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Five challenges for stochastic epidemic models involving global transmission.
Britton, Tom; House, Thomas; Lloyd, Alun L; Mollison, Denis; Riley, Steven; Trapman, Pieter.
Afiliação
  • Britton T; Department of Mathematics, Stockholm University, Stockholm 106 91, Sweden. Electronic address: tom.britton@math.su.se.
  • House T; Warwick Infectious Disease Epidemiology Research Centre (WIDER) and Warwick Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.
  • Lloyd AL; Department of Mathematics and Biomathematics Graduate Program, North Carolina State University, Raleigh, NC 27695, USA; Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.
  • Mollison D; Department of Actuarial Mathematics and Statistics, Heriot-Watt University, Edinburgh EH14 4AS, Scotland, UK.
  • Riley S; MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, UK; Department of Community Medicine and School of Public Health, The University of Hong Kong, 21 Sassoon Road, Pokfulam, Hong Kong, China.
  • Trapman P; Department of Mathematics, Stockholm University, Stockholm 106 91, Sweden.
Epidemics ; 10: 54-7, 2015 Mar.
Article em En | MEDLINE | ID: mdl-25843384
ABSTRACT
The most basic stochastic epidemic models are those involving global transmission, meaning that infection rates depend only on the type and state of the individuals involved, and not on their location in the population. Simple as they are, there are still several open problems for such models. For example, when will such an epidemic go extinct and with what probability (questions depending on the population being fixed, changing or growing)? How can a model be defined explaining the sometimes observed scenario of frequent mid-sized epidemic outbreaks? How can evolution of the infectious agent transmission rates be modelled and fitted to data in a robust way?
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estatísticos / Epidemias Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Modelos Estatísticos / Epidemias Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2015 Tipo de documento: Article