Identifying optimal COVID-19 testing strategies for schools and businesses: Balancing testing frequency, individual test technology, and cost

PLoS One. 2021 Mar 25;16(3):e0248783. doi: 10.1371/journal.pone.0248783. eCollection 2021.


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.

MeSH terms

  • COVID-19 / diagnosis*
  • COVID-19 / virology
  • COVID-19 Testing / economics*
  • Cost-Benefit Analysis
  • Delayed Diagnosis
  • Humans
  • Mass Screening / economics
  • Prevalence
  • RNA, Viral / analysis
  • RNA, Viral / metabolism
  • SARS-CoV-2 / genetics
  • SARS-CoV-2 / isolation & purification
  • Schools
  • Sensitivity and Specificity


  • RNA, Viral

Grant support

Authors [GL, NS, CK, DG, EB] are employees of UnitedHealth Group. Author [DG] also serves as the Chief of Infectious Disease for ProHealth NY, part of Optum. These funders provided support in the form of salaries for authors [GL, NS, CK, DG, EB], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.