18 Feb 2026

Infection Risk Assessment for Socially Structured Population Using Stochastic Microexposure Model

Abstract: Predicting infection outbreak dynamics within local microenvironments is a challenging task. Some methods assume smaller population pools and often lack the statistical power of inferences. Others are designed for larger population pools and cannot be downscaled to accommodate the details of microenvironments. Practicable infection risk assessment models should account for population size, geometry and occupancy of public places, behavioral and professional patterns of daily routines, and societal structure. This study is based on the stochastic microexposure model, which has been generalized to describe clustered populations. The methodology is demonstrated for a community of several thousand students on campus. The results indicate the social structure has the first order effect on the spread of the infection. Depending on the number, size, and degree of inner- and outer-cluster connections, the outbreak exhibits distinct durations, power, and multiple peaks of infection. Moreover, the contribution of different microenvironments to infection risk evolves during the course of the outbreak. Social structure plays a major role in infection spread and should be accounted for in risk prediction tools. The stochastic microexposure model accounts for the social structure of a population at multiple scales and can predict the dynamic contributions of different microenvironments to infection spread risks.