Clinical Impact, Costs, and Cost-effectiveness of Expanded Severe Acute Respiratory Syndrome Coronavirus 2 Testing in Massachusetts

Abstract

BACKGROUND: We projected the clinical and economic impact of alternative testing strategies on coronavirus disease 2019 (COVID-19) incidence and mortality in Massachusetts using a microsimulation model. METHODS: We compared 4 testing strategies: (1) hospitalized: polymerase chain reaction (PCR) testing only for patients with severe/critical symptoms warranting hospitalization; (2) symptomatic: PCR for any COVID-19-consistent symptoms, with self-isolation if positive; (3) symptomatic + asymptomatic once: symptomatic and 1-time PCR for the entire population; and (4) symptomatic + asymptomatic monthly: symptomatic with monthly retesting for the entire population. We examined effective reproduction numbers (Re = 0.9-2.0) at which policy conclusions would change. We assumed homogeneous mixing among the Massachusetts population (excluding those residing in long-term care facilities). We used published data on disease progression and mortality, transmission, PCR sensitivity/specificity (70%/100%), and costs. Model-projected outcomes included infections, deaths, tests performed, hospital-days, and costs over 180 days, as well as incremental cost-effectiveness ratios (ICERs, $/quality-adjusted life-year [QALY]). RESULTS: At Re = 0.9, symptomatic + asymptomatic monthly vs hospitalized resulted in a 64% reduction in infections and a 46% reduction in deaths, but required >66-fold more tests/day with 5-fold higher costs. Symptomatic + asymptomatic monthly had an ICER <$100 000/QALY only when Re ≥1.6; when test cost was ≤$3, every 14-day testing was cost-effective at all Re examined. CONCLUSIONS: Testing people with any COVID-19-consistent symptoms would be cost-saving compared to testing only those whose symptoms warrant hospital care. Expanding PCR testing to asymptomatic people would decrease infections, deaths, and hospitalizations. Despite modest sensitivity, low-cost, repeat screening of the entire population could be cost-effective in all epidemic settings.