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首页> 外文期刊>Journal of Infection >A population-based spatio-temporal analysis of Clostridium difficile infection in Queensland, Australia over a 10-year period
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A population-based spatio-temporal analysis of Clostridium difficile infection in Queensland, Australia over a 10-year period

机译:基于人口的时空分析澳大利亚昆士兰州艰难梭菌感染的10年时间

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Objectives: To identify the spatio-temporal patterns and environmental factors associated with Clostridium difficile infection (CDI) in Queensland, Australia. Methods: Data from patients tested for CDI were collected from 392 postcodes across Queensland between May 2003 and December 2012. A binomial logistic regression model, with CDI status as the outcome, was built in a Bayesian framework, incorporating fixed effects for sex, age, source of the sample (healthcare facility or community), elevation, rainfall, land surface temperature, seasons of the year, time in months and spatially unstructured random effects at the postcode level. Results: C. difficile was identified in 13.1% of the samples, the proportion significantly increased over the study period from 5.9% in 2003 to 18.8% in 2012. CDI peaked in summer (14.6%) and was at its lowest in autumn (10.1%). Other factors significantly associated with CDI included female sex (OR: 1.08; 95%CI: 1.01-1.14), community source samples (OR: 1.12; 95%CI: 1.05-1.20), and higher rainfall (OR: 1.09; 95%CI: 1.02-1.17). There was no significant spatial variation in CDI after accounting for the fixed effects in the model. Conclusions: There was an increasing annual trend in CDI in Queensland from 2003 to 2012. Peaks of CDI were found in summer (December-February), which is at odds with the current epidemiological pattern described for northern hemisphere countries. Epidemiologically plausible explanations for this disparity require further investigation.
机译:目的:确定澳大利亚昆士兰州艰难梭菌感染(CDI)相关的时空格局和环境因素。方法:从2003年5月至2012年12月在昆士兰州的392个邮政编码中收集了接受CDI测试的患者的数据。在贝叶斯框架下建立了以CDI状态为结果的二项式Logistic回归模型,该模型结合了性别,年龄,样本的来源(医疗机构或社区),海拔,降雨量,地表温度,一年中的季节,以月为单位的时间以及邮政编码级别的空间非结构化随机效应。结果:在艰难梭菌中检出了13.1%的样品,该比例在研究期间从2003年的5.9%显着提高到2012年的18.8%。CDI在夏季达到峰值(14.6%),在秋季达到最低(10.1%)。 %)。与CDI显着相关的其他因素包括女性(OR:1.08; 95%CI:1.01-1.14),社区来源样本(OR:1.12; 95%CI:1.05-1.20)和更高的降雨(OR:1.09; 95% CI:1.02-1.17)。考虑到模型中的固定效应后,CDI没有明显的空间变化。结论:从2003年到2012年,昆士兰州的CDI呈逐年上升的趋势。夏季(12月至2月)的CDI达到峰值,这与北半球国家目前的流行病学模式不符。对于这种差异的流行病学合理解释需要进一步调查。

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