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Kemeny-based testing for COVID-19.
Yilmaz, Serife; Dudkina, Ekaterina; Bin, Michelangelo; Crisostomi, Emanuele; Ferraro, Pietro; Murray-Smith, Roderick; Parisini, Thomas; Stone, Lewi; Shorten, Robert.
  • Yilmaz S; Dyson School of Design Engineering, Imperial College London, London, United Kingdom.
  • Dudkina E; Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, Pisa, Italy.
  • Bin M; Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom.
  • Crisostomi E; Department of Energy, Systems, Territory and Constructions Engineering, University of Pisa, Pisa, Italy.
  • Ferraro P; Dyson School of Design Engineering, Imperial College London, London, United Kingdom.
  • Murray-Smith R; School of Computing Science, University of Glasgow, Glasgow, Scotland.
  • Parisini T; Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom.
  • Stone L; Department of Engineering and Architecture, University of Trieste, Trieste, Italy.
  • Shorten R; KIOS Research and Innovation Center of Excellence, University of Cyprus, Nicosia, Cyprus.
PLoS One ; 15(11): e0242401, 2020.
Article in English | MEDLINE | ID: covidwho-937230
ABSTRACT
Testing, tracking and tracing abilities have been identified as pivotal in helping countries to safely reopen activities after the first wave of the COVID-19 virus. Contact tracing apps give the unprecedented possibility to reconstruct graphs of daily contacts, so the question is who should be tested? As human contact networks are known to exhibit community structure, in this paper we show that the Kemeny constant of a graph can be used to identify and analyze bridges between communities in a graph. Our 'Kemeny indicator' is the value of the Kemeny constant in the new graph that is obtained when a node is removed from the original graph. We show that testing individuals who are associated with large values of the Kemeny indicator can help in efficiently intercepting new virus outbreaks, when they are still in their early stage. Extensive simulations provide promising results in early identification and in blocking the possible 'super-spreaders' links that transmit disease between different communities.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Contact Tracing / Coronavirus Infections Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pone.0242401

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Contact Tracing / Coronavirus Infections Type of study: Diagnostic study / Prognostic study Limits: Humans Language: English Journal: PLoS One Journal subject: Science / Medicine Year: 2020 Document Type: Article Affiliation country: Journal.pone.0242401