Report 34 - COVID-19 Infection Fatality Ratio Estimates from Seroprevalence
Zotero / K4D COVID-19 Health Evidence Summaries Group / Top-Level Items 2020-11-09
Type
Report
Author
Nicholas F Brazeau
Author
Robert Verity
Author
Sara Jenks
Author
Han Fu
Author
Charles Whittaker
Author
Peter Winskill
Author
Ilaria Dorigatti
Author
Patrick Walker
Author
Steven Riley
Author
Ricardo P Schnekenberg
Author
Henrique Hoeltgebaum
Author
Thomas A Mellan
Author
Swapnil Mishra
Author
Juliette T Unwin
Author
Oliver J Watson
Author
Zulma M Cucunubá
Author
Marc Baguelin
Author
Lilith Whittles
Author
Samir Bhatt
Author
Azra C Ghani
Author
Neil M Ferguson
Author
Lucy C Okell
URL
http://www.imperial.ac.uk/medicine/departments/school-public-health/infectious-disease-epidemiology/mrc-global-infectious-disease-analysis/covid-19/report-34-ifr/
Date
29/10/2020
Institution
Imperial College London
Language
en-GB
Abstract
Report 34 - COVID-19 Infection Fatality Ratio: Estimates from Seroprevalence
The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the current pandemic. Previous estimates have relied on data early in the epidemic, or have not fully accounted for uncertainty in serological test characteristics and delays from onset of infection to seroconversion, death, and antibody waning. After screening 175 studies, we identified 10 representative antibody surveys to obtain updated estimates of the IFR using a modelling framework that addresses the limitations listed above. We inferred serological test specificity from regional variation within serosurveys, which is critical for correctly estimating the cumulative proportion infected when seroprevalence is still low. We find that age-specific IFRs follow an approximately log-linear pattern, with the risk of death doubling approximately every eight years of age. Using these age-specific estimates, we estimate the overall IFR in a typical low-income country, with a population structure skewed towards younger individuals, to be 0.23% (0.14-0.42 95% prediction interval range). In contrast, in a typical high income country, with a greater concentration of elderly individuals, we estimate the overall IFR to be 1.15% (0.78-1.79 95% prediction interval range). We show that accounting for seroreversion, the waning of antibodies leading to a negative serological result, can slightly reduce the IFR among serosurveys conducted several months after the first wave of the outbreak, such as Italy. In contrast, uncertainty in test false positive rates combined with low seroprevalence in some surveys can reconcile apparently low crude fatality ratios with the IFR in other countries. Unbiased estimates of the IFR continue to be critical to policymakers to inform key response decisions. It will be important to continue to monitor the IFR as new treatments are introduced.
Report Number
34