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Strategic testing approaches for targeted disease monitoring can be used to inform pandemic decision-making
Authors:James D. Nichols,Tiffany L. Bogich,Emily Howerton,Ottar N. Bjø  rnstad,Rebecca K. Borchering,Matthew Ferrari,Murali Haran,Christopher Jewell,Kim M. Pepin,William J. M. Probert,Juliet R. C. Pulliam,Michael C. Runge,Michael Tildesley,Cé  cile Viboud,Katriona Shea
Abstract:More than 1.6 million Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) tests were administered daily in the United States at the peak of the epidemic, with a significant focus on individual treatment. Here, we show that objective-driven, strategic sampling designs and analyses can maximize information gain at the population level, which is necessary to increase situational awareness and predict, prepare for, and respond to a pandemic, while also continuing to inform individual treatment. By focusing on specific objectives such as individual treatment or disease prediction and control (e.g., via the collection of population-level statistics to inform lockdown measures or vaccine rollout) and drawing from the literature on capture–recapture methods to deal with nonrandom sampling and testing errors, we illustrate how public health objectives can be achieved even with limited test availability when testing programs are designed a priori to meet those objectives.

COVID-19 testing programs are very important to help control the pandemic. In this Essay, the authors show that objective-driven, strategic sampling designs and analytics can be used to maximize the information gained by COVID-19 testing programs and improve population-level decisions, while maintaining the value of these programs for patient-level management.
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