Article ; Online: Optimized strategy for schistosomiasis elimination: results from marginal benefit modeling.
2023 Volume 16, Issue 1, Page(s) 419
Abstract: Background: Poverty contributes to the transmission of schistosomiasis via multiple pathways, with the insufficiency of appropriate interventions being a crucial factor. The aim of this article is to provide more economical and feasible intervention ... ...
Abstract | Background: Poverty contributes to the transmission of schistosomiasis via multiple pathways, with the insufficiency of appropriate interventions being a crucial factor. The aim of this article is to provide more economical and feasible intervention measures for endemic areas with varying levels of poverty. Methods: We collected and analyzed the prevalence patterns along with the cost of control measures in 11 counties over the last 20 years in China. Seven machine learning models, including XGBoost, support vector machine, generalized linear model, regression tree, random forest, gradient boosting machine and neural network, were used for developing model and calculate marginal benefits. Results: The XGBoost model had the highest prediction accuracy with an R Conclusions: In the elimination phase of the national schistosomiasis program, emphasizing risk surveillance holds significant importance in terms of cost-saving. |
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MeSH term(s) | Animals ; Cattle ; Schistosomiasis/epidemiology ; Schistosomiasis/prevention & control ; Schistosomiasis/drug therapy ; Molluscacides/pharmacology ; China/epidemiology ; Snails ; Prevalence |
Chemical Substances | Molluscacides |
Language | English |
Publishing date | 2023-11-15 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 2409480-8 |
ISSN | 1756-3305 ; 1756-3305 |
ISSN (online) | 1756-3305 |
ISSN | 1756-3305 |
DOI | 10.1186/s13071-023-06001-x |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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