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Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

机译:病媒传播疾病的空间显式多标准决策分析

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The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular.
机译:媒介传播疾病的复杂流行病学给预防和控制策略的设计和实施带来了巨大挑战,尤其是在社会和环境迅速变化的情况下。已经针对许多重要的媒介传播疾病开发了基于环境因素(例如气候和景观)来预测疾病风险的空间模型。由此产生的风险图对于突出针对公共卫生计划的领域具有证明的价值。但是,这些方法通常仅提供有关疾病风险本身的空间分布的技术信息,对于复杂情况下的决策而言,这些信息可能并不完整。在确定监视和干预策略的优先级时,决策者通常还需要考虑其他重要方面的空间上明确的信息,例如公众接受程度,人口脆弱性,资源可用性,干预效果和土地利用等区域特异性。需要一种支持公共卫生决策的统一策略,该策略将用于评估空间显性疾病风险的可用数据与其他标准相结合,以实施有效的预防和控制策略。多标准决策分析(MCDA)是一种决策支持工具,可使用数据驱动和定性指标来考虑各种定量和定性标准,以评估具有透明度和利益相关者参与的替代策略。在这里,我们提出了一种基于MCDA的方法来开发地理空间模型和用于病媒传播疾病管理的空间明确的决策支持工具。我们描述了MCDA提供的概念框架以及技术方面的考虑,实施方法和预期成果。我们得出的结论是,MCDA是一种强大的工具,具有广泛的潜力,可用于一般,尤其是病媒传播疾病管理的公共卫生决策。

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