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登革热的流行病学及其季节气候变化对其动态的影响:中国东南沿海潮汕地区的时空描述性分析。

Epidemiology of dengue and the effect of seasonal climate variation on its dynamics: a spatio-temporal descriptive analysis in the Chao-Shan area on China's southeastern coast.

机构信息

Good Clinical Practice Office, Cancer Hospital of Shantou University Medical College, Shantou, China.

Department of Preventive Medicine, Shantou University Medical College, Shantou, China.

出版信息

BMJ Open. 2019 May 24;9(5):e024197. doi: 10.1136/bmjopen-2018-024197.

DOI:10.1136/bmjopen-2018-024197
PMID:31129573
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6538008/
Abstract

OBJECTIVE

Dengue is a mosquito-transmitted virus infection that remains rampant across the tropical and subtropical areas worldwide. However, the spatial and temporal dynamics of dengue transmission are poorly understood in Chao-Shan area, one of the most densely populated regions on China's southeastern coast, limiting disease control efforts. We aimed to characterise the epidemiology of dengue and assessed the effect of seasonal climate variation on its dynamics in the area.

DESIGN

A spatio-temporal descriptive analysis was performed in three cities including Shantou, Chaozhou and Jieyang in Chao-Shan area during the period of 2014-2017.

SETTING

Data of dengue cases of three cities including Shantou, Chaozhou and Jieyang in Chao-Shan area during 2014-2017 were extracted. Data for climatic variables including mean temperature, relative humidity and rainfall were also compiled.

METHODOLOGY

The epidemiology and dynamics of dengue were initially depicted, and then the temporal dynamics related to climatic drivers was assessed by a wavelet analysis method. Furthermore, a generalised additive model for location, scale and shape model was performed to study the relationship between seasonal dynamics of dengue and climatic drivers.

RESULTS

Among the cities, the number of notified dengue cases in Chaozhou was greatest, accounting for 78.3%. The median age for the notified cases was 43 years (IQR: 27.0-58.0 years). Two main regions located in Xixin and Chengxi streets of Chaozhou with a high risk of infection were observed, indicating that there was substantial spatial heterogeneity in intensity. We found an annual peak incidence occurred in autumn across the region, most markedly in 2015. This study reveals that periods of elevated temperatures can drive the occurrence of dengue epidemics across the region, and the risk of transmission is highest when the temperature is between 25°C and 28°C.

CONCLUSION

Our study contributes to a better understanding of dengue dynamics in Chao-Shan area.

摘要

目的

登革热是一种通过蚊子传播的病毒感染,在全球热带和亚热带地区仍然猖獗。然而,在中国东南沿海人口最密集的地区之一——潮汕地区,登革热传播的时空动态仍知之甚少,这限制了疾病的控制工作。我们旨在描述登革热的流行病学,并评估季节性气候变化对该地区登革热动态的影响。

设计

在 2014-2017 年期间,对包括汕头市、潮州市和揭阳市在内的潮汕地区的三个城市进行了时空描述性分析。

地点

提取了包括汕头市、潮州市和揭阳市在内的潮汕地区三个城市 2014-2017 年的登革热病例数据。还编制了包括平均温度、相对湿度和降雨量在内的气候变量数据。

方法

首先描述了登革热的流行病学和动态,然后通过小波分析方法评估了与气候驱动因素有关的时间动态。此外,还进行了广义加性模型的位置、规模和形状模型,以研究登革热季节性动态与气候驱动因素之间的关系。

结果

在所研究的城市中,潮州市报告的登革热病例数最多,占 78.3%。报告病例的中位数年龄为 43 岁(IQR:27.0-58.0 岁)。发现潮州市的西新和城西街两个主要区域存在高感染风险,表明该地区存在很大的空间异质性。本研究发现,该地区的年度高峰发病时间在秋季,2015 年最为明显。本研究表明,高温期可导致该地区登革热的发生,当温度在 25°C 至 28°C 之间时,传播风险最高。

结论

本研究有助于更好地了解潮汕地区登革热的动态。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/b4d71181d5c1/bmjopen-2018-024197f06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/91b6905a0d0d/bmjopen-2018-024197f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/ba4f9af84537/bmjopen-2018-024197f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/88b17e660519/bmjopen-2018-024197f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/f94be5dfc920/bmjopen-2018-024197f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/8b60ecbe9b59/bmjopen-2018-024197f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/b4d71181d5c1/bmjopen-2018-024197f06.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/91b6905a0d0d/bmjopen-2018-024197f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/ba4f9af84537/bmjopen-2018-024197f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/88b17e660519/bmjopen-2018-024197f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/f94be5dfc920/bmjopen-2018-024197f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/8b60ecbe9b59/bmjopen-2018-024197f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/39d9/6538008/b4d71181d5c1/bmjopen-2018-024197f06.jpg

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