Modeling lymphatic filariasis transmission and eradication in Papua New Guinea

项目描述（由申请人提供）：本项目的主要目的是促进对巴布亚新几内亚（PNG）和其他地方按蚊传播淋巴丝虫病（LF）的流行病学和使用年度大规模药物管理（MDA）策略的控制，并开发和应用有效的基于模型的决策支持工具，以优化社区一级寄生虫控制的设计和评估。该研究将利用最近资助的NIH ICIDR项目收集的过去和新的实地数据，研究基于MDA的策略（包括在MDA中增加媒介控制）对巴布亚新几内亚流行社区丝虫病传播的影响，以实现四个具体目标：1)开发和验证一个专门用于描述巴布亚新几内亚按蚊对LF种群动态的数学模型；2)通过对导出模型的确定性版本与随机版本的比较分析来估计和验证干预终点；3)测试基于MDA的策略的模型预测效果，包括MDA加使用经杀虫剂处理的蚊帐（ITNs）的媒介控制。利用新ICIDR项目收集的这些干预措施效果的经验数据；4)开发和实施一种软件工具，将构建的模型与流行地点的数据联系起来，以促进LF控制项目的优化规划、评估和管理。因此，拟议的研究将基于现有的实地数据，并将由本项目合作者收集，涉及LF干预措施、这些数据的分析/建模以及描述人类和病媒种群感染动态的数据（后者的数据将通过本项目中进行病媒喂养实验收集）和理论分析。这项对全球消灭脊灰规划具有重要意义的工作的主要产出将是：1)基于不同感染标记的疟蚊媒介传播模型的建立；2)寄生虫消灭终点的建立；3)基于模型的评估方案的制定，以评估项目有效性；4)采用种群动态方法对LF控制策略进行经济评估；5)将ITNs媒介控制纳入MDA项目的动态评估。6)构建一个模型和数据集成的软件工具，以帮助LF控制方案的优化设计和评估。

DESCRIPTION (provided by applicant): The chief aims of this project are to advance understanding of the epidemiology of lymphatic filariasis (LF) transmission by anopheline mosquitoes and its control using annual mass drug administration (MDA) strategies in Papua New Guinea (PNG) and elsewhere, and to develop and apply effective model-based decision support tools for optimizing the design and evaluation of parasite control at the community level. The research will take advantage of past and new field data to be collected by a recently funded NIH ICIDR program, on the impacts of MDA-based strategies, including the addition of vector control to MDA, on filariasis transmission in PNG endemic communities, in order to meet four specific aims: 1) development and validation of a mathematical model specific to describing the population dynamics of LF by anopheline mosquitoes in PNG, 2) estimation and validation of intervention endpoints via the comparative analysis of deterministic versus stochastic versions of the derived model, 3) testing model predictions of the impacts of MDA-based strategies, including MDA plus vector control by the use of Insecticide-Treated Bednets (ITNs), using empirical data on the effects of these interventions collected by the new ICIDR program, and 4) development and implementation of a software tool linking the constructed model and data from endemic sites to facilitate the undertaking of optimal planning, evaluation and management of LF control programs. The proposed research will thus be based on field data available and to be collected by the collaborators on this project on LF interventions, the analyses/modeling of these data and data describing infection dynamics in both the human and vector populations (data on the latter to be collected by conducting vector feeding experiments in this project), and theoretical analyses. The major outputs from this work of vital significance to the global LF elimination program will be: 1) the development of models of LF transmission by anopheline vectors based on various markers of infection, 2) the derivation of endpoints for parasite elimination, 3) the development of model-based evaluation protocols for assessing program effectiveness, 4) the taking of a population dynamic approach to economic assessments of LF control strategies, 5) the dynamic evaluation of including vector control via ITNs to MDA programs, and 6) the construction of a model- and data- integrated software tool for aiding the optimal design and evaluation of LF control programs.