4.6 Article

Strategic testing approaches for targeted disease monitoring can be used to inform pandemic decision-making

期刊

PLOS BIOLOGY
卷 19, 期 6, 页码 -

出版社

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pbio.3001307

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资金

  1. National Science Foundation (NSF) Ecology and Evolution of Infectious Diseases (EEID) program award Division of Environmental Biology (DEB) [1911962]
  2. Biotechnology and Biological Sciences Research Council (BBSRC) [BB/T004312/1]
  3. National Science Foundation (NSF) Division of Environmental Biology (DEB) COVID-19 RAPID [2028301, 2037885]
  4. Huck Institutes for the Life Sciences at The Pennsylvania State University
  5. National Institutes of Health
  6. U.S. Department of Agriculture, Animal and Plant Health Inspection Service
  7. U.S.Geological Survey
  8. Li Ka Shing Foundation
  9. Department of Science and Innovation
  10. National Research Foundation (NRF)
  11. BBSRC [BB/T004312/1] Funding Source: UKRI
  12. Direct For Biological Sciences
  13. Division Of Environmental Biology [1911962, 2037885] Funding Source: National Science Foundation
  14. Direct For Biological Sciences
  15. Division Of Environmental Biology [2028301] Funding Source: National Science Foundation

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By focusing on specific objectives such as individual treatment or disease prediction and control, and drawing from capture-recapture methods to deal with nonrandom sampling and testing errors, public health objectives can be achieved even with limited test availability when testing programs are designed a priori to meet those objectives.
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.

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