Title: Using frailty models in mathematical epidemiology to reveal how diseases are transmitted
Authors: Steven Abrams - University of Antwerp and UHasselt (Belgium) [presenting]
Niel Hens - Hasselt University (Belgium)
Steffen Unkel - University Medical Center Gottingen (Germany)
Andreas Wienke - Martin Luther University Halle-Wittenberg (Germany)
Abstract: In mathematical epidemiology, frailty models are commonly used for representing individual heterogeneities relevant to the transmission of infectious diseases. More specifically, these frailty models naturally encompass individual differences in susceptibility to infection, infectiousness upon infection and variation in social activity levels corresponding to specific (effective) contacts relevant to disease spread. Here, we focus on both time-invariant and time-varying frailty models, thereby enabling heterogeneities to evolve over time, for the infection-specific infection hazards. The genesis of these models and how they can be derived from the biological processes underlying disease transmission are demonstrated. Multivariate frailty models including shared and correlated frailties are useful for describing the association between (bivariate) infection times when applied to either right-censored or interval-censored data. Hence, we apply these models to model bivariate current status data thereby unraveling the routes of transmission for these diseases.