Immune Response, Transmission Model, and Contact Network Determinants of Disease Spread
We investigate how differences in individual immunity shape disease spread in real populations, using examples from sexually transmitted and airborne diseases.
Our modeling approach considers how susceptibility, transmissibility, and sickness behavior covary with immune history, viral load, and health, including how contacts change when people are symptomatic. The project combines within-individual virus dynamics and social mixing data, using statistical and network science tools to efficiently model infectious disease transmission on dynamic contact networks that include individual heterogeneity. The expected result is a flexible framework that links immune response, behavior, and contact networks to produce more realistic outbreak forecasts and better guidance for control strategies.