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Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing

Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-125845
  • Background Schistosomiasis 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. Methodology We employedBackground Schistosomiasis 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. Methodology We 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 Findings Environmental 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/Significance A 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.zeige mehrzeige weniger

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Autor(en): Yvonne Walz, Martin Wegmann, Stefan Dech, Penelope Vounastou, Jean-Noel Poda, Eliézer K. N'Goran, Giovanna Raso, Jürg Utzinger
URN:urn:nbn:de:bvb:20-opus-125845
Dokumentart:Artikel / Aufsatz in einer Zeitschrift
Institute der Universität:Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie
Sprache der Veröffentlichung:Englisch
Titel des übergeordneten Werkes / der Zeitschrift (Englisch):PLoS Neglected Tropical Diseases
Erscheinungsjahr:2015
Band / Jahrgang:9
Heft / Ausgabe:11
Seitenangabe:e0004217
Originalveröffentlichung / Quelle:PLoS Neglected Tropical Diseases 9(11): e0004217. doi:10.1371/journal.pntd.0004217
DOI:https://doi.org/10.1371/journal.pntd.0004217
Allgemeine fachliche Zuordnung (DDC-Klassifikation):5 Naturwissenschaften und Mathematik / 52 Astronomie / 526 Mathematische Geografie
Freie Schlagwort(e):Burkina Faso; agricultural irrigation; habitats; remote sensing; rivers; schistosomiasis; snails; surface water
Datum der Freischaltung:04.02.2016
Sammlungen:Open-Access-Publikationsfonds / Förderzeitraum 2015
Lizenz (Deutsch):License LogoCC BY: Creative-Commons-Lizenz: Namensnennung