Model for evaluating cost-effectiveness of surveillance testing for SARS-CoV2
Abstract
Testing people without symptoms for SARS-CoV-2 followed by isolation of those who test positive could mitigate the covid-19 epidemic pending arrival of an effective vaccine. Key questions for such programs are who should be tested, how often, and when should such testing stop. Answers to these questions depend on test and population characteristics. A cost-effectiveness model that provides answers depending on user-adjustable parameter values is described. Key parameters are the value ascribed to preventing a death and the reproduction number (roughly, rate of spread) at the time surveillance testing is initiated. For current rates of spread, cost-effectiveness usually requires a value per life saved greater than $100,000 and depends critically on the extent and frequency of testing.
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