Research Incubator Public Health and Infection, School of Medicine, Faculty of Health Sciences, Universidad Tecnológica de Pereira (UTP), Pereira, Risaralda, Colombia.
Department of Community Medicine, Faculty of Health Sciences, Universidad Tecnológica de Pereira (UTP), Pereira, Risaralda, Colombia; Public Health Direction, Department Health Secretary of Risaralda, Pereira, Risaralda, Colombia.
J Infect Public Health. 2015 May-Jun;8(3):291-7. doi: 10.1016/j.jiph.2014.11.005. Epub 2015 Jan 3.
Dengue continues to be the most important viral vector-borne disease in the world, particularly in Asia and Latin America, and is significantly affected by climate variability. The influence of climate in an endemic region of Colombia, from 2010 to 2011, was assessed. Epidemiological surveillance data (weekly cases) were collected, and incidence rates were calculated. Poisson regression models were used to assess the influence of the macroclimatic variable ONI (Oscillation Niño Index) and the microclimatic variable pluviometry (mm of rain for Risaralda) on the dengue incidence rate, adjusting by year and week. During the study period, 13,650 cases were reported. In 2010, the rates ranged from 8.6 cases/100,000 pop. up to a peak of 75.3 cases/100,000 pop. for a cumulative rate of 456.2 cases/100,000 pop. in that week. The climate variability in 2010 was higher (ONI 1.6, El Niño to -1.5, La Niña) than in 2011 (ONI -1.4, La Niña to -0.2, Neutral). The mean pluviometry was 248.45mm (min 135.9-max 432.84). During El Niño, cases were significantly higher (mean 433.81) than during the climate neutral period (142.48) and during the La Niña (52.80) phases (ANOVA F=66.59; p<0.001). Regression models showed that the ONI (coefficient 0.329; 95%CI 0.209-0.450) and pluviometry (coefficient 0.003; 95%CI 0.002-0.004) were highly significant independent variables associated with dengue incidence rate, after adjusting by year and week (p<0.001, pseudo r(2)=0.6913). El Niño significantly affected the incidence of dengue in Risaralda. This association with climate change and variability should be considered in the elements influencing disease epidemiology. In addition, predictive models should be developed further with more available data from disease surveillance.
登革热仍然是世界上最重要的病毒性媒介传播疾病，特别是在亚洲和拉丁美洲，且其发病率明显受气候变异性的影响。本研究评估了 2010 年至 2011 年哥伦比亚一流行地区的气候影响。收集了流行病学监测数据（每周病例数），并计算了发病率。采用泊松回归模型，调整年份和周数后，评估了宏气候变量 ONI（厄尔尼诺南方涛动指数）和微气候变量降雨量（里萨拉尔达降雨量，mm）对登革热发病率的影响。研究期间，报告了 13650 例病例。2010 年，发病率范围为 8.6/100000 人口至 75.3/100000 人口的峰值，当周累计发病率为 456.2/100000 人口。2010 年的气候变率较高（ONI 为 1.6，厄尔尼诺至-1.5，拉尼娜），而 2011 年的气候变率较低（ONI 为-1.4，拉尼娜至-0.2，中性）。平均降雨量为 248.45mm（最小 135.9mm，最大 432.84mm）。在厄尔尼诺期间，病例数明显高于气候中性期（平均 433.81）和拉尼娜期（52.80）（方差分析 F=66.59；p<0.001）。回归模型显示，ONI（系数 0.329；95%CI 0.209-0.450）和降雨量（系数 0.003；95%CI 0.002-0.004）是与登革热发病率高度相关的独立变量，调整年份和周数后仍有统计学意义（p<0.001，伪 r(2)=0.6913）。厄尔尼诺显著影响了里萨拉尔达登革热的发病率。在考虑疾病流行病学影响因素时，应考虑到这种与气候变化和变率的关联。此外，应进一步利用疾病监测的更多可用数据开发预测模型。
