A general epidemic model and its application to mask design considering different preferences towards masks
Chaoqian Wang, Hamdi Kavak

TL;DR
This study models epidemic spread considering different mask-wearing behaviors and evaluates how mask design influences collective protection, revealing that filterability enhancements can significantly curb transmission depending on population preferences.
Contribution
It introduces a comprehensive epidemic model incorporating diverse mask-wearing preferences and analyzes the impact of mask design on collective epidemic control.
Findings
Wearing masks consistently benefits epidemic control.
Enhancing mask filterability from face to outside is generally more effective.
When mask-wearers are abundant, improving outside-to-face filterability becomes more impactful.
Abstract
While most masks have a limited effect on personal protection, how effective are they for collective protection? How to enlighten the design of masks from the perspective of collective dynamics? In this paper, we assume three preferences in the population: (i) never wearing a mask; (ii) wearing a mask if and only if infected; (iii) always wearing a mask. We study the epidemic transmission in an open system within the Susceptible-Infected-Recovered (SIR) model framework. We use agent-based Monte Carlo simulation and mean-field differential equations to investigate the model, respectively. Ternary heat maps show that wearing masks is always beneficial in curbing the spread of the epidemic. Based on the model, we investigate the potential implications of different mask designs from the perspective of collective dynamics. The results show that strengthening the filterability of the mask…
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