COVID-19 Activity Risk Calculator as a Gamified Public Health Intervention Tool

• Main Authors: Natraj, Shreyasvi, Bhide, Malhar, Yap, Nathan, Liu, Meng, Seth, Agrima, Berman, Jonathan, Glorioso, Christin
• Format: Journal Article
• Language: English
• Published: 05.12.2022
• Subjects: Computer Science - Computers and Society; Computer Science - Information Retrieval; Computer Science - Numerical Analysis; Mathematics - Numerical Analysis; Statistics - Methodology
• DOI: 10.48550/arxiv.2212.05035

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.