Determining the lethality of COVID-19: Lessons for addressing bias and uncertainty in evidence synthesis
Conference
64th ISI World Statistics Congress - Ottawa, Canada
Format: IPS Abstract
Keywords: "bayesian, "statistical, covid-19, meta-analysis, selection bias
Session: IPS 79 - Statistical methods for managing emerging infectious diseases
Wednesday 19 July 2 p.m. - 3:40 p.m. (Canada/Eastern)
Abstract
I consider a Bayesian evidence synthesis approach for estimating the COVID-19 infection fatality rate which accounts for many important sources of bias and uncertainty inherent in both the seroprevalence and mortality data. The various challenges in estimating the COVID-19 IFR provide valuable lessons for epidemiologists conducting evidence synthesis with challenging data.