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Optimized Strategy for the Control and Prevention of Newly Emerging Influenza Revealed by the Spread Dynamics Model

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  • Wen-Dou Zhang
  • Zheng-Hu Zu
  • Qing Xu
  • Zhi-Jing Xu
  • Jin-Jie Liu
  • Tao Zheng

Abstract

No matching vaccine is immediately available when a novel influenza strain breaks out. Several nonvaccine-related strategies must be employed to control an influenza epidemic, including antiviral treatment, patient isolation, and immigration detection. This paper presents the development and application of two regional dynamic models of influenza with Pontryagin’s Maximum Principle to determine the optimal control strategies for an epidemic and the corresponding minimum antiviral stockpiles. Antiviral treatment was found to be the most effective measure to control new influenza outbreaks. In the case of inadequate antiviral resources, the preferred approach was the centralized use of antiviral resources in the early stage of the epidemic. Immigration detection was the least cost-effective; however, when used in combination with the other measures, it may play a larger role. The reasonable mix of the three control measures could reduce the number of clinical cases substantially, to achieve the optimal control of new influenza.

Suggested Citation

  • Wen-Dou Zhang & Zheng-Hu Zu & Qing Xu & Zhi-Jing Xu & Jin-Jie Liu & Tao Zheng, 2014. "Optimized Strategy for the Control and Prevention of Newly Emerging Influenza Revealed by the Spread Dynamics Model," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    • Handle: RePEc:plo:pone00:0084694
    DOI: 10.1371/journal.pone.0084694
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    1. Raymond Gani & Steve Leach, 2001. "Transmission potential of smallpox in contemporary populations," Nature, Nature, vol. 414(6865), pages 748-751, December.
    2. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
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