Modelling the spatial and seasonal distribution of suitable habitats of schistosomiasis intermediate host snails using Maxent in Ndumo area, KwaZulu-Natal Province, South Africa. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Manyangadze, Tawanda; Chimbari, Moses; Gebreslasie, Michael; Ceccato, Pietro; Mukaratirwa, Samson
• Is Part Of: Parasites & vectors. Volume 9:Issue 1(2016)
• Page Start: 1
• Page End: 10
• Publication Date: 2016-12
• Subjects: Maxent -- Predictive modelling -- Snail-borne disease modelling -- Schistosomiasis; Parasitism -- Periodicals; Parasites -- Periodicals; Vector-pathogen relationships -- Periodicals; Animals as carriers of disease -- Periodicals; Insects as carriers of disease -- Periodicals; 616.96
• DOI: 10.1186/s13071-016-1834-5
• Languages: English
• ISSNs: 1756-3305

Abstract

Abstract Background Schistosomiasis is a snail-borne disease endemic in sub-Saharan Africa transmitted by freshwater snails. The distribution of schistosomiasis coincides with that of the intermediate hosts as determined by climatic and environmental factors. The aim of this paper was to model the spatial and seasonal distribution of suitable habitats forBulinus globosus andBiomphalaria pfeifferi snail species (intermediate hosts forSchistosoma haematobium andSchistosoma mansoni, respectively) in the Ndumo area of uMkhanyakude district, South Africa. Methods Maximum Entropy (Maxent) modelling technique was used to predict the distribution of suitable habitats forB. globosus andB. pfeifferi using presence-only datasets with ≥ 5 and ≤ 12 sampling points in different seasons. Precipitation, maximum and minimum temperatures, Normalised Difference Vegetation Index (NDVI), Normalised Difference Water Index (NDWI), pH, slope and Enhanced Vegetation Index (EVI) were the background variables in the Maxent models. The models were validated using the area under the curve (AUC) and omission rate. Results The predicted suitable habitats for intermediate snail hosts varied with seasons. The AUC for models in all seasons ranged from 0.71 to 1 and the prediction rates were between 0.8 and 0.9. AlthoughB. globosus was found at more localities in the Ndumo area, there was also evidence of cohabiting withB. pfiefferi at some of the locations. NDWI had significant contribution to the models in all seasons. Conclusion The Maxent model is robust in snail habitat suitability modelling even with small dataset of presence-only sampling sites. Application of the methods and design used in this study may be useful in developing a control and management programme for schistosomiasis in the Ndumo area.