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

Harry F. LEE, Jie FEI, Christopher Y. S. CHAN, Qing PEI, Xin JIA, Ricci P.H. YUE

Research output: Contribution to journalArticlespeer-review

24 Citations (Scopus)

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 AD1370–1909 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. Copyright © 2016 Elsevier Ltd.
Original languageEnglish
Pages (from-to)53-63
JournalSocial Science & Medicine
Volume174
Early online dateDec 2016
DOIs
Publication statusPublished - Feb 2017

Citation

Lee, H. F., Fei, J., Chan, C. Y. S., Pei, Q., Jia, X., & Yue, R. P. H. (2017). Climate change and epidemics in Chinese history: A multi-scalar analysis. Social Science & Medicine, 174, 53-63.

Keywords

  • China
  • Climate change
  • Temperature
  • Epidemics
  • Multi-scalar analysis
  • Spatial scales

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