Leishmaniasis transmission: distribution and coarse-resolution ecology of two vectors and two parasites in Egypt

Abstract

Introduction:In past decades, leishmaniasis burden has been low across Egypt; however, changing environment and land use has placed several parts of the country at risk. As a consequence, leishmaniasis has become a particularly difficult health problem, both for local inhabitants and for multinational military personnel. Methods: To evaluate coarse-resolution aspects of the ecology of leishmaniasis transmission, collection records for sandflies and Leishmania species were obtained from diverse sources. To characterize environmental variation across the country, we used multitemporal Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for [2005][2006][2007][2008][2009][2010][2011]. Ecological niche models were generated using MaxEnt, and results were analyzed using background similarity tests to assess whether associations among vectors and parasites (i.e., niche similarity) can be detected across broad geographic regions. Results: We found niche similarity only between one vector species and its corresponding parasite species (i.e., Phlebotomus papatasi with Leishmania major), suggesting that geographic ranges of zoonotic cutaneous leishmaniasis and its potential vector may overlap, but under distinct environmental associations. Other associations (e.g., P. sergenti with L. major) were not supported. Mapping suitable areas for each species suggested that northeastern Egypt is particularly at risk because both parasites have potential to circulate. Conclusions: Ecological niche modeling approaches can be used as a firstpass assessment of vector-parasite interactions, offering useful insights into constraints on the geography of transmission patterns of leishmaniasis.

Inferring distributional shifts of epidemiologically important North and Central American sandflies from Pleistocene to future scenarios

“…This is similar to other studies in the Old World, which include an analysis of the ecological niche shared between P. papatasi and Le. major in Egypt (Samy et al ., ). Lutzomyia cruciata was the species for which the greatest increase in niche breadth was projected in all future scenarios in previous analyses (González et al ., ; Moo‐Llanes et al ., ).…”

An Ecological Framework for Modeling the Geography of Disease Transmission

“…Ecological niche modeling (ENM) has proven useful to forecast the distribution of a vast number of organisms [10-13] and is increasingly employed to predict parasite distributions locally and globally [14][15][16][17]. Despite great strides made in the implementation of ENM to forecast complex biological phenomena such as disease systems [18], traditional frameworks may render biologically unrealistic predictions and thus must be revised, as we show in this review.…”

“…However, the black-box oversimplification may be perilous as it neglects ecological complexity (e.g., the identity of key host species for transmission). Alternatively, component-based approaches consider the individual ecologies of all species involved in disease transmission (e.g., parasites, hosts) [16,17,32]. This approach allows the identification of host species and prioritization of areas for disease surveillance and control.…”

“…As human activities intensify, contact with wildlife and exposure to novel parasites increase, potentially driving zoonotic disease emergence [1,7]. Given the threat that EIDs pose to human populations, understanding the underlying drivers of parasite geographic distribution and their spillover to humans is particularly relevant for epidemiologists, public-health practitioners, and policy makers [9].Ecological niche modeling (ENM) has proven useful to forecast the distribution of a vast number of organisms [10-13] and is increasingly employed to predict parasite distributions locally and globally [14][15][16][17]. Despite great strides made in the implementation of ENM to forecast complex biological phenomena such as disease systems [18], traditional frameworks may render biologically unrealistic predictions and thus must be revised, as we show in this review.…”

Modelling of the distribution of Biomphalaria glabrata and Biomphalaria straminea in the metropolitan region of Recife, Pernambuco, Brazil

“…Since the beginning of this century, several authors have started to use these techniques also towards advancing human health (Campos et al, 2002;Fortes et al, 2004;Lourenço and Landim, 2005;Castro and Singer, 2007;Cardim et al, 2013;Samy et al, 2014). In particular, these techniques have been used to model diseases such as schistosomiasis in studies developed by Guimarães et al (2009Guimarães et al ( , 2010Guimarães et al ( , 2012 to estimate the spatial distribution of Biomphalaria snails in the state of Minas Gerais.…”