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Outbreak patterns of the novel avian influenza (H7N9)

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  • Pan, Ya-Nan
  • Lou, Jing-Jing
  • Han, Xiao-Pu

Abstract

The attack of novel avian influenza (H7N9) in East China caused a serious health crisis and public panic. In this paper, we empirically analyze the onset patterns of human cases of the novel avian influenza and observe several spatial and temporal properties that are similar to other infectious diseases. More specifically, using the empirical analysis and modeling studies, we find that the spatio-temporal network that connects the cities with human cases along the order of outbreak timing emerges two-regime-power-law edge-length distribution, indicating the picture that several islands with higher and heterogeneous risk straggle in East China. The proposed method is applicable to the analysis of the spreading situation in the early stage of disease outbreak using quite limited dataset.

Suggested Citation

  • Pan, Ya-Nan & Lou, Jing-Jing & Han, Xiao-Pu, 2014. "Outbreak patterns of the novel avian influenza (H7N9)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 265-270.
    • Handle: RePEc:eee:phsmap:v:401:y:2014:i:c:p:265-270
    DOI: 10.1016/j.physa.2014.01.040
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    References listed on IDEAS

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    1. Cristopher Moore & M. E. J. Newman, 2000. "Epidemics and Percolation in Small-World Networks," Working Papers 00-01-002, Santa Fe Institute.
    2. Lin Wang & Xiang Li & Yi-Qing Zhang & Yan Zhang & Kan Zhang, 2011. "Evolution of Scaling Emergence in Large-Scale Spatial Epidemic Spreading," PLOS ONE, Public Library of Science, vol. 6(7), pages 1-11, July.
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    Cited by:

    1. Wen Dong & Kun Yang & Quan-Li Xu & Yu-Lian Yang, 2015. "A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014," IJERPH, MDPI, vol. 12(12), pages 1-18, December.

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