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COVID-19 Age-Mortality Curves Are Flatter in Developing Countries

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  • Demombynes,Gabriel

Abstract

A greater share of reported COVID-19 deaths occur at younger ages in low- and middle-income countries (LMICs) compared to high-income countries (HICs). Based on data from 26 countries, people age 70 and older constitute 37 percent of deaths attributed to COVID-19 in LMICs on average, versus 87 percent in HICs. Only part of this difference is accounted for by differences in population age structure. In this paper, COVID-19 mortality rates are calculated for each age group by dividing the number of COVID-19 deaths by the underlying population. The resulting age-mortality curves are flatter in countries with lower incomes. In HICs, the COVID-19 mortality rate for those ages 70-79 is 12.6 times the rate for those ages 50-59. In LMICs, that ratio is just 3.5. With each year of age, the age-specific mortality rate increases by an average of 12.6 percent in HICs versus 7.1 percent in LMICs. This pattern holds overall and separately for men's and women's mortality rates. It reflects some combination of variation across countries in age patterns of infection rates, fatality rates among those infected, and under-attribution of deaths to COVID-19. The findings highlight that experiences with COVID-19 in wealthy countries may not be generalizable to developing countries.

Suggested Citation

  • Demombynes,Gabriel, 2020. "COVID-19 Age-Mortality Curves Are Flatter in Developing Countries," Policy Research Working Paper Series 9313, The World Bank.
    • Handle: RePEc:wbk:wbrwps:9313
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    References listed on IDEAS

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    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Developing economies

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    3. Isaac Sasson, 2021. "Age and COVID-19 mortality: A comparison of Gompertz doubling time across countries and causes of death," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(16), pages 379-396.
    4. Sabelo Nick Dlamini & Wisdom Mdumiseni Dlamini & Ibrahima Socé Fall, 2022. "Predicting COVID-19 Infections in Eswatini Using the Maximum Likelihood Estimation Method," IJERPH, MDPI, vol. 19(15), pages 1-12, July.
    5. Demombynes,Gabriel & De Walque,Damien B. C. M. & Gubbins,Paul Michael & Urdinola,Beatriz Piedad & Veillard,Jeremy Henri Maurice, 2021. "COVID-19 Age-Mortality Curves for 2020 Are Flatter in Developing Countries Using Both Official DeathCounts and Excess Deaths," Policy Research Working Paper Series 9807, The World Bank.
    6. Nicole Mun Sim Lai, 2022. "Why did care home residents face an elevated risk of death from COVID-19? A demographic perspective using data from Belgium and from England and Wales," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 20(1), pages 499-526.
    7. Godwin Attah Obande & Ahmad Ibrahim Bagudo & Suharni Mohamad & Zakuan Zainy Deris & Azian Harun & Chan Yean Yean & Ismail Aziah & Kirnpal Kaur Banga Singh, 2021. "Current State of COVID-19 Pandemic in Africa: Lessons for Today and the Future," IJERPH, MDPI, vol. 18(19), pages 1-15, September.
    8. Galanis, Giorgos & Georgiadis, Andreas, 2024. "Socioeconomic conditions and contagion dynamics of the COVID-19 pandemic with and without mitigation measures: Evidence from 185 countries," World Development, Elsevier, vol. 175(C).
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