A Comparative Evaluation of Indoor Transmission-Risk Assessment Metrics for Infectious Diseases

Abstract

Governments worldwide have implemented non-pharmaceutical interventions (NPIs) to control the spread of coronavirus disease 2019 (COVID-19), and it is crucial to accurately assess the effectiveness of such measures. Many studies have quantified the risk of infection transmission and used simulations to compare the risk before and after the implementation of NPIs to judge policies’ effectiveness. However, the choice of metric used to quantify the risk can lead to different conclusions regarding the effectiveness of a policy. In this study, we analyze the correlation between different transmission-risk metrics, pedestrian environments, and types of infectious diseases using simulation-generated data. Our findings reveal conflicting results among five different metric types in specific environments. More specifically, we observe that, when the randomness of pedestrian trajectories in indoor spaces is low, the closeness centrality exhibits a higher correlation coefficient with infection-based metrics than with contact-based metrics. Furthermore, even within the same pedestrian environment, the likelihood of discrepancies between infection-based metrics and other metrics increases for infectious diseases with low transmission rates. These results highlight the variability in the measured effectiveness of NPIs depending on the chosen metric. To evaluate NPIs accurately, facility managers should consider the type of facility and infectious disease and not solely rely on a single metric. This study provides a simulation model as a tool for future research and improves the reliability of pedestrian-simulation-based NPI effectiveness analysis methods.