Modeling Infectious Disease Parameters Based on Serological and Social Contact Data : A Modern Statistical Perspective

Mathematical epidemiology of infectious diseases usually involves describing the flow of individuals between mutually exclusive infection states. One of the key parameters describing the transition from the susceptible to the infected class is the hazard of infection, often referred to as the force...

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Autors principals: Hens, Niels, Shkedy, Ziv (Autor), Aerts, Marc (Autor), Faes, Christel (Autor), Van Damme, Pierre, 19..- (Autor), Beutels, Philippe (Autor)
Format: Livre numérique
Idioma:Anglais
Publicat: New York, NY : Springer New York 2012.
Cham : Springer Nature
Col·lecció:Statistics for Biology and Health 63
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Nota: Archives Springer e-books (Licence nationale)
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Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Modeling infectious disease parameters based on serological and social contact data, a modern statistical perspective, Niels Hens, Ziv Shkedy, Marc Aerts...[et al.], 2012, Berlin, Springer, 1 vol. (XVI-298 p.), Statistics for biology and health, 978-1-4614-4071-0
• Modeling Infectious Disease Parameters Based on Serological and Social Contact Data, Texte imprimé, 9781461440734
• Modeling Infectious Disease Parameters Based on Serological and Social Contact Data, Texte imprimé, 9781489987969
Taula de continguts:
  • Mathematical models for infectious diesease
  • The static model
  • The dynamic model
  • The stochastic model
  • Implementation of models in MATLAB
  • Data sources for modelling infectious diseases
  • Estimation from serological data
  • Parametric models for teh prevalence and the force of infection
  • Non-parametric approaches to model the prevalence and force of infection
  • Semi-parametric approaches to model the prevalence and force of infection
  • A Bayesian approach
  • Modelling the prevalence and the force of infection direction from antibody levels
  • Modelling multivariate serological data
  • Estimation from other data sources
  • Estimating mixing patterns and Ro in a heterogenous population
  • Modelling in a homogeneous population
  • Modelling in a heterogeneous population
  • Modelling AIDS outbreak data
  • Modelling hepatitis C among injection drug users
  • Modelling dengue
  • Modelling bovine herpes virus in cattle.