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Effects of human dynamics on epidemic spreading in Côte d’Ivoire

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  • Li, Ruiqi
  • Wang, Wenxu
  • Di, Zengru

Abstract

Understanding and predicting outbreaks of contagious diseases are crucial to the development of society and public health, especially for underdeveloped countries. However, challenging problems are encountered because of complex epidemic spreading dynamics influenced by spatial structure and human dynamics (including both human mobility and human interaction intensity). We propose a systematical model to depict nationwide epidemic spreading in Côte d’Ivoire, which integrates multiple factors, such as human mobility, human interaction intensity, and demographic features. We provide insights to aid in modeling and predicting the epidemic spreading process by data-driven simulation and theoretical analysis, which is otherwise beyond the scope of local evaluation and geometrical views. We show that the requirement that the average local basic reproductive number to be greater than unity is not necessary for outbreaks of epidemics. The observed spreading phenomenon can be roughly explained as a heterogeneous diffusion–reaction process by redefining mobility distance according to the human mobility volume between nodes, which is beyond the geometrical viewpoint. However, the heterogeneity of human dynamics still poses challenges to precise prediction.

Suggested Citation

  • Li, Ruiqi & Wang, Wenxu & Di, Zengru, 2017. "Effects of human dynamics on epidemic spreading in Côte d’Ivoire," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 30-40.
  • Handle: RePEc:eee:phsmap:v:467:y:2017:i:c:p:30-40
    DOI: 10.1016/j.physa.2016.09.059
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    References listed on IDEAS

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    1. Carol Y. Lin, 2008. "Modeling Infectious Diseases in Humans and Animals by KEELING, M. J. and ROHANI, P," Biometrics, The International Biometric Society, vol. 64(3), pages 993-993, September.
    2. Zhesi Shen & Wen-Xu Wang & Ying Fan & Zengru Di & Ying-Cheng Lai, 2014. "Reconstructing propagation networks with natural diversity and identifying hidden sources," Nature Communications, Nature, vol. 5(1), pages 1-10, September.
    3. Yang, Zimo & Cui, Ai-Xiang & Zhou, Tao, 2011. "Impact of heterogeneous human activities on epidemic spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4543-4548.
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    Citations

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    Cited by:

    1. Gao, Lei & Li, Ruiqi & Shu, Panpan & Wang, Wei & Gao, Hui & Cai, Shimin, 2018. "Effects of individual popularity on information spreading in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 489(C), pages 32-39.
    2. Wang, Ning-Ning & Jin, Zhen & Wang, Ya-Jing & Di, Zeng-Ru, 2020. "Epidemics spreading in periodic double layer networks with dwell time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    3. He, Yifan & Zhao, Chen & Zeng, An, 2022. "Ranking locations in a city via the collective home-work relations in human mobility data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).
    4. Zhu, Xuzhen & Wang, Ruijie & Wang, Zexun & Chen, Xiaolong & Wang, Wei & Cai, Shimin, 2019. "Double-edged sword effect of edge overlap on asymmetrically interacting spreading dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 617-624.
    5. Li, Ruiqi & Richmond, Peter & Roehner, Bertrand M., 2018. "Effect of population density on epidemics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 713-724.

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