Imperial College London
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Dr Zulma M Cucunubá

Faculty of Medicine, School of Public Health

Honorary Lecturer
 
 
 
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Contact

 

zulma.cucunuba

 
 
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Location

 

G27Medical SchoolSt Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@techreport{Brazeau:2020:10.25561/83545,
author = {Brazeau, N and Verity, R and Jenks, S and Fu, H and Whittaker, C and Winskill, P and Dorigatti, I and Walker, P and Riley, S and Schnekenberg, RP and Heltgebaum, H and Mellan, T and Mishra, S and Unwin, H and Watson, O and Cucunuba, Perez Z and Baguelin, M and Whittles, L and Bhatt, S and Ghani, A and Ferguson, N and Okell, L},
doi = {10.25561/83545},
title = {Report 34: COVID-19 infection fatality ratio: estimates from seroprevalence},
url = {http://dx.doi.org/10.25561/83545},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - RPRT
AB  - 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.  The code for reproducing these results are av
AU  - Brazeau,N
AU  - Verity,R
AU  - Jenks,S
AU  - Fu,H
AU  - Whittaker,C
AU  - Winskill,P
AU  - Dorigatti,I
AU  - Walker,P
AU  - Riley,S
AU  - Schnekenberg,RP
AU  - Heltgebaum,H
AU  - Mellan,T
AU  - Mishra,S
AU  - Unwin,H
AU  - Watson,O
AU  - Cucunuba,Perez Z
AU  - Baguelin,M
AU  - Whittles,L
AU  - Bhatt,S
AU  - Ghani,A
AU  - Ferguson,N
AU  - Okell,L
DO  - 10.25561/83545
PY  - 2020///
TI  - Report 34: COVID-19 infection fatality ratio: estimates from seroprevalence
UR  - http://dx.doi.org/10.25561/83545
UR  - https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2020-09-28-COVID19-Report-34.pdf
UR  - http://hdl.handle.net/10044/1/83545
ER  -
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