Dataset Information

Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.

ABSTRACT:

Background

The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated.

Methodology/principal findings

We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d'Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2-20) and children per school (10-50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2-5 schools per district failed to detect schistosomiasis in low endemicity areas (1-10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20-30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15-20 schools per district.

Conclusions/significance

Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15-20 schools per district and 20-30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose.

SUBMITTER: Knowles SCL

PROVIDER: S-EPMC5464666 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Publications

Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.

Knowles Sarah C L SCL Sturrock Hugh J W HJW Turner Hugo H Whitton Jane M JM Gower Charlotte M CM Jemu Samuel S Phillips Anna E AE Meite Aboulaye A Thomas Brent B Kollie Karsor K Thomas Catherine C Rebollo Maria P MP Styles Ben B Clements Michelle M Fenwick Alan A Harrison Wendy E WE Fleming Fiona M FM

PLoS neglected tropical diseases 20170526 5

<h4>Background</h4>The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated.<h4>Methodology/principal findings</h4>We used baseline schistosomiasis mapping surveys from three countries ...[more]

PMID: 28552961

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Project description:BackgroundOver the past 20 years, schistosomiasis control has been scaled up. Preventive chemotherapy with praziquantel is the main intervention. We aimed to assess the effect of preventive chemotherapy on schistosomiasis prevalence in sub-Saharan Africa, comparing 2000-10 with 2011-14 and 2015-19.MethodsIn this spatiotemporal modelling study, we analysed survey data from school-aged children (aged 5-14 years) in 44 countries across sub-Saharan Africa. The data were extracted from the Global Neglected Tropical Diseases database and augmented by 2018 and 2019 survey data obtained from disease control programmes. Bayesian geostatistical models were fitted to Schistosoma haematobium and Schistosoma mansoni survey data. The models included data on climatic predictors obtained from satellites and other open-source environmental databases and socioeconomic predictors obtained from various household surveys. Temporal changes in Schistosoma species prevalence were estimated by a categorical variable with values corresponding to the three time periods (2000-10, 2011-14, and 2015-19) during which preventive chemotherapy interventions were scaled up.FindingsWe identified 781 references with relevant geolocated schistosomiasis survey data for 2000-19. There were 19 166 unique survey locations for S haematobium and 23 861 for S mansoni, of which 77% (14 757 locations for S haematobium and 18 372 locations for S mansoni) corresponded to 2011-19. Schistosomiasis prevalence among school-aged children in sub-Saharan Africa decreased from 23·0% (95% Bayesian credible interval 22·1-24·1) in 2000-10 to 9·6% (9·1-10·2) in 2015-19, an overall reduction of 58·3%. The reduction of S haematobium was 67·9% (64·6-71·1) and that of S mansoni 53·6% (45·2-58·3) when comparing 2000-10 with 2015-19.InterpretationOur model-based estimates suggest that schistosomiasis prevalence in sub-Saharan Africa has decreased considerably, most likely explained by the scale-up of preventive chemotherapy. There is a need to consolidate gains in the control of schistosomiasis by means of preventive chemotherapy, coupled with other interventions to interrupt disease transmission.FundingEuropean Research Council and WHO.

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Dataset Information

Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.

Background

Methodology/principal findings

Conclusions/significance

Publications

Optimising cluster survey design for planning schistosomiasis preventive chemotherapy.

Similar Datasets

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