Adaptive Targeted Infectious Disease Testing

Friday, 22 May 2020

COVID-19 research titled 'Adaptive Targeted Infectious Disease Testing'.

Alexander Teytelboym and Maximilian Kasy have co-authored this research paper.

We show how to efficiently use costly testing resources in an epidemic, when testing outcomes can be used to make quarantine decisions. If the cost of false quarantine and false release exceed the cost of testing, the optimal myopic testing policy targets individuals with an intermediate likelihood of being infected. A high cost of false release means that testing is optimal for individuals with a low probability of infection, and a high cost of false quarantine means that testing is optimal for individuals with a high probability of infection. If individuals arrive over time, the policy-maker faces a dynamic tradeoff: using tests for individuals for whom testing yields the maximum immediate benefit vs. spreading out testing capacity across the population to learn prevalence rates thereby benefiting later individuals. We describe a simple policy that is nearly optimal from a dynamic perspective. We briefly discuss practical aspects of implementing our proposed policy, including imperfect testing technology, appropriate choice of prior, and non-stationarity of the prevalence rate.

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