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Parameter Estimation on a Stochastic SIR Model with Media Coverage

Author

Listed:
  • Changguo Li
  • Yongzhen Pei
  • Meixia Zhu
  • Yue Deng

Abstract

Media coverage reduces the transmission rate from infective to susceptible individuals and is reflected by suitable nonlinear functions in mathematical modeling of the disease. We here focus on estimating the parameters in the transmission rate based on a stochastic SIR epidemic model with media coverage. In order to reduce the computational load, the Newton-Raphson algorithm and Markov Chain Monte Carlo (MCMC) technique are incorporated with maximum likelihood estimation. Simulations validate our estimation results and the necessity of a model with media coverage when modeling the contagious diseases.

Suggested Citation

  • Changguo Li & Yongzhen Pei & Meixia Zhu & Yue Deng, 2018. "Parameter Estimation on a Stochastic SIR Model with Media Coverage," Discrete Dynamics in Nature and Society, Hindawi, vol. 2018, pages 1-7, June.
    • Handle: RePEc:hin:jnddns:3187807
    DOI: 10.1155/2018/3187807
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    Cited by:

    1. Olivares, Alberto & Staffetti, Ernesto, 2021. "Uncertainty quantification of a mathematical model of COVID-19 transmission dynamics with mass vaccination strategy," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).

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