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How socio-environmental factors are associated with Japanese encephalitis in Shaanxi, China—a Bayesian spatial analysis

  • Xi'an Jiaotong University
  • Shaanxi Center for Disease Control and Prevention
  • Queensland University of Technology

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Evidence indicated that socio-environmental factors were associated with occurrence of Japanese encephalitis (JE). This study explored the association of climate and socioeconomic factors with JE (2006–2014) in Shaanxi, China. JE data at the county level in Shaanxi were supplied by Shaanxi Center for Disease Control and Prevention. Population and socioeconomic data were obtained from the China Population Census in 2010 and statistical yearbooks. Meteorological data were acquired from the China Meteorological Administration. A Bayesian conditional autoregressive model was used to examine the association of meteorological and socioeconomic factors with JE. A total of 1197 JE cases were included in this study. Urbanization rate was inversely associated with JE incidence during the whole study period. Meteorological variables were significantly associated with JE incidence between 2012 and 2014. The excessive precipitation at lag of 1–2 months in the north of Shaanxi in June 2013 had an impact on the increase of local JE incidence. The spatial residual variations indicated that the whole study area had more stable risk (0.80–1.19 across all the counties) between 2012 and 2014 than earlier years. Public health interventions need to be implemented to reduce JE incidence, especially in rural areas and after extreme weather.

Original languageEnglish
Article number608
JournalInternational Journal of Environmental Research and Public Health
Volume15
Issue number4
DOIs
StatePublished - Apr 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Contingent risk factors
  • Geographical information system
  • Japanese encephalitis
  • Meteorological variables
  • Shaanxi of China

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