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

Authors
  • Nichols, James D1
  • Bogich, Tiffany L2, 3
  • Howerton, Emily2, 3
  • Bjørnstad, Ottar N2, 4
  • Borchering, Rebecca K2, 3
  • Ferrari, Matthew2, 3
  • Haran, Murali5
  • Jewell, Christopher6
  • Pepin, Kim M7
  • Probert, William J M8
  • Pulliam, Juliet R C9
  • Runge, Michael C1
  • Tildesley, Michael10
  • Viboud, Cécile11
  • Shea, Katriona2, 3
  • 1 U.S. Geological Survey, Eastern Ecological Science Center at the Patuxent Research Refuge, Laurel, Maryland, United States of America. , (United States)
  • 2 Department of Biology, The Pennsylvania State University, University Park, Pennsylvania, United States of America. , (United States)
  • 3 The Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, Pennsylvania, United States of America. , (United States)
  • 4 Department of Entomology, The Pennsylvania State University, University Park, Pennsylvania, United States of America. , (United States)
  • 5 Department of Statistics, The Pennsylvania State University, University Park, Pennsylvania, United States of America. , (United States)
  • 6 Lancaster Medical School, Lancaster University, Lancaster, United Kingdom. , (United Kingdom)
  • 7 National Wildlife Research Center, United States Department of Agriculture, Animal and Plant Health Inspection Service, Wildlife Services, Fort Collins, Colorado, United States of America. , (United States)
  • 8 Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom. , (United Kingdom)
  • 9 South African DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Cape Town, Western Cape, South Africa. , (South Africa)
  • 10 Zeeman Institute: Systems Biology and Infectious Disease Epidemiology Research (SBIDER), Mathematics Institute and School of Life Sciences, University of Warwick, Coventry, United Kingdom. , (United Kingdom)
  • 11 Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America. , (United States)
Type
Published Article
Journal
PLoS Biology
Publisher
Public Library of Science
Publication Date
Jun 17, 2021
Volume
19
Issue
6
Identifiers
DOI: 10.1371/journal.pbio.3001307
PMID: 34138840
Source
Medline
Language
English
License
Unknown

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.

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