Clinical and Economic Effects of Widespread Rapid Testing to Decrease SARS-CoV-2 Transmission

Abstract

Background: The value of frequent, rapid testing to reduce community transmission of SARS-CoV-2 is poorly understood.

Objective: To define performance standards and predict the clinical, epidemiologic, and economic outcomes of nationwide, home-based antigen testing.

Design: A simple compartmental epidemic model that estimated viral transmission, portrayed disease progression, and forecast resource use, with and without testing.

Data sources: Parameter values and ranges as informed by Centers for Disease Control and Prevention guidance and published literature.

Target population: U.S. population.

Time horizon: 60 days.

Perspective: Societal; costs included testing, inpatient care, and lost workdays.

Intervention: Home-based SARS-CoV-2 antigen testing.

Outcome measures: Cumulative infections and deaths, number of persons isolated and hospitalized, and total costs.

Results of base-case analysis: Without a testing intervention, the model anticipates 11.6 million infections, 119 000 deaths, and $10.1 billion in costs ($6.5 billion in inpatient care and $3.5 billion in lost productivity) over a 60-day horizon. Weekly availability of testing would avert 2.8 million infections and 15 700 deaths, increasing costs by $22.3 billion. Lower inpatient outlays ($5.9 billion) would partially offset additional testing expenditures ($12.5 billion) and workdays lost ($14.0 billion), yielding incremental cost-effectiveness ratios of $7890 per infection averted and $1 430 000 per death averted.

Results of sensitivity analysis: Outcome estimates vary widely under different behavioral assumptions and testing frequencies. However, key findings persist across all scenarios, with large reductions in infections, mortality, and hospitalizations. Costs per death averted are roughly an order of magnitude lower than commonly accepted willingness-to-pay values per statistical life saved ($5 to $17 million).

Limitations: Analysis was restricted to at-home testing. There are uncertainties concerning test performance.

Conclusion: High-frequency home testing for SARS-CoV-2 with an inexpensive, imperfect test could contribute to pandemic control at justifiable cost and warrants consideration as part of a national containment strategy.

Primary funding source: National Institutes of Health.

Figure 1.. Daily infections as a function of behavioral scenarios.

This figure reports the daily number of infections (vertical axis) under three behavioral scenarios with home-based testing and no home-based testing over a 60-day horizon (horizontal axis). The colored lines denote different testing and behavioral assumptions: no testing (blue); best case (orange); base case (gray); and worst case (yellow).

Figure 2.. Cumulative infections as a function of testing frequency.

In this figure, the number of cumulative infections (vertical axis, in millions) is reported for a range of home-based testing frequencies (horizontal axis, ranging from 1 to 15 days between tests). The colored lines denote different testing and behavioral assumptions: no testing (blue); best case (orange); base case (gray); and worst case (yellow).