Event-specific interventions to minimize COVID-19 transmission (preprint)

ABSTRACT

Coronavirus disease 2019 (COVID-19) is a global pandemic with over 11 million cases worldwide. Currently there is no treatment and no vaccine. Interventions such as hand washing, 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 infected 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 re-open economies with principled measures to reduce COVID-19 transmission.