The Role of Masks in Mitigating Viral Spread on Networks
Yurun Tian, Anirudh Sridhar, Chai Wah Wu, Simon A. Levin, Kathleen M., Carley, H.Vincent Poor, Osman Yagan

TL;DR
This paper presents a comprehensive analysis of how different types of masks influence viral spread on networks, using a novel agent-based model and analytical expressions to inform effective mitigation strategies.
Contribution
It introduces a new agent-based model incorporating various mask types and derives analytical formulas for key epidemiological metrics, enhancing understanding of mask efficacy in network-based viral spread.
Findings
Masks with high outward efficiency are most effective early in an epidemic.
Masks with high inward efficiency are better for reducing epidemic size after spread.
Degree-based mask allocation outperforms random allocation in mitigation.
Abstract
Masks have remained an important mitigation strategy in the fight against COVID-19 due to their ability to prevent the transmission of respiratory droplets between individuals. In this work, we provide a comprehensive quantitative analysis of the impact of mask-wearing. To this end, we propose a novel agent-based model of viral spread on networks where agents may either wear no mask or wear one of several types of masks with different properties (e.g., cloth or surgical). We derive analytical expressions for three key epidemiological quantities: the probability of emergence, the epidemic threshold, and the expected epidemic size. In particular, we show how the aforementioned quantities depend on the structure of the contact network, viral transmission dynamics, and the distribution of the different types of masks within the population. Through extensive simulations, we then investigate…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Complex Network Analysis Techniques · Opinion Dynamics and Social Influence
