Modeling Impacts of COVID-19 Testing

Headshot of Milton Weinstein.

CHDS’s Milton Weinstein and colleagues developed a dynamic state-transition microsimulation model to compare the clinical impact, costs, and cost-effectiveness of different COVID-19 testing strategies. They modeled four testing strategies of decreasing stringency ranging from testing only those with severe symptoms to repeat testing of people who were asymptomatic, projecting clinical outcomes and COVID-19 related resource utilization. They found that testing people with any COVID-19 consistent symptoms would be cost-saving compared to testing only those requiring hospitalization. Expanding testing to asymptomatic people would decrease infections, hospitalizations and deaths, and would be cost-effective when the pandemic is surging, even when test costs are high; when test cost are low, repeat testing of the entire population would decrease infections and deaths and be cost-effective even when the epidemic is slowing.

Learn more: Read the Press Release
Learn more: Read the full article, Clinical Impact, costs, and Cost-Effectiveness of Expanded SARS-CoV-2 Testing in Massachusetts
Learn more: Read about Models for Health Decision Science

Related news: Forecasting COVID-19 with Nicholas Reich
Related news: Uncertainty in Valuing COVID-19 Risks