University of California, Berkeley
Berkeley, CA 94705
Institutional Affiliation: University of California, Berkeley
NBER Working Papers and Publications
|July 2020||Group Testing in a Pandemic: The Role of Frequent Testing, Correlated Risk, and Machine Learning|
with , , : w27457
Group testing increases efficiency by pooling patient specimens and clearing the entire group with one negative test. Optimal grouping strategy is well studied in one-off testing scenarios with reasonably well-known prevalence rates and no correlations in risk. We discuss how the strategy changes in a pandemic environment with repeated testing, rapid local infection spread, and highly uncertain risk. First, repeated testing mechanically lowers prevalence at the time of the next test. This increases testing efficiency, such that increasing frequency by x times only increases expected tests by around √x rather than x. However, this calculation omits a further benefit of frequent testing: infected people are quickly removed from the population, which lowers prevalence and generates further eﬃ...