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Covid-19 Vulnerability Hotspots in Central Africa

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A presentation by Julie Collins, Senior Associate Scientist, AKADEMIYA2063

Publicado en: Datos y análisis
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Covid-19 Vulnerability Hotspots in Central Africa

  1. 1. COVID-19 Vulnerability Hot Spots: Central Africa Better preparedness through early identification and targeting of the most exposed communities Julie Collins Senior Associate Scientist, AKADEMIYA2063 AKADEMIYA2063 Webinar Series on COVID-19 November 19, 2020
  2. 2. Outline Motivation Methodology Central Africa vulnerability analysis Enterprise-level analysis, DRC Future directions Conclusions 2
  3. 3. Motivation • Effects of crises are not geographically uniform • Both the spread of COVID-19 and the ability to respond to its effects vary between and within countries • The severity of impacts on people’s livelihoods and food security depends in part on existing patterns of vulnerability • Objective: Identify areas within countries and regions that show the highest levels of vulnerability to negative impacts of COVID • These areas can be monitored closely and interventions prepared 3
  4. 4. Methodology Vulnerability: • Propensity of a district to be exposed to spread of COVID-19; • Limited capacity to control the pandemic and care for infected people; • Households’ exposure to negative food security impacts 1) Consider various factors shaping vulnerability  Food security status  Nutrition status  Disease prevalence  Access to health services  Density 4
  5. 5. Methodology 2) Build composite indicator to create typology of vulnerability • Assign each area a value for each indicator: 𝐼 > 𝐼 𝑘 + 0.67 ∗ 𝑠𝑡𝑑(𝐼 𝑘) ∶ 3 = 𝑀𝑢𝑐ℎ 𝑚𝑜𝑟𝑒 𝑣𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑙𝑒 𝐼 𝑘 + 0.67 ∗ 𝑠𝑡𝑑(𝐼 𝑘) ≤ 𝐼 < 𝐼 𝑘 ∶ 2 = 𝑀𝑜𝑟𝑒 𝑣𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑙𝑒 𝐼 𝑘 ≤ 𝐼 < 𝐼 𝑘 − 0.67 ∗ 𝑠𝑡𝑑(𝐼 𝑘) ∶ 1 = 𝐿𝑒𝑠𝑠 𝑣𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑙𝑒 𝐼 < 𝐼 𝑘 − 0.67 ∗ 𝑠𝑡𝑑(𝐼 𝑘) ∶ 0 = 𝑀𝑢𝑐ℎ 𝑙𝑒𝑠𝑠 𝑣𝑢𝑙𝑛𝑒𝑟𝑎𝑏𝑙𝑒 • Calculate the composite vulnerability index for each area by summing up all the indicators as follows: Vulindex𝑖𝑗 = K − 𝑘 𝑤𝑙𝑖𝑗𝑘 Where K represents the number of indicators included in the composite index, w𝑙𝑖𝑗𝑘 the weight associated with the rank l (0, 1, 2, 3) of the 𝑘 𝑡ℎ indicator of area j in country i. w𝑙𝑖𝑗𝑘 = k − 𝑙 k 5
  6. 6. Indicators and data sources Factor Indicator Source Nutrition status Stunting Demographic and Health Surveys (DHS)Access to health services Proportion of women (15-49) for whom distance to health facilities is a big problem Proportion of women (15-49) getting assistance during childbirth from doctor, nurse/midwife etc. Disease prevalence Prevalence of diabetes DHS or statistical year book Prevalence of high blood pressure DHS or statistical year book Food security status Share of food in total expenditure National surveys Overcrowding Population density of inhabited areas Center for International Earth Science Information, Columbia University 6
  7. 7. Results for Central Africa 7
  8. 8. Food and nutrition security: Stunting • Significant variation within countries • Especially high rates in central and eastern DRC, northern Chad • Pockets of higher vulnerability in Cameroon 8
  9. 9. Food and nutrition security: Share of food in total expenditure • More within-region than within-country variation • Especially high vulnerability in DRC 9
  10. 10. Access to healthcare 10
  11. 11. Disease burden 11
  12. 12. Population density • Measured as density of inhabited areas • DRC and some areas of Chad have the highest density • Cameroon is relatively less vulnerable in terms of density 12
  13. 13. Composite vulnerability index 13 • All countries have regions of much higher and much lower vulnerability
  14. 14. Effects on firms in DRC 14
  15. 15. Data • 103 firms surveyed in April-May 2020 by the Fédération des Entreprises du Congo (FEC) • Over 60 percent of surveyed firms are in Kinshasa, followed by North Kivu (16%) 62% 16% 6% 5% 5% 4% 2% 1% Firm location Kinshasa Nord Kivu Haut Katanga Lualaba Sud Kivu Maniema Ituri Kasai 15
  16. 16. Enterprise size and sector • Strong representation of enterprises in the service sector • Firms range from micro to very large, with distinct sectoral patterns 0% 20% 40% 60% 80% 100% Banks, financial services Mining Manufacturing Energy Construction Agriculture, agro-processing Health, medical, pharmacy IT, digital, telecommunications Hospitality and tourism General trade / transport Misc. services Overall Number of employees by sector Less than 10 10 to 50 50 to 100 100 to 250 250 to 500 More than 500 18% 15% 13% 10% 9% 8% 8% 7% 6% 5% 3% Firm sector (percent) General trade / transport Misc. services Hospitality and tourism IT, digital, telecommunications Manufacturing Agriculture, agro-processing Health, medical, pharmacy Energy Banks, financial services Mining Construction 16
  17. 17. Effects of COVID-19 on firms • Large shares of firms reduced activities; many firms could not pay debts, salaries or taxes • A handful of firms reported no effect or increased sales How did COVID-19 affect your activities? Response Percent of firms No contracts signed or orders received from clients 42 Inability to pay debts to suppliers and banks 38 Inability to pay salaries 38 Less than 50% decrease in activities 36 More than 50% decrease in activities 34 Inability to pay taxes and fees 34 Cessation of activities 20 Increase in unsold stocks 19 Impossibility of importing raw materials 17 Inability to meet demand due to reduced activities 16 Suspension of work contracts 16 No impact on our activities 6 Increase in sales 2 Note: Percentages sum to over 100 due to multiple responses 17
  18. 18. Firms’ responses to COVID-19 • Over one third of firms instituted telework • Many firms suspended investments, reduced production, and / or laid off staff Note: Percentages sum to over 100 due to multiple responses What measures have you taken during the COVID-19 crisis? Response Percent of firms Adoption of telework by some staff 37 Suspension of investments 36 Layoff / suspension of contracts for a portion of staff 33 Reduction in production 31 Cancellation of orders from suppliers 19 Reduction in imports 19 Cancellation of orders received from clients 17 Termination / renegotiation of leases 16 Sale of assets to meet commitments 9 Shifting to other activities 8 Increase in imports of finished products 4 Increase in imports of raw materials 3 18
  19. 19. Effects on employment • Less than half of all firms retained all employees • Hospitality and tourism firms were the least likely to retain all personnel and the most likely to close 0% 20% 40% 60% 80% 100% Hospitality and tourism Energy General trade / transport Manufacturing IT, digital, telecommunications Misc. services Agriculture, agro-processing Banks, financial services Health, medical, pharmacy Construction Mining Overall Did you retain your personnel during the COVID-19 period? Yes, all Yes, more than 50% Yes, half Yes, less than 50% No, firm closed 19
  20. 20. Effects on financial standing 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Hospitality and tourism General trade / transport Manufacturing Energy IT, digital, telecommunications Health, medical, pharmacy Banks, financial services Misc. services Agriculture, agro-processing Mining Construction Overall What are your estimated losses due to COVID-19? Less than 10% of annual revenues received in 2019 Between 10% and 50% of annual revenues received in 2019 Between 50% and 75% of annual revenues received in 2019 More than 75% of annual revenues received in 2019 20
  21. 21. Effects by firm size • Firms of all sizes suffered losses, but the largest firms were more able to retain employees and avoid large financial losses 0% 20% 40% 60% 80% 100% More than 250 employees 100 to 250 employees 50 to 100 employees 10 to 50 employees Less than 10 employees Did you retain your personnel during the COVID- 19 period? Yes, all Yes, more than 50% Yes, half Yes, less than 50% No, firm closed 0% 20% 40% 60% 80% 100% More than 250 100 to 250 employees 50 to 100 employees 10 to 50 employees Less than 10 employees What are your estimated losses due to COVID-19? Less than 10% of annual revenues received in 2019 Between 10% and 50% of annual revenues received in 2019 Between 50% and 75% of annual revenues received in 2019 More than 75% of annual revenues received in 2019 21
  22. 22. Desired support from governments • Three-fourths of firms would like to see tax reductions in response to COVID-19 What measures would you like the government to take to restart your activities? Response Percent of firms Reduce taxes 75 Create a support fund for businesses affected by COVID-19 61 Subsidize businesses affected by COVID-19 55 Facilitate access to bank credit 43 Note: Percentages sum to over 100 due to multiple responses 22
  23. 23. Future directions for vulnerability analysis 1) Explore other data sources and indicators 2) Construct indicators on micronutrient deficiencies 3) Examine changes in micronutrient consumption resulting from COVID-related food price changes 23
  24. 24. Conclusion • Responses to COVID-19 need to prioritize most severely affected areas • In the absence of data on actual impacts, important to assess likely hotspots early • Areas with high levels of chronic vulnerability may be hardest hit by COVID-19 and its effects on food security • Employees of small firms and firms in exposed sectors are particularly vulnerable 24
  25. 25. THANK YOU AKADEMIYA2063 – Kicukiro / Niboye KK 360 St 8 I P.O. Box 4729 Kigali-Rwanda 25
  26. 26. Calories: Daily intake per adult equivalent (2012) 26
  27. 27. Iron: Daily intake per adult equivalent (2012) 27

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