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Editorials: 50 years since the first surgeon general's report on smoking and health: A happy anniversary?

机译:社论:自第一位外科医生关于吸烟与健康的报告发表以来已有50年:周年快乐?

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This article attempts to quantify the risk to Europe of dengue, following the arrival and spread there of one of dengue's vector species Aedes (Stegomyia) albopictus. A global risk map for dengue is presented, based on a global database of the occurrence of this disease, derived from electronic literature searches. Remotely sensed satellite data (from NASA's MODIS series), interpolated meteorological data, predicted distribution maps of dengue's two main vector species, Aedes aegypti and Aedes albopictus, a digital elevation surface and human population density data were all used as potential predictor variables in a non-linear discriminant analysis modelling framework. One hundred bootstrap models were produced by randomly sub-sampling three different training sets for dengue fever, severe dengue (i.e. dengue haemorrhagic fever, DHF) and all-dengue, and output predictions were averaged to produce a single global risk map for each type of dengue. This paper concentrates on the all-dengue models. Key predictor variables were various thermal data layers, including both day- and night-time Land Surface Temperature, human population density, and a variety of rainfall variables. The relative importance of each may be shown visually using rainbow files and quantitatively using a ranking system. Vegetation Index variables (a common proxy for humidity or saturation deficit) were rarely chosen in the models. The kappa index of agreement indicated an excellent (dengue haemorrhagic fever, Cohen's kappa. = 0.79. ±. 0.028, AUC. = 0.96. ±. 0.007) or good fit of the top ten models in each series to the data (Cohen's kappa. = 0.73. ±. 0.018, AUC. = 0.94. ±. 0.007 for dengue fever and 0.74. ±. 0.017, AUC. = 0.95. ±. 0.005 for all dengue). The global risk map predicts widespread dengue risk in SE Asia and India, in Central America and parts of coastal South America, but in relatively few regions of Africa. In many cases these are less extensive predictions than those of other published dengue risk maps and arise because of the key importance of high human population density for the all-dengue risk maps produced here. Three published dengue risk maps are compared using the Fleiss kappa index, and are shown to have only fair agreement globally (Fleiss kappa. = 0.377). Regionally the maps show greater (but still only moderate) agreement in SE Asia (Fleiss kappa. = 0.566), fair agreement in the Americas (Fleiss kappa. = 0.325) and only slight agreement in Africa (Fleiss kappa. = 0.095). The global dengue risk maps show that very few areas of rural Europe are presently suitable for dengue, but several major cities appear to be at some degree of risk, probably due to a combination of thermal conditions and high human population density, the top two variables in many models. Mahalanobis distance images were produced of Europe and the southern United States showing the distance in environmental rather than geographical space of each site from any site where dengue currently occurs. Parts of Europe are quite similar in Mahalanobis distance terms to parts of the southern United States, where dengue occurred in the recent past and which remain environmentally suitable for it. High standards of living rather than a changed environmental suitability keep dengue out of the USA. The threat of dengue to Europe at present is considered to be low but sufficiently uncertain to warrant monitoring in those areas of greatest predicted environmental suitability, especially in northern Italy and parts of Austria, Slovenia and Croatia, Bosnia and Herzegovina, Serbia and Montenegro, Albania, Greece, south-eastern France, Germany and Switzerland, and in smaller regions elsewhere.
机译:本文试图量化登革热媒介之一伊蚊(Stegomyia)albopictus到那里传播之后,登革热对欧洲的危害。基于从电子文献搜索中得出的该疾病发生的全球数据库,展示了登革热的全球风险图。遥感卫星数据(来自NASA的MODIS系列),内插的气象数据,登革热的两个主要媒介物种埃及伊蚊和白纹伊蚊的预测分布图,数字高程图和人口密度数据均被用作非霍乱中的潜在预测变量。 -线性判别分析建模框架。通过随机抽样三种不同的登革热,严重登革热(即登革出血热,DHF)和全登革热训练集,生成了一百个自举模型,并对输出预测值进行平均,以针对每种类型的登革热产生单一的全球风险图登革热。本文着重于全登革热模型。关键的预测变量是各种热数据层,包括白天和晚上的陆地表面温度,人口密度以及各种降雨变量。可以使用Rainbow文件直观地显示每个对象的相对重要性,并使用排名系统定量显示每个对象的相对重要性。在模型中很少选择植被指数变量(湿度或饱和度不足的常见替代指标)。 kappa指数表示良好(登革出血热,Cohen's kappa。= 0.79。±。0.028,AUC。= 0.96。±。0.007)或每个系列中排名前十的模型与数据的良好拟合(Cohen's kappa。对于登革热,= 0.73±0.018,AUC。= 0.94。±0.007;对于所有登革热,为0.74。±0.017,AUC。= 0.95。±0.005)。全球风险图谱预测,东南亚和印度,中美洲和南美洲沿海部分地区将有广泛的登革热风险,但在非洲的相对少数地区。在许多情况下,与其他已发布的登革热风险图相比,这些预测没有那么广泛,并且由于高人口密度对于此处生成的所有登革热风险图的关键重要性而产生。使用Fleiss kappa指数比较了三个已发布的登革热风险图,显示它们在全球范围内只有公平的共识(Fleiss kappa = 0.377)。从区域来看,地图显示东南亚地区(Fleiss kappa。= 0.566)有更大的协议(但仍然只是中等水平),美洲地区(Fleiss kappa。= 0.325)有公平的协议,而非洲则只有轻微的协议(Fleiss kappa。= 0.095)。全球登革热风险图显示,目前欧洲农村地区几乎没有适合登革热的地区,但几个主要城市似乎处于一定程度的风险,这可能是由于高温条件和高人口密度共同造成的,前两个变量在许多模型中。从欧洲和美国南部拍摄的马哈拉诺比斯距离图像显示了距目前登革热发生地点的每个地点在环境而非地理空间中的距离。在马哈拉诺比斯距离方面,欧洲部分地区与美国南部的地区非常相似,美国南部地区的登革热是最近发生的,并且在环境上仍然适合该地区。高生活水平而不是改变的环境适应性将登革热排除在美国之外。目前认为登革热对欧洲的威胁很小,但不确定性足以确保在预期的环境适宜性最高的地区进行监测,尤其是在意大利北部以及奥地利,斯洛文尼亚和克罗地亚的部分地区,波斯尼亚和黑塞哥维那,塞尔维亚和黑山,阿尔巴尼亚的部分地区,希腊,法国东南部,德国和瑞士,以及其他地区的较小区域。

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