Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles

Kulinkina, Alexandra V., Walz, Yvonne, Koch, Magaly, Biritwum, Nana-Kwadwo and Utzinger, Juerg, (2018). Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles. PLOS Neglected Tropical Diseases, 12(6), 1-22

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  • Sub-type Journal article
    Author Kulinkina, Alexandra V.
    Walz, Yvonne
    Koch, Magaly
    Biritwum, Nana-Kwadwo
    Utzinger, Juerg
    Title Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles
    Appearing in PLOS Neglected Tropical Diseases
    Volume 12
    Issue No. 6
    Publication Date 2018
    Place of Publication San Francisco
    Publisher PLOS Neglected Tropical Diseases
    Start page 1
    End page 22
    Language eng
    Abstract Schistosomiasis is a water-related neglected tropical disease that disproportionately affects school-aged children in poor communities of low- and middle-income countries. Schistosomiasis transmission risk is affected by environmental, socioeconomic, and behavioral factors, including water, sanitation, and hygiene (WASH) conditions. We used fine spatial resolution (10–30 m) remotely sensed data, in combination with measures of local water access and groundwater quality, to predict schistosomiasis risk in 73 rural Ghanaian communities. We found that applying environmental models to specific locations where people contact surface water bodies (i.e., potential transmission locations), rather than to locations where prevalence is measured, improved model performance. A remotely sensed water index and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated. In the study area, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following deworming). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.
    UNBIS Thesaurus SCHISTOSOMIASIS
    REMOTE SENSING
    Keyword Risk
    Spatial predication
    Access
    Copyright Holder Kulinkina et al.
    Copyright Year 2018
    Copyright type Creative commons
    DOI 10.1371/journal.pntd.0006517
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    Created: Tue, 08 Jan 2019, 21:46:14 JST by Aarti Basnyat on behalf of UNU EHS