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      Report 34: COVID-19 infection fatality ratio: estimates from seroprevalence

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          Abstract

          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 over 171 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 seven years of age. Using these age-specific estimates, we estimate that the overall IFR in a low-income country, with a population structure skewed towards younger individuals, can be expected to be approximately 0.18% (0.09-0.44 95% prediction interval range). In contrast, in high income countries, with a greater concentration of elderly individuals, we estimate that the overall IFR can be expected to be approximately 1.08% (0.58-2.27 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 longer 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.

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          Author and article information

          Journal
          Imperial College London
          2020
          29 October 2020
          28 October 2020
          Affiliations
          [1 ] Imperial College London
          Article
          10.25561/83545
          43ae8cff-b4f1-4316-b08a-9960e746079b

          © 2020. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/).

          http://creativecommons.org/licenses/by-nc-nd/4.0/

          10000-01-01

          History

          COVID19,Coronavirus,COVID-19
          COVID19, Coronavirus, COVID-19

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