Background COVID-19 test sensitivity and specificity have been widely examined and discussed, yet optimal use of these tests will depend on the goals of testing, the population or setting, and the anticipated underlying disease prevalence. We model various combinations of key variables to identify and compare a range of effective and practical surveillance strategies for schools and businesses. Methods We coupled a simulated data set incorporating actual community prevalence and test performance characteristics to a susceptible, infectious, removed (SIR) compartmental model, modeling the impact of base and tunable variables including test sensitivity, testing frequency, results lag, sample pooling, disease prevalence, externally-acquired infections, symptom checking, and test cost on outcomes including case reduction and false positives. Findings Increasing testing frequency was associated with a non-linear positive effect on cases averted over 100 days. While precise reductions in cumulative number of infections depended on community disease prevalence, testing every 3 days versus every 14 days (even with a lower sensitivity test) reduces the disease burden substantially. Pooling provided cost savings and made a high-frequency approach practical; one high-performing strategy, testing every 3 days, yielded per person per day costs as low as $1.32. Interpretation A range of practically viable testing strategies emerged for schools and businesses. Key characteristics of these strategies include high frequency testing with a moderate or high sensitivity test and minimal results delay. Sample pooling allowed for operational efficiency and cost savings with minimal loss of model performance.
【초록키워드】 Infection, Symptom, outcome, underlying disease, Prevalence, sensitivity, Schools, infections, Disease prevalence, Characteristics, Surveillance, Sensitivity and specificity, Community, School, compartmental model, pooling, moderate, Combination, Frequency, False positives, COVID-19 test, Efficiency, data set, reduction, base, finding, cumulative, positive, while, variable, approach, susceptible, effective, Sensitivity test, identify, Sample, examined, include, the disease, provided, per day, reductions in, reduce, Increasing, anticipated, 【제목키워드】 COVID-19 testing, School, Frequency, balancing, identifying,