Modeling Effectiveness of Testing Strategies to Prevent Coronavirus Disease 2019 (COVID-19) in Nursing Homes-United States, 2020

Abstract

Background: Identifying asymptomatic individuals early through serial testing is recommended to control coronavirus disease 2019 (COVID-19) in nursing homes, both in response to an outbreak ("outbreak testing" of residents and healthcare personnel) and in facilities without outbreaks ("nonoutbreak testing" of healthcare personnel). The effectiveness of outbreak testing and isolation with or without nonoutbreak testing was evaluated.

Methods: Using published SARS-CoV-2 transmission parameters, the fraction of SARS-CoV-2 transmissions prevented through serial testing (weekly, every 3 days, or daily) and isolation of asymptomatic persons compared with symptom-based testing and isolation was evaluated through mathematical modeling using a Reed-Frost model to estimate the percentage of cases prevented (ie, "effectiveness") through either outbreak testing alone or outbreak plus nonoutbreak testing. The potential effect of simultaneous decreases (by 10%) in the effectiveness of isolating infected individuals when instituting testing strategies was also evaluated.

Results: Modeling suggests that outbreak testing could prevent 54% (weekly testing with 48-hour test turnaround) to 92% (daily testing with immediate results and 50% relative sensitivity) of SARS-CoV-2 infections. Adding nonoutbreak testing could prevent up to an additional 8% of SARS-CoV-2 infections (depending on test frequency and turnaround time). However, added benefits of nonoutbreak testing were mostly negated if accompanied by decreases in infection control practice.

Conclusions: When combined with high-quality infection control practices, outbreak testing could be an effective approach to preventing COVID-19 in nursing homes, particularly if optimized through increased test frequency and use of tests with rapid turnaround.

Keywords: COVID-19; infection control; nursing homes; public health; testing.