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首页> 外文期刊>Parasitology >LYMFASIM, a simulation model for predicting the impact of lymphatic filariasis control: quantification for African villages.
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LYMFASIM, a simulation model for predicting the impact of lymphatic filariasis control: quantification for African villages.

机译：LYMFASIM，用于预测淋巴丝虫病控制效果的模拟模型：非洲村庄的量化。

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摘要

LYMFASIM is a simulation model for lymphatic filariasis transmission and control. We quantified its parameters to simulate Wuchereria bancrofti transmission by Anopheles mosquitoes in African villages, using a wide variety of reported data. The developed model captures the general epidemiological patterns, but also the differences between communities. It was calibrated to represent the relationship between mosquito biting rate and the prevalence of microfilariae (mf) in the human population, the age-pattern in mf prevalence, and the relation between mf prevalence and geometric mean mf intensity. Explorative simulations suggest that the impact of mass treatment depends strongly on the mosquito biting rate and on the assumed coverage, compliance and efficacy. Our sensitivity analysis showed that some biological parameters strongly influence the predicted equilibrium pre-treatment mf prevalence (e.g. the lifespan of adult worms and mf). Other parameters primarily affect the post-treatment trends (e.g. severity of density dependence in the mosquito uptake of infection from the human blood, between-person variability in exposure to mosquito bites). The longitudinal data, which are being collected for evaluation of ongoing elimination programmes, can help to further validate the model. The model can help to assess when ongoing elimination activities in African populations can be stopped and to design surveillance schemes. It can be a valuable tool for decision making in the Global Programme to Eliminate Lymphatic Filariasis.
机译：LYMFASIM是淋巴丝虫病传播和控制的模拟模型。我们使用各种报道的数据，对它的参数进行了量化，以模拟非洲村庄中按蚊在非洲村庄传播的乌氏假单胞菌传播。所开发的模型既捕获了一般的流行病学模式，也捕获了社区之间的差异。进行了校准，以表示蚊虫叮咬率与人口中微丝aria病（mf）的患病率，mf患病率的年龄模式以及mf患病率与几何平均mf强度之间的关系。探索性模拟表明，大规模治疗的影响在很大程度上取决于蚊虫的叮咬率以及假定的覆盖率，依从性和功效。我们的敏感性分析表明，某些生物学参数会强烈影响预计的平衡预处理mf患病率（例如成虫和mf的寿命）。其他参数主要影响治疗后的趋势（例如，蚊子吸收人血中密度依赖性的严重性，蚊虫叮咬的人与人之间的变异性）。正在收集纵向数据以评估进行中的消除计划，这些数据可以帮助进一步验证模型。该模型可以帮助评估何时可以停止在非洲人口中进行的消除活动，并设计监测方案。它可以成为全球消除淋巴丝虫病计划中决策的宝贵工具。

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