Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis

Zheng Cao, Tao Liu, Xing Li, Jin Wang, Hualiang Lin, Lingling Chen, Zhifeng Wu and Wenjun Ma
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Zheng Cao: Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
Tao Liu: Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
Xing Li: Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
Jin Wang: Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
Hualiang Lin: Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China
Lingling Chen: School of Geographical Sciencesof Guangzhou University, Guangzhou 510006, China
Zhifeng Wu: School of Geographical Sciencesof Guangzhou University, Guangzhou 510006, China
Wenjun Ma: Guangdong Provincial Institute of Public Health, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China

IJERPH, 2017, vol. 14, issue 7, 1-14

Abstract: Background : Large spatial heterogeneity was observed in the dengue fever outbreak in Guangzhou in 2014, however, the underlying reasons remain unknown. We examined whether socio-ecological factors affected the spatial distribution and their interactive effects. Methods : Moran’s I was applied to first examine the spatial cluster of dengue fever in Guangzhou. Nine socio-ecological factors were chosen to represent the urbanization level, economy, accessibility, environment, and the weather of the 167 townships/streets in Guangzhou, and then the geographical detector was applied to analyze the individual and interactive effects of these factors on the dengue outbreak. Results : Four clusters of dengue fever were identified in Guangzhou in 2014, including one hot spot in the central area of Guangzhou and three cold spots in the suburban districts. For individual effects, the temperature ( q = 0.33) was the dominant factor of dengue fever, followed by precipitation ( q = 0.24), road density ( q = 0.24), and water body area ( q = 0.23). For the interactive effects, the combination of high precipitation, high temperature, and high road density might result in increased dengue fever incidence. Moreover, urban villages might be the dengue fever hot spots. Conclusions : Our study suggests that some socio-ecological factors might either separately or jointly influence the spatial distribution of dengue fever in Guangzhou.

Keywords: dengue fever; socio-ecological factors; geographical detectors; GIS and RS (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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