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

Seid, Ahmed and Gadisa, Endalamaw and Tsegaw, Teshome and Abera, Adugna and Teshome, Aklilu and Mulugeta, Abate and Herrero, Merce and Argaw, Daniel and Jorge, Alvar and Kebede, Asnakew and Aseffa, Abraham (2014) Risk map for cutaneous leishmaniasis in Ethiopia based on environmental factors as revealed by geographical information systems and statistics. Geospatial Health, 8 (2). pp. 377-387. ISSN 1970-7096

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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

Item Type:	Article
Uncontrolled Keywords:	Cutaneous leishmaniasis, risk mapping, environmental factors, geographical information systems, Ethiopia
Subjects:	600 Tecnologia - Scienze applicate > 610 Medicina e salute (Classificare qui la tecnologia dei servizi medici) > 614 Medicina legale; incidenza delle malattie; Medicina preventiva pubblica > 614.4 Incidenza delle malattie e misure pubblica per prevenirle (classificare qui l'Epidemiologia, l'Epidemiologia clinica)
Depositing User:	Chiara D'Arpa
Date Deposited:	29 Jul 2014 16:06
Last Modified:	29 Jul 2014 16:06
URI:	http://eprints.bice.rm.cnr.it/id/eprint/9507

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