Adaptive targeted infectious disease testing

Abstract

We show how to efficiently use costly testing resources in an epidemic, when testing outcomes can be used to make quarantine decisions. If the costs 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 trade-off: 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.

The economics of the COVID-19 pandemic: an assessment

“…Another important intervention is an effective testing strategy: testing individuals for the infection and isolating those who test positive. However, such a strategy must also be workable: countries have finite testing resources and testing capacity can be difficult or impossible to ramp up ( Kasy and Teytelboym, 2020 , this issue). In Cleevely et al (2020) , the authors question the viability of universal random testing, a strategy in which a random fraction of the entire population would be selected each day for testing.…”

“…The authors show that this approach dramatically reduces the required testing resources. Following on from this, Kasy and Teytelboym (2020) examine the trade-offs involved in allocating testing resources to some individuals but not others; the so-called ‘shadow cost’ of a test. They explore the difficult dynamic balancing that policy-makers face, between using tests to protect people today, versus using tests to identify the prevalence of the disease in the population to benefit people in the future.…”

Testing, Voluntary Social Distancing and the Spread of an Infection

“…More closely related are Drakopoulos and Randhawa [2020] and Ely et al [2020] who both study optimal testing policy when tests are inaccurate (and Kasy et al [2020] who investigate the implications of false quarantine). None of these papers analyze the impact of testing on voluntary social distancing and behavior.…”

Test Sensitivity for Infection versus Infectiousness of SARS-CoV-2

“…Notably, Galeotti et al (2020) do provide an exposition of taking an information theoretic approach to the value of testing but do not raise issues of infectiousness (as opposed to infection). Other work that examines the informational value of testing examines how to allocate costly or scarce tasks on the basis of available data or observations that underpins pre-test probabilities (see Ely et al (2020) and Kasy and Teytelboym (2020)). Bergstrom et al (2020) examine the optimal frequency of testing to reduce contagion.…”