Department of Neurosciences, Faculty of Medicine, University of Geneva, Geneva, Switzerland.
Academics for the Future of Science Inc., Cambridge, MA, USA.
Sci Rep. 2023 Aug 11;13(1):13056. doi: 10.1038/s41598-023-40338-8.
The Coronavirus disease 2019 (COVID-19) pandemic, caused by the virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has impacted over 200 countries leading to hospitalizations and deaths of millions of people. Public health interventions, such as risk estimators, can reduce the spread of pandemics and epidemics through influencing behavior, which impacts risk of exposure and infection. Current publicly available COVID-19 risk estimation tools have had variable effectiveness during the pandemic due to their dependency on rapidly evolving factors such as community transmission levels and variants. There has also been confusion surrounding certain personal protective strategies such as risk reduction by mask-wearing and vaccination. In order to create a simple easy-to-use tool for estimating different individual risks associated with carrying out daily-life activity, we developed COVID-19 Activity Risk Calculator (CovARC). CovARC is a gamified public health intervention as users can "play with" how different risks associated with COVID-19 can change depending on several different factors when carrying out routine daily activities. Empowering the public to make informed, data-driven decisions about safely engaging in activities may help to reduce COVID-19 levels in the community. In this study, we demonstrate a streamlined, scalable and accurate COVID-19 risk calculation system. Our study also demonstrates the quantitative impact of vaccination and mask-wearing during periods of high case counts. Validation of this impact could inform and support policy decisions regarding case thresholds for mask mandates, and other public health interventions.
新型冠状病毒病 2019（COVID-19）大流行是由病毒严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2）引起的，已经影响了 200 多个国家，导致数百万人住院和死亡。公共卫生干预措施，如风险评估器，可以通过影响行为来减少大流行和传染病的传播，从而影响暴露和感染的风险。由于依赖于社区传播水平和变体等快速演变的因素，当前公共可用的 COVID-19 风险估计工具在大流行期间的效果各不相同。围绕某些个人防护策略也存在困惑，例如戴口罩和接种疫苗可降低风险。为了创建一个简单易用的工具来估计与进行日常活动相关的不同个体风险，我们开发了 COVID-19 活动风险计算器（CovARC）。CovARC 是一种游戏化的公共卫生干预措施，因为用户可以在进行日常活动时“玩”不同的 COVID-19 风险如何因几种不同因素而变化。让公众能够就安全参与活动做出明智的、基于数据的决策，可能有助于降低社区中的 COVID-19 水平。在这项研究中，我们展示了一个简化、可扩展和准确的 COVID-19 风险计算系统。我们的研究还表明了在高病例数期间接种疫苗和戴口罩的定量影响。这种影响的验证可以为有关口罩强制令和其他公共卫生干预措施的病例阈值的政策决策提供信息和支持。
