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Advances and challenges in predicting the impact of lymphatic filariasis elimination programmes by mathematical modelling

机译:通过数学模型预测淋巴丝虫病消除计划的影响方面的进展和挑战

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摘要

Mathematical simulation models for transmission and control of lymphatic filariasis are useful tools for studying the prospects of lymphatic filariasis elimination. Two simulation models are currently being used. The first, EPIFIL, is a population-based, deterministic model that simulates average trends in infection intensity over time. The second, LYMFASIM, is an individual-based, stochastic model that simulates acquisition and loss of infection for each individual in the simulated population, taking account of individual characteristics. For settings like Pondicherry (India), where Wuchereria bancrofti infection is transmitted by Culex quinquefasciatus, the models give similar predictions of the coverage and number of treatment rounds required to bring microfilaraemia prevalence below a level of 0.5%. Nevertheless, published estimates of the duration of mass treatment required for elimination differed, due to the use of different indicators for elimination (EPIFIL: microfilaraemia prevalence < 0.5% after the last treatment; LYMFASIM: reduction of microfilaraemia prevalence to zero, within 40 years after the start of mass treatment). The two main challenges for future modelling work are: 1) quantification and validation of the models for other regions, for investigation of elimination prospects in situations with other vector-parasite combinations and endemicity levels than in Pondicherry; 2) application of the models to address a range of programmatic issues related to the monitoring and evaluation of ongoing control programmes. The models' usefulness could be enhanced by several extensions; inclusion of different diagnostic tests and natural history of disease in the models is of particular relevance.
机译:用于淋巴丝虫病传播和控制的数学模拟模型是研究消除淋巴丝虫病前景的有用工具。当前正在使用两个仿真模型。第一个是EPIFIL,它是基于人群的确定性模型,可以模拟一段时间内感染强度的平均趋势。第二个是LYMFASIM,它是一个基于个体的随机模型,该模型考虑了个体特征,模拟了模拟种群中每个个体的感染情况和感染损失情况。对于像Pondicherry(印度)这样的地方,班克斯氏库蚊传播了Wuchereria bancrofti感染,这些模型对使微丝虫病患病率降至0.5%以下所需的治疗范围和治疗轮次做出了类似的预测。但是,由于使用了不同的消除指标,已公布的消除大规模治疗持续时间的估计值有所不同(EPIFIL:上次治疗后微丝蛋白血症患病率<0.5%; LYMFASIM:微丝蛋白血症患病率在术后40年内降至零开始大规模治疗)。未来的建模工作面临的两个主要挑战是:1)对其他地区的模型进行量化和验证,以调查与庞迪榭里地区不同的媒介-寄生虫组合和地方性流行情况下的消除前景; 2)应用模型来解决与正在进行的控制计划的监视和评估有关的一系列计划问题。可以通过几个扩展来增强模型的实用性。在模型中包含不同的诊断测试和自然疾病史具有特殊意义。

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