Article Text

Download PDFPDF

Predicted COVID-19 fatality rates based on age, sex, comorbidities and health system capacity
  1. Selene Ghisolfi1,2,
  2. Ingvild Almås1,
  3. Justin C Sandefur3,
  4. Tillman von Carnap1,
  5. Jesse Heitner4,
  6. Tessa Bold1
  1. 1 Institute for International Economic Studies, Stockholm University, Stockholm, Sweden
  2. 2 LEAP, Bocconi University, Milan, Italy
  3. 3 Center for Global Development, Washington, DC, USA
  4. 4 Aceso Global, Washington, DC, USA
  1. Correspondence to Professor Tessa Bold; tessa.bold{at}iies.su.se

Abstract

Early reports suggest the fatality rate from COVID-19 varies greatly across countries, but non-random testing and incomplete vital registration systems render it impossible to directly estimate the infection fatality rate (IFR) in many low- and middle-income countries. To fill this gap, we estimate the adjustments required to extrapolate estimates of the IFR from high-income to lower-income regions. Accounting for differences in the distribution of age, sex and relevant comorbidities yields substantial differences in the predicted IFR across 21 world regions, ranging from 0.11% in Western Sub-Saharan Africa to 1.07% for high-income Asia Pacific. However, these predictions must be treated as lower bounds in low- and middle-income countries as they are grounded in fatality rates from countries with advanced health systems. To adjust for health system capacity, we incorporate regional differences in the relative odds of infection fatality from childhood respiratory syncytial virus. This adjustment greatly diminishes but does not entirely erase the demography-based advantage predicted in the lowest income settings, with regional estimates of the predicted COVID-19 IFR ranging from 0.37% in Western Sub-Saharan Africa to 1.45% for Eastern Europe.

  • public health
  • SARS
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/.

View Full Text

Statistics from Altmetric.com

Footnotes

  • Handling editor Seye Abimbola

  • Twitter @justinsandefur

  • Contributors All authors contributed to the design of the research. SG and TB compiled and analysed the data. TB, SG, JH and JCS contributed to writing. IA and TvC reviewed and edited the manuscript.

  • Funding This study was supported by Bill & Melinda Gates Foundation.

  • Competing interests None declared.

  • Patient consent for publication Not required.

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

  • Data availability statement Data are available upon request.

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.