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International Journal of Biometeorology

, Volume 62, Issue 11, pp 1973–1986 | Cite as

Modeling the spatially varying risk factors of dengue fever in Jhapa district, Nepal, using the semi-parametric geographically weighted regression model

  • Bipin Kumar Acharya
  • ChunXiang Cao
  • Tobia Lakes
  • Wei Chen
  • Shahid Naeem
  • Shreejana Pandit
Original Paper

Abstract

Dengue fever is expanding rapidly in many tropical and subtropical countries since the last few decades. However, due to limited research, little is known about the spatial patterns and associated risk factors on a local scale particularly in the newly emerged areas. In this study, we explored spatial patterns and evaluated associated potential environmental and socioeconomic risk factors in the distribution of dengue fever incidence in Jhapa district, Nepal. Global and local Moran’s I were used to assess global and local clustering patterns of the disease. The ordinary least square (OLS), geographically weighted regression (GWR), and semi-parametric geographically weighted regression (s-GWR) models were compared to describe spatial relationship of potential environmental and socioeconomic risk factors with dengue incidence. Our result revealed heterogeneous and highly clustered distribution of dengue incidence in Jhapa district during the study period. The s-GWR model best explained the spatial association of potential risk factors with dengue incidence and was used to produce the predictive map. The statistical relationship between dengue incidence and proportion of urban area, proximity to road, and population density varied significantly among the wards while the associations of land surface temperature (LST) and normalized difference vegetation index (NDVI) remained constant spatially showing importance of mixed geographical modeling approach (s-GWR) in the spatial distribution of dengue fever. This finding could be used in the formulation and execution of evidence-based dengue control and management program to allocate scare resources locally.

Keywords

Dengue fever Spatial heterogeneity Geographically weighted regression Nepal Risk factors 

Notes

Acknowledgements

We would like to express our sincere gratitude to Epidemiology and Disease Control Division (EDCD), Department of Health Services, Government of Nepal, for providing us dengue data. We are also thankful to Dr. Surendra Karki, University of Illinois, Urbana-Champaign, USA, and Dr. Laxman Khanal, Central Department of Zoology, Institute of Science and Technology, Tribhuvan University, Kathmandu, Nepal, and two anonymous reviewers for the feedback and comments on an early version of this manuscript. Two authors, Bipin Kumar Acharya and Shahid Naeem, acknowledge the Chinese Academy of Sciences (CAS) and The World Academy of Sciences (TWAS) for awarding the CAS-TWAS President’s fellowship for their PhD study.

Funding

The work in this paper was financially supported by the National Key Research and Development Program of China (No. 2016YFB0501505) and the Natural Science Foundation of China (No. 41601368).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© ISB 2018

Authors and Affiliations

  1. 1.Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Department of GeographyHumboldt-Universität zu BerlinBerlinGermany
  4. 4.Kanti Children’s Hospital MaharajgunjKathmandu 3Nepal

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