Comparing prevention strategies for pathogen control in heterogeneous surface touch networks

Abstract

Surface contact is a key pathway for pathogen transmission, amplified by the scale-free, heterogeneous structure of real-world surface touch networks. This study used mean-field theory to develop a dynamic model comparing three prevention strategies—random cleaning, targeted cleaning, and targeted inactivation strategy—in controlling pathogen spread. Parameterized with restaurant touch data, the model reveals that each strategy requires a minimum cleaning frequency threshold for effective contamination control. Targeted cleaning and targeted inactivation consistently achieve lower thresholds than random cleaning, requiring less frequent intervention to maintain control. In the restaurant network, random cleaning needs a critical cleaning frequency of 2.34/min, while targeted cleaning and targeted inactivation achieve lower thresholds of 1.28/min and 1.27/min, respectively. When cleaning frequency falls below these thresholds, targeted inactivation demonstrates superior contamination control, with the proportion of contaminated surfaces approaching zero when the prevention fraction reaches approximately 0.05. The relative performance of random versus targeted cleaning under insufficient frequency varies with network parameters such as heterogeneity and coverage. Early intervention timing further enhances all strategies' efficacy. These findings provide modeling-based insights for selecting optimal surface prevention strategies based on network characteristics and resource constraints in indoor environments.