Sánchez-Gómez Amaya, Amela Carmen, Fernández-Carrión Eduardo, Martínez-Avilés Marta, Sánchez-Vizcaíno José Manuel, Sierra-Moros María José
Coordinating Centre for Health Alerts and Emergencies, General Directorate of Public Health, Quality and Innovation, Ministry of Health, Social Services and Equality, Madrid, Spain Paseo del Prado 18-20, 28071 Madrid, Spain.
VISAVET Centre and Animal Health Department, Faculty of Veterinary Sciences, Complutense University, Avenida Puerta de Hierro, s/n, 28040 Madrid, Spain.
Acta Trop. 2017 May;169:163-169. doi: 10.1016/j.actatropica.2017.02.022. Epub 2017 Feb 16.
West Nile fever is an emergent disease in Europe. The objective of this study was to conduct a predictive risk mapping of West Nile Virus (WNV) circulation in Spain based on historical data of WNV circulation. Areas of Spain with evidence of WNV circulation were mapped based on data from notifications to the surveillance systems and a literature review. A logistic regression-based spatial model was used to assess the probability of WNV circulation. Data were analyzed at municipality level. Mean temperatures of the period from June to October, presence of wetlands and presence of Special Protection Areas for birds were considered as potential predictors. Two predictors of WNV circulation were identified: higher temperature [adjusted odds ratio (AOR) 2.07, 95% CI 1.82-2.35, p<0.01] and presence of wetlands (3.37, 95% CI 1.89-5.99, p<0.01). Model validations indicated good predictions: area under the ROC curve was 0.895 (95% CI 0.870-0.919) for internal validation and 0.895 (95% CI 0.840-0.951) for external validation. This model could support improvements of WNV risk- based surveillance in Spain. The importance of a comprehensive surveillance for WNF, including human, animal and potential vectors is highlighted, which could additionally result in model refinements.
西尼罗河热是欧洲一种新出现的疾病。本研究的目的是根据西尼罗河病毒（WNV）传播的历史数据，对西班牙WNV传播进行预测性风险绘图。根据向监测系统报告的数据和文献综述，绘制出西班牙有WNV传播证据的区域。使用基于逻辑回归的空间模型来评估WNV传播的概率。数据在市镇层面进行分析。将6月至10月期间的平均温度、湿地的存在以及鸟类特别保护区的存在视为潜在预测因素。确定了WNV传播的两个预测因素：较高温度[调整优势比（AOR）2.07，95%置信区间1.82 - 2.35，p<0.01]和湿地的存在（3.37，95%置信区间1.89 - 5.99，p<0.01）。模型验证表明预测效果良好：内部验证的ROC曲线下面积为0.895（95%置信区间0.870 - 0.919），外部验证的为0.895（95%置信区间0.840 - 0.951）。该模型可支持改进西班牙基于WNV风险的监测。强调了对西尼罗河热进行全面监测的重要性，包括对人类、动物和潜在病媒的监测，这还可能导致模型的完善。
