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Climate change and epidemics in Chinese history: A multi-scalar analysis

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  • Lee, Harry F.
  • Fei, Jie
  • Chan, Christopher Y.S.
  • Pei, Qing
  • Jia, Xin
  • Yue, Ricci P.H.

Abstract

This study seeks to provide further insight regarding the relationship of climate-epidemics in Chinese history through a multi-scalar analysis. Based on 5961 epidemic incidents in China during 1370–1909 CE we applied Ordinary Least Square regression and panel data regression to verify the climate-epidemic nexus over a range of spatial scales (country, macro region, and province). Results show that epidemic outbreaks were negatively correlated with the temperature in historical China at various geographic levels, while a stark reduction in the correlational strength was observed at lower geographic levels. Furthermore, cooling drove up epidemic outbreaks in northern and central China, where population pressure reached a clear threshold for amplifying the vulnerability of epidemic outbreaks to climate change. Our findings help to illustrate the modifiable areal unit and the uncertain geographic context problems in climate-epidemics research. Researchers need to consider the scale effect in the course of statistical analyses, which are currently predominantly conducted on a national/single scale; and also the importance of how the study area is delineated, an issue which is rarely discussed in the climate-epidemics literature. Future research may leverage our results and provide a cross-analysis with those derived from spatial analysis.

Suggested Citation

  • Lee, Harry F. & Fei, Jie & Chan, Christopher Y.S. & Pei, Qing & Jia, Xin & Yue, Ricci P.H., 2017. "Climate change and epidemics in Chinese history: A multi-scalar analysis," Social Science & Medicine, Elsevier, vol. 174(C), pages 53-63.
    • Handle: RePEc:eee:socmed:v:174:y:2017:i:c:p:53-63
    DOI: 10.1016/j.socscimed.2016.12.020
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    References listed on IDEAS

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    1. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521828284, September.
    2. Edward L. Glaeser & Bruce I. Sacerdote & Jose A. Scheinkman, 2003. "The Social Multiplier," Journal of the European Economic Association, MIT Press, vol. 1(2-3), pages 345-353, 04/05.
    3. A S Fotheringham & D W S Wong, 1991. "The Modifiable Areal Unit Problem in Multivariate Statistical Analysis," Environment and Planning A, , vol. 23(7), pages 1025-1044, July.
    4. Harry Lee & David Zhang, 2013. "A tale of two population crises in recent Chinese history," Climatic Change, Springer, vol. 116(2), pages 285-308, January.
    5. Pei, Qing & Zhang, David D. & Li, Guodong & Winterhalder, Bruce & Lee, Harry F., 2015. "Epidemics in Ming and Qing China: Impacts of changes of climate and economic well-being," Social Science & Medicine, Elsevier, vol. 136, pages 73-80.
    6. Frees,Edward W., 2004. "Longitudinal and Panel Data," Cambridge Books, Cambridge University Press, number 9780521535380, September.
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    Cited by:

    1. Xiaoyang Liu & Chao Liu & Xiaoping Zeng, 2017. "Online Social Network Emergency Public Event Information Propagation and Nonlinear Mathematical Modeling," Complexity, Hindawi, vol. 2017, pages 1-7, June.

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