Skip to main content

Discrete time modelling of disease incidence time series by using Markov chain Monte Carlo methods

Buy Article:

$43.00 plus tax (Refund Policy)

Summary. 

A stochastic discrete time version of the susceptible–infected–recovered model for infectious diseases is developed. Disease is transmitted within and between communities when infected and susceptible individuals interact. Markov chain Monte Carlo methods are used to make inference about these unobserved populations and the unknown parameters of interest. The algorithm is designed specifically for modelling time series of reported measles cases although it can be adapted for other infectious diseases with permanent immunity. The application to observed measles incidence series motivates extensions to incorporate age structure as well as spatial epidemic coupling between communities.
No References
No Citations
No Supplementary Data
No Article Media
No Metrics

Keywords: Disease incidence time series; Markov chain Monte Carlo methods; Stochastic modelling of infectious diseases

Document Type: Research Article

Affiliations: University of Warwick, Coventry, UK

Publication date: 2005-06-01

  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more