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

Soc Sci Med. 2017 Feb:174:53-63. doi: 10.1016/j.socscimed.2016.12.020. Epub 2016 Dec 15.

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.

Keywords: China; Climate change; Epidemics; Multi-scalar analysis; Spatial scales; Temperature.

Publication types

  • Historical Article
  • Research Support, Non-U.S. Gov't

MeSH terms

  • China / epidemiology
  • Climate Change / statistics & numerical data*
  • Epidemics / history*
  • Epidemics / statistics & numerical data*
  • History, 15th Century
  • History, 16th Century
  • History, 17th Century
  • History, 18th Century
  • History, Medieval
  • Humans
  • Meteorology / statistics & numerical data
  • Spatial Analysis