Schimmoller Brian J, Trovão Nídia S, Isbell Molly, Goel Chirag, Heck Benjamin F, Archer Tenley C, Cardinal Klint D, Naik Neil B, Dutta Som, Daniel Ahleah Rohr, Beheshti Afshin
Signature Science LLC, Austin, TX, 78759, USA.
COVID-19 International Research Team.
medRxiv. 2022 Mar 16:2022.03.02.22271806. doi: 10.1101/2022.03.02.22271806.
The COVID-19 Exposure Assessment Tool (CEAT) allows users to compare respiratory relative risk to SARS-CoV-2 for various scenarios, providing understanding of how combinations of protective measures affect exposure, dose, and risk. CEAT incorporates mechanistic, stochastic and epidemiological factors including the: 1) emission rate of virus, 2) viral aerosol degradation and removal, 3) duration of activity/exposure, 4) inhalation rates, 5) ventilation rates (indoors/outdoors), 6) volume of indoor space, 7) filtration, 8) mask use and effectiveness, 9) distance between people, 10) group size, 11) current infection rates by variant, 12) prevalence of infection and immunity in the community, 13) vaccination rates of the community, and 14) implementation of COVID-19 testing procedures. Demonstration of CEAT, from published studies of COVID-19 transmission events, shows the model accurately predicts transmission. We also show how health and safety professionals at NASA Ames Research Center used CEAT to manage potential risks posed by SARS-CoV-2 exposures. Given its accuracy and flexibility, the wide use of CEAT will have a long lasting beneficial impact in managing both the current COVID-19 pandemic as well as a variety of other scenarios.
新冠病毒暴露评估工具(CEAT)允许用户比较各种场景下感染新冠病毒的呼吸相对风险,有助于理解防护措施的组合如何影响暴露、剂量和风险。CEAT纳入了机械、随机和流行病学因素,包括:1)病毒排放率,2)病毒气溶胶降解和清除,3)活动/暴露持续时间,4)吸入率,5)通风率(室内/室外),6)室内空间体积,7)过滤,8)口罩使用及有效性,9)人与人之间的距离,10)群体规模,11)当前变异毒株的感染率,12)社区感染和免疫流行率,13)社区疫苗接种率,以及14)新冠病毒检测程序的实施情况。从已发表的新冠病毒传播事件研究中对CEAT的演示表明,该模型能够准确预测传播情况。我们还展示了美国国家航空航天局艾姆斯研究中心的健康与安全专业人员如何使用CEAT来管理新冠病毒暴露带来的潜在风险。鉴于其准确性和灵活性,CEAT的广泛应用将对当前新冠疫情以及各种其他场景的管理产生长期有益影响。