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Surveillance testing of SARS-CoV-2
Daniel B Larremore; Bryan Wilder; Evan Lester; Soraya Shehata; James M Burke; James A Hay; Milind Tambe; Michael J Mina; Roy Parker.
Affiliation
  • Daniel B Larremore; University of Colorado Boulder
  • Bryan Wilder; Harvard University
  • Evan Lester; University of Colorado Boulder
  • Soraya Shehata; University of Colorado Boulder
  • James M Burke; University of Colorado Boulder
  • James A Hay; Harvard T H Chan School of Public Health
  • Milind Tambe; Harvard University
  • Michael J Mina; Harvard School of Public Health
  • Roy Parker; University of Colorado Boulder
Preprint in English | medRxiv | ID: ppmedrxiv-20136309
ABSTRACT
The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with pre-symptomatic, symptomatic, and asymptomatic infections, the re-opening of societies and the control of virus spread will be facilitated by robust surveillance, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are usually too low to detect, followed by an exponential viral growth, leading to a peak viral load and infectiousness, and ending with declining viral levels and clearance. Given the pattern of viral load kinetics, we model surveillance effectiveness considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective surveillance depends largely on frequency of testing and the speed of reporting, and is only marginally improved by high test sensitivity. We therefore conclude that surveillance should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Diagnostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Diagnostic study Language: English Year: 2020 Document type: Preprint
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