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Sequential Modelling of the Effects of Mass Drug Treatments on Anopheline-Mediated Lymphatic Filariasis Infection in Papua New Guinea

机译:药物治疗对巴布亚新几内亚的按蚊碱介导的淋巴丝虫病感染的影响的顺序模型

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摘要

BackgroundLymphatic filariasis (LF) has been targeted by the WHO for global eradication leading to the implementation of large scale intervention programs based on annual mass drug administrations (MDA) worldwide. Recent work has indicated that locality-specific bio-ecological complexities affecting parasite transmission may complicate the prediction of LF extinction endpoints, casting uncertainty on the achievement of this initiative. One source of difficulty is the limited quantity and quality of data used to parameterize models of parasite transmission, implying the important need to update initially-derived parameter values. Sequential analysis of longitudinal data following annual MDAs will also be important to gaining new understanding of the persistence dynamics of LF. Here, we apply a Bayesian statistical-dynamical modelling framework that enables assimilation of information in human infection data recorded from communities in Papua New Guinea that underwent annual MDAs, into our previously developed model of parasite transmission, in order to examine these questions in LF ecology and control.
机译:背景世界卫生组织已将淋巴丝虫病(LF)定位为全球根除目标,从而导致在世界范围内根据每年的大规模药物管理(MDA)实施大规模干预计划。最近的工作表明,影响寄生虫传播的因地而异的生物生态复杂性可能会使LF灭绝终点的预测复杂化,从而使该计划的实现变得不确定。困难的来源之一是用于参数化寄生虫传播模型的数据数量和质量有限,这意味着更新初始派生参数值的重要需求。在年度MDA之后对纵向数据进行顺序分析对于获得对LF持久性动力学的新认识也很重要。在这里,我们将贝叶斯统计动态建模框架应用于我们以前开发的寄生虫传播模型,该框架能够将经历了年度MDA的巴布亚新几内亚社区记录的人类感染数据中的信息同化,以研究LF生态学中的这些问题和控制。

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