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Asymmetric percolation drives a double transition in sexual contact networks.
Allard, Antoine; Althouse, Benjamin M; Scarpino, Samuel V; Hébert-Dufresne, Laurent.
Afiliação
  • Allard A; Centre de Recerca Matemàtica, E-08193 Bellaterra (Barcelona), Spain.
  • Althouse BM; Institute for Disease Modeling, Bellevue, WA 98005.
  • Scarpino SV; Information School, University of Washington, Seattle, WA 98105.
  • Hébert-Dufresne L; Department of Biology, New Mexico State University, Las Cruces, NM 88003.
Proc Natl Acad Sci U S A ; 114(34): 8969-8973, 2017 08 22.
Article em En | MEDLINE | ID: mdl-28790185
Zika virus (ZIKV) exhibits unique transmission dynamics in that it is concurrently spread by a mosquito vector and through sexual contact. Due to the highly asymmetric durations of infectiousness between males and females-it is estimated that males are infectious for periods up to 10 times longer than females-we show that this sexual component of ZIKV transmission behaves akin to an asymmetric percolation process on the network of sexual contacts. We exactly solve the properties of this asymmetric percolation on random sexual contact networks and show that this process exhibits two epidemic transitions corresponding to a core-periphery structure. This structure is not present in the underlying contact networks, which are not distinguishable from random networks, and emerges because of the asymmetric percolation. We provide an exact analytical description of this double transition and discuss the implications of our results in the context of ZIKV epidemics. Most importantly, our study suggests a bias in our current ZIKV surveillance, because the community most at risk is also one of the least likely to get tested.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Infecções Sexualmente Transmissíveis / Infecção por Zika virus / Modelos Teóricos Limite: Animals / Female / Humans / Male Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Infecções Sexualmente Transmissíveis / Infecção por Zika virus / Modelos Teóricos Limite: Animals / Female / Humans / Male Idioma: En Ano de publicação: 2017 Tipo de documento: Article