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

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Ahmed Seid
Endalamaw Gadisa *
Teshome Tsegaw
Adugna Abera
Aklilu Teshome
Abate Mulugeta
Merce Herrero
Daniel Argaw
Alvar Jorge
Asnakew Kebede
Abraham Aseffa
(*) Corresponding Author:
Endalamaw Gadisa | endalamawgadisa@yahoo.com

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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