Modelling the effect of heterogeneous adherence behaviour on infection spread in crowds

Abstract

Human behaviour shapes infectious disease transmission, yet most models neglect behavioural variability. We present a local-scale infection model using survey data to assess how adherence to public health measures influences disease spread in crowds. We sampled self-reported adherence to mask-wearing and physical distancing and integrated these values in the simulation software Vadere.
Simulations of a scenario where people queue at a ticket checkpoint show that both measures substantially reduce exposure, with mask-wearing being more effective. Adherence of the infectious agent has the strongest impact. Adherence to physical distancing alters movement patterns, such as a non-adherent agent bypassing a queue. These findings underscore the need to integrate behavioural data into local-scale infection models to capture the interplay between movement, behaviour, and infection risk. This work provides a foundation to observe the effect of social and contextual factors on disease spread.