A population consists of individuals, and these individuals are often different in a number of ways that are relevant for our understanding of infectious processes within this population. These host heterogeneities may be discrete (e.g., hospitalized/quarantined vs. unquarantined persons), discretized (e.g., 5-year age bands) or continuous (e.g., age). Host factor models seek to explain the pathogenic dynamics, where there are meaningful differences in the way different populations transmit disease (β differences), recover from disease (γ differences), or in some other clinically meaningful factor. This chapter explores the mathematical modeling of such heterogeneities, initially using separate compartments and eventually using the abstraction of the WAIFW (who acquires infection from whom) matrix.
Computational Modeling of Infectious Disease: With Applications in Python, 2023, Pages 93-119,