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

Abstract

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.

Risk Mapping and Situational Analysis of Cutaneous Leishmaniasis in an Endemic Area of Central Iran: A GIS-Based Survey

“…This method has been previously used to predict spatial incidence of VL in India [33], although some other studies have used different approaches for modeling risk of leishmaniasis [34,35]. It can be observed that the high endemic areas are in northeastern part of the province in all years although there are a number of villages in the western and northern regions of the study area with high incidence of the disease during 2009–2010.…”

Natural infection of bats with Leishmania in Ethiopia

“…Cutaneous leishmaniasis is widely distributed and usually prevalent in highland areas with occasional reports in the lowland regions of Omo (south) and Awash (central east) (Hailu et al, 2006a). The annual incidence of CL ranges from 20,000 to 50,000 cases, but this is probably an under-estimate (Alvar et al, 2012), with over 28 million people residing in regions with risk of transmission (Seid et al, 2014). The main causative agent of CL in Ethiopia is Leishmania aethiopica, however, infections due to Leishmania tropica and Leishmania major were also reported in the country (Hailu et al, 2006a,b;Abbasi et al, 2013).…”

Spatial and temporal distribution of American cutaneous leishmaniasis in Acre state, Brazil

“…Therefore, geographical information systems (GISs) and spatial analysis, in view of their usefulness in terms of understanding and visualizing the epidemiological behaviour of diseases such as leishmaniasis, have been important tools in achieving these objectives both in Brazil [4–6] and in other countries [7–10]. …”