Mosquito habitat and dengue risk potential in Kenya: alternative methods to traditional risk mapping techniques

  • David F. Attaway | dattaway@gmu.edu Department of Geography and GeoInformation Science, George Mason University, Fairfax; ESRI, Redlands, United States.
  • Kathryn H. Jacobsen Department of Global and Community Health, George Mason University, Fairfax, United States.
  • Allan Falconer Department of Geography and GeoInformation Science, George Mason University, Fairfax, United States.
  • Germana Manca Department of Geography and GeoInformation Science, George Mason University, Fairfax, United States.
  • Lauren Rosenshein Bennett ESRI, Redlands; Center for Information Systems and Technology, Claremont Graduate University, Claremont, United States.
  • Nigel M. Waters Department of Geography and GeoInformation Science, George Mason University, Fairfax, USA; GIS Center of Excellence, George Mason University, Fairfax, USA; Institute of Public Health, Faculty of Medicine, University of Calgary, Calgary, Canada.

Abstract

Outbreaks, epidemics and endemic conditions make dengue a disease that has emerged as a major threat in tropical and sub-tropical countries over the past 30 years. Dengue fever creates a growing burden for public health systems and has the potential to affect over 40% of the world population. The problem being investigated is to identify the highest and lowest areas of dengue risk. This paper presents “Similarity Search”, a geospatial analysis aimed at identifying these locations with- in Kenya. Similarity Search develops a risk map by combining environmental susceptibility analysis and geographical infor- mation systems, and then compares areas with dengue prevalence to all other locations. Kenya has had outbreaks of dengue during the past 3 years, and we identified areas with the highest susceptibility to dengue infection using bioclimatic variables, elevation and mosquito habitat as input to the model. Comparison of the modelled risk map with the reported dengue epi- demic cases obtained from the open source reporting ProMED and Government news reports from 1982-2013 confirmed the high-risk locations that were used as the Similarity Search presence cells. Developing the risk model based upon the bio- climatic variables, elevation and mosquito habitat increased the efficiency and effectiveness of the dengue fever risk mapping process.

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Published
2014-11-01
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Original Articles
Keywords:
dengue, geographical information system, risk mapping, medical geography, Kenya.
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How to Cite
Attaway, D. F., Jacobsen, K. H., Falconer, A., Manca, G., Bennett, L. R., & Waters, N. M. (2014). Mosquito habitat and dengue risk potential in Kenya: alternative methods to traditional risk mapping techniques. Geospatial Health, 9(1), 119-130. https://doi.org/10.4081/gh.2014.10