Journal Article

Optimized strategy for schistosomiasis elimination: results from marginal benefit modeling

Jia, Tie-Wu, Lv, Chao, Zhou, Xiao-Nong, Xu, Jing, Yang, Guo-Jing, Li, Qin, Zhang, Li-Juan, Zheng, Jin-Xin, Feng, Xin-Yu

2023

Overview

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 2 of 0.7308. Results showed that risk surveillance, snail control with molluscicides and treatment were the most effective interventions in controlling schistosomiasis prevalence. The best combination of interventions was interlacing seven interventions, including risk surveillance, treatment, toilet construction, health education, snail control with molluscicides, cattle slaughter and animal chemotherapy. The marginal benefit of risk surveillance is the most effective intervention among nine interventions, which was influenced by the prevalence of schistosomiasis and cost. Conclusions In the elimination phase of the national schistosomiasis program, emphasizing risk surveillance holds significant importance in terms of cost-saving. Graphical Abstract

• Publisher: BioMed Central,BioMed Central Ltd,Springer Nature B.V,BMC
• Subject: Analysis / Biomedical and Life Sciences / Biomedicine / cattle / Chemotherapy / China / Control / Cost analysis / Cost-effectiveness / Costs / Discount rates / drug therapy / Economic aspects / Elimination of infectious diseases of poverty as a key contribution to achieving the SDGs / Endemic diseases / Entomology / GDP / Generalized linear models / Gross Domestic Product / Health aspects / Health education / Infection control / Infections / Infectious Diseases / Integrated control strategy / Intervention / linear models / Livestock / Machine learning / Machine learning analysis / Marginal benefit analysis / Methods / Missing data / Modeling / Molluscicides / Mollusks / monitoring / Neural networks / Parasitology / Poverty / prediction / Regression analysis / Regression models / risk / Risk management / Schistosomiasis / Schistosomiasis elimination / slaughter / snails / Statistical models / Support vector machines / Surveillance / Tropical Medicine / Veterinary Medicine/Veterinary Science / Virology