Statistical Inference on a Stochastic Epidemic Model

Raúl Fierro, Víctor Leiva, N. Balakrishnan
  • Communications in Statistics - Simulation and Computation, May 2014, Taylor & Francis
  • DOI: 10.1080/03610918.2013.835409

Statistical Inference on a Stochastic Epidemic Model

What is it about?

Satistical inference for the parameters of a discrete-time stochastic SIR epidemic model is developed. We use a Markov chain for describing the dynamic behavior of the epidemic. Specifically, we propose estimators for the contact and removal rates based on the maximum likelihood and martingale methods, and establish their asymptotic distributions. Finally, a comparison of the maximum likelihood and martingale estimators is conducted by means of Monte Carlo simulations.

Why is it important?

The obtained results are applied in the statistical analysis of the basic reproduction number, a useful quantity for establishing vaccination policies.The obtained results are applied in the statistical analysis of the basic reproduction number, a useful quantity for establishing vaccination policies.

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http://dx.doi.org/10.1080/03610918.2013.835409

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