Abstract
Wearing masks is an easy way to operate and popular measure for preventing epidemics. Although masks can slow down the spread of viruses, their efficacy in gathering environments involving heterogeneous person-to-person contacts remains unknown. Therefore, we aim to investigate the epidemic prevention effect of masks in different real-life gathering environments. This study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering environments. The transmission of COVID-19 is simulated using the Monte Carlo simulation method. The heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general society. Furthermore, the heterogeneity of gathering environments causes the epidemic prevention effect of masks to differ. Wearing masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools, high schools, and hospitals. However, the use of masks alone in primary schools and hospitals cannot control outbreaks. In high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse, masks can meet the need for prevention. Given the heterogeneity of individual behavior, if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing, the epidemic prevention effect of masks can be improved. Finally, asymptomatic infection has varying effects on the prevention effect of masks in different environments. The effect can be weakened or eliminated by increasing the usage rate of masks in high schools and workplaces. However, the effect on primary schools and hospitals cannot be weakened. This study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention.
| Original language | English |
|---|---|
| Pages (from-to) | 550–562 |
| Number of pages | 13 |
| Journal | Frontiers of Engineering Management |
| Volume | 9 |
| Issue number | 4 |
| Online published | 25 May 2022 |
| DOIs | |
| Publication status | Published - Dec 2022 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Keywords
- COVID-19
- masks
- behavioral heterogeneity
- asymptomatic infection
- WUHAN
Publisher's Copyright Statement
- COPYRIGHT TERMS OF DEPOSITED POSTPRINT FILE: This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s42524-022-0193-5
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