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The role of simple mathematical models in malaria elimination strategy design

机译:简单数学模型在消除疟疾策略设计中的作用

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Background Malaria has recently been identified as a candidate for global eradication. This process will take the form of a series of national eliminations. Key issues must be considered specifically for elimination strategy when compared to the control of disease. Namely the spread of drug resistance, data scarcity and the adverse effects of failed elimination attempts. Mathematical models of various levels of complexity have been produced to consider the control and elimination of malaria infection. If available, detailed data on malaria transmission (such as the vector life cycle and behaviour, human population behaviour, the acquisition and decay of immunity, heterogeneities in transmission intensity, age profiles of clinical and subclinical infection) can be used to populate complex transmission models that can then be used to design control strategy. However, in many malaria countries reliable data are not available and policy must be formed based on information like an estimate of the average parasite prevalence. Methods A simple deterministic model, that requires data in the form of a single estimate of parasite prevalence as an input, is developed for the purpose of comparison with other more complex models. The model is designed to include key aspects of malaria transmission and integrated control. Results The simple model is shown to have similar short-term dynamic behaviour to three complex models. The model is used to demonstrate the potential of alternative methods of delivery of controls. The adverse effects on clinical infection and spread of resistance are predicted for failed elimination attempts. Since elimination strategies present an increased risk of the spread of drug resistance, the model is used to demonstrate the population level protective effect of multiple controls against this very serious threat. Conclusion A simple model structure for the elimination of malaria is suitable for situations where data are sparse yet strategy design requirements are urgent with the caveat that more complex models, populated with new data, would provide more information, especially in the long-term.
机译:背景技术最近,疟疾已被确定为全球根除疟疾的候选人。此过程将采取一系列国家淘汰的形式。与疾病控制相比,必须专门针对消除策略考虑关键问题。即耐药性的蔓延,数据缺乏和消除尝试失败的不利影响。已经产生了各种复杂程度的数学模型来考虑控制和消除疟疾感染。如果有的话,可以使用有关疟疾传播的详细数据(例如媒介生命周期和行为,人口行为,免疫力的获取和衰减,传播强度的异质性,临床和亚临床感染的年龄分布)来填充复杂的传播模型然后可以用来设计控制策略。但是,在许多疟疾国家,没有可靠的数据,必须根据诸如平均寄生虫流行率的估计值之类的信息来制定政策。方法为了与其他更复杂的模型进行比较,开发了一个简单的确定性模型,该模型需要将寄生虫患病率的单个估计形式的数据作为输入。该模型旨在包括疟疾传播和综合控制的关键方面。结果该简单模型显示出与三个复杂模型相似的短期动态行为。该模型用于证明替代方法的潜力。对于消除失败的尝试,预测了对临床感染和耐药性扩散的不利影响。由于消除策略会增加耐药性扩散的风险,因此该模型用于证明针对此非常严重威胁的多种控制措施在人群水平上的保护作用。结论消除疟疾的简单模型结构适用于数据稀少而策略设计要求迫切的情况,需要注意的是,用新数据填充的更复杂的模型将提供更多的信息,尤其是从长期来看。

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