Speaker
Description
Host heterogeneity is a key driver of epidemic dynamics, yet most epidemic models assume homogeneous hosts and represent transmission and recovery using constant rates. In many infections, however, variation in within-host pathogen dynamics generates substantial differences in infectiousness, disease progression, and infection outcomes across individuals. Understanding when such heterogeneity must be represented explicitly remains an important challenge in epidemic modeling.
We investigate this question using West Nile virus (WNV), a mosquito-borne pathogen maintained in transmission cycles between mosquitoes and a diverse community of avian hosts that exhibit strong heterogeneity in viral load dynamics and infectiousness. We develop a stochastic individual-based multiscale model that explicitly represents within-host viral dynamics for multiple bird species and mechanistically links viral load to mosquito infection probability. This framework captures biologically grounded heterogeneity in infectiousness, latent and infectious periods, and disease-induced mortality.
By comparing the resulting epidemic dynamics with those predicted by an equivalent single-scale model parameterized using mean epidemiological traits, we assess when average transmission parameters suffice and when explicitly representing within-host heterogeneity is necessary to capture epidemic behavior.
