Event-specific interventions to minimize COVID-19 transmission

被引:34
|
作者
Tupper, Paul [1 ]
Boury, Himani [2 ]
Yerlanov, Madi [1 ]
Colijn, Caroline [1 ,3 ]
机构
[1] Simon Fraser Univ, Dept Math, Burnaby, BC V5A 1S6, Canada
[2] Simon Fraser Univ, Fac Hlth Sci, Burnaby, BC V5A 1S6, Canada
[3] Imperial Coll London, Dept Math, London SW7 2AZ, England
关键词
COVID-19; disease transmission; epidemics; interventions; SARS-COV-2;
D O I
10.1073/pnas.2019324117
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
COVID-19 is a global pandemic with over 25 million cases world-wide. Currently, treatments are limited, and there is no approved vaccine. Interventions such as handwashing, masks, social distancing, and "social bubbles" are used to limit community transmission, but it is challenging to choose the best interventions for a given activity. Here, we provide a quantitative framework to determine which interventions are likely to have the most impact in which settings. We introduce the concept of "event R," the expected number of new infections due to the presence of a single infectious individual at an event. We obtain a fundamental relationship between event R and four parameters: transmission intensity, duration of exposure, the proximity of individuals, and the degree of mixing. We use reports of small outbreaks to establish event R and transmission intensity in a range of settings. We identify principles that guide whether physical distancing, masks and other barriers to transmission, or social bubbles will be most effective. We outline how this information can be obtained and used to reopen economies with principled measures to reduce COVID-19 transmission.
引用
收藏
页码:32038 / 32045
页数:8
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