Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA, 02142, USA.
Department of Life Science & Institute of Bioinformatics and Structural Biology, National Tsing Hua University, No. 101, Section 2, Kuang-Fu Road, Hsinchu, 300044, Taiwan.
Nat Commun. 2020 Aug 13;11(1):4049. doi: 10.1038/s41467-020-17922-x.
The ongoing novel coronavirus disease (COVID-19) pandemic has already infected millions worldwide and, with no vaccine available, interventions to mitigate transmission are urgently needed. While there is broad agreement that travel restrictions and social distancing are beneficial in limiting spread, recommendations around face mask use are inconsistent. Here, we use mathematical modeling to examine the epidemiological impact of face masks, considering resource limitations and a range of supply and demand dynamics. Even with a limited protective effect, face masks can reduce total infections and deaths, and can delay the peak time of the epidemic. However, random distribution of masks is generally suboptimal; prioritized coverage of the elderly improves outcomes, while retaining resources for detected cases provides further mitigation under a range of scenarios. Face mask use, particularly for a pathogen with relatively common asymptomatic carriage, is an effective intervention strategy, while optimized distribution is important when resources are limited.
正在持续的新型冠状病毒病(COVID-19)大流行已经在全球感染了数百万人,由于没有疫苗可用,因此急需采取干预措施来减轻传播。虽然人们普遍认为旅行限制和社交距离对限制传播是有益的,但关于口罩使用的建议却不一致。在这里,我们使用数学模型来研究口罩的流行病学影响,同时考虑资源限制以及各种供应和需求动态。即使口罩的保护效果有限,也可以减少总感染人数和死亡人数,并可以延迟疫情高峰期。但是,口罩的随机分配通常不是最佳选择;优先为老年人提供口罩可以改善结果,而在各种情况下,为检测到的病例保留资源可以进一步减轻影响。口罩的使用,特别是对于具有相对常见无症状携带的病原体,是一种有效的干预策略,而在资源有限的情况下,优化分配则很重要。