OJBMOpen Journal of Business and Management2329-3284Scientific Research Publishing10.4236/ojbm.2020.86146OJBM-103889ArticlesBusiness&Economics The Present Value of Human Life Losses Associated with Coronavirus Disease in Africa JosesMuthuri Kirigia1RoseNabi Deborah Karimi Muthuri2LenityHonesty Kainyu Nkanata1NewtonGitonga Muthuri3Chandaria School of Business, United States International University—Africa, Nairobi, KenyaFaculty of Health Sciences, University of Pretoria, Pretoria, South AfricaAfrican Sustainable Development Research Consortium (ASDRC), Nairobi, Kenya131020200806237123952, October 202027, October 2020 30, October 2020© Copyright 2014 by authors and Scientific Research Publishing Inc. 2014This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/

The coronavirus disease (COVID-19) continues to ravage human lives, social systems, and economies around the world. The objective of this study was to estimate the total present value (TPV AFC ) of human life losses associated with COVID-19 in Africa continent as of 1 August 2020. A human capital approach model was used to estimate the TPV AFC of the 19,682 human lives lost due to COVID-19 in Africa continent (excluding 44 deaths in Sahrawi Arab Democratic Republic and territories of Mayotte and Reunion). The average life expectancy for 54 countries with data and a 3% discount rate were used. A sensitivity analysis was conducted at 5% and 10% discount rates. The human lives lost due to COVID-19 had a TPV AFC of Int$1,721,030,766, and average TPV AFC of Int$87,442 per human life lost. About 81.3% of TPV AFC accrued to persons below 60 years. The TPV AFC of human life losses from COVID-19 will continue growing until the pandemic is eradicated.

Coronavirus COVID-19 Gross Domestic Product Value of Human Life1. Introduction

Africa continent has 55 countries (plus territories of Mayotte and Reunion), with an estimated total population of 1,340,598,113 persons (17.2% of the global population) in 2020 (Worldometer, 2020). The continent has an estimated gross domestic product (GDP) of Int$7.6 trillion and a per capita GDP of Int$5720 in 2020 (International Monetary Fund (IMF), 2020).

As of 1 August 2020, the world had a total of 17,757,496 confirmed coronavirus disease (COVID-19) cases, among them 682,998 deaths, 11,160,054 recovered cases, and 5,914,444 active cases (Worldometer, 2020). By the same date, all countries and territories in Africa had reported a total of 931,777 confirmed cases, including 19,726 deaths, 583,665 recovered cases, and 328,386 active cases. In Africa, COVID-19 deaths varied widely from one in the Sahrawi Arab Democratic Republic to 8005 in South Africa (Worldometer, 2020).

Africa’s capability of containing the spread of COVID-19 depends on the resilience of national health systems (NHS), disease surveillance and response systems (DSRS), and other systems that tackle social determinants of health (SDHS). The universal health coverage (UHC) service index (a proxy for NHS) for the WHO African Region (AFR) was 46 (on a scale of 0 to target of 100), and that of the WHO Eastern Mediterranean Region (EMR) was 57 in 2017, which implied the existence of gaps in essential health services coverage of 54 and 43, respectively (WHO and The World Bank, 2017). Among the Africa continent countries, the UHC index gap varied widely from 22 in Algeria to 75 in Somalia in 2019 (Kirigia, Rutere, Muthuri, & Kirigia, 2020).

The average of International Health Regulations [IHR] (a proxy for DSRS) core capacity scores for AFR was 44% and 66% for EMR in 2019, denoting IHR gaps of 56% and 34%, respectively (WHO, 2013, 2020a). The population using a hand-washing facility with soap and water (a proxy for the SDHS) in AFR was 28% and 66% in EMR in 2017, signifying gaps of 72% and 34%, respectively (WHO, 2020a). The population without basic hand-washing facilities in Africa varied from 10% in Egypt to 99% in Liberia in 2017 (Rutere, Muthuri, Kirigia, & Kirigia, 2020).

According to Rice (2000), “cost of illness studies translates the adverse effects of diseases or injuries into dollar terms, the universal language of decision-makers and the policy arena” (p. 178). Studies in Canada (Kirigia & Muthuri, 2020a), China (Kirigia & Muthuri, 2020b), Spain (Kirigia & Muthuri, 2020c), Turkey (Kirigia, Muthuri, & Nkanata, 2020), the United Kingdom [UK] (Kirigia & Muthuri, 2020d), and the United States of America [USA] (Kirigia & Muthuri, 2020e) assessed the monetary value of human life losses associated with COVID-19 for use in advocacy for increased investments in NHS, DSRS, and SDHS to combat current and future pandemics. There is a dearth of evidence on the total present value (TPVAFC) of human lives lost due to COVID-19 in the continent. This study estimated the TPVAFC of human life losses associated with COVID-19 in the Africa continent as of 1 August 2020.

2. Materials and Methods2.1. Ethical Considerations

The study did not require ethical approval since it relied exclusively on secondary data from international databases that are in the public domain (Worldometer, 2020; International Monetary Fund (IMF), 2020; WHO, 2019, 2020b).

2.2. Study Location and Design

This study encompassed 54 countries of the Africa continent. The Sahrawi Arab Democratic Republic (Western Sahara) was excluded because data on GDP per capita and current health expenditure per capita was missing. It was a cross-sectional assessment of the monetary value of all the 19,682 human life losses associated with COVID-19 as of 1 August 2020 (Worldometer, 2020). Since the study involved the cumulative number of deaths up to 1 August 2020, sampling was not relevant.

2.3. Analytical Framework

Three approaches exist for monetary valuation of a statistical life, i.e. the human capital approach (HCA), the revealed preferences approach, and the willingness-to-pay approach (WTP) (Jones-Lee, 1985). The HCA was applied in the current study to value human life losses associated with COVID-19 in Africa due to the availability of relevant data.

The HCA employed in the current study owes its antecedents to the seminal work of Landefeld and Seskin (1982). Weisbrod (1961) and WHO (2009a) clarified that human life is to be valued using discounted future earnings net of the individual’s consumption. Any premature death from COVID-19 (or any other cause) results in potential years of life lost (YLL), which are equal to the average life expectancy at birth for a specific country minus the age of onset of death (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020). In line with Weisbrod (1961) and WHO (2009a), the net per capita GDP (i.e., specific country’s per capita GDP minus current health expenditure per person) is used in monetary valuation of YLL.

The economic model used in the current study was that applied to estimate discounted monetary value human life losses associated with COVID-19 in Canada (Kirigia & Muthuri, 2020a), China (Kirigia & Muthuri, 2020b), Spain (Kirigia & Muthuri, 2020c), Turkey (Kirigia, Muthuri, & Nkanata, 2020), the UK (Kirigia & Muthuri, 2020d), and the USA (Kirigia & Muthuri, 2020e).

The TPVAFC is the sum of present value of human lives lost from COVID-19 as of 1st August 2020 in each of the 54 countries ( CPV j = 1 , ⋯ , 55 ). That is:

TPV AFC = CPV 1 + CPV 2 + CPV 3 + ⋯ + CPV j (1)

The present value of human lives lost through COVID-19 in the jth country ( CPV j = 1 , ⋯ , 55 ) is the sum of the discounted present value of lives lost among the 0 - 9-year-olds (PV0-9), 10 - 19-year-olds (PV10-19), 20 - 29-year-olds (PV20-29), 30 - 39-year-olds (PV30-39), 40 - 49-year-olds (PV40-49), 50 - 59-year-olds (PV50-59), 60 - 69-year-olds (PV60-69), and the 70-year-olds and above (PV≥70) (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020). Formally:

CPV j = ∑ i = 1 I PV i (2)

The ith age group present value (PVi) equals a product of discount factor, YLL, net per capita GDP (NPCGDP), and COVID-19 deaths for age group (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020). That is:

PV i = 1 , ⋯ , 9 = ∑ t = 1 T A 1 × ( A 2 − A 3 ) × ( A 4 − A 5 ) × ( A 6 × A 7 ) (3)

where: A1 is the discount factor obtained using the formula 1 / ( 1 + r ) t , r is the discount rate, which was 3% in the current study (Kirigia & Muthuri, 2020a,

2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020); ∑ t = 1 t = n   is the

summation from year t = 1 to T; t is the first YLL and T is the final year of the total number of YLL per COVID-19 human life lost within an age group; A2 is the per capita GDP for a specific country in International Dollars (Int) or Purchasing Power Parity (PPP); A3 is the current health expenditure per person for a specific country; A4 is the average life expectancy at birth for a specific country; A5 is the average age of onset of death for each age group; A6 is the total number of human lives lost from COVID-19 in a specific country; A7 is the proportion of COVID-19 human lives lost borne by a specific age group. The base year for the analysis was 2020. Equations 1, 2 and 3 were estimated using the Excel Software (Microsoft, New York, USA).

2.4. Sensitivity Analysis

The economic model was reanalyzed three times assuming 1) 5% and 10% discount rates (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020); and 2) the world’s highest life expectancy of 87.17 years in 2020 (i.e., Hong Kong’s average female life expectancy at birth) to gauge the impact on TPVAFC (Worldometer, 2020). After each rerun of the economic model, the change was calculated by subtracting the original TPV estimate (TPVOLD) from the new TPV estimate (TPVNEW). The percentage change equals the change in TPV divided by the original TPVOLD estimate, multiplied by 100. Algebraically:

Percentagechange = ( TPV NEW − TPV OLD ) | TPV OLD | × 100

For example, in this study, TPVOLD = Int$1,721,030,766; and following a reanalysis of the HCA model with the world highest life expectancy the TPVNEW = Int$4,064,146,193. Thus:

Percentagechange = ( 4064146193 − 1721030766 ) | 1721030766 | × 100 = 136.1 %

2.5. Data and Data Sources

The analysis included 54 countries in the African continent (see TableS1 for the names). The Sahrawi Arab Democratic Republic (Western Sahara) and the territories of Mayotte and Reunion (which had a total of 44 COVID-19 deaths) were excluded because of missing data on per capita GDP (International Monetary Fund (IMF), 2020) and current health expenditure per person (WHO, 2020b). The discount rates of 3%, 5%, and 10% were from recent studies that estimate the monetary value of human life losses associated with COVID-19 (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020).

The average life expectancies at birth for each of the 54 countries and the world’s highest life expectancy of 88.17 years in 2020 were from the Worldometer database (see TableS2) (Worldometer, 2020). The ages of onset of death were 4.5 years for group 0 - 9 years, i.e. [0 + 9)/2; 14.5 years for group 10 - 19 years; 24.5 years for group 20 - 29 years; 34.5 years for group 30 - 39 years; 44.5 years for group 40 - 49 years; 54.5 years for group 50 - 59 years; 64.5 years for group 60 - 69 years; and 70 years for group 70 years and above.

The data on per capita GDP expressed in International Dollars (Int$) (or Purchasing Power Parity) in 2020 for each of the 54 countries were from IMF World Economic Outlook Database (see TableS3) (International Monetary Fund (IMF), 2020). The 2017 (latest available) data on current health expenditures per person for each of the 54 countries were collated from the WHO Global Health Expenditure Database (see TableS4) (WHO, 2020b). The estimated NPCGDP data is in TableS5.

Data on the total number of COVID-19 deaths as of 1 August 2020 for each of the 54 countries were from the Worldometer database (see TableS6) (Worldometer, 2020). The proportions used to share the number of COVID-19 deaths in each country across the eight age groups was calculated using 2020 data from Statista database (see TableS7) (WHO, 2019). The estimated YLL by age group per country are in TableS8.

3. Results3.1. Findings Assuming Each Country’s Life Expectancy at Birth and a 3% Discount Rate

Table 1 presents the discounted value of human lives lost from COVID-19 in continental Africa by 1 August 2020.

The 19,682 human lives lost (equal to 198,575 YLL) due to COVID-19 in Africa had TPVAFC of Int$1,721,030,766. Out of which, approximately 0.6% accrued to 0 - 9-year-olds, 0.9% to 10 - 19-year-olds, 4.1% to 20 - 29-year-olds, 15.8% to 30 - 39-year-olds, 26.5% to 40 - 49-year-olds, 33.4% to 50 - 59-year-olds, 12.9% to 60 - 69-year-olds, and 5.8% to the 70-year-olds and above. The average was Int$87,442 per human life lost due to COVID-19; and Int$1.29 per person in the population.

As shown in Figure 1, the CPV of human lives lost varied widely from Int$0 in Eritrea and Seychelles (where there were no reported COVID-19 deaths) to Int$697,921,220 in Egypt.

Twenty-eight (52%) countries had CPV of less than Int$1 million, 20 (37%) countries had between Int$1 million and Int$10 million, and six (11%) countries had Int$11 million and above. Three countries (Algeria, Egypt, and South Africa) accounted for 90% of the TPVAFC of human lives lost in the continent.

The present value of human life losses from COVID-19 in Africa as of 1 August 2020 (in 2020, Int$ or PPP)
CountryPopulation in 2020* [A]COVID-19 deaths as of 1 August 2020* [B]Total present value of human life lost (Int$) [C]**Present value per human life lost (Int$) [D = C/B]**Present value of human life lost per person in population (Int$) [E = C/A]**
Algeria43,851,0431210245,299,956202,7275.59
Angola32,866,268522,020,07838,8480.06
Benin12,123,19836643,83517,8840.05
Botswana2,351,6252297,052148,5260.13
Burkina Faso20,903,27853545,96810,3010.03
Burundi11,890,7811333533350.00
Cameroon26,545,8643916,768,58117,3110.25
Cape Verde555,988231,962,14185,3103.53
Central African Republic4,829,76459113,91619310.02
Chad16,425,85975512,96168390.03
Comoros869,5957118,95516,9940.14
Congo5,518,092542,371,74943,9210.43
Cote d’Ivoire26,378,2751021,757,30617,2280.07
Democratic Republic of Congo (DRC)89,561,404215848,34639460.01
Equatorial Guinea1,402,985836,520,72978,5634.65
Eritrea3,546,4270000
Ethiopia114,963,5832745,155,48918,8160.04
Gabon2,225,728496,766,041138,0823.04
Gambia, The2,416,6649135,57315,0640.06
Ghana31,072,9451827,661,25042,0950.25
Guinea13,132,79246573,64312,4710.04
Guinea-Bissau1,967,99826211,65581410.11
Kenya53,771,3003419,543,97227,9880.18
Lesotho2,142,25213119,82792170.06
Liberia5,057,67775607,75681030.12
Madagascar27,691,0191061,366,58612,8920.05
Malawi19,129,955114795,62869790.04
Mali20,250,8341241,358,74010,9580.07
Mauritania4,649,6601574,776,90030,4261.03
Mauritius1,271,767103,071,846307,1852.42
Mozambique31,255,4351172,36365780.00
Namibia2,540,91610617,44261,7440.24
Niger24,206,63669393,18956980.02
Nigeria206,139,58787914,222,52316,1800.07
Rwanda12,952,2095107,24321,4490.01
Sao Tome and Principe219,16115454,14730,2762.07
Senegal16,743,9302056,151,99030,0100.37
Ghana31,072,9451827,661,25042,0950.25
Seychelles98,3400000
Sierra Leone7,976,98567282,86742220.04
South Africa59,308,6908005602,528,30175,26910.16
South Sudan11,193,72946266,49057930.02
Swaziland (Eswatini)1,160,164412,073,93450,5841.79
Tanzania59,734,21321482,04622,9550.01
Togo8,278,73719172,50690790.02
Uganda45,741,000344,13614,7120.00
Zambia18,383,9561513,527,85623,3630.19
Zimbabwe14,862,92767866,49612,9330.06
Djibouti988,002582,375,99540,9652.40
Egypt102,334,4034805697,921,220145,2496.82
Libya6,871,287747,111,55596,1021.03
Morocco36,910,55835342,956,126121,6891.16
Somalia15,893,21993220,06023660.01
Sudan43,849,26974618,189,51324,3830.41
Tunisia11,818,618508,062,957161,2590.68
TOTAL1,338,826,59119,6821,721,030,76687,4421.29

Source: * Worldometer (2020). **Authors estimates.

3.2. Findings Assuming Each Country’s Life Expectancy and 5% and 10% Discount Rates

Alternate reanalysis of the economic model (in subsection 2.3) using 5% and 10% discount rates reduced the TPVAFC by Int$273,841,437 (15.9%) and Int$695,688,478 (40.4%), respectively. In turn, the average present value per human life diminished by Int$13,913.3 and Int$35,346.

3.3. Findings Assuming World Highest Life Expectancy and 3% Discount Rate

Re-calculation of the economic model (in subsection 2.3) substituting individual country’s national life expectancy with the world highest life expectancy of 88.17 years increased the TPVAFC by Int$2,343,115,427 (136.1%) and the present value per human life by Int$119,049.

4. Discussion4.1. Key Findings

Our study succeeded in estimating the TPVAFC of human lives lost due to COVID-19 in the Continent as of 1 August 2020. The TPVAFC of Int$1,721,030,766 was equivalent to 0.023% of the total GDP of the African Continent. The present value of Int$87,442 per human life loss associated with COVID-19 was 15-fold Africa’s GDP per capita in 2020.

4.2. Comparison with Similar Studies

The present value per human life lost from COVID-19 in Africa was lower than Canada’s Int$231,217 per death (Kirigia & Muthuri, 2020a), China’s Int$356,203 per death (Kirigia & Muthuri, 2020b), Spain’s Int$470,798 per death (Kirigia & Muthuri, 2020c), Turkey’s Int$228,514 per death (Kirigia, Muthuri, & Nkanata, 2020), the UK’s Int$225,104 per death (Kirigia & Muthuri, 2020d), and the USA’s Int$292,889 per death (Kirigia & Muthuri, 2020e). The lower present value per human life lost in Africa may be due to both lower GDP per capita, and lower life expectancy at birth (leading to a smaller number of YLL) (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e).

4.3. Research Innovation

To the best of our knowledge, this was the first study to have estimated the present value of human life losses associated with coronavirus disease in Africa. As explained in the WHO guide to identifying the economic consequences of disease and injury (WHO, 2009a), the evidence contained in this article can be used by the ministries of health in African countries to advocate for increased investments into health-related sectors to bridge existing gaps in the coverage of essential health services, IHR core capacities, and water and sanitation services.

4.4. Study Limitations

First, the completeness of cause-of-death data in the AFR was 6% and 32% in EMR, implying cause-of-death for 94% and 68% of deaths, respectively, is not recorded (WHO, 2019). The relatively low completeness of cause-of-death during the ordinary non-pandemic period implies that the notified COVID-19 cases and deaths could be a gross underestimate for many African countries. The under-reporting is exacerbated by the low level of COVID-19 testing in Africa (Worldometer, 2020).

Second, the cost of societal resources used in the prevention, diagnosis, contact tracing, isolation/quarantine, hospital management of COVID-19 cases; and funerals for the dead was omitted (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020). Third, the macroeconomic effects of COVID-19 on education, financial services, trade, tourism, travel, and manufacturing sectors were omitted (Kirigia, Muthuri, & Nkanata, 2020).

Fourth, according to Jones-Lee (1985) the HCA when strictly applied, it would value YLL among retirees and homemakers at zero. Jones-Lee (1985) advocates for elicitation of WTP for small changes in probability death (e.g. from COVID-19) because the approach “… is firmly rooted in the principles of ex-ante Paretian welfare economics and the related precepts of conventional social cost-benefit analysis (p. 143)”.

4.5. Future Research Directions

First, the quality of economic evaluation studies hinges on the quality of underlying epidemiological evidence. Thus, there is need for quality epidemiological studies on morbidity and mortality due to pandemics; effectiveness of existing and potential preventive, diagnostic, management, and rehabilitative interventions from randomized controlled effectiveness trials; effectiveness of alternative ways of delivering interventions; and human behaviour in intervention uptake and adherence to recommended procedures.

Second, once the pandemic is eradicated, there will be a need for comprehensive studies into the macroeconomic effects of COVID-19 on education, financial services, trade, tourism, travel, manufacturing, and other sectors. Such evidence could be used in advocating for coordinated and managed inter-sectoral action for implementation of health-in-all policies to leapfrog equitable health development, mitigate, and better combat future public health emergencies (WHO, 2009b, 2010, 2012a, 2012b).

Third, the health policy development and decision-making processes require evidence on both costs and consequences (or benefits) of preventive, management, and rehabilitative interventions for COVID-19 (Drummond, Sculpher, Torrance, O’Brien, & Stoddard, 2007; Kirigia, 2009; Cookson, Griffin, Norheim, & Culyer, 2020). For comparative purposes, future studies should consider applying the WTP approach to value human life losses associated with COVID-19, which would facilitate comparison with those obtained in the current study using the HCA.

5. Conclusion

The estimated TPVAFC of human lives lost due to COVID-19 in Africa is likely to be an underestimate due to abovementioned limitations. COVID-19 is a burden on the NHS, the DSRS, the SDHS, and the economies of African countries. The TPVAFC will continue growing until the pandemic is eradicated. The TPVAFC evidence, in conjunction with human rights arguments (rights to life, health, medical care, clothing, food, housing, and social security) (United Nations (UN), 1948), can be used in advocacy for increased domestic and external investments to bridge existing gaps in NHS, DSRS, and SDHS. Since our study was of limited scope, assessments of the economy-wide impact of COVID-19; and costs and consequences of preventive, treatment, and rehabilitative interventions are needed to guide policy (Kirigia & Muthuri, 2020a, 2020b, 2020c, 2020d, 2020e; Kirigia, Muthuri, & Nkanata, 2020).

Acknowledgements

We owe profound gratitude to Jehovah Jireh for meeting all our needs in the entire process of conceiving and writing this paper. This paper is dedicated to health workers, who are the frontline soldiers in the war against COVID-19 in the Continent. The views expressed in this paper are only those of authors and should not be attributed to their institutions of affiliation.

Authors’ Contributions

JMK, RNDKM, LHKN, and NGM designed the study; reviewed the literature; extracted data from the international databases; analyzed and interpreted findings; and drafted the manuscript together. All the authors approved the version of the manuscript submitted.

Funding

The study did not receive funding from any source.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

Cite this paper

Kirigia, J. M., Muthuri, R. N. D. K., Nkanata, L. H. K., & Muthuri, N. G. (2020). The Present Value of Human Life Losses Associated with Coronavirus Disease in Africa. Open Journal of Business and Management, 8, 2371-2395. https://doi.org/10.4236/ojbm.2020.86146

Supplement Names of countries and territories in the Africa continent
Country and Territories Names
Algeria
Angola
Benin
Botswana
Burkina Faso
Burundi
Cameroon
Cabo Verde
Central African Republic
Chad
Comoros
Congo
Côte d’Ivoire
Democratic Republic of the Congo
Equatorial Guinea
Eritrea
Ethiopia
Gabon
Gambia
Ghana
Guinea
Guinea-Bissau
Kenya
Lesotho
Liberia
Madagascar
Malawi
Mali
Mauritania
Mauritius
Mozambique
Namibia
Niger
Nigeria
Rwanda
Sao Tome and Principe
Senegal
Seychelles
Sierra Leone
South Africa
Swaziland (Eswatini)
Togo
Uganda
United Republic of Tanzania
Zambia
Zimbabwe
South Sudan
Djibouti
Egypt
Libya
Morocco
Somalia
Sudan
Tunisia
Sahrawi Arab Democratic Republic (Western Sahara)
Territories
Reunion
Mayotte

Source: Worldometer (2020).

Africa continent countries average life expectancies at birth in 2020
CountryAverage life expectancy in 2020
Algeria77.5
Angola62.2
Benin62.8
Botswana69.9
Burkina Faso63
Burundi62.7
Cameroon60.3
Cape Verde73.6
Central African Republic54.4
Chad55.2
Comoros65
Congo65.2
Côte d’Ivoire58.8
Dem. Rep. of the Congo61.6
Equatorial Guinea59.8
Eritrea67.5
Ethiopia67.8
Gabon67
Gambia63.3
Ghana64.9
Guinea62.6
Guinea-Bissau59.4
Kenya67.5
Lesotho55.7
Liberia65
Madagascar68.2
Malawi65.6
Mali60.5
Mauritania65.6
Mauritius75.5
Mozambique62.1
Namibia64.9
Niger63.6
Nigeria55.8
Rwanda70
Sao Tome and Principe71
Senegal68.9
Seychelles73.7
Sierra Leone55.9
South Africa64.9
Swaziland61.1
Togo62.1
Uganda64.4
United Republic of Tanzania66.4
Zambia64.7
Zimbabwe62.2
South Sudan58.7
Djibouti67.9
Egypt72.5
Libya73.4
Morocco77.4
Somalia58.3
Sudan66.0
Tunisia77.4
Sahrawi Arab Democratic Republic (Western Sahara)71.1
Territories
Reunion82
Mayotte80

Source: Worldometer (2020).

Africa countries per capita gross domestic product (2020, Int$ or PPP)
CountryPer capita gross domestic product (Int$)
Algeria16,091
Angola6763
Benin3648
Botswana19,388
Burkina Faso2181
Burundi724
Cameroon4099
Cape Verde8176
Central African Republic864
Chad2603
Comoros2898
Democratic Republic of the Congo873
Congo7336
Côte d’Ivoire4754
Equatorial Guinea19,961
Eritrea1103
Ethiopia2702
Gabon19,839
Gambia2892
Ghana7343
Guinea2574
Guinea-Bissau2113
Kenya4078
Lesotho3655
Liberia1428
Madagascar1776
Malawi1292
Mali2569
Mauritania5158
Mauritius26,461
Mozambique1372
Namibia11,451
Niger1152
Nigeria6172
Rwanda2642
São Tomé and Príncipe3499
Senegal4079
Seychelles33,118
Sierra Leone1765
South Africa13,965
Swaziland11,319
Tanzania3562
Togo1913
Uganda2753
Zambia4174
Zimbabwe2778
South Sudan1715
Djibouti5855
Egypt14,800
Libya9446
Morocco9667
Somalia904
Sudan3986
Tunisia13,093

Source: International Monetary Fund (IMF) (2020). Note: Int$: International Dollars (Int$). PPP: Purchasing-power-parity.

Africa countries current health expenditure per capita
CountryCurrent health expenditure per person (Int$)
Algeria975
Angola186
Benin85
Botswana1044
Burkina Faso129
Burundi59
Cameroon174
Cabo Verde357
Central African Republic42
Chad87
Comoros123
Democratic Republic of the Congo37
Congo165
Cote d’Ivoire176
Equatorial Guinea759
Eritrea59
Ethiopia67
Gabon500
Gambia56
Ghana147
Guinea89
Guinea-Bissau123
Kenya158
Lesotho266
Liberia105
Madagascar85
Malawi115
Mali84
Mauritania170
Mauritius1278
Mozambique62
Namibia895
Niger79
Nigeria221
Rwanda134
Sao Tome and Principe134
Senegal143
Seychelles1485
Sierra Leone205
South Africa1098
Swaziland600
Tanzania104
Togo104
Uganda123
Zambia180
Zimbabwe201
South Sudan176
Djibouti117
Egypt614
Libya429
Morocco438
Somalia275
Sudan314
Tunisia863

Source: WHO (2020b).

Africa countries net gross domestic product per capita in 2020
CountriesNet GDP per capita (Int$)
Algeria15,116
Angola6577
Benin3563
Botswana18,343
Burkina Faso2052
Burundi664
Cameroon3926
Cabo Verde7819
Central African Republic822
Chad2515
Comoros2775
Congo7172
Côte d’Ivoire4578
Democratic Republic of the Congo836
Equatorial Guinea19,202
Eritrea1043
Ethiopia2635
Gabon19,340
Gambia2836
Ghana7196
Guinea2485
Guinea-Bissau1990
Kenya3920
Lesotho3390
Liberia1323
Madagascar1691
Malawi1178
Mali2485
Mauritania4988
Mauritius25,183
Mozambique1311
Namibia10,555
Niger1073
Nigeria5951
Rwanda2507
Sao Tome and Principe3364
Senegal3935
Seychelles31,633
Sierra Leone1560
South Africa12,867
South Sudan1539
Swaziland10,719
Togo1809
Uganda2630
Tanzania3457
Zambia3994
Zimbabwe2577
Djibouti5738
Egypt14,187
Libya9017
Morocco9229
Somalia629
Sudan3672
Tunisia12,229

Source: Authors estimates using data from International Monetary Fund (IMF) (2020) and WHO (2020b). Note: Net GDP per capita equals GDP per capita minus current health expenditure per person.

Africa countries coronavirus disease deaths as of 1 August 2020
CountriesCOVID19 Deaths in 2020: 1 August 2020
Algeria1210
Angola52
Benin36
Botswana2
Burkina Faso53
Burundi1
Cameroon391
Cabo Verde23
CAR59
Chad75
Comoros7
Congo54
Cote d’Ivoire102
Democratic Republic of Congo (DRC)215
Djibouti58
Egypt4805
Equatorial Guinea83
Eritrea0
Ethiopia274
Gabon49
Gambia9
Ghana182
Guinea46
Guinea-Bissau26
Kenya341
Lesotho13
Liberia75
Libya74
Madagascar106
Malawi114
Mali124
Mauritania157
Mauritius10
Morocco353
Mozambique11
Namibia10
Niger69
Nigeria879
Rwanda5
STP15
Senegal205
Seychelles0
Sierra Leone67
Somalia93
South Africa8005
South Sudan46
Sudan746
Swaziland/Eswatini41
Togo19
Tunisia50
Uganda3
Tanzania21
Zambia151
Zimbabwe67
Reunion4
Mayotte39
Western Sahara1
TOTAL19726

Source: Worldometer (2020).

Proportions used to share COVID-19 deaths across eight age groups
Age brackets(A) COVID-19 deaths in South Africa as of as of 22 June 2020(C). Proportion [C = A/B]
0 - 930.001563314
10 - 1950.002605524
20 - 29260.013548723
30 - 391160.06044815
40 - 492440.127149557
50 - 594710.245440334
60 - 695060.263678999
70 & above5480.285565399
(B) TOTAL1919

Source: Statista (2020). Note: The 11 deaths whose age was unknown were not included in calculations of the proportions.

Africa continent countries years of life lost from COVID-19 by 1st August 2020
CountriesYears of life lost per age group
0 - 910 - 1920 - 2930 - 3940 - 4950 - 5960 - 6970+TOTAL
Algeria1381998693145507768314148259222,998
Angola56278711799--341
Benin3519628474--246
Botswana0014683-23
Burkina Faso572891125110--365
Burundi001222--7
Cameroon3447190610786559--2226
Cape Verde241554851085524347
Central African Republic56247174---179
Chad68319410212--253
Comoros1141318181-56
Congo573010014214210-437
Cote D’Ivoire91247150185106--508
DRC1926108352467375--1348
Equatorial Guinea71040127162108--454
Eritrea---------
Ethiopia2738161552812895239-2724
Gabon57289614015133-460
Gambia115162119--63
Ghana172410033547346621-1436
Guinea46247810692--310
Guinea Bissau2312394931--137
Kenya34471996809961086267-3307
Lesotho11517184--47
Liberia7104113819519310-595
Madagascar111563216320357104-1084
Malawi11156421430631134-955
Mali111561195253184--718
Mauritania15218729542142744-1310
Mauritius1272539522916170
Mozambique116182521--72
Namibia1151826251-78
Niger6937121168154--495
Nigeria709437211291257270--3193
Rwanda1131116197-58
STP229335161264188
Senegal2129123426635723236-2193
Seychelles---------
Sierra Leone5729879723--249
South Africa7561051438014,70120,74320,394802-62,826
South Sudan4521678348--229
Swaziland4520668666--247
Tanzania231240586110-187
Togo2210324336--124
Uganda002587--23
Zambia1420822763883788-1166
Zimbabwe6834112150126--437
Djibouti683411717219052-579
Egypt511727312711,04917,13121,27510,186348567,492
Libya81149174272344174731106
Morocco40582539161478198712047496684
Somalia8114313416488--446
Sudan72100420142120402107297-6457
Tunisia6836130209281170105943
TOTAL1930270411,39538,94156,88561,50218,1707047198,575
Percent1.01.45.719.628.631.09.23.5100.0

Source: Author estimates. Note: Years of life lost (YLL) in an age group equals national life expectancy minus average age at onset of death from COVID-19 in an age group.

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