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Potential impacts of climate variability on Dengue Hemorrhagic Fever in Honduras, 2010

机译:气候变化对洪都拉斯登革热出血热的潜在影响,2010年

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Climate change and variability are affecting human health and disease direct or indirectly through many mechanisms. Dengue is one of those diseases that is strongly influenced by climate variability; however its study in Central America has been poorly approached. In this study, we assessed potential associations between macroclimatic and microclimatic variation and dengue hemorrhagic fever (DHF) cases in the main hospital of Honduras during 2010. In this year, 3,353 cases of DHF were reported in the Hospital Escuela, Tegucigalpa. Climatic periods marked a difference of 158% in the mean incidence of cases, from El Ni?o weeks (-99% of cases below the mean incidence) to La Ni?a months (+59% of cases above it) (p0.01). Linear regression showed significantly higher dengue incidence with lower values of Oceanic Ni?o Index (p=0.0097), higher rain probability (p=0.0149), accumulated rain (p=0.0443) and higher relative humidity (p=0.0292). At a multiple linear regression model using those variables, ONI values shown to be the most important and significant factor found to be associated with the monthly occurrence of DHF cases (r 2=0.649; β standardized=-0.836; p=0.01). As has been shown herein, climate variability is an important element influencing the dengue epidemiology in Honduras. However, it is necessary to extend these studies in this and other countries in the Central America region, because these models can be applied for surveillance as well as for prediction of dengue.
机译:气候变化和多变性通过许多机制直接或间接影响着人类健康和疾病。登革热是受气候变化强烈影响的疾病之一。然而,在中美洲的研究却很少。在这项研究中,我们评估了洪都拉斯主要医院2010年大气候和小气候变化与登革出血热(DHF)病例之间的潜在关联。今年,特古西加尔巴Escuela医院报告了3353例DHF病例。从El Ni?o周(低于平均发生率的-99%)到La Ni?a月(高于平均发生率的+ 59%),气候周期的平均发病率差异了158%。 0.01)。线性回归显示登革热发病率显着较高,而海洋Ni?o指数较低(p = 0.0097),降雨概率较高(p = 0.0149),累积降雨(p = 0.0443)和相对湿度较高(p = 0.0292)。在使用这些变量的多元线性回归模型中,ONI值被证明是与DHF病例每月发生相关的最重要和显着因素(r 2 = 0.649;β标准化= -0.836; p = 0.01)。如本文所示,气候变化是影响洪都拉斯登革热流行病学的重要因素。但是,有必要将这些研究扩展到中美洲地区的这个国家和其他国家,因为这些模型可以用于监视以及登革热的预测。

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