Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling.

ABSTRACT:

Background

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 COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion.

Methods

We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from diff

SUBMITTER: Brazeau NF 

PROVIDER: S-EPMC9120146 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature