INTRODUCTION: Pooled testing is a potentially efficient alternative strategy for COVID‐19 testing in congregate settings. We evaluated the utility and cost‐savings of pooled testing based on imperfect test performance and potential dilution effect due to pooling and created a practical calculator for online use. METHODS: We developed a 2‐stage pooled testing model accounting for dilution. The model was applied to hypothetical scenarios of 100 specimens collected during a one‐week time‐horizon cycle for varying levels of COVID‐19 prevalence and test sensitivity and specificity, and to 338 skilled nursing facilities (SNFs) in Los Angeles County (Los Angeles) (data collected and analyzed in 2020). RESULTS: Optimal pool sizes ranged from 1 to 12 in instances where there is a least one case in the batch of specimens. 40% of Los Angeles SNFs had more than one case triggering a response‐testing strategy. The median number (minimum; maximum) of tests performed per facility were 56 (14; 356) for a pool size of 4, 64 (13; 429) for a pool size of 10, and 52 (11; 352) for an optimal pool size strategy among response‐testing facilities. The median costs of tests in response‐testing facilities were $8250 ($1100; $46,100), $6000 ($1340; $37,700), $6820 ($1260; $43,540), and $5960 ($1100; $37,380) when adopting individual testing, a pooled testing strategy using pool sizes of 4, 10, and optimal pool size, respectively. CONCLUSIONS: Pooled testing is an efficient strategy for congregate settings with a low prevalence of COVID‐19. Dilution as a result of pooling can lead to erroneous false‐negative results.
Optimal uses of pooled testing for COVID‐19 incorporating imperfect test performance and pool dilution effect: An application to congregate settings in Los Angeles County