Predictive vs. Empiric Assessment of Schistosomiasis: Implications for Treatment Projections in Ghana |
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| Authors: | Achille Kabore Nana-Kwadwo Biritwum Philip W. Downs Ricardo J. Soares Magalhaes Yaobi Zhang Eric A. Ottesen |
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| Affiliation: | 1RTI International, Washington, District of Columbia, United States of America;2Neglected Tropical Diseases Control Programme, Ghana Health Service, Accra, Ghana;3University of Queensland, Infectious Disease Epidemiology Unit, School of Population Health, Brisbane, Australia;4Helen Keller International, Regional Office for Africa, Dakar, Senegal;London School of Hygiene & Tropical Medicine, United Kingdom |
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| Abstract: | BackgroundMapping the distribution of schistosomiasis is essential to determine where control programs should operate, but because it is impractical to assess infection prevalence in every potentially endemic community, model-based geostatistics (MBG) is increasingly being used to predict prevalence and determine intervention strategies.Conclusions/SignificanceUsing the current predictive map for Ghana as a spatial decision support tool by aggregating prevalence estimates to the district level was clearly not adequate for guiding the national program, but the alternative of assessing each school in potentially endemic areas of Ghana or elsewhere is not at all feasible; modelling must be a tool complementary to empiric assessments. Thus for practical usefulness, predictive risk mapping should not be thought of as a one-time exercise but must, as in the current study, be an iterative process that incorporates empiric testing and model refining to create updated versions that meet the needs of disease control operational managers. |
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