Date Published: November 20, 2015
Publisher: Public Library of Science
Author(s): Yvonne Walz, Martin Wegmann, Stefan Dech, Penelope Vounatsou, Jean-Noël Poda, Eliézer K. N’Goran, Jürg Utzinger, Giovanna Raso, Justin V. Remais. http://doi.org/10.1371/journal.pntd.0004217
Abstract: BackgroundSchistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health.MethodologyWe employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d’Ivoire and validated against readily available survey data from school-aged children.Principal FindingsEnvironmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d’Ivoire.Conclusions/SignificanceA predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data.
Partial Text: Schistosomiasis is a neglected tropical disease caused by blood flukes of the genus Schistosoma. From a public health perspective, schistosomiasis is considered the most important water-based disease. Indeed, data from mid-2003 suggest that 779 million people were at risk of schistosomiasis with more than 200 million people infected, predominantly in sub-Saharan Africa . An infection with schistosomes depends on the spatial and temporal distribution of specific freshwater snails that act as intermediate hosts and are the prerequisite that a Schistosoma parasite reaches the development stage to infect humans. The global strategy endorsed by the World Health Organization to control schistosomiasis is the large-scale administration of the antischistosomal drug praziquantel to at-risk populations to prevent morbidity [2,3]. The sustainability of this control strategy has been challenged, as there is rapid re-infection after deworming [4–6]. In recent years, a shift occurred from morbidity control to transmission control and local elimination, and hence, there is a stronger focus on intermediate host snails and transmission sites, along with primary prevention tailored to specific social-ecological systems [7–9].
In the current study, we developed a new modeling approach, which is based on a multitude of remotely sensed environmental metrics to delineate potential schistosomiasis transmission sites, and allows quantification of suitability for disease-related parasite and snail species. The validation of habitat variables in relation to field measurements and observations showed partial agreement. This validation procedure aimed at identifying strengths and weaknesses of remote sensing environmental metrics to assess environmental suitability for potential schistosomiasis transmission. Lessons learned are offered for discussion.