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The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2.
Domenech de Cellès, Matthieu; Goult, Elizabeth; Casalegno, Jean-Sebastien; Kramer, Sarah C.
Affiliation
  • Domenech de Cellès M; Max Planck Institute for Infection Biology, Infectious Disease Epidemiology group, Charitéplatz 1, Campus Charité Mitte, 10117 Berlin, Germany.
  • Goult E; Max Planck Institute for Infection Biology, Infectious Disease Epidemiology group, Charitéplatz 1, Campus Charité Mitte, 10117 Berlin, Germany.
  • Casalegno JS; Laboratoire de Virologie des HCL, IAI, CNR des virus à transmission respiratoire (dont la grippe) Hôpital de la Croix-Rousse F-69317, Lyon cedex 04, France.
  • Kramer SC; Virpath, Centre International de Recherche en Infectiologie (CIRI), Université de Lyon Inserm U1111, CNRS UMR 5308, ENS de Lyon, UCBL F-69372, Lyon cedex 08, France.
Proc Biol Sci ; 289(1966): 20212358, 2022 01 12.
Article in En | MEDLINE | ID: mdl-35016540
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Influenza, Human / Coinfection / COVID-19 Type of study: Diagnostic_studies / Prevalence_studies / Risk_factors_studies Limits: Humans Language: En Journal: Proc Biol Sci Journal subject: BIOLOGIA Year: 2022 Document type: Article Affiliation country: Germany
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Influenza, Human / Coinfection / COVID-19 Type of study: Diagnostic_studies / Prevalence_studies / Risk_factors_studies Limits: Humans Language: En Journal: Proc Biol Sci Journal subject: BIOLOGIA Year: 2022 Document type: Article Affiliation country: Germany