Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Pavillon de la santé publique, Université de Montréal, Saint-Hyacinthe, Québec, Canada.
Int J Health Geogr. 2011 Dec 29;10:70. doi: 10.1186/1476-072X-10-70.
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.
虫媒传染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重大挑战,特别是在社会和环境快速变化的情况下。已经针对许多重要的虫媒传染病开发了基于环境因素(如气候和景观)预测疾病风险的空间模型。由此产生的风险图对于突出公共卫生计划的目标区域具有重要价值。然而,这些方法通常仅提供疾病风险空间分布的技术信息,对于在复杂情况下做出决策可能不够完整。在确定监测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明确信息,例如公众接受度的区域特异性、人口脆弱性、资源可用性、干预效果和土地利用。需要制定一种统一的策略来支持公共卫生决策,该策略将评估空间明确疾病风险的现有数据与其他标准相结合,以实施有效的预防和控制策略。多准则决策分析 (MCDA) 是一种决策支持工具,允许使用数据驱动和定性指标来考虑多种定量和定性标准,以透明和利益相关者参与的方式评估替代策略。在这里,我们提出了一种基于 MCDA 的方法来开发空间模型和空间明确的决策支持工具,以管理虫媒传染病。我们描述了 MCDA 提供的概念框架以及技术考虑因素、实施方法和预期结果。我们得出的结论是,MCDA 是一种强大的工具,具有在一般公共卫生决策和特别是虫媒传染病管理中应用的巨大潜力。