Background: In-person interaction offers invaluable benefits to people. To guarantee safe in-person activities during a COVID-19 outbreak, effective identification of infectious individuals is essential. In this study, we aim to analyze the impact of screening with antigen tests in schools and workplaces on identifying COVID-19 infections.
Methods: We assess the effectiveness of various screening test strategies with antigen tests in schools and workplaces through quantitative simulations. The primary outcome of our analyses is the proportion of infected individuals identified. The transmission process at the population level is modeled using a deterministic compartmental model. Infected individuals are identified through screening tests or symptom development. The time-varying sensitivity of antigen tests and infectiousness is determined by a viral dynamics model. Screening test strategies are characterized by the screening schedule, sensitivity of antigen tests, screening duration, timing of screening initiation, and available tests per person.
Results: Here, we show that early and frequent screening is the key to maximizing the effectiveness of the screening program. For example, 44.5% (95% CI: 40.8-47.5) of infected individuals are identified by daily testing, whereas it is only 33.7% (95% CI: 30.5-37.3) when testing is performed at the end of the program duration. If high sensitivity antigen tests (Detection limit: copies/mL) are deployed, it reaches 69.3% (95% CI: 66.5-72.5).
Conclusions: High sensitivity antigen tests, high frequency screening tests, and immediate initiation of screening tests are important to safely restart educational and economic activities in-person. Our computational framework is useful for assessing screening programs by incorporating situation-specific factors.
During the COVID-19 pandemic, people actively sought safer ways to resume in-person educational and economic activities while keeping the risk of infection low. For this, it may have been key to implement regular screening tests for individuals in places like schools and workplaces, since these tests can identify positive cases and help prevent the spread of the virus within these settings. Here, we introduce a computer model that evaluates the effectiveness of different screening programs in those facilities. The model involves how the virus spreads between people and within the human body, considering how the accuracy of tests can change as the infection progresses. The study examines various screening strategies. The simulations demonstrate that using highly sensitive tests, conducting frequent screenings, and starting the tests immediately are crucial for effectively identifying positive cases. Our approach can be flexibly expanded in the future to consider various factors like vaccination and new variants.
© 2025. The Author(s).