A statistical model investigating the prevalence of tuberculosis in New York City using counting processes with two change-points.

@article{Achcar2008ASM,
  title={A statistical model investigating the prevalence of tuberculosis in New York City using counting processes with two change-points.},
  author={Jorge Alberto Achcar and Edson Zangiacomi Martinez and Antonio Ruffino-Netto and Carlos Daniel Paulino and Priscila Bernadina Soares},
  journal={Epidemiology and infection},
  year={2008},
  volume={136 12},
  pages={
          1599-605
        }
}
We considered a Bayesian analysis for the prevalence of tuberculosis cases in New York City from 1970 to 2000. This counting dataset presented two change-points during this period. We modelled this counting dataset considering non-homogeneous Poisson processes in the presence of the two-change points. A Bayesian analysis for the data is considered using Markov chain Monte Carlo methods. Simulated Gibbs samples for the parameters of interest were obtained using WinBugs software. 
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