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Income inequality and pandemics: insights from HIV/AIDS and COVID-19—a multicountry observational study
  1. John Ele-Ojo Ataguba1,2,
  2. Charles Birungi3,
  3. Santiago Cunial4,
  4. Matthew Kavanagh5,6
  1. 1 African Health Economics and Policy Association, Accra, Ghana
  2. 2 Health Economics Laboratory, University of Manitoba Faculty of Health Sciences, Winnipeg, Manitoba, Canada
  3. 3 Equitable Financing, Joint United Nations Programme on HIV/AIDS, Nairobi, Kenya
  4. 4 Political Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
  5. 5 School of Health, Georgetown University, Washington, DC, USA
  6. 6 UNAIDS–Georgetown Collaborating Centre on HIV Policy and Inequality, Joint United Nations Programme on HIV/AIDS, Geneve, Switzerland
  1. Correspondence to Dr John Ele-Ojo Ataguba; john.ataguba{at}umanitoba.ca

Abstract

Objectives Assess the relationship between income inequality and HIV incidence, AIDS mortality and COVID-19 mortality.

Design Multicountry observational study.

Setting 217 countries for HIV/AIDS analysis, 151 countries for COVID-19 analysis.

Participants Used three samples of national-level data: a sample of all countries with available data (global sample), a subsample of African countries (African sample) and a subsample excluding African countries (excluding African sample).

Main outcome measures HIV incidence rate per 1000 people, AIDS mortality rate per 100 000 people and COVID-19 excess mortality rate per 100 000 people. The Gini index of income inequality was the primary explanatory variable.

Results A positive and significant relationship exists between the Gini index of income inequality and HIV incidence across all three samples (p<0.01), with the effect of income inequality on HIV incidence being higher in the African sample than in the rest of the world. Also, a statistically positive association exists for all samples between income inequality and the AIDS mortality rate, as higher income inequality increases AIDS mortality (p<0.01). For COVID-19 excess mortality rate, a positive and statistically significant relationship exists with the Gini index for the entire sample and the excluding African sample (p<0.05), but the African sample alone did not deliver significant results (p<0.1).

Conclusion COVID-19 excess deaths, HIV incidence and AIDS mortality are significantly associated with income inequality globally—more unequal countries have a higher HIV incidence, AIDS mortality and COVID-19 excess deaths than their more equal counterparts. Income inequality undercuts effective pandemic response. There is an urgent need for concerted efforts to tackle income inequality and to build pandemic preparedness and responses that are adapted and responsive to highly unequal societies, prioritising income inequality among other social determinants of health.

  • COVID-19
  • Health policies and all other topics
  • HIV

Data availability statement

Data are available in a public, open access repository. All data used in this paper are available in the public domain from different sources. HIV/AIDS data are available from the UNAIDS (https://aidsinfo.unaids.org/), COVID-19 data from The Economist (https://www.economist.com/graphic-detail/coronavirus-excess-deaths-estimates), health expenditure data from the World Bank (https://data.worldbank.org/indicator) or WHO, and the Gini index of income inequality from the World Inequality Database (https://wid.world/data/).

https://creativecommons.org/licenses/by/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/.

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Data availability statement

Data are available in a public, open access repository. All data used in this paper are available in the public domain from different sources. HIV/AIDS data are available from the UNAIDS (https://aidsinfo.unaids.org/), COVID-19 data from The Economist (https://www.economist.com/graphic-detail/coronavirus-excess-deaths-estimates), health expenditure data from the World Bank (https://data.worldbank.org/indicator) or WHO, and the Gini index of income inequality from the World Inequality Database (https://wid.world/data/).

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Footnotes

  • Handling editor Seye Abimbola

  • Twitter @c_birungi, @MMKavanagh

  • Contributors JE-OA, CB, SC and MK conceived the study. JE-OA, SC and CB were primarily responsible for statistical analysis supported by MK. JE-OA, CB, SC and MK prepared the manuscript. All authors approved the final version of the manuscript. JE-OA and CB are the study guarantors.

  • Funding This work was supported in part by a grant to UNAIDS from the Bill & Melinda Gates Foundation (Grant INV-004700). The Canada Research Chairs supports JE-OA as a Canada Research Chair in Health Economics and UNAIDS supports the work of CB and MK.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.