Exploring Determinants of Spatial Variations in the Dengue Fever Epidemic Using Geographically Weighted Regression Model: A Case Study in the Joint Guangzhou-Foshan Area, China, 2014

Hongyan Ren, Lan Zheng, Qiaoxuan Li, Wu Yuan and Liang Lu
Additional contact information
Hongyan Ren: State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Lan Zheng: State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Qiaoxuan Li: State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Wu Yuan: School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
Liang Lu: Department of Vector Biology and Control, Natural Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China

IJERPH, 2017, vol. 14, issue 12, 1-13

Abstract: Dengue fever (DF) is a common and rapidly spreading vector-borne viral disease in tropical and subtropical regions. In recent years, this imported disease has posed an increasing threat to public health in China, especially in many southern cities. Although the severity of DF outbreaks in these cities is generally associated with known risk factors at various administrative levels, spatial heterogeneities of these associations remain little understood on a finer scale. In this study, the neighboring Guangzhou and Foshan (GF) cities were considered as a joint area for characterizing the spatial variations in the 2014 DF epidemic at various grid levels from 1 × 1 km 2 to 6 × 6 km 2 . On an appropriate scale, geographically weighted regression (GWR) models were employed to interpret the influences of socioeconomic and environmental factors on this epidemic across the GF area. DF transmissions in Guangzhou and Foshan cities presented synchronous temporal changes and spatial expansions during the main epidemic months. Across the GF area, this epidemic was obviously spatially featured at various grid levels, especially on the 2 × 2 km 2 scale. Its spatial variations were relatively sufficiently explained by population size, road density, and economic status integrated in the GWR model with the lowest Akaike Information Criterion (AICc = 5227.97) and highest adjusted R square (0.732) values. These results indicated that these three socioeconomic factors acted as geographical determinants of spatial variability of the 2014 DF epidemic across the joint GF area, although some other potential factors should be added to improve the explaining the spatial variations in the central zones. This work improves our understanding of the effects of socioeconomic conditions on the spatial variations in this epidemic and helps local hygienic authorities to make targeted joint interventions for preventing and controlling this epidemic across the GF area.

Keywords: dengue fever; spatial variations; Guangzhou and Foshan; socioeconomic factors; geographically weighted regression (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:

Downloads: (external link)
https://www.mdpi.com/1660-4601/14/12/1518/pdf (application/pdf)
https://www.mdpi.com/1660-4601/14/12/1518/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:14:y:2017:i:12:p:1518-:d:121830

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().