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Trading contact tracing efficiency for finding patient zero.
Waniek, Marcin; Holme, Petter; Farrahi, Katayoun; Emonet, Rémi; Cebrian, Manuel; Rahwan, Talal.
  • Waniek M; Computer Science, Science Division, New York University Abu Dhabi, Abu Dhabi, UAE.
  • Holme P; Aalto University, Espoo, Finland.
  • Farrahi K; Kobe University, Kobe, Japan.
  • Emonet R; University of Southampton, Southampton, UK.
  • Cebrian M; CNRS, Laboratoire Hubert Curien UMR 5516, UJM-Saint-Etienne, Université de Lyon, Saint-Étienne, France.
  • Rahwan T; Center for Humans and Machines, Max Planck Institute for Human Development, Berlin, Germany. manuel.cebrian@uc3m.es.
Sci Rep ; 12(1): 22582, 2022 12 30.
Article in English | MEDLINE | ID: covidwho-2186054
ABSTRACT
As the COVID-19 pandemic has demonstrated, identifying the origin of a pandemic remains a challenging task. The search for patient zero may benefit from the widely-used and well-established toolkit of contact tracing methods, although this possibility has not been explored to date. We fill this gap by investigating the prospect of performing the source detection task as part of the contact tracing process, i.e., the possibility of tuning the parameters of the process in order to pinpoint the origin of the infection. To this end, we perform simulations on temporal networks using a recent diffusion model that recreates the dynamics of the COVID-19 pandemic. We find that increasing the budget for contact tracing beyond a certain threshold can significantly improve the identification of infected individuals but has diminishing returns in terms of source detection. Moreover, disease variants of higher infectivity make it easier to find the source but harder to identify infected individuals. Finally, we unravel a seemingly-intrinsic trade-off between the use of contact tracing to either identify infected nodes or detect the source of infection. This trade-off suggests that focusing on the identification of patient zero may come at the expense of identifying infected individuals.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Observational study Topics: Variants Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Observational study Topics: Variants Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article