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The Effects of Socioeconomic and Environmental Factors on the Incidence of Dengue Fever in the Pearl River Delta, China, 2013

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  • Xiaopeng Qi
  • Yong Wang
  • Yue Li
  • Yujie Meng
  • Qianqian Chen
  • Jiaqi Ma
  • George F Gao

Abstract

Background: An outbreak of dengue fever (DF) occurred in Guangdong Province, China in 2013 with the highest number of cases observed within the preceding ten years. DF cases were clustered in the Pearl River Delta economic zone (PRD) in Guangdong Province, which accounted for 99.6% of all cases in Guangdong province in 2013. The main vector in PRD was Aedes albopictus. We investigated the socioeconomic and environmental factors at the township level and explored how the independent variables jointly affect the DF epidemic in the PRD. Methodology/Principal Findings: Six factors associated with the incidence of DF were identified in this project, representing the urbanization, poverty, accessibility and vegetation, and were considered to be core contributors to the occurrence of DF from the perspective of the social economy and the environment. Analyses were performed with Generalized Additive Models (GAM) to fit parametric and non-parametric functions to the relationships between the response and predictors. We used a spline-smooth technique and plotted the predicted against the observed co-variable value. The distribution of DF cases was over-dispersed and fit the negative binomial function better. The effects of all six socioeconomic and environmental variables were found to be significant at the 0.001 level and the model explained 45.1% of the deviance by DF incidence. There was a higher risk of DF infection among people living at the prefectural boundary or in the urban areas than among those living in other areas in the PRD. The relative risk of living at the prefectural boundary was higher than that of living in the urban areas. The associations between the DF cases and population density, GDP per capita, road density, and NDVI were nonlinear. In general, higher “road density” or lower “GDP per capita” were considered to be consistent risk factors. Moreover, higher or lower values of “population density” and “NDVI” could result in an increase in DF cases. Conclusion: In this study, we presented an effect analysis of socioeconomic and environmental factors on DF occurrence at the smallest administrative unit (township level) for the first time in China. GAM was used to effectively detect the nonlinear impact of the predictors on the outcome. The results showed that the relative importance of different risk factors may vary across the PRD. This work improves our understanding of the differences and effects of socioeconomic and environmental factors on DF and supports effectively targeted prevention and control measures. Author Summary: Dengue fever is an infectious disease transmitted by mosquitoes. It is a major public health problem in tropical and subtropical regions around the world. Dengue fever is of great interest in the Pearl River Delta economic zone (PRD) of Guangdong province, China because the outbreak in 2013 was the largest in the previous 10 years. Due to the low degree of diversity in the climatic conditions in the PRD, socioeconomic and environmental factors may be the major contributing factors. The objective of this paper was to perform an assessment and detect the socioeconomic and environmental impact on cases at the smallest administrative unit (the township level). Six factors were identified in this work, representing urbanization, poverty, accessibility and vegetation. The effects of all these factors were found to be significant. The results showed that the relative importance of different risk factors may vary across the PRD. The higher risk areas and vulnerable populations identified in this paper will provide guidance for public health practitioners to create targeted, strategic plans and implement effective public health prevention and control measures.

Suggested Citation

  • Xiaopeng Qi & Yong Wang & Yue Li & Yujie Meng & Qianqian Chen & Jiaqi Ma & George F Gao, 2015. "The Effects of Socioeconomic and Environmental Factors on the Incidence of Dengue Fever in the Pearl River Delta, China, 2013," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(10), pages 1-13, October.
  • Handle: RePEc:plo:pntd00:0004159
    DOI: 10.1371/journal.pntd.0004159
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    1. Kensuke Goto & Balachandran Kumarendran & Sachith Mettananda & Deepa Gunasekara & Yoshito Fujii & Satoshi Kaneko, 2013. "Analysis of Effects of Meteorological Factors on Dengue Incidence in Sri Lanka Using Time Series Data," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-8, May.
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    1. Shi Yin & Chao Ren & Yuan Shi & Junyi Hua & Hsiang-Yu Yuan & Lin-Wei Tian, 2022. "A Systematic Review on Modeling Methods and Influential Factors for Mapping Dengue-Related Risk in Urban Settings," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    2. Hongyan Ren & Lan Zheng & Qiaoxuan Li & Wu Yuan & Liang Lu, 2017. "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," IJERPH, MDPI, vol. 14(12), pages 1-13, December.
    3. Ting-Wu Chuang & Ka-Chon Ng & Thi Luong Nguyen & Luis Fernando Chaves, 2018. "Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan," IJERPH, MDPI, vol. 15(3), pages 1-12, February.
    4. Renaud Marti & Zhichao Li & Thibault Catry & Emmanuel Roux & Morgan Mangeas & Pascal Handschumacher & Jean Gaudart & Annelise Tran & Laurent Demagistri & Jean-François Faure & José Joaquín Carvajal & , 2020. "A Mapping Review on Urban Landscape Factors of Dengue Retrieved from Earth Observation Data, GIS Techniques, and Survey Questionnaires," Post-Print hal-02682042, HAL.
    5. Chi-Chieh Huang & Tuen Yee Tiffany Tam & Yinq-Rong Chern & Shih-Chun Candice Lung & Nai-Tzu Chen & Chih-Da Wu, 2018. "Spatial Clustering of Dengue Fever Incidence and Its Association with Surrounding Greenness," IJERPH, MDPI, vol. 15(9), pages 1-12, August.
    6. Qiaoxuan Li & Hongyan Ren & Lan Zheng & Wei Cao & An Zhang & Dafang Zhuang & Liang Lu & Huixian Jiang, 2017. "Ecological Niche Modeling Identifies Fine-Scale Areas at High Risk of Dengue Fever in the Pearl River Delta, China," IJERPH, MDPI, vol. 14(6), pages 1-13, June.
    7. Jiucheng Xu & Keqiang Xu & Zhichao Li & Fengxia Meng & Taotian Tu & Lei Xu & Qiyong Liu, 2020. "Forecast of Dengue Cases in 20 Chinese Cities Based on the Deep Learning Method," IJERPH, MDPI, vol. 17(2), pages 1-14, January.
    8. Shuli Zhou & Suhong Zhou & Lin Liu & Meng Zhang & Min Kang & Jianpeng Xiao & Tie Song, 2019. "Examining the Effect of the Environment and Commuting Flow from/to Epidemic Areas on the Spread of Dengue Fever," IJERPH, MDPI, vol. 16(24), pages 1-13, December.
    9. Haogao Gu & Ross Ka-Kit Leung & Qinlong Jing & Wangjian Zhang & Zhicong Yang & Jiahai Lu & Yuantao Hao & Dingmei Zhang, 2016. "Meteorological Factors for Dengue Fever Control and Prevention in South China," IJERPH, MDPI, vol. 13(9), pages 1-12, August.
    10. Zheng Cao & Tao Liu & Xing Li & Jin Wang & Hualiang Lin & Lingling Chen & Zhifeng Wu & Wenjun Ma, 2017. "Individual and Interactive Effects of Socio-Ecological Factors on Dengue Fever at Fine Spatial Scale: A Geographical Detector-Based Analysis," IJERPH, MDPI, vol. 14(7), pages 1-14, July.

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