MONITORING IMPACTS OF COVID-19 ROUND 17 AND OTHER SHOCKS JAN-FEB 2024 Publication Date Aziz Atamanov, Frédéric Cochinard, John Ilukor, Audrey Kemigisha, Andrew Mupere, and Giulia Ponzini BACKGROUND In June 2020, the Uganda Bureau of Statistics (UBOS), in collaboration with the World Bank, officially launched the Uganda High-Frequency Phone Survey (UHFPS) to track the impacts of the COVID -19 pandemic regularly. In June 2022, the scope UGANDA of the survey was expanded to monitor economic sentiments and the socioeconomic implications of other shocks, such as the Russia-Ukraine war, the Ebola outbreak, and extreme weather events. In addition, the survey is also being used to col- lect perceptions on different development policies and programs. The survey aimed to recontact the entire sample of households that had been interviewed during the Uganda National Panel Survey (UNPS) 2019/20 round and that had phone numbers for at least one household member or a reference individual. The sample was refreshed in the 13th round conducted in July/August 2023 by adding households from the Uganda National Household Survey 2019/20. The timeline of each round is shown in Table 1. This brief focuses on the socio-economic well-being of Ugandans as reported in round 17 conducted in January/February 2024. Table 1. Number of completed interviews by round R1 R2 R3 R4 R5 R6 R7 R8 R9 R10 R11 R12 R13 R14 R15 R16 R17 (Oct/ (Dec (Feb/ (June (July/ (Sep/Oct (Oct/Nov (Feb (Mar/Apr (Oct/ (June/ (Aug (July/ (Aug/ (Oct/ (Dec (Jan/ Nov 22/Jan Mar 20) Aug 20) 20) 20) 21) 21) Nov 21) July 22) 22) Aug 24) Sep 24) Nov 24) 24) Feb 24) 22) 23) 23) Interviews 2227 2199 2147 2136 2122 2100 1950 1881 1871 1668 1666 1783 1765 1838 1729 1795 1761 KEY FINDINGS • Respondents shared more optimistic views on current and future household financial well -being and country economic situation in January/February 2024 compared to December 2023. Other indicators, such as self -reported food consumption adequacy, health care standards and total income, have improved too. • Despite more optimistic economic sentiments, 40 percent of respondents continue to expect to be negatively hit by weather shocks with higher expectations among the rural and the poorest households. • Employment rate fell from 80 percent in December 2023 to 75 percent in January/February 2023, but most work stoppages were seasonal. • Access to essential products has improved, but a substantial gap between the poorest and the richest households has remained. • About 70 percent of households experienced at least one shock with food inflation being a prevalent shock during the last 12 months. Weather shocks were more likely to affect the poor households, while lower prices on outputs, job losses and non -farm business closure were more likely to affect more affluent households. ECONOMIC INDICATORS Economic sentiments and subjective economic wellbeing Respondents shared more optimistic sentiments about current and future household financial well-being in early 2024. Figure 1 shows that about 45 percent of the respondents in December 2023 felt that their household financial well-being was lower than 12 months before. In January/February 2024 this share dropped by 10 percentage points to 35 percent. Negative expectations about future household financial well-being in the 12 months ahead declined from 23 percent in December 2023 to 17 percent in January/February 2024. Respondents became more optimistic about the current and future country’s economic situation. Figure 3 and Figure 4 show respondents’ views on the current and future economic situation of the country. There was a significant decline in negative views on the current economic situation from 54 percent in December 2023 to 39 percent in January/February 2024. Fewer respondents in January/February 2024 expected the country’s future economic situation to be worse com- pared to December 2023: 23 versus 32 percent accordingly. © 2024 International Bank for Reconstruction and Development/The World Bank MONITORING IMPACTS OF COVID-19 AND Figure 1. Views about current household financial wellbeing Figure 2. Expectations about future household financial wellbeing compared to 12 months ago across rounds, % during next 12 months across rounds, % Figure 3. Views about current country economic situation com- Figure 4. Expectations about future country economic situation pared to 12 months ago across rounds, % across rounds, % More optimistic views on household income, ability to meet minimum needs, and overall happiness were observed in January/February 2024 compared to December 2023. Figure 5 shows that about half of all respondents felt that total income increased or at least stayed the same in January/February 2024 compared to 43 percent reported in December 2023. Moreover, more respondents felt that their food consumption and standards of health care were at least adequate. No significant changes were observed with regards to overall happiness and overall subjective perceptions of standards of living (Figure 5). About half of respondents remained happy in January/February 2024 and about 36 percent felt that they were living well given their income. Figure 5. Different subjective indicators across rounds, % Figure 6. Share of respondents who feel negative weather events are likely to affect household wellbeing, % 2 MONITORING IMPACTS OF COVID-19 AND OTHER Despite more optimistic views on subjective wellbeing, about 40 percent of respondents expect weather events to neg- atively affect the household wellbeing and this number has not changed much across rounds. As shown in Figure 6, negative weather expectations are particularly pronounced among rural residents (49 percent), those living in the Eastern (47 percent) and Western (47 percent) regions and among the poorest households from the bottom consumption quintile (45 percent). Employment, prices and access to essential products The employment rate dropped to 75 percent in January/February 2024, but most work stoppages were seasonal. Figure 7 shows that the share of respondents working during the seven days before the interview declined from 80 percent in December 2023 to 75 percent in January/February 2024. The decline in employment was observed in rural and urban are- as. Respondents reported the reasons for stopping the work. Figure 8 shows that most respondents stopped working in January/February 2024 because of seasonal stoppages/vocations, while economic reasons such as closure of business, lay- offs and so forth accounted for only nine percent of all stoppages. Figure 7. Working respondents across rounds, % Figure 8. Main reason for work stoppage, % Note: Data is treated as a cross-section. Note: Economic reasons include closure of business, lay-offs, lack of inputs. Access to many essential goods has improved. Figure 9 shows a decline or no change in the shares of households who were not able to access fully or partially needed essential products in January/February 2024 compared to October/ November 20231. In particular, access to fuel/gasoline, sugar, eggs, fresh milk, eggplants have improved. At least partially, this may be related to relatively stable prices as shown in Figure 11. Nevertheless, access to essential products remains extremely limited for the poorest households. Figure 10 shows the percentage of households who were not able to access fully any essential products for the poorest and richest consumption quintiles. For most products inability to access them is at least five times lower among households from the bottom 20 percent of population compared to those from the rich- est top 20 percent. Figure 9. Inability to buy essential products (fully or desired Figure 10. Inability to buy any essential product when needed during amount) when needed during last 7 days across different last 7 days across different rounds, % Access information was not collected in the 16th round of the phone survey. 1 3 MONITORING IMPACTS OF COVID-19 AND Note: This figure shows shares of households who were not able to get Note: This figure shows shares of households who were not able to access fully to essential good or were not able to get desired amounts. access any essential good. Figure 11. Price index for selected products across rounds (May/June 2022 is a base) Note: For brevity price indexes for several rounds are omitted from the figure. Prices on fertilizers, gasoline and diesel have been collected since August 2022 only so we use February/March 2023 as a base for them. Shocks and copping strategies Seven out of ten respondents experienced at least one shock during the last 12 months. Food inflation was the key shocks affecting 46 percent of households, followed by injury, illness or death of an income earning member (25 percent), increase in prices of business of farm inputs (20 percent), fall in prices of farming/business outputs (19 percent), irregular rains (15 percent), increase in fuel prices (13 percent), droughts (11 percent). The incidence of any remaining shocks did not exceed 10 percent. The poorest households from the bottom consumption quintile were more likely to be affected by weather shocks such as droughts and irregular rains due to higher involvement in agricultural activities and higher likeli- hood of living in rural areas. In contrast, households from the richest top quintile were more likely to be affected by in- creased fuel prices, lower prices on business/farming outputs, job losses and nonfarm business closures. Figure 12. Incidence of selected shocks during last 12 months, % of households Note: For brevity price indexes for several rounds are omitted from the figure. Prices on fertilizers, gasoline and diesel have been collected since August 2022 only. 4 MONITORING IMPACTS OF COVID-19 AND Figure 13. Incidence of coping strategies used at least once to cope with any shock, % of households Note: Coping strategies are defined regardless the number of times used. Poorest households were less likely to rely on savings than the richest households and were more likely to rely on more detrimental coping strategies. Figure 13 shows incidence of strategies households used at least once to cope with any shock. About 53 percent of households have not done anything to cope with shocks. It was followed by a strategy of re- ducing food consumption pursued by 25 percent of households. About 23 percent of households got assistance from friends and family and 22 percent relied on savings. Other important strategies included engaging in additional income generating activities (17 percent), crediting purchases (15 percent), selling crops or food stock (11 percent). Other strate- gies were used by less than 10 percent of households. The richest households from the top consumption quintile were more likely to use savings compared to those from the poorest quintile (26 versus 14 percent accordingly). Lack of savings, access to safety nets and usage of inferior coping strategies may jeopardize long-term wellbeing and prospects of the poorest households. Food consumption score and nutritional quality About 40 percent of respondents had inadequate food consumption from a nutritional point of view based on the food consumption score (FCS) in the latest round. The Food Consumption Score (FCS) here is an index that aggregates re- spondents’ data on the diversity and frequency of food groups consumed over the seven -day period prior to the inter- view. The index is then weighed according to the relative nutritional value of the consumed food groups. As shown in Fig- ure 14, 13 percent of households had poor FCS. About 27 percent of respondents had borderline values of FCS, while 60 percent had an acceptable food consumption score. This is slightly worse than FCS in December 2023 when five percent of respondents had poor FCS and closer to what was reported in October/November 2023 when 12 percent of respondents had poor FCS. As one would expect, respondents from the poorest bottom consumption quintile have lower FCS. Indeed, 58 percent of households from the poorest consumption quintile had an acceptable food consumption score compared to 70 percent among the households from the richest quintile. Figure 14. Respondents by food consumption score in January/ Figure 15. Share of respondents who never consumed protein, iron, Notes: Household's food consumption status is defined by the following thresholds: 0-21: Poor; 21.5-35: Borderline; >35: Acceptable. 5 MONITORING IMPACTS OF COVID-19 AND Consumption of iron and vitamin A rich products is much lower than consumption of protein rich products. The phone survey collects information about the nutritional quality of food consumed by respondents, focusing on three main nutri- ents, such as vitamin A, protein, and iron. Figure 15 shows the share of respondents who never consumed products rich in vitamin A, protein, and iron during the last seven days. Respondents consume less iron and vitamin A rich products than protein rich products. Thus, 64 percent of households did not consume any iron-rich food (e.g., meat, fish) during the last seven days in January/February 2024 compared to 31 percent of households not consuming vitamin A rich food and only five percent of households not consuming protein rich food. Lower consumption of iron rich products can be partially relat- ed to the fact that most respondents acquire iron rich products in the market and not from home production. Data Notes: The Uganda High-Frequency Phone Survey has been implemented by the Uganda Bureau of Statistics (UBOS) since June 2020. This survey is part of a World Bank global effort to support countries in their data collection efforts to monitor the impact of COVID -19 and other shocks. A World Bank team from the Development Data Group and the Poverty and Equity Global Practice provided technical support. This survey is the seventeenth of planned 18 waves of the High -Frequency Phone Survey. In the 10th Round 1,668 households were successfully interviewed. In the 11th, 12th, 13th, 14th, 15th, and 16th rounds, 1,666, 1,783, 1,765, 1,838, 1,729, and 1,795 households were successfully inter- viewed. In this Round 1,761 households were successfully interviewed. The data are representative at the regional and national level and survey weights were calculated to adjust for non -response and undercoverage. For further details on the data, visit https://www.worldbank.org/lsms-covid19 6