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Characterizing the dynamics underlying global spread of epidemics

Author

Listed:
  • Lin Wang

    (The University of Hong Kong)

  • Joseph T. Wu

    (The University of Hong Kong)

Abstract

Over the past few decades, global metapopulation epidemic simulations built with worldwide air-transportation data have been the main tool for studying how epidemics spread from the origin to other parts of the world (e.g., for pandemic influenza, SARS, and Ebola). However, it remains unclear how disease epidemiology and the air-transportation network structure determine epidemic arrivals for different populations around the globe. Here, we fill this knowledge gap by developing and validating an analytical framework that requires only basic analytics from stochastic processes. We apply this framework retrospectively to the 2009 influenza pandemic and 2014 Ebola epidemic to show that key epidemic parameters could be robustly estimated in real-time from public data on local and global spread at very low computational cost. Our framework not only elucidates the dynamics underlying global spread of epidemics but also advances our capability in nowcasting and forecasting epidemics.

Suggested Citation

  • Lin Wang & Joseph T. Wu, 2018. "Characterizing the dynamics underlying global spread of epidemics," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-017-02344-z
    DOI: 10.1038/s41467-017-02344-z
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    Cited by:

    1. Zhang, Gui-Qing & Baró, Jordi & Cheng, Fang-Yin & Huang, He & Wang, Lin, 2019. "Avalanche dynamics of a generalized earthquake model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1463-1471.
    2. Zou, Yang & Xiong, Zhongyang & Zhang, Pu & Wang, Wei, 2018. "Social contagions on multiplex networks with different reliability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 728-735.
    3. Seungwon Jung & Jaeuk Moon & Eenjun Hwang, 2020. "Cluster-Based Analysis of Infectious Disease Occurrences Using Tensor Decomposition: A Case Study of South Korea," IJERPH, MDPI, vol. 17(13), pages 1-19, July.
    4. Chen, Ning & Zhu, Xuzhen & Chen, Yanyan, 2019. "Information spreading on complex networks with general group distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 671-676.
    5. Long, Linbo & Zhong, Kan & Wang, Wei, 2018. "Malicious viruses spreading on complex networks with heterogeneous recovery rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 746-753.
    6. Wang, Qingqing & Du, Chunpeng & Geng, Yini & Shi, Lei, 2020. "Historical payoff can not overcome the vaccination dilemma on Barabási–Albert scale-free networks," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    7. Ling Zhong, 2021. "A dynamic pandemic model evaluating reopening strategies amid COVID-19," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-19, March.
    8. Lu, Peng & Nie, Shizhao, 2019. "The strength distribution and combined duration prediction of online collective actions: Big data analysis and BP neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    9. Wang, Min & Cheng, Qing & Huang, Jincai & Cheng, Guangquan, 2021. "Research on optimal hub location of agricultural product transportation network based on hierarchical hub-and-spoke network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    10. Sánchez, Allan G.S. & Posadas–Castillo, C. & Garza–González, E., 2021. "Determining efficiency of small-world algorithms: A comparative approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 187(C), pages 687-699.
    11. Liu, Xiang-Chun & Zhu, Xu-Zhen & Tian, Hui & Zhang, Zeng-Ping & Wang, Wei, 2019. "Identifying localized influential spreaders of information spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 92-97.
    12. Shu, Panpan & Wang, Wei & Eugene Stanley, H. & Braunstein, Lidia A., 2018. "A general social contagion dynamic in interconnected lattices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 272-279.
    13. Zhu, Shu-Shan & Zhu, Xu-Zhen & Wang, Jian-Qun & Zhang, Zeng-Ping & Wang, Wei, 2019. "Social contagions on multiplex networks with heterogeneous population," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 105-113.
    14. Zhu, Xuzhen & Liu, Yuxin & Wang, Shengfeng & Wang, Ruijie & Chen, Xiaolong & Wang, Wei, 2021. "Allocating resources for epidemic spreading on metapopulation networks," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    15. Pueyo, Salvador, 2020. "Jevons' paradox and a tax on aviation to prevent the next pandemic," SocArXiv vb5q3, Center for Open Science.
    16. Deng, Zheng-Hong & Qiao, Hong-Hai & Song, Qun & Gao, Li, 2019. "A complex network community detection algorithm based on label propagation and fuzzy C-means," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 217-226.
    17. Zhang, Shuhua & Zhang, Zhipeng & Wu, Yu’e & Yan, Ming & Xie, Yunya, 2018. "Tolerance-based punishment and cooperation in spatial public goods game," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 267-272.
    18. Jun Cai & Bo Xu & Karen Kie Yan Chan & Xueying Zhang & Bing Zhang & Ziyue Chen & Bing Xu, 2019. "Roles of Different Transport Modes in the Spatial Spread of the 2009 Influenza A(H1N1) Pandemic in Mainland China," IJERPH, MDPI, vol. 16(2), pages 1-15, January.
    19. Xueli Wang & Moqin Zhou & Jinzhu Jia & Zhi Geng & Gexin Xiao, 2018. "A Bayesian Approach to Real-Time Monitoring and Forecasting of Chinese Foodborne Diseases," IJERPH, MDPI, vol. 15(8), pages 1-13, August.

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