Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics

  • Ahmed Seid Armauer Hansen Research Institute, Addis Ababa, Ethiopia.
  • Endalamaw Gadisa | endalamawgadisa@yahoo.com Armauer Hansen Research Institute, Addis Ababa, Ethiopia.
  • Teshome Tsegaw Armauer Hansen Research Institute, Addis Ababa, Ethiopia.
  • Adugna Abera Armauer Hansen Research Institute, Addis Ababa, Ethiopia.
  • Aklilu Teshome Armauer Hansen Research Institute, Addis Ababa, Ethiopia.
  • Abate Mulugeta Disease Prevention and Control Programmes, World Health Organization, Addis Ababa, Ethiopia.
  • Merce Herrero Disease Prevention and Control Programmes, World Health Organization, Addis Ababa, Ethiopia.
  • Daniel Argaw Department for the Control of Neglected Tropical Diseases, World Health Organization, Geneva, Switzerland.
  • Alvar Jorge Department for the Control of Neglected Tropical Diseases, World Health Organization, Geneva, Switzerland.
  • Asnakew Kebede UNICEF-Ethiopia Country Office, Addis Ababa, Ethiopia.
  • Abraham Aseffa Armauer Hansen Research Institute, Addis Ababa, Ethiopia.

Abstract

Cutaneous leishmaniasis (CL) is a neglected tropical disease strongly associated with poverty. Treatment is problematic and no vaccine is available. Ethiopia has seen new outbreaks in areas previously not known to be endemic, often with co-infection by the human immunodeficiency virus (HIV) with rates reaching 5.6% of the cases. The present study concerns the development of a risk model based on environmental factors using geographical information systems (GIS), statistical analysis and modelling. Odds ratio (OR) of bivariate and multivariate logistic regression was used to evaluate the relative importance of environmental factors, accepting P ≤0.056 as the inclusion level for the model’s environmental variables. When estimating risk from the viewpoint of geographical surface, slope, elevation and annual rainfall were found to be good predictors of CL presence based on both probabilistic and weighted overlay approaches. However, when considering Ethiopia as whole, a minor difference was observed between the two methods with the probabilistic technique giving a 22.5% estimate, while that of weighted overlay approach was 19.5%. Calculating the population according to the land surface estimated by the latter method, the total Ethiopian population at risk for CL was estimated at 28,955,035, mainly including people in the highlands of the regional states of Amhara, Oromia, Tigray and the Southern Nations, Nationalities and Peoples’ Region, one of the nine ethnic divisions in Ethiopia. Our environmental risk model provided an overall prediction accuracy of 90.4%. The approach proposed here can be replicated for other diseases to facilitate implementation of evidence-based, integrated disease control activities.

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Published
2014-05-01
Section
Original Articles
Keywords:
cutaneous leishmaniasis, risk mapping, environmental factors, geographical information systems, Ethiopia.
Statistics
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How to Cite
Seid, A., Gadisa, E., Tsegaw, T., Abera, A., Teshome, A., Mulugeta, A., Herrero, M., Argaw, D., Jorge, A., Kebede, A., & Aseffa, A. (2014). Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics. Geospatial Health, 8(2), 377-387. https://doi.org/10.4081/gh.2014.27