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Comprehensive analysis of information dissemination in disasters

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  • Zhang, N.
  • Huang, H.
  • Su, Boni

Abstract

China is a country that experiences a large number of disasters. The number of deaths caused by large-scale disasters and accidents in past 10 years is around 900,000. More than 92.8 percent of these deaths could be avoided if there were an effective pre-warning system deployed. Knowledge of the information dissemination characteristics of different information media taking into consideration governmental assistance (information published by a government) in disasters in urban areas, plays a critical role in increasing response time and reducing the number of deaths and economic losses. In this paper we have developed a comprehensive information dissemination model to optimize efficiency of pre-warning mechanics. This model also can be used for disseminating information for evacuees making real-time evacuation plans. We analyzed every single information dissemination models for pre-warning in disasters by considering 14 media: short message service (SMS), phone, television, radio, news portals, Wechat, microblogs, email, newspapers, loudspeaker vehicles, loudspeakers, oral communication, and passive information acquisition via visual and auditory senses. Since governmental assistance is very useful in a disaster, we calculated the sensitivity of governmental assistance ratio. The results provide useful references for information dissemination during disasters in urban areas.

Suggested Citation

  • Zhang, N. & Huang, H. & Su, Boni, 2016. "Comprehensive analysis of information dissemination in disasters," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 846-857.
    • Handle: RePEc:eee:phsmap:v:462:y:2016:i:c:p:846-857
    DOI: 10.1016/j.physa.2016.06.043
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    References listed on IDEAS

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    Cited by:

    1. Feng, Xinhang & Jiang, Yanli & Gai, Wenmei, 2024. "Rural community response to accidental toxic gas release: An individual emergency response model during self-organized evacuations," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. N. Zhang & H. Huang, 2018. "Assessment of world disaster severity processed by Gaussian blur based on large historical data: casualties as an evaluating indicator," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 92(1), pages 173-187, May.
    3. Zhang, N. & Ni, X.Y. & Huang, H. & Duarte, M., 2017. "Risk-based personal emergency response plan under hazardous gas leakage: Optimal information dissemination and regional evacuation in metropolises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 237-250.
    4. Yanxin Wang & Jian Li & Xi Zhao & Gengzhong Feng & Xin (Robert) Luo, 2020. "Using Mobile Phone Data for Emergency Management: a Systematic Literature Review," Information Systems Frontiers, Springer, vol. 22(6), pages 1539-1559, December.
    5. Cui, Yapeng & Ni, Shunjiang & Shen, Shifei & Wang, Zhiru, 2020. "Modeling the dynamics of information dissemination under disaster," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).

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