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Optimal media reporting intensity on mitigating spread of an emerging infectious disease

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  • Weike Zhou
  • Yanni Xiao
  • Jane Marie Heffernan

Abstract

Mass media reports can induce individual behaviour change during a disease outbreak, which has been found to be useful as it reduces the force of infection. We propose a compartmental model by including a new compartment of the intensity of the media reports, which extends existing models by considering a novel media function, which is dependent both on the number of infected individuals and on the intensity of mass media. The existence and stability of the equilibria are analyzed and an optimal control problem of minimizing the total number of cases and total cost is considered, using reduction or enhancement in the media reporting rate as the control. With the help of Pontryagin’s Maximum Principle, we obtain the optimal media reporting intensity. Through parameterization of the model with the 2009 A/H1N1 influenza outbreak data in the 8th Hospital of Xi’an in Shaanxi Province of China, we obtain the basic reproduction number for the formulated model with two particular media functions. The optimal media reporting intensity obtained here indicates that during the early stage of an epidemic we should quickly enhance media reporting intensity, and keep it at a maximum level until it can finally weaken when epidemic cases have decreased significantly. Numerical simulations show that media impact reduces the number of cases during an epidemic, but that the number of cases is further mitigated under the optimal reporting intensity. Sensitivity analysis implies that the outbreak severity is more sensitive to the weight α1 (weight of media effect sensitive to infected individuals) than weight α2 (weight of media effect sensitive to media items).

Suggested Citation

  • Weike Zhou & Yanni Xiao & Jane Marie Heffernan, 2019. "Optimal media reporting intensity on mitigating spread of an emerging infectious disease," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-18, March.
    • Handle: RePEc:plo:pone00:0213898
    DOI: 10.1371/journal.pone.0213898
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    References listed on IDEAS

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    1. Hou, Juan & Teng, Zhidong, 2009. "Continuous and impulsive vaccination of SEIR epidemic models with saturation incidence rates," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(10), pages 3038-3054.
    2. Greenhalgh, David & Rana, Sourav & Samanta, Sudip & Sardar, Tridip & Bhattacharya, Sabyasachi & Chattopadhyay, Joydev, 2015. "Awareness programs control infectious disease – Multiple delay induced mathematical model," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 539-563.
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    Cited by:

    1. Nafiseh Shamsi Gamchi & S. Ali Torabi & Fariborz Jolai, 2021. "A novel vehicle routing problem for vaccine distribution using SIR epidemic model," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(1), pages 155-188, March.

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