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Beyond scale-free networks: integrating multilayer social networks with molecular clusters in the local spread of COVID-19.
Fujimoto, Kayo; Kuo, Jacky; Stott, Guppy; Lewis, Ryan; Chan, Hei Kit; Lyu, Leke; Veytsel, Gabriella; Carr, Michelle; Broussard, Tristan; Short, Kirstin; Brown, Pamela; Sealy, Roger; Brown, Armand; Bahl, Justin.
Afiliación
  • Fujimoto K; School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA. Kayo.Fujimoto@uth.tmc.edu.
  • Kuo J; School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA.
  • Stott G; Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA.
  • Lewis R; School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA.
  • Chan HK; School of Public Health, University of Texas Health Science Center at Houston, 7000 Fannin Street, UCT 2514, Houston, TX, 77030, USA.
  • Lyu L; Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA.
  • Veytsel G; Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA.
  • Carr M; City of Houston Health Department, Houston, TX, USA.
  • Broussard T; City of Houston Health Department, Houston, TX, USA.
  • Short K; City of Houston Health Department, Houston, TX, USA.
  • Brown P; City of Houston Health Department, Houston, TX, USA.
  • Sealy R; City of Houston Health Department, Houston, TX, USA.
  • Brown A; City of Houston Health Department, Houston, TX, USA.
  • Bahl J; Institute of Bioinformatics, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA. Justin.Bahl@uga.edu.
Sci Rep ; 13(1): 21861, 2023 12 09.
Article en En | MEDLINE | ID: mdl-38071385
This study evaluates the scale-free network assumption commonly used in COVID-19 epidemiology, using empirical social network data from SARS-CoV-2 Delta variant molecular local clusters in Houston, Texas. We constructed genome-informed social networks from contact and co-residence data, tested them for scale-free power-law distributions that imply highly connected hubs, and compared them to alternative models (exponential, log-normal, power-law with exponential cutoff, and Weibull) that suggest more evenly distributed network connections. Although the power-law model failed the goodness of fit test, after incorporating social network ties, the power-law model was at least as good as, if not better than, the alternatives, implying the presence of both hub and non-hub mechanisms in local SARS-CoV-2 transmission. These findings enhance our understanding of the complex social interactions that drive SARS-CoV-2 transmission, thereby informing more effective public health interventions.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: COVID-19 Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos