Social distancing in pedestrian dynamics and its effect on disease spreading

TL;DR

This study models how social distancing affects disease spread in pedestrian populations, showing that even partial adherence significantly reduces exposure risk, with effectiveness varying based on transmission modes.

Contribution

It introduces a novel agent-based pedestrian model incorporating social distancing forces and analyzes its impact on epidemic dynamics with indirect transmission.

Findings

Social distancing reduces exposure risk significantly.

Partial adherence by infectious individuals has a large impact.

Effectiveness decreases when indirect transmission dominates.

Abstract

Non-pharmaceutical measures such as social distancing, can play an important role to control an epidemic in the absence of vaccinations. In this paper, we study the impact of social distancing on epidemics for which it is executable. We use a mathematical model combining human mobility and disease spreading. For the mobility dynamics, we design an agent based model consisting of pedestrian dynamics with a novel type of force to resemble social distancing in crowded sites. For the spreading dynamics, we consider the compartmental SIE dynamics plus an indirect transmission with the footprints of the infectious pedestrians being the contagion factor. We show that the increase in the intensity of social distancing has a significant effect on the exposure risk. By classifying the population into social distancing abiders and non-abiders, we conclude that the practice of social distancing, even by a minority of potentially infectious agents, results in a drastic change on the population exposure risk, but reduces the effectiveness of the protocols when practiced by the rest of the population. Furthermore, we observe that for contagions which the indirect transmission is more significant, the effectiveness of social distancing would be reduced. This study can provide a quantitative guideline for policy-making on exposure risk reduction.