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中国大陆长沙市 1991-2010 年大气湿度变化与肾综合征出血热传播。

Atmospheric moisture variability and transmission of hemorrhagic fever with renal syndrome in Changsha City, Mainland China, 1991-2010.

机构信息

College of Resources and Environment Science, Hunan Normal University, Changsha, China.

出版信息

PLoS Negl Trop Dis. 2013 Jun 6;7(6):e2260. doi: 10.1371/journal.pntd.0002260. Print 2013.

Abstract

BACKGROUND

The transmission of hemorrhagic fever with renal syndrome (HFRS) is influenced by environmental determinants. This study aimed to explore the association between atmospheric moisture variability and the transmission of hemorrhagic fever with renal syndrome (HFRS) for the period of 1991-2010 in Changsha, China.

METHODS AND FINDINGS

Wavelet analyses were performed by using monthly reported time series data of HFRS cases to detect and quantify the periodicity of HFRS. A generalized linear model with a Poisson distribution and a log link model were used to quantify the relationship between climate and HFRS cases, highlighting the importance of moisture conditions. There was a continuous annual oscillation mode and multi-annual cycle around 3-4 years from 1994 to 1999. There was a significant association of HFRS incidence with moisture conditions and the Multivariate El Niño-Southern Oscillation Index (MEI). Particularly, atmospheric moisture has a significant effect on the propagation of HFRS; annual incidence of HFRS was positively correlated with annual precipitation and annual mean absolute humidity.

CONCLUSIONS

The final model had good accuracy in forecasting the occurrence of HFRS and moisture condition can be used in disease surveillance and risk management to provide early warning of potential epidemics of this disease.

摘要

背景

肾综合征出血热(HFRS)的传播受到环境决定因素的影响。本研究旨在探讨 1991-2010 年期间长沙大气水分变化与肾综合征出血热(HFRS)传播之间的关系。

方法与结果

采用月报告 HFRS 病例时间序列数据进行小波分析,以检测和量化 HFRS 的周期性。采用泊松分布和对数链接模型的广义线性模型来量化气候与 HFRS 病例之间的关系,突出了水分条件的重要性。从 1994 年到 1999 年,存在连续的年度波动模式和大约 3-4 年的多年周期。HFRS 发病率与湿度条件和多变量厄尔尼诺-南方涛动指数(MEI)存在显著关联。特别是大气湿度对 HFRS 的传播有显著影响;HFRS 的年发病率与年降水量和年平均绝对湿度呈正相关。

结论

最终模型在预测 HFRS 发生方面具有良好的准确性,湿度条件可用于疾病监测和风险管理,为该病的潜在流行提供预警。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b6e/3674989/16b881076ecd/pntd.0002260.g001.jpg

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