Burkina Faso 2003 DHS 2003 national 36.7 1999 DHS 1998­99 national 36.0 1993 DHS 1992­93 national 35.0 Burundi 2000 MICS 2000 national 16.5 Cameroon 2000 MICS 2000 national 24.8 1991 DHS 1991 national 23.0 Central African Republic 2000 MICS 2000 national 31.8 Chad 2000 MICS 2000 national 29.2 1997 DHS 1996­97 national 32.0 Comoros 2000 MICS 2000 national 31.0 Côte d'Ivoire 2000 MICS 2000 national 30.7 1999 DHS 1998­99 national 36.0 Congo, Dem Rep. of 2001 MICS 2001 national 41.1 Egypt 1995 DHS 1995­96 national 40.0 1992 DHS 1992 national 21.0 Equatorial Guinea 2000 MICS 2000 national 25.1 Eritrea 2002 DHS 2002 national 29.8 Ethiopia 2001 RBM 2001 14 districts 88.6 2000 DHS 2000 national 28.4 Gabon 2000 DHS 2000 national 29.1 Gambia, The 2000 MICS 2000 national 14.8 Ghana 2003 DHS 2003 national 21.3 1998 DHS 1998­99 national 26.8 1988 DHS 1988 national 35.0 Guinea 1999 DHS 1999 national 41.9 Guinea-Bissau 2000 MICS 2000 national 42.2 Kenya 2003 DHS 2003 national 41.6 2000 MICS 2000 national 15.3 Kenya 1998 DHS 1998 national 42.3 1993 DHS 1993 national 41.0 1989 DHS 1988­89 national 42.0 Liberia 1986 DHS 1986 national 50.0 Madagascar 2000 MICS 2000 national 15.9 1992 DHS 1992 national 27.0 Malarial Case Notification and Coverage with Key Interventions 125 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 25.3 24.7 24.7 25.7 25.6 24.0 26.0 26.4 23.0 42.0 40.4 35.9 43.7 -- -- -- -- -- -- -- 15.0 16.0 -- -- -- -- -- 3.6 4.2 3.8 4.0 -- -- -- -- -- -- -- 28.5 38.0 37.3 36.5 39.6 37.7 30.1 37.1 34.5 30.1 36.5 -- -- -- -- -- 36.3 33.7 27.8 36.3 -- -- -- -- -- 17.6 15.5 14.8 16.6 14.5 19.6 17.7 14.1 17.0 24.8 24.8 22.9 25.6 26.9 23.6 26.3 23.0 23.4 -- -- -- -- -- -- -- -- -- 32.9 30.8 27.7 34.4 35.8 33.9 32.4 29.3 27.0 29.1 29.3 28.4 29.4 23.8 30.5 30.0 32.5 30.1 -- -- -- -- -- -- -- -- -- 30.5 31.5 25.0 32.6 29.8 33.9 33.0 29.9 28.5 30.8 30.6 29.0 31.9 32.2 33.0 29.5 28.5 28.6 -- -- -- -- -- -- -- -- -- 41.0 41.3 37.7 42.8 38.4 46.0 43.3 41.2 36.2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 27.0 23.1 33.2 27.5 -- -- -- -- -- 30.5 29.1 24.2 32.7 35.9 32.8 30.7 28.3 19.7 -- -- -- -- -- -- -- -- -- 29.0 27.8 25.0 28.8 -- -- -- -- -- -- -- 30.1 26.1 -- -- -- -- -- 14.4 15.3 14.4 15.1 14.8 15.6 12.3 19.1 12.4 21.7 20.8 22.4 20.7 21.5 19.0 22.0 23.3 20.9 26.8 26.9 26.0 27.1 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 42.2 41.7 39.2 42.9 -- -- -- -- -- 42.3 42.0 46.5 40.3 42.3 40.0 39.5 45.1 44.7 42.2 41.0 40.4 41.9 38.4 44.7 43.3 42.0 40.1 15.7 15.1 10.8 17.0 21.6 16.4 14.2 14.5 8.6 42.4 42.2 41.7 42.4 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 15.9 15.9 11.5 16.9 15.3 23.6 13.5 13.4 6.9 -- -- -- -- -- -- -- -- -- 126 Rolling Back Malaria Data Table 13, continued AFRICA, continued COUNTRY YEAR SOURCE SCALE TOTAL Malawi 2004 MoH 2004 national 39.0 2000 DHS 2000 national 41.6 1992 DHS 1992 national 40.0 Mali 2001 DHS 2001 national 26.8 1987 DHS 1987 national 33.0 Mauritania 2004 DHS 2003­04 national 37.5 2001 DHS 2000­01 national 31.1 Morocco 1992 DHS 1992 national 27.0 Namibia 2000 DHS 2000 national 19.4 1992 DHS 1992 national 34.0 Niger 2000 MICS 2000 national 41.6 1992 DHS 1992 national 45.0 Nigeria 2003 DHS 2003 national 31.6 1999 DHS 1999 national 30.2 1990 DHS 1990 national 32.0 Rwanda 2000 DHS 2000 national 32.7 MICS 2000 national 33.4 1992 DHS 1992 national 41.0 São Tomé and Principe 2000 MICS 2000 national 29.0 Senegal 2000 MICS 2000 national 20.5 1993 DHS 1992­93 national 38.0 Sierra Leone 2000 MICS 2000 national 45.9 Somalia 1999 MICS 1999 national 17.0 Sudan 2000 MICS 2000 national 20.7 Swaziland 2000 MICS 2000 national 4.0 Togo 2000 MICS 2000 national 36.2 Uganda 2003 Fapohunda BM 2003 6 districts 46.3 2001 DHS 2000­01 national 43.9 Uganda 2001 MoH 2001 (RBM Baseline survey) 4 districts 1.0 1989 DHS 1988­89 national 41.0 Tanzania 1999 DHS 1999 national 35.1 1996 DHS 1996 national 30.0 1992 DHS 1991­92 national 31.0 Zambia 2002 DHS 2002­03 national 43.3 1999 MICS 1999 national 14.4 1997 DHS 1996­97 national 40.0 1992 DHS 1992 national 43.0 Zimbabwe 1999 DHS 1999 national 25.8 Malarial Case Notification and Coverage with Key Interventions 127 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- 28.6 40.1 -- -- -- -- -- -- -- 31.9 43.0 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 27.0 26.6 24.0 27.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 39.9 34.4 34.1 40.2 -- -- -- -- -- 30.6 31.6 31.9 30.4 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 19.0 19.9 20.9 18.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 42.5 40.5 25.8 43.9 45.5 45.0 40.4 47.9 28.8 -- -- -- -- -- -- -- -- -- 31.6 31.6 27.8 33.3 -- -- -- -- -- 31.8 28.6 26.5 31.6 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 31.5 35.1 22.7 35.3 38.1 38.5 31.4 32.1 18.1 -- -- -- -- -- -- -- -- -- 29.4 28.9 28.6 29.1 28.1 30.5 36.8 27.8 28.4 21.9 19.2 15.1 26.9 26.6 23.8 19.0 15.3 16.7 -- -- -- -- -- -- -- -- -- 46.3 45.6 43.9 46.6 46.3 50.1 45.2 48.5 37.8 17.5 16.5 18.5 17.6 -- -- -- -- -- 21.8 19.6 18.4 22.8 21.0 20.5 21.2 20.5 20.6 3.8 4.1 9.1 3.0 2.5 2.8 3.2 6.1 8.6 35.9 36.4 28.8 38.9 41.2 37.9 39.1 35.6 20.9 -- -- -- -- -- -- -- -- -- 44.7 43.1 32.9 45.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 36.5 33.7 33.4 35.5 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 42.2 44.4 33.2 47.8 -- -- -- -- -- 14.4 14.4 10.7 16.3 15.6 15.9 19.0 12.5 8.5 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 26.4 25.1 22.6 27.3 -- -- -- -- -- 128 Rolling Back Malaria Data Table 13, continued ASIA COUNTRY YEAR SOURCE SCALE TOTAL Afghanistan 2003 MICS 2003 national 1.2 Armenia 2000 DHS 2000 national 16.5 Azerbaijan 2000 MICS 2000 national 13.7 Bangladesh 1997 DHS 1996­97 national 31.0 Cambodia 2000 DHS 2000 national 35.4 Indonesia 2000 MICS 2000 national 3.1 1997 DHS 1997 national 26.0 1994 DHS 1994 national 28.0 1991 DHS 1991 national 27.0 Iraq 2000 MICS 2000 national 18.2 Lao PDR 2000 National Health Survey 2002 national 2.9 Nepal 2001 DHS 2001 national 32.0 Pakistan 1991 DHS 1990­91 national 30.0 Philippines 1998 DHS 1998 national 26.0 1993 DHS 1993 national 25.0 Tajikistan 2000 MICS 2000 national 1.7 Timor Leste 2002 MICS 2002 national 27.9 Turkey 1993 DHS 1993 national 30.0 Turkmenistan 2000 DHS 2000 national 4.0 Vietnam 2000 MICS 2000 national 13.1 Yemen 1997 DHS 1997 national 40.0 1992 DHS 1991­92 national 46.0 Malarial Case Notification and Coverage with Key Interventions 129 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 1.4 1.5 2.5 1.4 -- -- -- -- -- 16.0 17.0 18.6 14.2 -- -- -- -- -- 14.0 13.4 13.9 13.5 15.6 11.9 12.0 16.0 11.9 -- -- -- -- -- -- -- -- -- 35.7 35.2 34.5 35.6 -- -- -- -- -- 3.1 3.1 2.2 3.6 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 19.2 17.3 20.8 15.2 -- -- -- -- -- 3.1 2.7 3.2 2.7 2.6 3.4 2.1 4.1 2.0 32.1 31.8 26.7 32.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 26.1 25.7 24.9 26.7 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 2.0 1.4 0.1 2.1 3.1 1.0 2.6 1.1 0.4 28.8 27.1 23.4 29.3 33.4 31.1 26.8 28.5 19.3 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 13.5 12.7 12.5 13.2 10.5 14.0 19.1 12.4 11.4 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 130 Rolling Back Malaria Data Table 13, continued THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Bolivia 1998 DHS 1998 national 32.0 Brazil 1996 DHS 1996 national 26.0 Colombia 2000 DHS 2000 national 25.5 1995 DHS 1995 national 28.0 1990 DHS 1990 national 19.0 1986 DHS 1986 national 30.0 Dominican Republic 2002 DHS 2002 national 26.4 1996 DHS 1996 national 28.8 1991 DHS 1991 national 27.0 Guatemala 1999 DHS 1998­99 national 27.0 MICS national 20.3 1995 DHS 1995 national 28.0 Guyana 2000 MICS 2000 national 18.5 Haiti 2000 DHS 2000 national 40.6 1995 DHS 1994­95 national 40.0 Nicaragua 2001 DHS 2001 national 24.9 1998 DHS 1997­98 national 23.0 Paraguay 1990 DHS 1990 national 31.0 Peru 2000 DHS 2000 national 26.0 1996 DHS 1996 national 28.0 Malarial Case Notification and Coverage with Key Interventions 131 GENDER RESIDENCE MALE FEMALE URBAN RURAL -- -- -- -- -- -- -- -- 26.2 24.7 27.2 21.6 -- -- -- -- -- -- -- -- -- -- -- -- 26.9 28.8 26.1 27.1 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 18.2 56.8 -- -- -- -- 3.5 3.7 -- 5.0 41.2 40.0 31.6 45.0 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 132 Rolling Back Malaria Data Table 14: Percentage of Febrile Children under Five Years Old That Received Treatment with Chloroquine, by Back- ground Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Angola 2001 MICS 2001 national 56.9 Benin 2001 DHS 2001 national 59.0 Burkina Faso 2003 DHS 2003 national 47.7 Burundi 2000 MICS 2000 national 23.3 Cameroon 2000 MICS 2000 national 48.3 Central African Republic 2000 MICS 2000 national 65.7 Chad 2000 MICS 2000 national 31.1 Comoros 2000 MICS 2000 national 61.5 Côte d'Ivoire 2000 MICS 2000 national 56.3 Congo, Dem. Rep. of 2001 MICS 2001 national 45.0 Equatorial Guinea 2000 MICS 2000 national 41.2 Eritrea 2002 DHS 2002 national 2.4 Ethiopia 2000 DHS 2000 national 1.6 Gabon 2000 DHS 2000 national 38.8 Gambia, The 2000 MICS 2000 national 54.5 Ghana 2003 DHS 2003 national 59.2 Guinea-Bissau 2000 MICS 2000 national 58.3 Kenya 2003 DHS 2003 national 3.4 2000 MICS 2000 national 43.5 Madagascar 2000 MICS 2000 national 29.7 Malawi 2000 DHS 2000 national 1.3 Mali 2001 DHS 2001 national 38.2 Mauritania 2004 DHS 2003­04 national 28.3 2001 DHS 2000­01 national 21.3 Mozambique 2003 2003 subnational 14.9 Namibia 2000 DHS 2000 national 14.4 Niger 2000 MICS 2000 national 48.1 Nigeria 2003 DHS 2003 national 32.9 Rwanda 2000 DHS 2000 national 4.6 MICS 2000 national 7.1 São Tomé and Principe 2000 MICS 2000 national 60.7 Senegal 2000 MICS 2000 national 35.9 Sierra Leone 2000 MICS 2000 national 59.6 Somalia 1999 MICS 1999 national 18.5 Sudan 2000 MICS 2000 national 49.4 Malarial Case Notification and Coverage with Key Interventions 133 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 57.1 56.8 57.6 55.6 52.4 58.7 60.0 55.5 57.7 57.5 60.5 60.3 58.5 -- -- -- -- -- -- -- 52.3 47.1 35.9 43.9 49.0 56.9 55.1 22.8 23.9 25.0 23.2 14.8 27.5 24.6 21.2 26.0 47.4 49.3 48.3 48.3 41.7 46.8 47.8 59.8 47.8 65.3 66.1 71.4 62.7 57.7 62.3 68.8 70.6 73.1 30.1 32.0 39.9 28.8 20.0 33.8 28.9 32.7 39.5 60.7 62.2 63.0 61.1 48.4 66.6 60.3 67.4 64.6 55.8 56.9 67.4 48.9 40.9 53.7 59.6 72.0 67.1 44.4 45.5 49.2 43.2 40.7 43.8 47.8 45.9 45.9 40.0 42.7 43.6 39.5 40.2 41.4 43.2 39.9 42.7 3.4 1.3 2.8 2.3 1.5 1.8 2.5 4.9 0.9 -- -- -- -- -- -- -- -- -- -- -- 35.6 49.1 -- -- -- -- -- 58.9 50.4 57.0 53.1 54.9 54.4 54.7 58.1 47.4 58.0 60.5 61.7 57.9 55.2 52.1 64.0 69.6 56.3 57.4 59.1 71.5 51.7 43.7 56.0 57.1 61.7 76.2 3.7 3.0 2.6 3.5 6.5 4.7 1.7 0.9 2.1 44.9 40.7 35.7 44.5 43.4 39.8 46.8 44.0 41.7 29.5 29.9 23.3 30.8 28.1 31.2 30.4 30.5 21.2 -- -- 0.5 1.4 -- -- -- -- -- -- -- 52.1 34.4 -- -- -- -- -- 28.6 27.9 22.0 32.4 -- -- -- -- -- 20.0 22.7 25.9 17.8 -- -- -- -- -- -- -- 12.7 15.7 -- -- -- -- -- 14.7 14.0 6.3 19.2 -- -- -- -- -- 48.7 47.4 59.0 47.1 41.6 43.3 49.2 47.7 64.9 31.6 34.1 37.6 31.1 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 8.2 6.1 11.9 6.5 5.0 5.9 7.3 6.7 26.9 61.9 60.2 61.2 61.1 60.6 51.7 59.4 62.9 61.8 34.4 37.5 49.0 23.3 25.4 30.0 32.6 54.8 54.2 60.6 58.6 58.3 60.0 52.5 58.5 62.7 63.6 62.1 18.7 18.4 11.1 24.4 -- -- -- -- -- 50.6 48.1 59.4 41.6 45.0 47.5 48.4 45.9 54.9 134 Rolling Back Malaria Data Table 14, continued AFRICA, continued COUNTRY YEAR SOURCE SCALE TOTAL Swaziland 2000 MICS 2000 national 22.6 Togo 2000 MICS 2000 national 59.2 Tanzania 1999 DHS 1999 national 52.9 Zambia 2002 DHS 2002­03 national 49.7 2000 MICS 1999 national -- 1999 MICS 1999 national 56.4 ASIA COUNTRY YEAR SOURCE SCALE TOTAL Azerbaijan 2000 MICS 2000 national -- Indonesia 2000 MICS 2000 national 3.3 Iraq 2000 MICS 2000 national 0.9 Lao PDR 2000 National Health Survey 2002 national 8.7 Tajikistan 2000 MICS 2000 national 67.2 Timor Leste 2002 MICS 2002 national 42.7 Vietnam 2000 MICS 2000 national 3.7 THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Guatemala 1999 MICS national 18.0 Guyana 2000 MICS 2000 national 2.1 Haiti 2000 DHS 2000 national 11.7 Nicaragua 2001 DHS 2001 national 1.6 Malarial Case Notification and Coverage with Key Interventions 135 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 25.4 18.9 28.0 21.8 30.1 12.0 25.8 28.1 18.8 59.9 58.5 61.4 58.6 56.6 57.5 60.3 59.9 68.5 -- -- -- -- -- -- -- -- -- -- -- 46.0 50.9 -- -- -- -- -- -- -- -- -- 50.2 50.4 65.5 54.7 62.4 56.6 56.2 56.2 56.5 -- -- -- -- -- GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST -- -- -- -- -- -- -- -- -- 2.4 4.2 2.2 3.6 -- -- -- -- -- 0.8 1.1 0.8 1.1 -- -- -- -- -- 7.4 7.9 2.1 10.1 8.3 14.0 9.5 2.4 10.6 61.1 76.0 100.0 66.7 56.5 85.7 71.4 62.5 100.0 42.2 43.3 51.8 40.5 38.0 36.6 45.2 41.9 58.4 4.1 3.3 5.9 3.2 4.7 5.1 0.4 3.9 5.1 GENDER RESIDENCE MALE FEMALE URBAN RURAL -- -- 22.7 -- -- 4.3 -- 2.1 12.6 10.8 7.3 13.2 -- -- -- -- 136 Rolling Back Malaria Data Table 15: Percentage of Febrile Children under Five Years Old That Received Treatment with Sulfadoxine Pyrimethamine (SP), by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Angola 2001 MICS 2001 national 1.4 Benin 2001 DHS 2001 national 0.9 Burkina Faso 2003 DHS 2003 national 0.2 Burundi 2000 MICS 2000 national 1.6 Cameroon 2000 MICS 2000 national 1.4 Central African Republic 2000 MICS 2000 national 0.3 Chad 2000 MICS 2000 national 1.2 Comoros 2000 MICS 2000 national 4.0 Côte d'Ivoire 2000 MICS 2000 national 2.5 Congo, Dem. Rep. of 2001 MICS 2001 national 0.8 Eritrea 2002 DHS 2002 national 0.5 Ethiopia 2000 DHS 2000 national 0.7 Gambia, The 2000 MICS 2000 national 3.1 Ghana 2003 DHS 2003 national 0.3 Guinea-Bissau 2000 MICS 2000 national 2.5 Kenya 2003 DHS 2003 national 11.1 2000 MICS 2000 national 26.3 Madagascar 2000 MICS 2000 national 0.7 Malawi 2000 DHS 2000 national 23.2 Mauritania 2004 DHS 2003­04 national 0.7 Mozambique 2003 HDS 2003 subnational 10.7 Niger 2000 MICS 2000 national 0.1 Nigeria 2003 DHS 2003 national 0.4 Rwanda 2000 DHS 2000 national 1.2 MICS 2000 national 2.3 São Tomé and Principe 2000 MICS 2000 national 0.8 Senegal 2000 MICS 2000 national 0.5 Sierra Leone 2000 MICS 2000 national 4.3 Somalia 1999 MICS 1999 national -- Sudan 2000 MICS 2000 national 1.4 Swaziland 2000 MICS 2000 national 5.7 Togo 2000 MICS 2000 national 3.4 Tanzania 1999 DHS 1999 national -- Zambia 2002 DHS 2002­03 national 2.4 2000 MICS 1999 national -- 1999 MICS 1999 national 2.4 Malarial Case Notification and Coverage with Key Interventions 137 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 1.6 1.2 1.0 2.4 1.0 0.7 1.6 2.5 0.8 0.7 1.0 0.4 1.0 -- -- -- -- -- -- -- 0.9 0.2 -- -- -- 0.6 1.0 1.8 1.5 -- 1.8 1.1 2.5 1.8 1.0 1.6 1.6 1.1 1.8 1.2 -- 2.1 1.8 2.3 0.8 0.3 0.3 0.5 0.2 0.2 0.2 -- 0.5 0.5 1.0 1.5 1.9 1.1 1.7 0.5 1.8 0.9 1.7 4.1 3.8 3.8 4.0 4.3 3.7 3.9 3.7 4.3 3.0 1.9 2.5 2.4 1.6 2.1 4.1 2.3 2.4 0.9 0.7 1.0 0.7 0.2 0.6 0.4 2.2 0.8 0.5 0.4 0.3 0.6 0.3 0.6 0.7 0.7 -- -- -- -- -- -- -- -- -- -- 4.0 2.4 3.9 2.7 4.0 3.0 3.2 2.5 2.7 0.5 -- 0.8 -- -- -- -- 0.6 1.0 2.7 2.2 3.4 2.0 0.7 0.9 3.8 3.4 3.7 11.9 10.2 7.6 11.9 11.1 12.5 15.1 8.3 7.6 25.7 28.9 33.9 25.8 23.5 29.6 21.7 24.8 39.9 1.2 0.2 -- 0.8 -- 0.5 1.3 1.8 1.8 -- -- 27.6 22.8 -- -- -- -- -- 1.2 -- 0.6 0.8 -- -- -- -- -- -- -- 9.2 11.3 -- -- -- -- -- 0.2 -- 0.2 0.1 -- -- -- 0.3 0.1 0.5 0.6 0.4 0.4 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 2.7 1.9 0.2 2.5 1.7 1.8 2.0 3.6 0.6 0.3 1.3 1.0 0.6 -- -- -- -- 1.0 0.6 0.3 -- 0.3 -- 0.2 0.5 0.5 2.1 4.3 4.3 6.7 3.6 2.7 1.6 4.9 7.7 5.6 -- -- -- -- -- -- -- -- -- 1.9 0.8 2.0 0.9 0.8 0.6 1.6 1.0 2.0 7.7 4.5 -- 9.9 25.2 4.3 4.3 -- -- 2.8 4.0 4.5 3.1 2.6 2.0 3.1 3.5 10.9 -- -- -- -- -- -- -- -- -- -- -- 4.7 1.7 -- -- -- -- -- -- -- -- -- 2.4 0.1 1.9 3.5 6.6 2.6 2.2 3.2 2.2 -- -- -- -- -- 138 Rolling Back Malaria Data Table 15, continued ASIA COUNTRY YEAR SOURCE SCALE TOTAL Indonesia 2000 MICS 2000 national 0.3 Iraq 2000 MICS 2000 national 0.3 Lao PDR 2000 National Health Survey 2002 national -- Tajikistan 2000 MICS 2000 national 57.4 Timor Leste 2002 MICS 2002 national 11.9 Vietnam 2000 MICS 2000 national 1.4 THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Guyana 2000 MICS 2000 national 0.5 Nicaragua 2001 DHS 2001 national 0.2 Malarial Case Notification and Coverage with Key Interventions 139 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 0.2 0.4 0.4 0.2 -- -- -- -- -- 0.2 0.3 0.3 0.2 -- -- -- -- -- -- -- -- -- -- -- -- -- -- 55.6 60.0 -- 58.3 56.5 71.4 52.4 62.5 50.0 12.2 11.5 11.7 11.9 13.3 12.3 5.7 14.3 14.1 1.4 1.4 0.5 1.6 1.4 4.4 0.4 -- -- GENDER RESIDENCE MALE FEMALE URBAN RURAL 1.0 -- -- 0.5 -- -- -- -- 140 Rolling Back Malaria Data Table 16: Percentage of Febrile Children under Five Years Old That Received Treatment with Any Antimalarial, by Background Characteristics AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Angola 2001 MICS 2001 national 63.0 Benin 2001 DHS 2001 national 60.4 Burkina Faso 2003 DHS 2003 national 49.6 1993 DHS 1992­93 national 31.5 Burundi 2000 MICS 2000 national 31.3 Cameroon 2000 MICS 2000 national 66.1 Central African Republic 2000 MICS 2000 national 68.8 Chad 2000 MICS 2000 national 31.9 Comoros 2000 MICS 2000 national 62.7 Côte d'Ivoire 2000 MICS 2000 national 57.5 Congo, Dem. Rep. of 2001 MICS 2001 national 45.4 Equatorial Guinea 2000 MICS 2000 national 48.6 Eritrea 2002 DHS 2002 national 3.6 Ethiopia 2001 RBM 2001 14 districts 73.7 2000 DHS 2000 national 3.0 Gambia, The 2000 MICS 2000 national 55.2 Ghana 2003 DHS 2003 national 62.8 1998 DHS 1998­99 national 60.7 Guinea-Bissau 2000 MICS 2000 national 58.4 Kenya 2003 DHS 2003 national 26.5 2000 MICS 2000 national 64.5 1998 DHS 1998 national 40.4 Madagascar 2000 MICS 2000 national 60.7 Malawi 2004 MoH 2004 national 31.6 2000 DHS 2000 national 27.0 Mauritania 2004 DHS 2003­04 national 33.4 Mozambique 2003 HDS 2003 subnational 14.8 Namibia 2000 DHS 2000 national 14.4 Niger 2000 MICS 2000 national 48.1 Nigeria 2003 DHS 2003 national 33.8 Rwanda 2000 DHS 2000 national 9.2 MICS 2000 national 12.6 São Tomé and Principe 2000 MICS 2000 national 61.2 Senegal 2000 MICS 2000 national 36.2 Sierra Leone 2000 MICS 2000 national 60.7 Somalia 1999 MICS 1999 national 18.5 Malarial Case Notification and Coverage with Key Interventions 141 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 63.1 62.8 63.1 62.7 57.8 64.2 64.2 65.0 62.7 59.0 62.0 62.3 59.7 -- -- -- -- -- -- -- 60.1 48.4 36.5 44.7 49.7 59.3 62.7 33.3 29.6 39.1 30.5 -- -- -- -- -- 30.2 32.6 41.7 30.6 23.9 34.2 29.8 28.8 37.4 67.0 65.1 70.8 64.4 59.1 66.7 61.0 76.7 70.8 69.0 68.6 75.8 65.2 59.3 64.6 71.6 74.7 79.0 30.9 32.8 41.2 29.5 21.1 34.3 29.5 33.5 40.5 62.2 63.1 65.2 62.1 51.2 67.5 60.7 67.9 66.3 57.0 58.0 68.6 49.8 41.9 54.3 60.8 73.2 69.5 44.9 45.9 49.6 43.7 40.9 44.3 47.8 46.9 46.7 47.2 50.2 55.2 42.9 44.2 45.2 53.8 49.1 53.2 4.2 2.9 4.0 3.5 2.4 3.3 4.2 5.8 1.5 -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- 59.6 51.0 58.0 53.5 54.9 56.0 56.5 58.1 47.4 62.1 63.5 65.2 61.4 59.0 55.4 65.0 76.9 58.3 60.7 60.7 60.1 60.9 -- -- -- -- -- 57.5 59.4 71.9 51.7 43.7 56.0 57.3 61.8 76.8 27.5 25.5 21.5 27.7 27.5 31.6 28.7 24.9 18.2 65.6 63.4 63.6 64.7 64.0 62.7 63.7 62.4 75.8 39.9 40.8 35.2 41.5 -- -- -- -- -- 59.3 62.3 61.9 60.5 66.0 55.9 64.2 58.2 52.7 -- -- 39.3 31.0 -- -- -- -- -- -- -- 33.7 26.3 -- -- -- -- -- 34.0 32.6 26.7 37.7 -- -- -- -- -- -- -- 12.7 12.7 -- -- -- -- -- 14.7 14.0 6.3 19.2 -- -- -- -- -- 48.7 47.4 59.0 47.1 41.6 43.3 49.2 47.7 64.9 32.5 35.2 38.5 32.2 -- -- -- -- -- -- -- 11.5 9.0 -- -- -- -- -- 14.5 11.1 20.7 11.7 8.8 10.0 12.0 16.0 30.4 62.2 60.8 61.9 61.4 60.6 51.7 59.4 62.9 62.4 34.9 37.6 52.7 30.1 25.4 30.0 33.1 54.8 56.1 61.4 59.9 60.8 60.7 53.3 58.5 63.9 65.2 64.4 18.7 18.4 11.1 24.4 -- -- -- -- -- 142 Rolling Back Malaria Data Table 16, continued AFRICA COUNTRY YEAR SOURCE SCALE TOTAL Sudan 2000 MICS 2000 national 50.2 Swaziland 2000 MICS 2000 national 25.5 Togo 2000 MICS 2000 national 60.0 Tanzania 1999 DHS 1999 national 53.4 Zambia 2002 DHS 2002­03 national 51.9 1999 MICS 1999 national 58.0 ASIA COUNTRY YEAR SOURCE SCALE TOTAL Azerbaijan 2000 MICS 2000 national 0.8 Indonesia 2000 MICS 2000 national 4.4 Iraq 2000 MICS 2000 national 1.3 Lao PDR 2000 National Health Survey 2002 national 8.7 Tajikistan 2000 MICS 2000 national 68.9 Timor Leste 2002 MICS 2002 national 47.7 Vietnam 2000 MICS 2000 national 6.5 THE AMERICAS COUNTRY YEAR SOURCE SCALE TOTAL Guyana 2000 MICS 2000 national 2.6 Malarial Case Notification and Coverage with Key Interventions 143 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 51.7 48.5 60.6 42.1 32.1 41.3 54.6 61.3 75.3 27.1 23.9 28.4 26.9 35.1 16.2 28.3 27.7 18.7 60.2 59.8 62.2 59.4 56.8 58.1 61.3 61.2 70.0 54.3 52.4 61.7 51.6 -- -- -- -- -- 52.8 51.0 49.3 52.7 -- -- -- -- -- 58.2 57.8 57.9 58.0 52.6 50.4 66.7 56.9 65.5 GENDER RESIDENCE WEALTH QUINTILE MALE FEMALE URBAN RURAL POOREST SECOND MIDDLE FOURTH RICHEST 1.4 -- 0.8 0.8 -- -- 2.6 1.7 -- 3.6 5.2 5.7 3.6 -- -- -- -- -- 1.1 1.5 1.1 1.7 -- -- -- -- -- 7.4 7.9 2.1 10.1 8.3 14.0 9.5 2.4 10.6 63.9 76.0 100.0 68.3 60.9 85.7 71.4 62.5 100.0 46.6 48.2 55.8 45.3 44.0 41.2 47.9 49.4 60.8 7.4 5.6 10.3 5.7 8.1 7.0 2.6 6.1 10.2 GENDER RESIDENCE MALE FEMALE URBAN RURAL 1.0 4.3 2.6 144 Rolling Back Malaria Data Table 17: Summary of Antimalarial Drug Efficacy Results, Expressed as Treatment Failure MONOTHERAPY Chloroquine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Angola 2002 6 41.8 8.2 54.1 14.8 52.1 Benin 1998­2002 14 19.4 3.4 47.6 14.1 23.2 Botswana 1997­2000 6 24.4 20.7 44.0 20.7 44.0 Burkina Faso 1996­2003 24 12.0 5.3 35.5 10.0 21.7 Burundi 2001 4 69.2 52.4 73.7 58.9 73.4 Cameroon 1994­2001 12 33.0 2.0 66.6 15.9 58.2 Central African Republic 1997­1998 5 20.8 19.0 57.1 19.3 39.6 Chad 1999­2003 3 21.5 14.2 67.4 14.2 67.4 Comoros 1997­2001 9 57.1 31.2 75.0 42.4 67.3 Congo 1999­2001 2 44.0 38.0 50.0 38.0 50.0 Côte d'Ivoire 1997­2002 26 16.4 1.8 43.1 11.4 19.3 Congo, Dem. Rep. of 2000­2001 7 48.0 29.4 80.0 34.0 50.0 Equatorial Guinea 1996­1999 2 48.9 42.1 55.6 42.1 55.6 Eritrea 1997­2001 29 42.8 12.6 66.6 28.6 47.3 Ethiopia 1996­1998 18 70.0 5.0 97.8 55.8 85.2 Gabon 2001 2 57.1 52.2 62.0 52.2 62.0 Gambia 1998­2003 4 12.2 2.9 28.2 6.1 21.6 Ghana 1998­2003 9 23.2 9.0 31.3 15.8 29.7 Guinea 1996­2001 8 15.6 7.7 28.3 9.9 22.6 Guinea-Bissau 2001 3 6.8 5.4 10.9 5.4 10.9 Kenya 1996­1999 7 65.8 15.2 84.8 31.7 80.4 Liberia 1999 2 25.9 22.5 29.2 22.5 29.2 Madagascar 1996­2004 13 9.5 0.0 25.6 6.9 17.1 Mali 1996­2003 19 11.0 2.0 24.3 4.2 13.0 Mauritania 1998 2 24.0 11.6 36.4 11.6 36.4 Mozambique 1998­2001 20 35.9 13.0 53.0 22.1 42.9 Namibia 1997­2003 9 19.0 4.0 66.7 6.5 35.1 Niger 1998­2001 2 19.2 17.4 20.9 17.4 20.9 Nigeria 1998­2002 11 25.8 2.0 53.7 13.6 38.7 Rwanda 1997­2000 6 52.4 18.5 60.6 33.2 59.2 Senegal 1996­2002 19 12.9 2.7 30.7 10.1 16.6 Sierra Leone 1998­2003 7 34.5 26.3 58.5 32.0 51.5 Somalia 1997­2003 5 51.0 27.5 78.0 30.4 74.0 South Africa 1997 4 53.8 40.0 62.5 44.2 60.8 Sudan High transmission area 1996­2003 5 53.1 16.6 60.7 32.4 59.4 Moderate/low transmission area 1996­2003 24 50.0 0.0 80.3 33.8 65.6 Swaziland 2000 1 12.5 Togo 1998­2001 6 6.1 0.0 28.8 1.6 23.7 Uganda 1996­2001 18 29.3 7.5 81.2 16.4 58.7 Tanzania Mainland 1997­2001 8 43.0 27.6 71.0 36.6 53.5 Zanzibar 1997­2001 2 60.5 60.2 60.8 60.2 60.8 Malarial Case Notification and Coverage with Key Interventions 145 Data Table 17--Chloroquine, continued AFRICA, continued RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Zambia 1996­2002 22 31.9 6.6 54.0 24.6 46.3 Zimbabwe 1999­2003 28 10.8 0.0 42.3 5.0 19.9 TOTAL: Africa 1994­2004 433 24.0 0.0 97.8 12.6 43.9 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Afghanistan 1999­2002 4 67.7 60.0 89.5 61.7 80.8 Bangladesh 1996­1999 3 63.6 50.0 77.2 50.0 77.2 Bhutan 1997 4 78.1 64.7 80.7 70.8 80.0 China 1997­1999 2 29.6 18.4 40.7 18.4 40.7 India 1996­2004 25 34.0 0.0 95.9 23.6 65.4 Indonesia 1995­2003 18 69.5 11.1 100.0 49.5 78.3 Iran, Islamic Rep. 2000­2002 4 72.5 61.0 75.0 66.4 74.2 Lao PDR 1998­2002 5 44.8 31.3 52.8 36.7 49.5 Malaysia 2003 1 58.7 Myanmar 1997­2002 18 24.7 6.0 76.0 12.5 34.7 Pakistan 2001­2002 13 28.9 18.2 79.0 25.9 66.6 Philippines 1996­2000 9 42.1 16.4 76.2 32.1 52.0 Saudi Arabia 1997­1998 2 15.4 12.4 18.4 12.4 18.4 Solomon Islands 1997­2001 5 27.8 10.7 66.7 12.2 49.8 Sri Lanka 2002­2003 2 31.8 10.0 53.5 10.0 53.5 Tajikistan 2002 1 56.0 Timor Leste 2000 1 66.7 Vietnam 1997­2001 4 52.3 6.2 71.9 27.0 64.3 Yemen 1998­2003 9 42.4 9.0 57.0 23.3 44.9 TOTAL: Asia 1995­2004 130 44.1 0.0 100.0 26.3 66.7 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Colombia 1997­1998 5 66.6 44.5 96.6 47.3 83.7 Ecuador 1998­2003 4 85.4 83.3 94.4 84.2 90.1 Guyana 1998 1 55.6 Peru 1998­2002 6 86.4 75.6 90.0 78.3 89.8 Venezuela 1997­2002 5 48.6 0.0 100.0 13.1 88.6 TOTAL: The Americas 1997­2003 21 81.0 0.0 100.0 52.8 88.8 146 Rolling Back Malaria Data Table 17, continued Sulfadoxine pyrimethamine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Angola 2002­2003 8 5.7 0.0 28.2 2.7 8.8 Benin 2002 5 9.5 1.6 17.2 4.8 16.8 Burkina Faso 1998­2003 9 0.8 0.0 6.3 0.0 4.3 Burundi 2001 4 30.8 10.9 52.8 20.2 42.4 Cameroon 1997­2003 8 9.0 0.0 14.1 6.7 11.0 Chad 2002­2003 2 11.7 4.0 19.4 4.0 19.4 Comoros 2004 2 1.5 0.0 3.0 0.0 3.0 Congo 1999­2002 3 0.0 0.0 9.5 0.0 9.5 Côte d'Ivoire 1999 2 14.8 5.9 23.6 5.9 23.6 Congo, Dem. Rep. of 2000­2004 12 9.3 0.0 30.2 4.4 18.3 Equatorial Guinea 1996­1999 2 5.0 0.0 10.0 0.0 10.0 Eritrea 2001­2002 6 3.1 0.0 15.4 0.0 10.3 Ethiopia 1997­2003 17 10.3 0.0 44.9 2.0 26.1 Gabon 2000 1 4.4 Ghana 1998­2003 3 3.0 0.0 5.2 0.0 5.2 Kenya 1996­2003 27 8.4 0.0 51.6 3.4 17.9 Madagascar 2003 1 0.0 Malawi 1998­2002 15 18.6 2.8 40.0 16.6 33.3 Mali 2001­2003 3 0.6 0.0 2.0 0.0 2.0 Mozambique 1998­2002 10 5.4 0.2 17.3 2.7 13.7 Namibia 1997­2003 5 8.8 0.0 22.8 0.0 18.6 Nigeria 2001­2002 7 9.3 5.7 43.5 7.7 40.5 Rwanda 2000 3 35.1 11.6 35.7 11.6 35.7 Senegal 2001­2002 7 3.3 1.7 10.2 2.0 5.8 Sierra Leone 2001­2003 5 11.2 7.8 23.4 9.1 17.7 Somalia 1997­2003 3 4.0 2.0 5.9 2.0 5.9 South Africa 1997­2002 6 7.3 3.6 87.8 3.7 55.7 Sudan High transmission area 1996­2003 3 6.0 0.0 12.0 0.0 12.0 Moderate/low transmission area 1996­2003 7 4.1 0.0 22.0 1.0 9.9 Uganda 1996­2002 25 11.4 0.0 25.0 5.0 16.8 Tanzania Mainland 1997­2002 15 10.5 1.4 33.8 5.6 16.9 Zanzibar 1997­2002 2 8.9 4.7 13.1 4.7 13.1 Zambia 1996­2003 17 7.9 0.0 17.9 3.3 14.2 Zimbabwe 1999 2 10.0 0.0 20.0 0.0 20.0 TOTAL: Africa 1996­2004 247 8.6 0.0 52.8 3.3 16.6 Malarial Case Notification and Coverage with Key Interventions 147 Data Table 17--Sulfadoxine pyrimethamine, continued ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Afghanistan 2002­2003 3 8.7 4.0 22.7 4.0 22.7 Bhutan 1998 1 34.8 India 1999­2003 12 17.9 0.0 68.2 3.0 45.4 Indonesia 1996­2003 12 17.8 0.0 82.9 12.0 43.0 Iran, Islamic Rep. 1999­2001 3 0.0 0.0 5.7 0.0 5.7 Lao PDR 2001­2002 3 18.0 17.9 18.7 17.9 18.7 Malaysia 1996 1 29.4 Myanmar 1997­2002 18 27.8 0.0 100.0 7.9 37.7 Nepal 1997­2003 7 22.0 0.0 88.2 0.0 72.7 Pakistan 2001­2002 4 13.0 8.7 18.7 9.8 16.9 Philippines 2000­2001 7 42.6 8.5 66.7 12.5 60.6 Tajikistan 2002 1 16.0 Timor Leste 2001 1 10.0 Vietnam 1997­2002 4 12.7 5.5 70.6 8.9 41.9 Yemen 2003 1 0.0 TOTAL: Asia 1996­2003 78 18.4 0.0 100.0 8.5 40.8 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bolivia 2002 1 18.7 Colombia 1997­2002 12 10.8 0.0 26.5 1.9 15.8 Ecuador 2001­2003 3 4.0 0.0 17.1 0.0 17.1 Peru 1998­2002 9 11.8 0.0 80.0 1.7 65.2 Venezuela 1997­1999 3 20.0 0.0 23.0 0.0 23.0 TOTAL: The Americas 1997­2003 28 12.2 0.0 80.0 1.7 19.4 148 Rolling Back Malaria Data Table 17, continued Amodiaquine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Angola 2002­2003 2 8.7 3.9 13.4 3.9 13.4 Burkina Faso 1996 1 4.4 Cameroon 1997­2003 9 1.6 0.0 5.3 0.0 3.2 Chad 2002­2003 2 3.4 1.9 4.9 1.9 4.9 Ethiopia 1998 7 18.9 6.2 66.7 6.5 45.8 Gabon 1997­2002 5 12.5 3.2 14.0 7.9 14.0 Kenya 1996­2003 24 2.4 0.0 23.1 0.0 8.3 Liberia 2001 1 7.4 Madagascar 2004 1 0.0 Mozambique 2001 1 8.4 Nigeria 2001­2002 2 1.5 0.0 2.9 0.0 2.9 Rwanda 2001­2002 6 0.0 0.0 2.3 0.0 2.0 Senegal 2001­2002 3 2.8 2.0 5.1 2.0 5.1 Sierra Leone 2002­2003 5 1.8 0.0 7.6 0.0 5.8 Sudan High transmission area 2001 2 6.5 6.0 7.0 6.0 7.0 Uganda 1999­2002 5 8.8 0.0 14.5 1.6 12.3 Tanzania Mainland 1999­2002 12 3.7 0.0 10.8 1.6 6.9 Zanzibar 1999­2002 2 5.6 4.7 6.5 4.7 6.5 TOTAL: Africa 1996­2004 90 3.3 0.0 66.7 0.0 8.4 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Afghanistan 2004 1 37.7 Pakistan 2002 1 83.3 TOTAL: Asia 2002­2004 2 60.5 37.7 83.3 37.7 83.3 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Colombia 1997­2002 7 11.5 0.0 50.0 3.2 27.3 TOTAL: The Americas 1997­2002 7 11.5 0.0 50.0 3.2 27.3 Malarial Case Notification and Coverage with Key Interventions 149 Data Table 17, continued Mefloquine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Malawi 1998 1 10.2 Sudan Moderate/low transmission area 1999 1 2.5 TOTAL: Africa 1998­1999 2 2.5 2.5 2.5 2.5 2.5 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bangladesh 1996 1 27.2 Bhutan 1999 1 9.7 India 1996­2001 3 4.5 0.0 7.8 0.0 7.8 Lao PDR 2001 1 0.0 Malaysia 1996 1 0.0 Myanmar 1997­2002 18 6.0 0.0 44.4 0.0 16.4 Thailand 1995­2003 19 13.8 2.0 68.4 7.5 28.0 Vietnam 1998­1999 4 11.7 0.0 42.3 0.0 32.8 TOTAL: Asia 1995­2003 48 8.0 0.0 68.4 2.7 18.5 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bolivia 2001 2 0.0 0.0 0.0 0.0 0.0 Brazil 1996­2002 6 5.2 0.0 9.7 0.5 7.9 Colombia 2002­2003 3 2.2 0.0 6.4 0.0 6.4 French Guiana 1996 1 3.4 Guyana 2003 1 28.1 Peru 1999­2000 4 0.0 0.0 0.0 0.0 0.0 Suriname 2002 1 7.3 TOTAL: The Americas 1996­2003 18 1.6 0.0 28.1 0.0 6.2 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. 150 Rolling Back Malaria Data Table 17, continued COMBINATION THERAPY Chloroquine sulfadoxine pyrimethamine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Comoros 2003 3 0.0 0.0 2.6 0.0 2.6 Eritrea 2002­2003 4 6.5 0.0 10.2 1.9 9.7 Rwanda 2000 6 13.2 6.1 39.7 8.1 37.7 Sudan Moderate/low transmission area 2003 2 10.2 5.9 14.4 5.9 14.4 Uganda 1996­2003 15 12.0 0.0 37.0 7.0 19.0 Zimbabwe 2001­2004 25 1.1 0.0 8.6 0.0 3.9 TOTAL: Africa 1996­2004 55 4.3 0.0 39.7 0.5 10.1 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bangladesh 1996­2003 7 30.7 12.9 37.2 24.0 33.0 India 1 6.5 Indonesia 1999­2003 2 22.2 6.2 38.2 6.2 38.2 Lao PDR 2001 2 12.3 7.8 16.7 7.8 16.7 Malaysia 1999­2003 4 47.6 32.6 62.5 38.2 57.0 Papua New Guinea 1998­2003 4 0.0 0.0 27.0 0.0 13.5 Philippines 2001­2002 3 18.4 11.1 29.6 11.1 29.6 Tajikistan 2003 1 2.1 Vanuatu 2001 1 16.0 TOTAL: Asia 1996­2003 25 24.0 0.0 62.5 7.2 33.0 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Colombia 2002 2 17.4 12.1 22.6 12.1 22.6 Ecuador 2003 1 0.0 TOTAL: The Americas 2002­2003 3 12.1 0.0 22.6 0.0 22.6 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. Malarial Case Notification and Coverage with Key Interventions 151 Data Table 17, continued Amodiaquine sulfadoxine pyrimethamine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Cameroon 2001­2003 4 0.0 0.0 0.0 0.0 0.0 Congo, Dem. Rep. of 2002­2004 5 1.7 0.0 6.0 0.7 4.4 Ghana 2002 1 1.4 Kenya 2003 2 2.0 1.6 2.4 1.6 2.4 Mozambique 2001 1 0.0 Rwanda 2001 3 0.0 0.0 0.0 0.0 0.0 Senegal 2001­2003 4 0.0 0.0 0.0 0.0 0.0 Uganda 1999­2003 12 1.6 0.0 13.0 0.5 3.5 Tanzania Mainland 1999 1 3.4 TOTAL: Africa 1999­2004 33 1.0 0.0 13.0 0.0 2.2 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Afghanistan 2003­2004 2 2.0 1.0 3.0 1.0 3.0 Papua New Guinea 1998 1 0.0 TOTAL: Asia 1998­2004 3 1.0 0.0 3.0 0.0 3.0 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Colombia 2001­2003 4 2.3 0.0 10.8 1.1 6.6 TOTAL: The Americas 2001­2003 4 2.3 0.0 10.8 1.1 6.6 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. 152 Rolling Back Malaria Data Table 17, continued Artemether lumefantrine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Burundi 2001 2 0.0 0.0 0.0 0.0 0.0 Comoros 2004 3 0.0 0.0 1.8 0.0 1.8 Ethiopia 2003 4 0.0 0.0 0.0 0.0 0.0 Gabon 2001­2002 2 0.8 0.0 1.6 0.0 1.6 Ghana 2003 1 0.0 Senegal 2003 1 0.0 South Africa 2002 1 0.0 Tanzania Zanzibar 2002 2 1.0 0.0 2.0 0.0 2.0 Zambia 2003 3 0.0 0.0 0.0 0.0 0.0 TOTAL: Africa 2001­2004 19 0.0 0.0 2.0 0.0 0.0 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bangladesh 2002 1 0.8 Cambodia 2001­2004 3 26.9 13.5 30.0 13.5 30.0 Lao PDR 2001­2003 2 4.7 3.1 6.3 3.1 6.3 Myanmar 2003 3 2.0 0.0 2.0 0.0 2.0 Thailand 1996­2002 6 2.6 0.0 3.9 0.5 3.5 Vietnam 2001 1 2.2 TOTAL: Asia 1996­2004 16 2.6 0.0 30.0 1.5 5.1 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Suriname 2003 2 2.0 1.9 2.0 1.9 2.0 TOTAL: The Americas 2003 2 2.0 1.9 2.0 1.9 2.0 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. Malarial Case Notification and Coverage with Key Interventions 153 Data Table 17, continued Artesunate amodiaquine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Angola 2003 1 0.0 Burundi 2001 2 1.3 0.0 2.6 0.0 2.6 Comoros 2003 3 0.0 0.0 0.0 0.0 0.0 Congo, Dem. Rep. of 2003­2004 3 0.0 0.0 1.4 0.0 1.4 Eritrea 2002­2003 3 0.0 0.0 1.4 0.0 1.4 Gabon 2001­2002 2 0.9 0.0 1.7 0.0 1.7 Ghana 2003 1 0.0 Mozambique 2001 1 0.0 Rwanda 2002 3 0.0 0.0 1.6 0.0 1.6 Senegal 2002 2 0.0 0.0 0.0 0.0 0.0 Sudan High transmission area 2003 2 0.4 0.0 0.8 0.0 0.8 Uganda 2002­2003 5 1.0 0.0 4.0 0.5 3.7 Tanzania Zanzibar 2002 2 1.9 1.8 1.9 1.8 1.9 TOTAL: Africa 2001­2004 30 0.0 0.0 4.0 0.0 1.5 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Myanmar 2003 4 4.0 3.0 7.0 3.5 5.5 Pakistan 2002 1 18.0 TOTAL: Asia 2002­2003 5 4.0 3.0 18.0 3.5 12.5 154 Rolling Back Malaria Data Table 17, continued Artesunate chloroquine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Gambia 2000 1 3.2 TOTAL: Africa 2000 1 3.2 3.2 3.2 3.2 3.2 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Pakistan 2002 1 28.8 Vietnam 2 37.4 28.0 46.8 28.0 46.8 TOTAL: Asia 2002 3 28.8 28.0 46.8 28.0 46.8 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. Malarial Case Notification and Coverage with Key Interventions 155 Data Table 17, continued Artesunate sulfadoxine pyrimethamine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Angola 2003 1 1.2 Comoros 2003 3 0.0 0.0 3.6 0.0 3.6 Congo, Dem. Rep. of 2002­2004 6 0.0 0.0 5.6 0.0 3.4 Ghana 2002 1 0.8 Mozambique 2001 1 0.0 Rwanda 2001 3 0.0 0.0 0.0 0.0 0.0 South Africa 2004 1 5.0 Sudan High transmission area 2003 2 1.7 0.8 2.5 0.8 2.5 Uganda 2000 1 0.5 Zambia 2002­2003 5 0.0 0.0 1.7 0.0 0.9 TOTAL: Africa 2000­2004 24 0.0 0.0 5.6 0.0 1.1 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Indonesia 1999 1 4.3 Myanmar 2003 2 0.0 0.0 0.0 0.0 0.0 Pakistan 2002 1 0.0 Sri Lanka 1999 1 0.0 Vietnam 2 33.2 8.3 58.1 8.3 58.1 TOTAL: Asia 1999­2003 7 0.0 0.0 58.1 0.0 8.3 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Ecuador 2003 2 0.0 0.0 0.0 0.0 0.0 Peru 2000 1 1.1 TOTAL: The Americas 2000­2003 3 0.0 0.0 1.1 0.0 1.1 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. 156 Rolling Back Malaria Data Table 17, continued Artesunate mefloquine AFRICA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Senegal 2002 2 0.0 0.0 0.0 0.0 0.0 TOTAL: Africa 2002 2 0.0 0.0 0.0 0.0 0.0 ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bangladesh 2002 1 0.9 Cambodia 2001­2004 12 3.7 0.0 18.8 1.1 8.1 India 2001 2 6.4 1.9 10.9 1.9 10.9 Lao PDR 2001­2003 2 0.0 0.0 0.0 0.0 0.0 Myanmar 1996­2003 10 1.5 0.0 8.0 0.0 5.1 Thailand 1995­2003 35 4.0 0.0 27.2 1.3 8.1 Vietnam 1998­2000 2 5.6 0.0 11.1 0.0 11.1 TOTAL: Asia 1995­2004 64 3.2 0.0 27.2 0.3 7.9 THE AMERICAS RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bolivia 2001 3 0.0 0.0 0.0 0.0 0.0 Guyana 2003 1 7.5 Peru 2000 1 0.0 Suriname 2002­2003 2 4.1 2.4 5.8 2.4 5.8 TOTAL: The Americas 2000­2003 7 0.0 0.0 7.5 0.0 5.8 Artesunate combinations ASIA RANGE PERCENTILE COUNTRY STUDY YEARS NUMBER OF STUDIES MEDIAN LOW HIGH 25TH 75TH Bhutan 2000­2003 8 4.9 1.1 12.0 2.2 8.7 TOTAL: Asia 2000­2003 8 4.9 1.1 12.0 2.2 8.7 Notes: Median, range, and quartiles are based on percentage clinical failure with at least 14-day follow up for countries in Africa south of the Sahara. For all other areas, including South Africa and moderate/low transmission areas of Sudan, percentage total failure is used. APPENDIX 3 Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam Summary In the last decade, while many countries have struggled to slow the spread of malaria, four countries--Brazil, Eritrea, India, and Vietnam--have suc- cessfully and dramatically reduced their malaria burden. The keys to these successes have been multiple, including: · Conducive country conditions · A sound and targeted technical approach, using a package of effective tools · Data-driven decision making based on good surveillance and operational research · Strong leadership and commitment at all levels of government · Community involvement in planning and implementation · Decentralized control of finances and implementation supported by a strong national control program · Ability of managers to efficiently navigate bureaucratic hurdles · Infrastructure and skilled technical capacity at national and subnational levels 157 158 Rolling Back Malaria · Proactive technical and programmatic support from partner agencies · Sufficient financing to take control activities to scale · Flexibility in approach by the World Bank. No single factor or small group of factors appears to be sufficient in achieving these successes. Many of these key success factors could be adapted to other country contexts. The World Bank played an essential role in both providing sufficient financing to achieve appropriate scale and mobilizing necessary supervisory support for the projects. A more proactive engagement by the Bank in other countries could yield similar successes. If the goals of RBM are to be achieved, governments and their partners must work to address as many of these key factors as are feasible and rele- vant. The World Bank must take a more active and flexible role in support- ing countries to roll back malaria. Introduction In recent years, several new and highly effective tools have been developed in the fight against malaria. Insecticide-treated bed nets can reduce all-cause child mortality by as much as 25 percent. Intermittent presumptive treat- ment of pregnant women can significantly reduce low birth weight in their newborns. In addition, ACTs hold great promise for reducing severe mor- bidity and mortality from malaria and for curtailing onward transmission of infection. Despite these great advances, progress in reducing the global burden of malaria has been slow. Many malaria-affected countries have experienced great difficulty taking these interventions to scale. Lack of sufficient financ- ing, poor public health infrastructures, limited skilled human capacity, poor quality health services and commodities in the private sector, and lack of intersectoral collaboration have all been posited as possible barriers to scal- ing up malaria control interventions. Such challenges have led some to question whether the RBM Partnership, which was formed in 1998 to assist countries to take proven malaria control measures to scale, will be success- ful in achieving its goal of halving the global burden of malaria by 50 per- cent by 2010. Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam 159 RBM, though, has not been without its achievements. With the support of the World Bank and other RBM partners, four countries have been suc- cessful in reducing malaria morbidity and mortality during the last decade. The experiences of Brazil, Eritrea, India, and Vietnam provide strong evi- dence that control of malaria is possible with existing tools. These success stories offer hope to other affected countries that control of malaria is pos- sible. This report briefly documents the malaria control efforts of these four countries and discusses key factors that led to the success of these programs. Methods Information for this report was gathered from a number of sources. World Bank project supervision documents and available published and unpub- lished reports were reviewed. Informal interviews were conducted with some World Bank staff persons who were involved in the design or supervi- sion of these projects. Information and insights were also sought from key country-level informants, including National Malaria Control Program Managers and WHO regional and country office staff. This report also reflects the viewpoints of the author, who was involved in the design and supervision of the Eritrea HIV/AIDS, Malaria, STD and TB (HAMSET) Control Project and in the supervision of the India Enhanced Malaria Con- trol Project (EMCP). All information was evaluated looking for common factors in the four countries that may have contributed to the success of the malaria control program. Draft versions of this manuscript were then shared with key World Bank and country informants for review and comment. Findings Brazil From 1989 through 1996, the Ministry of Health of Brazil implemented the Amazon Basin Malaria Control Project or PCMAM. Financial support was provided by the World Bank (US$73 million) and technical support from the Pan American Health Organization (PAHO). This project originally focused on vector control activities, including indoor residual spraying 160 Rolling Back Malaria (IRS) and environmental management, with a lesser focus on case manage- ment and disease surveillance. During the project period, two significant events would greatly affect the progress of malaria control efforts. Control of implementation of malaria control activities was devolved from SUCAM, the national malaria control program, to municipalities as part of a larger government decentralization initiative. SUCAM retained responsibility for procuring and distributing commodities, including drugs and insecticides, setting standards, and pro- viding technical support. Decentralization provided municipalities for the first time with the financial resources to invest in malaria control activities and generated local ownership of these efforts. During the same period, Brazil's national malaria control strategy was revised in line with WHO's global strategy. Features of the new strategy included highly selective targeting of control efforts to high-risk municipal- ities. This required strengthening of malaria case detection and better use of surveillance data in decision making. The new strategy also shifted emphasis from vector control activities to more aggressive management of clinical cases, which included the introduction of artemisinin-based drug treatments. Antimalarials were made widely available, including in local shops in mining areas. All cases of fever in these areas were presumptively treated for malaria. Malaria transmission was controlled elsewhere in Brazil by 1980, but in the Amazon Basin cases increased steadily until 1989, to almost half a mil- lion a year and the coefficient of mortality quadrupled in 1977-88. A World Bank project supported the program from late 1989 to mid-1996, and in 1992-93, with advice from the Pan American Health Organization, facili- tated a change toward earlier and more aggressive case treatment and more concentrated vector control. The epidemic stopped expanding in 1990-91 and reversed in 1992-96. The effect of this change was to reduce incidence much below the level it would have reached, preventing an estimated 1.73 million cases. The result of fewer cases and lower fatality from those cases that did occur was to avert an estimated 231,000 deaths over the 7-1/2 years of the program. Converting the savings in lives and in morbidity into Dis- ability-Adjusted Life Years (DALYs) yields almost 9 million DALYs, 5.1 mil- lion from treatment and 3.9 million from prevention. Nearly all the gain came from controlling deaths and therefore from controlling falciparum (Akhavan, Musgrove, Abrantes, and Gusmao 1999) Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam 161 Eritrea In response to a large malaria epidemic in 2000 and growing concerns about HIV/AIDS, the Ministry of Health of Eritrea established a new strategy for control of its high-burden communicable diseases. The combined program to control HIV/AIDS, malaria, STDs, and TB was dubbed HAMSET. The World Bank provided US$40 million support through the HAMSET Project. Coincident with this investment, USAID provided significant resources to the Ministry of Health for technical support on malaria through their Environmental Health Project (EHP). The technical strategy employed in Eritrea stressed more targeted use of IRS to the highest-risk areas, use of environmental management, scaling up of ITNs, and expansion of diagnosis and effective treatment. Key to these efforts was a strengthening of disease surveillance and operational research activities, and the use of these data in priority setting. EHP provided essen- tial technical support to these efforts, including support for expatriate staff to develop capacity in entomology and epidemiology at national and subna- tional levels. One of the objectives of the HAMSET program was to decentralize implementation of control activities to zoba (zonal) and sub-zoba levels. Zobas were provided with financial resources based on approved annual work plans. Many activities were focused on building technical and mana- gerial capacity at zoba and sub-zoba levels. In addition, communities were actively involved in malaria control activities, including the distribution and retreatment of ITNs and environmental management (for example, filling of temporary water bodies and larviciding). To date, the use of ITNs by children under five years in malarious areas of Eritrea has risen from 20 percent in 2000 to 63 percent in 2003, while the use of IRS has decreased. Despite recent heavy rains and large epidemics in neighboring countries, Eritrea has reduced malaria morbidity from 179,501 reported cases in 1999 to 65,540 cases in 2003, a 63 percent decline. Deaths from malaria fell from 176 to 78 during the same period, a decrease in mor- tality rate from 13.3 percent to 3.9 percent. India In 1997, the World Bank provided US$165 million in financing for the Enhanced Malaria Control Project (EMCP). EMCP invested in the 100 162 Rolling Back Malaria highest-risk districts in eight North Indian states. One of the primary objec- tives of EMCP was to assist India's Ministry of Health to transition from its unsuccessful eradication strategy to a more modern control strategy. Wide- spread use of IRS would become more targeted and supplemented by a broader range of control activities, including early diagnosis and prompt treatment of malaria cases, promotion of ITNs, use of alternative vector control methods (including environmental management and larvivorous fish), and strengthening of malaria surveillance. Progress during the first years of the project was slow, in part because the initial project design excluded state health departments from implementa- tion activities. Districts were to be supervised directly by the National Anti- Malaria Program. After an unsatisfactory mid-term review, the project was redesigned. Most notably, state malaria control societies were provided with financing and took on a primary role in supervising and supporting district health staff. After the redesign, implementation remained slow, causing the Bank to suspend disbursement. A change in leadership within the Ministry of Health and the National Anti-Malaria Program brought renewed interest in revi- talizing EMCP. Outstanding issues were quickly addressed, the suspension was lifted, and the implementation took off rapidly. Since the restart of the project, more than 300,000 village-based volun- teers have been trained in malaria case management and provided supplies of chloroquine. Laboratory capacity has been greatly expanded; approxi- mately 14 million blood slides were examined last year. Almost 3 million ITNs have been distributed and more than 20,000 larvivorous fish hatch- eries established. Local governments, community groups, and NGOs have become actively involved in a number of activities, including distribution and retreatment of ITNs, breeding and stocking of larvivorous fish, and community awareness campaigns. Reported cases of malaria declined by 93.3 percent, 80.8 percent, and 40.6 percent for the states of Maharashtra, Gujarat, and Rajasthan, respec- tively, from 1997 to 2002.20 Vietnam After many years of good control, Vietnam experienced a dramatic upsurge in malaria burden during the late 1980s and early 1990s. Vietnam's National Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam 163 Institute of Malariology, Parasitology, and Entomology (NIMPE) devel- oped an aggressive plan to control malaria and the Government of Vietnam requested financial support from the World Bank to implement this plan. In 1997, a Health Sector Support Project was launched with a sizable malaria control component (US$25 million). This project supported procurement of insecticides, drugs, and some equipment for all 61 provinces, but focused most of its resources on 15 high-burden provinces. These 15 provinces were targeted for training in case management, strengthening of surveillance activities, public awareness campaigns, and improvement of laboratory capacity. Technical support for implementation activities was provided by the WHO Regional Office for the Western Pacific. As with the other successful programs, the technical approach included targeted use of IRS, promotion of ITN use, and use of effective treatment for clinical cases. National drug policy was changed to replace ineffective treatments with mefloquine and later artemisinin-based drugs. More than 1 million ITNs were distributed with support from the project. Community groups (such as youth leagues and women's unions) and village heads played key roles in information, education, and communication (IEC) activities, distribution of ITNs, and community-based treatment activities. During the project period, the number of malaria cases dropped in 2003 to 37 percent of 1997 levels (445,200 to 164,706 cases). Malaria mortality decreased from 153 in 1997 to 50 in 2003, a mortality rate of 0.06 percent. Outbreaks of malaria ceased. Key Success Factors Epidemiologic factors The four countries are in different geographic regions, have different mos- quito vectors, and are subject to different climatic conditions. Despite these differences, there are some similarities in the epidemiologic pattern of malaria. All four countries are characterized by wide geographic variability of dis- ease risk and burden. The variability in risk is strongly related to variations in local climate. Arid, temperate, and mountainous regions have low to no risk, while risk is higher in tropical and subtropical areas and in areas with 164 Rolling Back Malaria heavy rainfall. The population at risk of severe disease and death is greatly affected by the intensity of transmission. In contrast to tropical Africa, where most of the burden is borne by young children, malaria in these four countries kills and severely debilitates people of all ages. In each of the four countries, development of new program strategies was preceded by periods of large epidemics or markedly increased malaria burden that heavily affected peo- ple in their productive years of life. Although overall transmission intensity is moderate to low in these four countries, one cannot necessarily conclude that similar success is unachiev- able in countries with intense transmission. Each of these countries has been successful in reducing malaria burden in pockets of high-level transmission where these efforts were primarily targeted. This should give hope that con- trol is possible in other high transmission areas. In addition, malaria burden in Brazil, India, and Vietnam is most heavily concentrated in areas with sizable tribal or indigenous populations. The health infrastructure in these areas is generally much weaker than in the rest of the country and comparable to that of many parts of Africa. These pop- ulations are usually the most disconnected from public health structures and most resistant to health promotion activities. Country context These four successful programs were launched in periods of relatively strong economic growth and political stability in these countries. Vietnam was rapidly recovering from a period of economic crisis. Brazil and India had growing economies. The effect of such favorable economic conditions on the health sector was most notable in Vietnam, where government investments in health almost tripled in the period between 1991 and 1994. Eritrea appears to be the one exception, as the country's economy has dete- riorated somewhat since the launch of the project. In each of these countries, commitment to malaria control was strong at the highest levels of government. At the core of this commitment was the recognition that malaria was a barrier to economic development. Evidence of such commitment moved well beyond simple rhetoric to increased investment of government resources in malaria control. Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam 165 Technical approach All four countries adopted strikingly similar technical approaches to control malaria. Prior to the implementation of these programs, their malaria con- trol strategies focused heavily on vector control, particularly use of IRS. The new strategy sought to use multiple approaches to controlling malaria, balancing case management with prevention measures, and introducing new technologies, particularly ITNs. In three of the four projects (India, Brazil, and Vietnam), this shift in strategy was explicitly listed as an objective of the World Bank-assisted project. The new strategy shifted emphasis to improving and expanding the avail- ability of effective case management. Vector control efforts, particularly IRS, became more targeted as alternative vector control measures were scaled up. Such alternative measures included environmental management (all coun- tries), larviciding (Eritrea), and use of larvivorous fish (India). With the exception of Brazil, distribution of ITNs became a key prevention strategy. Another fundamental change in the approach to malaria control was the emphasis on targeting interventions to high-risk areas. In Vietnam, Brazil, and India, a significant portion of the Bank's resources was for use only in such high-risk areas. In India, these were the 100 most heavily affected dis- tricts in eight states. Similarly, investments were highly targeted to high-risk municipalities in the Amazon Basin in Brazil and the 15 high-burden provinces in Vietnam. Even in Eritrea, where targeting was not central to the project design, control efforts were more focused on the most heavily affected zones. Such targeting was possible only because these countries invested heavily in improving their malaria surveillance systems. Laboratory capacity was strengthened and case reporting was streamlined, integrated, and computerized. These efforts improved both the completeness and time- liness of case reporting. There also was a strong emphasis in developing capacity at the subnational level to analyze and interpret surveillance data, which then impacted decision making at the district level. Programmatic factors Prior to the implementation of these programs, all four countries had ver- tical, centrally managed implementation strategies. Under this arrange- ment, village-level functionaries were paid by the national malaria control program and worked solely on malaria control. The most extreme example 166 Rolling Back Malaria of this was in Brazil, where malaria treatment was provided by free-stand- ing malaria clinics, which had no formal link to local public health facilities. With the development of new control strategies in these countries, there was a significant move toward integration and decentralization of imple- mentation. Brazil decentralized most government functions during the first few years of the malaria control program, shifting the responsibility and resources for malaria control to municipalities. In Eritrea and India, much of the responsibility for implementation was shifted to zonal and state health authorities, respectively. The decentralization of responsibility and resources frequently stimulated local governments to become more involved in malaria control efforts. Local involvement has been seen as piv- otal to the success in India, Brazil, and, to some extent, Eritrea. Despite this move toward integration, the national malaria control pro- grams remained strong and continued to play important roles in program implementation. The national programs were still looked to for technical support and for procurement of essential commodities, including drugs, insecticides, ITNs, and laboratory equipment. These four programs were led by directors who had strong technical and managerial skills. They understood the systems in which they worked and were capable of moving things quickly through their bureaucracies. These skills were likely acquired from years of managing vertical programs. All four countries appear to have benefited from the extensive networks that remained from the earlier vertical programs. These networks provided the basic infrastructure necessary for efficient and effective implementation of program activities. In general, these countries had much more developed public health infra- structures than many other malaria-affected countries, particularly those in Sub-Saharan Africa. It must be noted, though, that the areas targeted by these projects often had infrastructures that were much weaker than the rest of the country. One characteristic that distinguishes these four country programs from most other malaria-affected countries is the presence of skilled technical staff at the subnational level. India's experiences during the first half of the project period demonstrate that their program would not have achieved such success without the involvement of the state malaria control programs. The same could be said of the zonal malaria control officers in Eritrea. These programs also built technical and programmatic capacity at district and, in some cases, subdistrict levels. Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam 167 Partnership issues These four countries were notable in the limited number of major imple- mentation partners involved at the national level. Beyond the involvement of the World Bank, Vietnam, Brazil, and Eritrea had only one major part- ner in their efforts. In Vietnam and Brazil, it was the regional offices of WHO (Regional Office for the Western Pacific and the Pan American Health Organization) that played key roles in providing technical guidance and support. In Eritrea, USAID's Environmental Health Program played a similar technical support role. At the local level, partnerships have flourished. In India, the local health departments have often partnered with tribal welfare, education, and agri- cultural departments, as well as NGOs, community groups, local govern- ments, and private providers. Private shopkeepers also played an important role in expanding treatment in Brazil's mining areas. These partnerships have generally been focused on specific activities. For example, NGOs in India are contracted to distribute and re-treat ITNs and tribal welfare work- ers offer malaria treatment to the surrounding community. Financing The financing provided by the World Bank coupled with increases in resources provided by the government represented a dramatic increase in funding for malaria control activities in India, Eritrea, and Vietnam. Most strikingly, Vietnam's investment in malaria control increased almost 12-fold from 1991 to 1995 (from US$0.55 million to US$6.4 million). In all countries, the investments provided by governments went beyond support solely for salaries and minor operating expenses. In India, govern- ment support to the National Anti-Malaria Program was quite substantial and included resources for procurement of all required stocks of DDT. Sev- eral state governments also invested some of their own resources in malaria control. Notwithstanding the slow rate of implementation in the first years of each project, disbursement and use of funds was rather brisk compared to health projects in many other countries. What could account for the rapid- ity of disbursement was the control exerted over the available resources by the national malaria control program managers. These program managers had either direct control or easy access to those who did control the purse 168 Rolling Back Malaria strings. They also had a great capacity to move their bureaucracies so that finances flowed and procurements were made in a timely manner. This is in contrast to many African countries, where malaria control program man- agers have often reported significant barriers to accessing funds that have been allocated to their programs from World Bank grants and credits. One factor that was felt to be pivotal to the success of the program in Brazil was the decentralization of control of resources to municipalities. This allowed these local authorities to prioritize spending on malaria, based on local needs. It also provided a strong sense of ownership to municipal governments. The experience was similar for India, where the program ini- tially faltered until state health departments were given control of some resources. Providing resources directly to zonal health authorities was also a key component of the Eritrea project. World Bank factors The World Bank's approach to supervision of these projects was much more hands-on. The Bank ensured active technical supervision either through its own resources or through partner agencies, including WHO and USAID. Substantial programmatic support also was provided. In Eritrea, for exam- ple, when implementation was behind schedule, the Task Manager worked with the Ministry of Health to break large activities into a series of smaller tasks with benchmarks. This "Rapid Results Initiative" quickly accelerated implementation of project activities. Another feature of the Bank's involvement in these four countries was its flexibility. In India, after an unsatisfactory mid-term review, the Bank worked aggressively with the government to significantly restructure the project and remove major bottlenecks to implementation. The Bank also demonstrated flexibility in the procedures for procuring insecticides. Simi- larly, the Bank reallocated funds from an earlier health sector project in Eritrea so that the Ministry of Health could purchase antimalarial drugs in response to a large malaria epidemic. The Bank was not averse, though, to restricting the use of funds when progress was not satisfactory. In India, for example, when progress remained slow after the project redesign, the Bank suspended disbursement on all project components until the government met a series of benchmarks, which included the review and revision of some malaria control policies. Four Success Stories: Malaria Control in Brazil, Eritrea, India, and Vietnam 169 Conclusions Clearly, the success of these four malaria control programs was the result of the confluence of a number of factors. A sound targeted technical approach, skilled human resources and good infrastructure at national and subnational levels, strong technical and programmatic support from the World Bank and its partners, and sufficient finances were all essential for these programs to accomplish their goals. Many of the lessons learned from these program successes could be adapted by other countries. Countries interested in achieving such successes must strive to address most or all of these key factors. Focusing on only a few of them is unlikely to achieve these goals. These country examples also point out that design does matter. Control efforts faltered in India and Brazil until the programs were redesigned. Notably, decentralization of program implementation and financing greatly facilitated the progress of these programs. It also was important, though, that a strong central malaria control program be maintained. The World Bank played an important role in the success of these pro- grams that went beyond simply providing financing. Consistent and proac- tive technical and programmatic support mobilized by the Bank was an important contribution to their success. So, too, was the willingness of the Bank to be flexible, supporting the redesign and reallocation of financing to overcome barriers and meet the changing needs of the program. The Bank also used its leverage with governments that were reluctant to effect changes in policy or program implementation. If forced to select the most important factor in the success of these pro- grams, it would have to be strong commitment and leadership at all levels of government. Decision makers in these countries did not consider these interventions to be World Bank projects, but rather their country programs. Government and community leaders from national to local levels consid- ered malaria a priority problem and dedicated their resources and man- power to address it. Managers of national malaria control programs under- stood what worked in their countries and knew how to effectively navigate their bureaucracies. Without this leadership and ownership, it is doubtful that these programs would have gotten off the ground even if all other suc- cess factors had been in place. APPENDIX 4 Strategic Communications Context An important component of the Global Strategy and Program of Action for Malaria Control is a strategic communications plan. RBM partners held a communications and advocacy meeting on September 1­3, 2004, to develop a comprehensive strategy in support of malaria control, providing a context for the Bank to renew its operational and communications strategies simul- taneously. Goals · Generate or renew awareness among external partners of the Bank's pri- orities and business model for supporting countries in controlling malaria. · Generate or improve awareness among internal constituencies of the Bank's comparative advantages in malaria control and the potential for deploying it to maximum effect (including flexibility and simplification of procedures and instruments). Audience(s) Media: Help the media better understand core issues of malaria control as a core health and development issue. Highlight the Bank's role in malaria 171 172 Rolling Back Malaria control--past, present, and future. Advocate for better communication with the general public on challenges to achieving this goal. Civil Society/Faith-Based Organizations: Help civil society better understand the Bank's support for malaria control programs and challenges to suc- cess. Communicate what the Bank's role is and is not, so that this is reflected broadly. Bank Staff: Communicate internally with staff on the development impact of malaria, including all the subtopics relevant to their work. In other words, this is not just another fad, but a fundamental development issue. Bank Senior Management: Get senior management to speak publicly more often about malaria as a core part of the development agenda in many client countries. This should not only be occurring on Africa Malaria Day, but also more regularly at major international health forums. Policymakers/Parliamentarians: Raise awareness of Bank malaria control pro- grams among policy makers and decision makers in countries so that they fully understand what resources are available and how to gain access to funds. Communications Staff at the Bank: Coordinate announcements and interac- tion with the public at large on the Bank's malaria control programs. Strategically coordinate activities for the best possible impact, and estab- lish a core communications group that will be kept in the loop as issues develop. RBM Partners: Routinely communicate with the RBM Secretariat and core RBM partners on progress of the Bank's Global Malaria Strategy. Link up with global advocacy efforts in a visible way, including issuing joint press releases with selected partners, depending on the issue, the audi- ence, and the context. Messages: A communication campaign's bottom line. The Bank is fully committed to a serious effort to close the gap between knowing and doing in malaria control. The Bank will develop key messages that convey what we aim to achieve. The core malaria communications team will coordinate with the Bank's communicable disease coordinator and key Health, Nutrition, and Popula- Strategic Communications 173 tion (HNP) staff to establish core messages on two levels: (i) the global level and (ii) a regional/country level. A few initial ideas include: · Resolving nonfinancial constraints ­ Support program design and implementation ­ Facilitate access to undisbursed funds · Ensuring adequate financing ­ Increase IDA financing for malaria control ­ Leverage funds from other financiers · Rebranding the Bank's work on malaria ­ Outcome-oriented ­ Responsive to clients ­ Flexible means ­ Transparent Key strategies include: · Organizing a core Malaria Communications Campaign Team that meets regularly to discuss and update strategy. Merge the subunit communica- tion strategies for the better common good of achieving the Bank's over- all goals of rolling back malaria. This strategy will encompass corporate communications, development/project communications, internal com- munications, civil society, parliamentarians, and other relevant stake- holders as appropriate. · Developing a general map that lays out who the key team members are for each category. The main categories are: · Media · Civil society · Parliamentarians · Publications · Speakers bureau · Youth outreach · Partnerships · Private sector development 174 Rolling Back Malaria · Capitalizing on existing communications channels. Create a malaria communications toolkit to assist CommNet staff. CommNet staff should regularly participate in supervision missions in order to understand the successes and challenges of project implementation and share those sto- ries with key audiences. · Ensuring collaboration and active participation in the Malaria Commu- nications Strategy by regional representatives, especially from the Africa region. A key part of the overall strategy is building a solid, committed Bank-wide Malaria Communications Team with clear role definition. APPENDIX 5 High-Impact Partnerships: Private Sector and Civil Society As there are transaction costs to working in partnership, the benefits of so doing need to be clear. The reasoning behind this strategy is based on prag- matism. Without partnering with the formal and informal private sectors, as well as with civil society, the Bank will be unable to leverage their capacities to support substantial increases in coverage, which is critical to reducing dis- ease transmission, morbidity, and mortality. In addition, given the increas- ing financial demands for malaria control worldwide, coordination and cofi- nancing will be key. The Bank will leverage complementary investments by committing resources, identifying unmet needs, and supporting ownership and dialogue around common implementation strategies. Global-level part- nerships will be useful to the extent that they support country operations and help to achieve measurable impact at reasonable transaction costs. The Private Sector in Malaria Control Three layers of for-profit private sector will be engaged: (i) global providers for inputs such as ACTs and ITNs, (ii) international or local companies that employ large numbers of people in malarious affected countries, and (iii) health service providers, formal and informal. Each layer will have particu- lar contributions to be extracted and needs to be fulfilled. · Global providers need reliable forecasts. The Bank will have a regular dialogue to exchange information that has an impact on their forecasting. The new service, based at the RBM Secretariat called Malaria Medicines and Supply Service, aims to provide this function, but strengthened col- laboration with the Bank's procurement specialists and the IFC is needed. 175 176 Rolling Back Malaria · Large companies operating at the country level could become allies in the fight against malaria, offering treatment to their employees, their families, and communities. There are analogies to the role this part of the private sector plays in the fight against HIV/AIDS, and examples already exist relating to malaria. As part of its Chad-Cameroon Development Project, ExxonMobil protects project workers and their families with a strong malaria prevention and treatment program.21 · The informal health sector is the major supplier for malaria treatment in most countries. In the absence of adequate regulation and enforcement, what can be done to supply effective, good-quality medicines at prices affordable to the poor, through these informal channels? Issues such as pricing, financial incentives, distribution mechanisms, quality assurance, and counterfeiting come to mind. Educating and empowering consumers is an important aspect in this regard. Civil Society and Malaria Control At the country level: · Not-for-profit health care providers (NGOs, faith-based providers, and others) are already providing the majority of malaria control services, particularly in Sub-Saharan Africa. Linkages with national malaria con- trol programs and with district implementation plans, however, are weak. Empowerment of local communities is key, starting with goal setting and monitoring of results in a practical and meaningful way. Nonprofits should have flexibility to channel funds to the providers that deliver results. · Include local civil society in the top-level dialogue as much as possible, with an explicit understanding that the goal is to achieve measurable improvements in morbidity and mortality due to malaria through effec- tive interventions. At the global level: · Maintain stakeholder dialogue at the global level throughout the strategy development and implementation process. High-Impact Partnerships: Private Sector and Civil Society 177 · Meet with global civil society leadership around country-specific projects and operational topics to ensure linkages with local counterparts where applicable. · Ensure that civil society is updated on active and pipeline Bank support for malaria and that a mechanism exists through which they might align their support with the Bank's work, and vice versa. APPENDIX 6 Impact of Malaria on Schoolchildren and the Education Sector Incidence: Estimates from Africa suggest that 20­50 percent of school-age children experience clinical malaria attacks in a given year (Clarke et al.). Higher rates have been reported from endemic areas of Asia (Luxem- burger et al. 1994). Mortality: Of all mortality in schoolchildren, 15­20 percent is attributable to malaria. In an area of intense transmission in Asia, 27 percent of all malaria mortality was in the school-age group (Bundy et al. 2000). Enrollment: In Sub-Saharan Africa, 600,000 children under five years of age experience cerebral malaria, and each year 9,000­19,000 children (more than 2 percent of the survivors) experience neurological complications, including developmental and behavioral impairments, lasting for more than six months (Mung'ala-Odera, Snow, and Newton 2004; Murphy and Breman 2001). A study in Kenya found that these children were less likely to have been enrolled in school (Holding and Snow 2001). Absenteeism: Studies in the Democratic Republic of Congo, Kenya, Senegal, and on the Thailand-Myanmar border indicate that malaria is a cause in 5­8 percent of all absenteeism, equivalent to 50 percent of all preventable absenteeism (Brooker et al. 2000; Bundy et al. 2000; Hold- ing and Snow 2001; Luxemburger et al. 1994; Trape et al. 1987, 1993). Cognition, learning, and educational achievement: School performance of 6­14-year-olds has been related to the number of previous clinical 179 180 Rolling Back Malaria malaria attacks (Fernando et al. 2003a; Fernando et al. 2003b). These effects appear to be mediated through the anemia that is associated with both asymptomatic and clinical malaria, and the neurological conse- quences of cerebral malaria. Anemia occurs in 50 percent of school- children in Africa and 12 percent to 38 percent of schoolchildren in Asia (Partnership for Child Development 2001). Schoolchildren with anemia score more poorly (~ 1­3 standard deviation worse) on tests of education and of general reasoning ability (Pollitt et al. 1989). In Kenya, school- children who had been hospitalized with cerebral malaria were 4.5 times more likely to suffer from mild to severe learning difficulties three to four years later, even though half of the children had no neurological problems at the time of hospitalization (Holding et al. 1999). Impact on the education system: Malaria is reported to have a significant impact on education supply, through absenteeism of teachers. Anecdotal evidence suggests that in areas of unstable transmission, absenteeism of teachers can close schools during the transmission season. Conclusions · There is strong evidence that malaria has an impact on the health and cognition of schoolchildren that adversely affects their education. · Malaria interventions both early in life and at school age offer benefits for educational outcomes. · There is a relative absence of efforts to address malaria in the school-age population. · Ministries of education have a strong commitment to improving the health of schoolchildren and recognize the importance of malaria. Notes 1. Malaria is a potentially deadly disease that is caused by infection with the parasite of the genus Plasmodium, which is transmitted to humans through the bite of a female Anopheles mosquito infected with the parasite. The most severe form of human malaria infection is caused by Plasmodium falciparum. The other forms in humans are caused by Plasmodium vivax, Plasmodium malariae, and Plasmodium ovale. For further details, see: http://www.who.int/topics/malaria/en/. 2. The Bank cofounded the Roll Back Malaria Partnership (RBM) in 1998, with the overall objective of halving the burden of malaria by 2010. RBM facilitates a coordi- nated global response to malaria. For further details, see: http://www.rollback- malaria.org. 3. In 2000, African heads of state, other country officials, and representatives of devel- opment organizations, including the World Bank, met in Abuja, Nigeria, to express commitments to tackling malaria and establishing targets for implementing the tech- nical strategies. The targets set for 2005 are known as the "Abuja Targets." 4. A frequently used measure of the burden of disease is the disability-adjusted life year (DALY) concept, which is a composite measure of both death and disability. The DALY is an indicator of the time lived with the disability and the time lost from pre- mature mortality. Years of life lost from premature mortality are estimated with respect to a standard expectation of life at each age. Years lived with a disability are translated into an equivalent time loss through multiplication by a set of weights that reflect reduction in functional capacity. As such, the DALY represents an attempt to combine in a single indicator the impact of disease on mortality and morbidity. 5. Lending is used here in a generic sense to include loans, credit, and grants. 6. In general, adaptable programs support phased long-term development strategies and programs. They are designed to provide greater flexibility and adaptation. Hor- izontal adaptable programs provide for the replication and scaling up of a program across countries, within a common framework. 7. See http://www.rollbackmalaria.org. 8. The number of Bank staff working on malaria decreased from seven full-time equiv- alent (FTE) in fiscal 1998 to zero FTE in fiscal 2002. There was one FTE secondee in fiscal 2002. In fiscal 2003­4 there were two FTE secondees, one each from the U.S. Centers for Disease Control and Prevention and the RBM Partnership Secre- tariat. The Bank incurred no salary costs for the secondees. Both were supported by two senior staff members, each of whom worked on malaria on a limited basis. As of December 2004, only the RBM secondee was working full time on malaria. In mid- 2004 the Bank appointed a Coordinator of Global Partnerships for Communicable Diseases to work part time on malaria. The total internal Bank budget for malaria control, including trust funds, declined from over US$0.7 million in fiscal 1998 to 181 182 Rolling Back Malaria US$0.1 million in fiscal 2002, and a little more than US$0.2 million in fiscal 2004. For fiscal 2005, the nonsalary budget for work on malaria was US$50,000, plus a contingency budget of US$250,000 to start preparing the Booster Program for Malaria Control. 9. In 2000, African heads of state, other country officials, and representatives of devel- opment organizations including the World Bank, met in Abuja, Nigeria, to express commitments to tackling malaria and establishing targets for implementing the tech- nical strategies. The targets set for 2005 are known as the "Abuja Targets." 10. Eradication is the reduction of new cases of the disease to zero. 11. Control is the reduction of the cases of the disease to an acceptable level, as deter- mined by the area in question (Hotez et al. 2004). 12. Source: Status of Enhanced Malaria Control Project (2003-04). Obtained by the World Bank from the Directorate of National Anti Malaria Program in December 2003. 13. Appendix 2 shows the percentage of households that have at least one mosquito net, the percentage of children under five years old that slept under a mosquito net dur- ing the night preceding the survey, and the percentage of pregnant women that slept under a mosquito net during the night preceding the survey. 14. Through its Development Grant Facility the Bank provides US$1 million annually to the RBM Partnership Secretariat. The RBM Secretariat is hosted by the World Health Organization in Geneva. 15. The declaration, known as the "Abuja Declaration," calls for halving the burden of malaria in Africa by 2010 and includes a number of indicators to be met by 2005. The full text of the Declaration can be accessed at the Roll Back Malaria Web site: http://www.rollbackmalaria.org. 16. Lending is used here in a generic sense to include loans, credit, and grants. 17. In general, adaptable programs support phased long-term development strategies and programs. They are designed to provide greater flexibility and adaptation. Hor- izontal adaptable programs provide for the replication and scaling up of a program across countries within a common framework. 18. Source: http://www.theglobalfund.org/en/about/how/#2. Accessed on November 17, 2004. 19. RBM Monitoring & Evaluation Reference Group. For further details, see http:// www.rbm.who.int/merg 20. Source: Status of Enhanced Malaria Control Project (2003-04). Obtained by the World Bank from the Directorate of National Anti Malaria Program in December 2003. 21. ExxonMobil. Chad/Cameroon Development Project. "Fighting Malaria in the Workforce." Downloaded on November 15, 2004 at: http://www.exxonmobil.com/ corporate/citizenship. References Akhavan, D., P. Musgrove, A. Abrantes, and R. Gusmao. 1999. "Cost-effective Malaria Control in Brazil: Cost Effectiveness of a Malaria Control Program in the Amazon Basin of Brazil, 1988­1996." Social Science and Medicine 49: 1385­99. Arrow, K., C. 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See Artemisinin-based combination therapy percentage of febrile children receiving any Adaptable programs. See Horizontal Adaptable antimalarial treatment, 142­143 Programs percentage of febrile children under age five Advance purchase contracts, 49 receiving chloroquine treatment, 134­135 Africa percentage of febrile children under age five amodiaquine treatment efficacy, 148 receiving sulfadoxine pyrimethamine treatment, chloroquine treatment efficacy, 144­145 138­139 combination therapy efficacy, 150­156 percentage of households having at least one drug-resistant forms of malaria, 18 mosquito net, 98­99, 102­103 financing for ACTs, 25 percentage of pregnant women sleeping under a malaria mortality statistics, 16, 17 mosquito net, 118 malarial case notification, 70­73, 80­85 sulfadoxine pyrimethamine treatment efficacy, 147 mefloquine treatment efficacy, 149 Amodiaquine treatment, 148, 151, 153 percentage of children under age five sleeping Antimalarial treatment under a mosquito net, 104­107, 110­113 chloroquine treatment, 19­20, 23, 132­135, percentage of children under age five with 144­145, 150, 154 reported fever, 124­127 combination therapy, 150­156 percentage of febrile children receiving any monotherapy, 144­149 antimalarial treatment, 140­143 percentage of febrile children receiving, 142­143 percentage of febrile children under age five sulfadoxine pyrimethamine treatment, 19, 23, receiving chloroquine treatment, 132­135 120­123, 136­139, 146­147, 150­151, 155 percentage of febrile children under age five Artemether treatment, 152 receiving sulfadoxine pyrimethamine treatment, Artemisinin-based combination therapy, 20­21, 23, 136­139 25 percentage of households having at least one Artesunate treatment, 153­156 mosquito net, 96­101 Asia percentage of pregnant women sleeping under a amodiaquine treatment efficacy, 148 mosquito net, 116­119 chloroquine treatment efficacy, 145 pregnant women receiving sulfadoxine combination therapy efficacy, 150­156 pyrimethamine, 120­123 malarial case notification, 74­77, 86­91 sulfadoxine pyrimethamine treatment efficacy, 146 mefloquine treatment efficacy, 149 Amazon Basin Malaria Control Project, 159 percentage of children under age five sleeping The Americas under a mosquito net, 108, 112­113 amodiaquine treatment efficacy, 148 percentage of children under age five with chloroquine treatment efficacy, 145 reported fever, 128­129 combination therapy efficacy, 150­152, 155­156 percentage of febrile children receiving any anti- malarial case notification, 78­79, 92­95 malarial treatment, 142­143 mefloquine treatment efficacy, 149 percentage of febrile children under age five receiving chloroquine treatment, 134­135 189 190 Rolling Back Malaria percentage of households having at least one Copenhagen Consensus, 21 mosquito net, 98­99, 102 CSOs. See Civil society organizations percentage of pregnant women sleeping under a mosquito net, 116 sulfadoxine pyrimethamine treatment efficacy, 147 DALY. See Disability-adjusted life years Assistant in the Task Force Secretariat, 54 Debt Service Reserve Account, 49 DEC. See Development Economics Democratic Republic of Congo Booster Program for Malaria Control Health Rehabilitation Project, 25 establishment of, vii, viii Demographic and Health Surveys, 60 features of, 37, 39, 41 Development Economics, 44 Horizontal Adaptable Programs, 6 DHS. See Demographic and Health Surveys implementation options, 41 Disability-adjusted life years, 5, 17, 181n options for accessing funds and technical support, Drug-resistant malaria, 16, 18, 19­21 7­9 phases of, 44­48 schedule of deliverables, 43­48 Education sector Brazil impact of malaria, 179­180 malaria control program, 16­17, 157­160, EHP. See Environmental Health Project 163­169 EMCP. See Enhanced Malaria Control Project Buydowns, 49 Enhanced Malaria Control Project, 159, 161­162 Environmental Health Project, 160­161 Eritrea Case notification rate, 68­69 HIV/AIDS, Malaria, STD and TB Control CDD approaches. See Community-driven Project, 159, 160­161 development approaches malaria control program, 16­18, 157­158, Chad-Cameroon Development Project, 176 160­161, 163­169 Children under age five. See also Schoolchildren ExxonMobil, 176 impact of malaria, 179 percentage of febrile children receiving any antimalarial treatment, 140­143 Fansidar. See Sulfadoxine pyrimethamine treatment percentage of febrile children receiving chloroquine treatment, 132­135 percentage of febrile children receiving sulfadox- GFATM. See Global Fund to Fight AIDS, ine pyrimethamine treatment, 136­139 Tuberculosis and Malaria percentage sleeping under a mosquito net, Ghana 104­115 incidence of malaria, 32­33 percentage with reported fever, 124­127 Global Fund to Fight AIDS, Tuberculosis and Chloroquine treatment, 19­20, 23, 132­135, Malaria, 21, 23, 43­44, 50­51 144­145, 150, 154 Global Malaria Database, 67 Civil society organizations Global Strategic Plan responsibilities in malaria control program, 8, 9, development of, vii, ix 43, 176­177 Global Strategy and Booster Program Clinically diagnosed deaths, 68 audience for, 12, 171­172 Clinically diagnosed severe cases, 68 purpose of, 3­5, 11 Combination therapy, 150­156 results-based monitoring and evaluation system, CommNet staff, 174 58­59, 61­65 Communications plan, 171­174 results framework, 57­58 Community-driven development approaches, 8, 39 strategic communications plan, 171­174 Index 191 HAMSET. See HIV/AIDS, Malaria, STD, and TB Joint Program of Work, 32 Control Project HDNHE. See Human Development Network Hub Health, Nutrition and Population Unit, 54, 172­173 LICUS. See Low Income Countries Under Stress Health Rehabilitation Project, 25 LLINs. See Long-lasting insecticidal nets Health Sector Support Project, 162 Long-lasting insecticidal nets, 23 Highly Indebted Poor Country Initiative, 25 Low Income Countries Under Stress HIPC Initiative. See Highly Indebted Poor Country malaria control programs, 8, 39 Initiative Lumefantrine treatment, 152 HIV/AIDS, Malaria, STD, and TB Control Project, 17­18, 159, 160­161 HIV/AIDS in Africa, 55 Malaria HIV programs, 8, 40 case notification, 67­95 Horizontal Adaptable Programs, 6, 37, 181n, 182n control of, 16, 182n Human Development Network Hub, 54 costs of disease prevention and treatment, 23­24 drug-resistant forms, 16, 18, 19­21 economic impact of disease, 5, 14, 16 I-PRSPs. See Interim Poverty Reduction and epidemiological burden, 67­69 Strategy Papers eradication of, 16, 182n IDA. See International Development Association estimates of financial need for control programs, IFC. See International Finance Corporation 21 Implementation Completion Report, 30 impact on schoolchildren and the education Imported cases, 68 sector, 179­180 Improving Health, Nutrition, and Population Outcomes mortality statistics, 3, 15, 17, 30, 67­79, 179 in Sub-Saharan Africa, 28 need for stronger World Bank effort, 13­14 India prevention methods, 15 Enhanced Malaria Control Project, 159 transmission of disease to humans, 181n malaria control program, 16­18, 157­158, Malaria Advisory Service, 45 161­162, 163­169 Malaria cases clinically diagnosed, 67­68 Indoor residual spraying, 159­160 Malaria Communications Campaign Team, 173­174 Insecticide-treated bed nets Malaria Control/Integrated Management of importance of, 7, 15 Childhood Illnesses Program Managers, 34­36 long-lasting insecticidal nets, 23 Malaria Control Projects, 8, 18, 39, 44­45 percentage of children under age five sleeping Malaria Medicines and Supply Service, 175 under a net, 104­115 Malaria Task Force percentage of households having at least one net, financing for, 54­55 96­103 members of, ix­x percentage of pregnant women sleeping under a objectives of, 9, 44, 53 net, 116­119 oversight, 54 retreatment of, 23 staffing, 54 use of, 18, 19, 20, 59­60, 161, 163 Malaria Team, 4, 13, 24 Institute of Medicine, 20­21 Malawi Health SWAp, 32 Interim Poverty Reduction and Strategy Papers, Management Information System, 60 28­29 MAP. See Multi-country HIV/AIDS Program International Development Association, 11, 17, 21, MDGs. See Millennium Development Goals 31 M&E. See Monitoring and evaluation system International Finance Corporation, vii, 7, 38, 49­50 Medium-Term Expenditure Framework, 8, 39 IRS. See Indoor residual spraying Mefloquine treatment, 149, 156 ITNs. See Insecticide-treated bed nets Millennium Development Goals, viii, 3, 4, 11, 31, 57 192 Rolling Back Malaria MIS. See Management Information System Private sector Monitoring and Evaluation Reference Working responsibilities in malaria control program, 45, 49, Group, 59­60 175­176 Monitoring and evaluation system, 58­59, 61­65 Probable diagnosed deaths, 68 Monotherapy, 144­149 Probable diagnosed severe cases, 68 Mosquito nets. See Insecticide-treated bed nets Program of Action MTEF. See Medium-Term Expenditure Framework development of, vii, ix Multi-country HIV/AIDS Program, 6 strategic communications plan, 171­174 Multiple Indicator Cluster Surveys, 60 PRSCs. See Poverty Reduction Support Credits PRSPs. See Poverty Reduction and Strategy Papers Public Health Specialist, 54 National Anti-Malaria Program, 162 National Institute of Malariology, Parasitology, and Entomology, 162 RBM. See Roll Back Malaria Partnership National Malaria Control Programs, 32, 34, 35 Republic of Rwanda NIMPE. See National Institute of Malariology, Poverty Reduction Support Credit and Grant to Parasitology, and Entomology the Republic of Rwanda, 31 NMCPs. See National Malaria Control Programs Roll Back Malaria Initiative, 49 Not-for-profit health care providers, 176 Roll Back Malaria Partnership establishment of, vii, 181n External Evaluation, 19, 26­27 Onchocerciasis Control Program, 40, 55 Global Malaria Database, 67 Operations Evaluation Department, 30 Global Strategic Plan, vii key interventions, 69 measurement tools, 60 PAHO. See Pan American Health Organization Monitoring and Evaluation Reference Pan American Health Organization, 159 Working Group, 59­60 Pan American Sanitary Conference, 15­16 peer reviewers, x­xi Parasitologically confirmed cases, 68 Secretariat, vii, x Parasitologically confirmed deaths, 68 strategic communications plan, 171­174 Parasitologically confirmed severe cases, 68 Web site, 182n Partners for Health Reform Plus Project, 25 Plasmodium falciparum, 20, 68 Plasmodium vivax, 68 Schoolchildren Post-conflict countries impact of malaria, 179­180 malaria control programs, 8, 39 Secretariat, Malaria Task Force, 54 Poverty Reduction and Economic Management Sectorwide approaches, 8, 9, 22, 28, 30­32 Network, 9, 54 Senegal Poverty Reduction and Strategy Papers, 9, 28­29 National Malaria Control Program, 34 Poverty Reduction Strategies, 7, 38 Sixth Expert Committee, 16 Poverty Reduction Strategy Initiative, 28 Southeast Asia Poverty Reduction Support Credit and Grant to the drug-resistant forms of malaria, 16 Republic of Rwanda, 31 Steering Committee, 9, 44, 54 Poverty Reduction Support Credits, 8, 9, 22, 28, Strategic Framework for Assistance to Africa, 39 30­31 Strategy and Program of Action, 35, 57 Pregnant women Sub-Saharan Africa percentage sleeping under a mosquito net, Improving Health, Nutrition, and Population 116­119 Outcomes in Sub-Saharan Africa, 28 receiving sulfadoxine pyrimethamine, 120­123 Index 193 Sulfadoxine pyrimethamine treatment, 19, 23, budget for malaria control programs, 181­182n 120­123, 136­139, 146­147, 150­151, 155 business model for malaria control program, 6, SWAps. See Sectorwide approaches 37, 41 cooperation with major partners, 50­51 establishment of the Roll Back Malaria Tanzania Partnership, vii, 181n financing for ACTs, 25 financial commitment to malaria control Tuberculosis programs, 8, 40 programs, 7, 27 Global Strategy and Booster Program, 3­5, 11 Malaria Task Force, 9 UNICEF. See United Nations Children's Fund Malaria Team, 4, 13, 24 United Nations Children's Fund need for stronger malaria control effort, 13­14 establishment of the Roll Back Malaria Partners for Health Reform Plus Project, 25 Partnership, vii performance rating of malaria control program United Nations Development Program involvement, 34­36 establishment of the Roll Back Malaria priorities for malaria control program, 37­41 Partnership, vii World Bank Group, vii U.S. Agency for International Development, 18, 25 World Health Assembly, 16 USAID. See U.S. Agency for International Develop- World Health Organization ment establishment of the Roll Back Malaria Partnership, vii malaria control interventions, 15 Vice presidential units, 44, 45, 54 Regional Office for Africa, 35 Vietnam Roll Back Malaria Department, vii­viii malaria control program, 16­17, 157­158, 162­169 VPUs. See Vice presidential units Young Professional, 54 WHO. See World Health Organization Zambia Health Sector Support Project, 30 World Bank Booster Program for Malaria Control, 6­9, 37, 41 T he purpose of Rolling Back Malaria: The World Bank Global Strategy & Booster Program is to translate the World Bank's corporate commitment into a serious effort to close the gap between knowing and doing in malaria control. It builds on lessons learned and takes into account World Bank­supported successes in countries such as Brazil, Eritrea, India, and Vietnam, among others. The World Bank will now deepen and expand its efforts to enable more countries to achieve and sustain large-scale impact in malaria control. The new business model combines an emphasis on outcomes with flexibility in approaches. Products and services related to malaria control will be tailored to client segments in order to meet the needs of countries and deploy the World Bank's comparative advantages while strengthening collaboration with partner agencies, cofinanciers, and civil society. In the short to medium term, the new Booster Program for Malaria Control will provide increased financing and technical support to accelerate program design and implementation, increase coverage, and improve outcomes more rapidly than in the recent past. Henceforth, malaria control will be mainstreamed into the Poverty Reduction Strategies and large sector-development programs that emphasize outcomes. Clients will have choices in the instruments for accessing funds and technical support from the World Bank, including malaria- specific programs where appropriate. The Global Strategy & Booster Program represents a significant upgrade of World Bank support for malaria control. It is a living document that will be updated to take account of lessons from future operations and new knowledge from research. www.worldbank.org/malaria ISBN 0-8213-6199-6