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Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020

BACKGROUND: Noroviruses are a leading cause of acute gastroenteritis (AGE) worldwide. The geographical characteristics of norovirus outbreaks in Beijing and their influencing factors remain unknown. This study aimed to explore the spatial distributions, geographical characteristics, and influencing...

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Autores principales: Chen, Yanwei, Liu, Baiwei, Wang, Yu, Zhang, Yewu, Yan, Hanqiu, Li, Weihong, Shen, Lingyu, Tian, Yi, Jia, Lei, Zhang, Daitao, Yang, Peng, Gao, Zhiyong, Wang, Quanyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10152695/
https://www.ncbi.nlm.nih.gov/pubmed/37131193
http://dx.doi.org/10.1186/s12879-023-08243-7
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author Chen, Yanwei
Liu, Baiwei
Wang, Yu
Zhang, Yewu
Yan, Hanqiu
Li, Weihong
Shen, Lingyu
Tian, Yi
Jia, Lei
Zhang, Daitao
Yang, Peng
Gao, Zhiyong
Wang, Quanyi
author_facet Chen, Yanwei
Liu, Baiwei
Wang, Yu
Zhang, Yewu
Yan, Hanqiu
Li, Weihong
Shen, Lingyu
Tian, Yi
Jia, Lei
Zhang, Daitao
Yang, Peng
Gao, Zhiyong
Wang, Quanyi
author_sort Chen, Yanwei
collection PubMed
description BACKGROUND: Noroviruses are a leading cause of acute gastroenteritis (AGE) worldwide. The geographical characteristics of norovirus outbreaks in Beijing and their influencing factors remain unknown. This study aimed to explore the spatial distributions, geographical characteristics, and influencing factors of norovirus outbreaks in Beijing, China. METHODS: Epidemiological data and specimens were collected through the AGE outbreak surveillance system in all 16 districts of Beijing. Data on spatial distribution, geographical characteristics, and influencing factors of norovirus outbreaks were analyzed using descriptive statistics methods. We measured spatial, geographical clustering of high- or low-value deviance from random distribution using Z-scores and P-values as statistical significance measures with Global Moran’s I statistics and Getis-Ord Gi in ArcGIS. Linear regression and correlation methods were used to explore influencing factors. RESULTS: Between September 2016 and August 2020, 1,193 norovirus outbreaks were laboratory-confirmed. The number of outbreaks varied seasonally, typically peaking in spring (March to May) or winter (October to December). Outbreaks primarily occurred around central districts at the town level, and spatial autocorrelation was evident in both the entire study period and in individual years. Hotspots of norovirus outbreaks in Beijing were primarily found in contiguous areas between three central districts (Chaoyang, Haidian, Fengtai) and four suburban districts (Changping, Daxing, Fangshan, Tongzhou). The average population numbers, mean number of all schools, and mean number of kindergartens and primary schools for towns in central districts and hotspot areas were higher than those in suburban districts and non-hotspot areas respectively. Additionally, population numbers and densities of kindergartens and primary schools were influencing factors at the town level. CONCLUSIONS: Hotspots of norovirus outbreaks in Beijing were in contiguous areas between central and suburban districts with high populations, and high kindergarten and primary school densities were the likely driving forces. Outbreak surveillance needs to focus on contiguous areas between central and suburban districts with increased monitoring, medical resources, and health education.
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spelling pubmed-101526952023-05-03 Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020 Chen, Yanwei Liu, Baiwei Wang, Yu Zhang, Yewu Yan, Hanqiu Li, Weihong Shen, Lingyu Tian, Yi Jia, Lei Zhang, Daitao Yang, Peng Gao, Zhiyong Wang, Quanyi BMC Infect Dis Research BACKGROUND: Noroviruses are a leading cause of acute gastroenteritis (AGE) worldwide. The geographical characteristics of norovirus outbreaks in Beijing and their influencing factors remain unknown. This study aimed to explore the spatial distributions, geographical characteristics, and influencing factors of norovirus outbreaks in Beijing, China. METHODS: Epidemiological data and specimens were collected through the AGE outbreak surveillance system in all 16 districts of Beijing. Data on spatial distribution, geographical characteristics, and influencing factors of norovirus outbreaks were analyzed using descriptive statistics methods. We measured spatial, geographical clustering of high- or low-value deviance from random distribution using Z-scores and P-values as statistical significance measures with Global Moran’s I statistics and Getis-Ord Gi in ArcGIS. Linear regression and correlation methods were used to explore influencing factors. RESULTS: Between September 2016 and August 2020, 1,193 norovirus outbreaks were laboratory-confirmed. The number of outbreaks varied seasonally, typically peaking in spring (March to May) or winter (October to December). Outbreaks primarily occurred around central districts at the town level, and spatial autocorrelation was evident in both the entire study period and in individual years. Hotspots of norovirus outbreaks in Beijing were primarily found in contiguous areas between three central districts (Chaoyang, Haidian, Fengtai) and four suburban districts (Changping, Daxing, Fangshan, Tongzhou). The average population numbers, mean number of all schools, and mean number of kindergartens and primary schools for towns in central districts and hotspot areas were higher than those in suburban districts and non-hotspot areas respectively. Additionally, population numbers and densities of kindergartens and primary schools were influencing factors at the town level. CONCLUSIONS: Hotspots of norovirus outbreaks in Beijing were in contiguous areas between central and suburban districts with high populations, and high kindergarten and primary school densities were the likely driving forces. Outbreak surveillance needs to focus on contiguous areas between central and suburban districts with increased monitoring, medical resources, and health education. BioMed Central 2023-05-02 /pmc/articles/PMC10152695/ /pubmed/37131193 http://dx.doi.org/10.1186/s12879-023-08243-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Yanwei
Liu, Baiwei
Wang, Yu
Zhang, Yewu
Yan, Hanqiu
Li, Weihong
Shen, Lingyu
Tian, Yi
Jia, Lei
Zhang, Daitao
Yang, Peng
Gao, Zhiyong
Wang, Quanyi
Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020
title Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020
title_full Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020
title_fullStr Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020
title_full_unstemmed Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020
title_short Spatio-temporal distribution and influencing factors of norovirus outbreaks in Beijing, China from 2016 to 2020
title_sort spatio-temporal distribution and influencing factors of norovirus outbreaks in beijing, china from 2016 to 2020
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10152695/
https://www.ncbi.nlm.nih.gov/pubmed/37131193
http://dx.doi.org/10.1186/s12879-023-08243-7
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