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Mapping multiple components of malaria risk for improved targeting of elimination interventions

机译:绘制疟疾风险的多个组成部分以更好地确定消除干预措施的目标

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摘要

There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National malaria programmes typically make operational decisions about where to implement vector control and surveillance activities based upon simple categorizations of annual parasite incidence. With technological advances, an enormous opportunity exists to better target specific malaria interventions to the places where they will have greatest impact by mapping and evaluating metrics related to a variety of risk components, each of which describes a different facet of the transmission cycle. Here, these components and their implications for operational decision-making are reviewed. For each component, related mappable malaria metrics are also described which may be measured and evaluated by malaria programmes seeking to better understand the determinants of malaria risk. Implementing tailored programmes based on knowledge of the heterogeneous distribution of the drivers of malaria transmission rather than only consideration of traditional metrics such as case incidence has the potential to result in substantial improvements in decision-making. As programmes improve their ability to prioritize their available tools to the places where evidence suggests they will be most effective, elimination aspirations may become increasingly feasible.
机译:通过使用数学模型来考虑疟疾风险和疟疾传播周期的组成成分已有很长的历史,然而,流行国家的战略规划往往没有充分利用现有的疾病情报来制定干预措施。国家疟疾规划通常会根据年度寄生虫发病率的简单分类,制定有关在何处实施病媒控制和监测活动的运营决策。随着技术的进步,存在巨大的机会,可以通过绘制和评估与各种风险成分相关的指标,将特定的疟疾干预措施更好地针对那些将对疟疾产生最大影响的地方,每个指标都描述了传播周期的不同方面。在此,对这些组件及其对运营决策的影响进行了回顾。对于每个组成部分,还描述了相关的可映射疟疾指标,可以通过疟疾计划进行测量和评估,以更好地了解疟疾风险的决定因素。基于对疟疾传播驱动因素的异质性分布的了解而实施量身定制的计划,而不是仅仅考虑传统的指标(例如病例发生率),就可能会极大地改善决策。随着计划提高将可用工具的优先级放到证据表明它们最有效的地方的能力,消除期望可能变得越来越可行。

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