COVID-19 testing protocols to guide duration of isolation: a cost-effectiveness analysis

BMC Public Health. 2023 May 11;23(1):864. doi: 10.1186/s12889-023-15762-0.

Abstract

Background: The Omicron variant of SARS-CoV-2 led to a steep rise in transmissions, and emerging variants continue to influence case rates across the US. As public tolerance for isolation abated, CDC guidance on duration of at-home isolation of COVID-19 cases was shortened to five days if no symptoms, with no laboratory test requirement, despite more cautious approaches advocated by other federal experts.

Methods: We conducted a decision tree analysis of alternative protocols for ending COVID-19 isolation, estimating net costs (direct and productivity), secondary infections, and incremental cost-effectiveness ratios. Sensitivity analyses assessed the impact of input uncertainty.

Results: Per 100 individuals, five-day isolation had 23 predicted secondary infections and a net cost of $33,000. Symptom check on day five (CDC guidance) yielded a 23% decrease in secondary infections (to 17.8), with a net cost of $45,000. Antigen testing on day six yielded 2.9 secondary infections and $63,000 in net costs. This protocol, compared to the next best protocol of antigen testing on day five of a maximum eight-day isolation, cost an additional $1,300 per secondary infection averted. Antigen or polymerase chain reaction testing on day five were dominated (more expensive and less effective) versus antigen testing on day six. Results were qualitatively robust to uncertainty in key inputs.

Conclusions: A six-day isolation with antigen testing to confirm the absence of contagious virus appears the most effective and cost-effective de-isolation protocol to shorten at-home isolation of individuals with COVID-19.

Keywords: Antigen test; COVID-19; Cost-effectiveness; Isolation; SARS-CoV-2.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • COVID-19 Testing
  • COVID-19* / diagnosis
  • Coinfection*
  • Cost-Benefit Analysis
  • Cost-Effectiveness Analysis
  • Humans
  • SARS-CoV-2

Supplementary concepts

  • SARS-CoV-2 variants