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澳大利亚达尔文市中类鼻疽病与气候因素的关联:23 年时间序列分析。

The association of melioidosis with climatic factors in Darwin, Australia: A 23-year time-series analysis.

机构信息

Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, NT 0811, Australia.

Centre for Clinical Vaccinology and Tropical Medicine, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.

出版信息

J Infect. 2016 Jun;72(6):687-697. doi: 10.1016/j.jinf.2016.02.015. Epub 2016 Mar 3.

DOI:10.1016/j.jinf.2016.02.015
PMID:26945846
Abstract

OBJECTIVES

Melioidosis is an often fatal disease in humans and animals and endemic in Southeast Asia and northern Australia. It is caused by the environmental bacterium Burkholderia pseudomallei. We analysed weather and climate factors preceding new melioidosis cases in Darwin and compared the time between weather event and admission to hospital for severe and average wet season rainfall.

METHODS

In a time-series analysis from 1990 to 2013 we applied a boosted regression tree and a negative binomial model to investigate the association between melioidosis cases and weather events. Fitted Fourier terms controlled for long-term seasonal trends.

RESULTS

We found a rise in the dew point, cloud cover, rainfall, maximum temperature and groundwater to be associated with an increased risk to acquire melioidosis. A shorter 'putative' incubation period was evident after severe rainfall events. Rainfall occurring early in the wet season was linked to more cases as was an increase in the local sea surface temperature reflecting local weather dynamics and precipitation.

CONCLUSIONS

Our findings demonstrate a statistical association between frequency of recorded melioidosis cases and the nature and timing of rainfall related events and suggest a future rise in the sea surface and ambient temperature may lead to increased melioidosis.

摘要

目的

类鼻疽病是一种在人类和动物中经常致命的疾病,在东南亚和澳大利亚北部流行。它是由环境细菌伯克霍尔德菌引起的。我们分析了达尔文新类鼻疽病例之前的天气和气候因素,并比较了严重和平均湿季降雨前的天气事件与住院之间的时间。

方法

在 1990 年至 2013 年的时间序列分析中,我们应用了增强回归树和负二项式模型来研究类鼻疽病例与天气事件之间的关联。拟合的傅里叶项控制了长期季节性趋势。

结果

我们发现露点、云量、降雨量、最高温度和地下水的升高与获得类鼻疽病的风险增加有关。在严重降雨事件后,“假定”潜伏期明显缩短。湿季早期发生的降雨与更多病例有关,当地海面温度的升高反映了当地天气动态和降水。

结论

我们的研究结果表明,记录的类鼻疽病例的频率与与降雨相关事件的性质和时间之间存在统计学关联,并表明未来海面和环境温度的升高可能导致类鼻疽病的增加。

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