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2005 - 2015年中国江苏省猩红热的时空流行病学研究

Spatiotemporal epidemiology of scarlet fever in Jiangsu Province, China, 2005-2015.

作者信息

Zhang Qi, Liu Wendong, Ma Wang, Shi Yingying, Wu Ying, Li Yuan, Liang Shuyi, Zhu Yefei, Zhou Minghao

机构信息

Department of Epidemiology and Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, 211166, China.

Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.

出版信息

BMC Infect Dis. 2017 Aug 30;17(1):596. doi: 10.1186/s12879-017-2681-5.

DOI:10.1186/s12879-017-2681-5
PMID:28854889
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5576110/
Abstract

BACKGROUND

A marked increase in the incidence rate of scarlet fever imposed a considerable burden on the health of children aged 5 to 15 years. The main purpose of this study was to depict the spatiotemporal epidemiological characteristics of scarlet fever in Jiangsu Province, China in order to develop and implement effective scientific prevention and control strategies.

METHODS

Smoothed map was used to demonstrate the spatial distribution of scarlet fever in Jiangsu Province. In addition, a retrospective space-time analysis based on a discrete Poisson model was utilized to detect clusters of scarlet fever from 2005 to 2015.

RESULTS

During the years 2005-2015, a total of 15,873 scarlet fever cases occurred in Jiangsu Province, with an average annual incidence rate of 1.87 per 100,000. A majority of the cases (83.67%) occurred in children aged 3 to 9 years. Each year, two seasonal incidence peaks were observed, the higher occurring between March and July, the lower between November and the following January. The incidence in the southern regions of the province was generally higher than that in the northern regions. Seven clusters, all of which occurred during incidence peaks, were detected via space-time scan statistical analysis. The most likely cluster and one of the secondary clusters were detected in the southern and northern high endemic regions, respectively.

CONCLUSION

The prevalence of scarlet fever in Jiangsu Province had a marked seasonality variation and was relatively endemic in some regions. Children aged 3 to 9 years were the major victims of this disease, and kindergartens and primary schools were the focus of surveillance and control. Targeted strategies and measures should be taken to reduce the incidence.

摘要

背景

猩红热发病率显著上升给5至15岁儿童的健康带来了相当大的负担。本研究的主要目的是描述中国江苏省猩红热的时空流行病学特征,以便制定和实施有效的科学防控策略。

方法

采用平滑地图展示江苏省猩红热的空间分布。此外,利用基于离散泊松模型的回顾性时空分析,检测2005年至2015年期间猩红热的聚集性病例。

结果

2005 - 2015年期间,江苏省共发生15873例猩红热病例,年均发病率为十万分之1.87。大多数病例(83.67%)发生在3至9岁的儿童中。每年观察到两个季节性发病高峰,较高的高峰出现在3月至7月之间,较低的高峰出现在11月至次年1月之间。该省南部地区的发病率普遍高于北部地区。通过时空扫描统计分析检测到7个聚集性病例,所有聚集性病例均发生在发病高峰期间。最可能的聚集性病例和一个次要聚集性病例分别在南部和北部高流行地区被检测到。

结论

江苏省猩红热的流行具有明显的季节性变化,且在一些地区呈相对地方性流行。3至9岁的儿童是该病的主要受害者,幼儿园和小学是监测和防控的重点。应采取针对性的策略和措施以降低发病率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/424f/5576110/dadccb6c3b8b/12879_2017_2681_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/424f/5576110/1ddb1845fbeb/12879_2017_2681_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/424f/5576110/ee67299e9ff7/12879_2017_2681_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/424f/5576110/dadccb6c3b8b/12879_2017_2681_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/424f/5576110/1ddb1845fbeb/12879_2017_2681_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/424f/5576110/ee67299e9ff7/12879_2017_2681_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/424f/5576110/dadccb6c3b8b/12879_2017_2681_Fig3_HTML.jpg

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本文引用的文献

1
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2
Effects of meteorological factors on incidence of scarlet fever during different periods in different districts of China.气象因素对中国不同地区不同时期猩红热发病率的影响。
Sci Total Environ. 2017 Mar 1;581-582:19-24. doi: 10.1016/j.scitotenv.2017.01.010. Epub 2017 Jan 7.
3
The Association between Environmental Factors and Scarlet Fever Incidence in Beijing Region: Using GIS and Spatial Regression Models.
Epidemiological Features of Infectious Diseases in Children and Adolescents: A Population-Based Observational Study in Shandong Province, China, 2013-2017.
儿童和青少年传染病的流行病学特征:2013 - 2017年中国山东省基于人群的观察性研究
Children (Basel). 2024 Mar 5;11(3):309. doi: 10.3390/children11030309.
4
[Spatial clustering analysis of scarlet fever incidence in China from 2016 to 2020].2016年至2020年中国猩红热发病率的空间聚集性分析
Nan Fang Yi Ke Da Xue Xue Bao. 2023 Apr 20;43(4):644-648. doi: 10.12122/j.issn.1673-4254.2023.04.19.
5
Epidemiological trend in scarlet fever incidence in China during the COVID-19 pandemic: A time series analysis.中国新冠大流行期间猩红热发病率的流行病学趋势:时间序列分析。
Front Public Health. 2022 Dec 15;10:923318. doi: 10.3389/fpubh.2022.923318. eCollection 2022.
6
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BMC Public Health. 2022 Nov 21;22(1):2139. doi: 10.1186/s12889-022-14469-y.
7
Forecasting the monthly incidence of scarlet fever in Chongqing, China using the SARIMA model.利用 SARIMA 模型预测中国重庆猩红热的月发病率。
Epidemiol Infect. 2022 Apr 21;150:e90. doi: 10.1017/S0950268822000693.
8
A Review of : Public Health Risk Factors, Prevention and Control.《公共卫生风险因素、预防与控制综述》
Pathogens. 2021 Feb 22;10(2):248. doi: 10.3390/pathogens10020248.
9
A Bayesian Spatiotemporal Analysis of Pediatric Group A Streptococcal Infections.A Bayesian Spatiotemporal Analysis of Pediatric Group A Streptococcal Infections. 儿童A组链球菌感染的贝叶斯时空分析。
Open Forum Infect Dis. 2019 Dec 10;6(12):ofz524. doi: 10.1093/ofid/ofz524. eCollection 2019 Dec.
10
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BMC Infect Dis. 2019 Dec 21;19(1):1074. doi: 10.1186/s12879-019-4705-9.
北京地区环境因素与猩红热发病率的关联:运用地理信息系统和空间回归模型
Int J Environ Res Public Health. 2016 Nov 4;13(11):1083. doi: 10.3390/ijerph13111083.
4
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Emerg Infect Dis. 2016 Jun;22(6):1075-8. doi: 10.3201/eid2206.151726.
5
Increasing prevalence of scarlet fever in China.中国猩红热患病率呈上升趋势。
BMJ. 2016 May 17;353:i2689. doi: 10.1136/bmj.i2689.
6
Applying geographical information systems (GIS) to arboviral disease surveillance and control: A powerful tool.将地理信息系统(GIS)应用于虫媒病毒病监测与控制:一种强大的工具。
Travel Med Infect Dis. 2016 Jan-Feb;14(1):9-10. doi: 10.1016/j.tmaid.2016.01.002. Epub 2016 Jan 21.
7
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Emerg Microbes Infect. 2012 Jul;1(7):e2. doi: 10.1038/emi.2012.9. Epub 2012 Jul 11.
10
Distribution of emm types among group A Streptococcus isolates from children in Korea.韩国儿童A群链球菌分离株中emm型的分布情况。
Diagn Microbiol Infect Dis. 2015 May;82(1):26-31. doi: 10.1016/j.diagmicrobio.2015.01.002. Epub 2015 Jan 15.