The code for reproducing these results are available as a R Research Compendium on Github: ` mrc-ide/reestimate_covidIFR_analysis`.Ģ9 de octubre de 2020 - Imperial College London It will be important to continue to monitor the IFR as new treatments are introduced. Unbiased estimates of the IFR continue to be critical to policymakers to inform key response decisions. 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. 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, 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). 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). We find that age-specific IFRs follow an approximately log-linear pattern, with the risk of death doubling approximately every eight years of age. 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. 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. 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. 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. WHO Collaborating Centre for Infectious Disease Modelling, MRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), Department of Mathematics, Imperial College London, Department of Clinical Biochemistry, Royal Infirmary of Edinburgh, Nuffield Department of Clinical Neurosciences, University of Oxford Summary Bacterial Evolutionary Epidemiology Group.Vaccine Epidemiology Research Group (VERG).London Centre for Neglected Tropical Disease Research.NIHR Health Protection Research Unit in Modelling and Health Economics.COVID-19 Response Team 2020-2021 report.MRC Centre for Global Infectious Disease Analysis Overview.Search Imperial Search MRC Centre for Global Infectious Disease Analysis Section Navigation

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