COVID-19 Statistical Modeling with Serologic Data

The purpose of the COVIDCurve project and R-software package was to provide a framework to fit age-specific infection fatality ratios (IFRs) in an epidemic that is using serologic data to estimate prevalence. The model was originally designed in response to the COVID-19 pandemic (hence the name) but is broadly applicable. Accurate inference of the IFR based on serological data is challenging due to a number of factors that can bias estimates away from the true value, including: (1) the delay between infection and death, (2) the dynamical process of seroconversion and seroreversion, (3) potential differences in age-specific attack rates, and (4) serological test characteristics.