Cargando…

Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020

BACKGROUND: This study aimed to identify the epidemiology, seasonality, aetiology and clinical characteristics of sporadic foodborne diseases in Zhejiang province during 2016–2020. METHODS: Descriptive statistical methods were used to analyze the data from surveillance network established by the Zhe...

Descripción completa

Detalles Bibliográficos
Autores principales: Qi, Xiaojuan, Alifu, Xialidan, Chen, Jiang, Luo, Wenliang, Wang, Jikai, Yu, Yunxian, Zhang, Ronghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9520896/
https://www.ncbi.nlm.nih.gov/pubmed/36171585
http://dx.doi.org/10.1186/s12889-022-14226-1
_version_ 1784799726548287488
author Qi, Xiaojuan
Alifu, Xialidan
Chen, Jiang
Luo, Wenliang
Wang, Jikai
Yu, Yunxian
Zhang, Ronghua
author_facet Qi, Xiaojuan
Alifu, Xialidan
Chen, Jiang
Luo, Wenliang
Wang, Jikai
Yu, Yunxian
Zhang, Ronghua
author_sort Qi, Xiaojuan
collection PubMed
description BACKGROUND: This study aimed to identify the epidemiology, seasonality, aetiology and clinical characteristics of sporadic foodborne diseases in Zhejiang province during 2016–2020. METHODS: Descriptive statistical methods were used to analyze the data from surveillance network established by the Zhejiang Provincial Center for Disease Control and Prevention. There were 31 designated hospitals in all 11 cities which were selected using probability proportionate to size sampling method. RESULTS: During the study period, the surveillance system received 75,124 cases with 4826 (6.42%) hospitalizations from 31 hospitals. The most common cause was Norovirus, 6120 cases (42.56%), followed by Salmonella, 3351 cases (23.30%). A significant seasonal trend was observed for the V. parahaemolyticus, with the highest rates over the summer period, peaking in August, 1171 cases (38.75%), a similar trend was also observed with Salmonella and Diarrheagenic E. coli. Norovirus infections showed the highest rate in November (904, 14.77%) and March (660,10.78%), the lowest in August, 215 cases (3.51%). Patients between 19 ~ 40 years were more likely to infected by Norovirus, V. parahaemolyticus and Diarrheagenic E. coli, patients below 1 year were the highest among patients with Salmonella infection, 881 cases (26.3%). The Norovirus, V. parahaemolyticus and Diarrheagenic E. coli infection with the highest positive detection rates among the workers were observed. The largest number cases of food categories were from aquatic product infection. The private home was the most common exposure setting. CONCLUSION: Our study highlighted the necessity for conducting an active, comprehensive surveillance for pathogens in all age groups, to monitor the changing dynamics in the epidemiology and aetiology of foodborne diseases to guide policies that would reduce related illnesses. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-14226-1.
format Online
Article
Text
id pubmed-9520896
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-95208962022-09-30 Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020 Qi, Xiaojuan Alifu, Xialidan Chen, Jiang Luo, Wenliang Wang, Jikai Yu, Yunxian Zhang, Ronghua BMC Public Health Research BACKGROUND: This study aimed to identify the epidemiology, seasonality, aetiology and clinical characteristics of sporadic foodborne diseases in Zhejiang province during 2016–2020. METHODS: Descriptive statistical methods were used to analyze the data from surveillance network established by the Zhejiang Provincial Center for Disease Control and Prevention. There were 31 designated hospitals in all 11 cities which were selected using probability proportionate to size sampling method. RESULTS: During the study period, the surveillance system received 75,124 cases with 4826 (6.42%) hospitalizations from 31 hospitals. The most common cause was Norovirus, 6120 cases (42.56%), followed by Salmonella, 3351 cases (23.30%). A significant seasonal trend was observed for the V. parahaemolyticus, with the highest rates over the summer period, peaking in August, 1171 cases (38.75%), a similar trend was also observed with Salmonella and Diarrheagenic E. coli. Norovirus infections showed the highest rate in November (904, 14.77%) and March (660,10.78%), the lowest in August, 215 cases (3.51%). Patients between 19 ~ 40 years were more likely to infected by Norovirus, V. parahaemolyticus and Diarrheagenic E. coli, patients below 1 year were the highest among patients with Salmonella infection, 881 cases (26.3%). The Norovirus, V. parahaemolyticus and Diarrheagenic E. coli infection with the highest positive detection rates among the workers were observed. The largest number cases of food categories were from aquatic product infection. The private home was the most common exposure setting. CONCLUSION: Our study highlighted the necessity for conducting an active, comprehensive surveillance for pathogens in all age groups, to monitor the changing dynamics in the epidemiology and aetiology of foodborne diseases to guide policies that would reduce related illnesses. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12889-022-14226-1. BioMed Central 2022-09-28 /pmc/articles/PMC9520896/ /pubmed/36171585 http://dx.doi.org/10.1186/s12889-022-14226-1 Text en © The Author(s) 2022 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
Qi, Xiaojuan
Alifu, Xialidan
Chen, Jiang
Luo, Wenliang
Wang, Jikai
Yu, Yunxian
Zhang, Ronghua
Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020
title Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020
title_full Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020
title_fullStr Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020
title_full_unstemmed Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020
title_short Descriptive study of foodborne disease using disease monitoring data in Zhejiang Province, China, 2016–2020
title_sort descriptive study of foodborne disease using disease monitoring data in zhejiang province, china, 2016–2020
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9520896/
https://www.ncbi.nlm.nih.gov/pubmed/36171585
http://dx.doi.org/10.1186/s12889-022-14226-1
work_keys_str_mv AT qixiaojuan descriptivestudyoffoodbornediseaseusingdiseasemonitoringdatainzhejiangprovincechina20162020
AT alifuxialidan descriptivestudyoffoodbornediseaseusingdiseasemonitoringdatainzhejiangprovincechina20162020
AT chenjiang descriptivestudyoffoodbornediseaseusingdiseasemonitoringdatainzhejiangprovincechina20162020
AT luowenliang descriptivestudyoffoodbornediseaseusingdiseasemonitoringdatainzhejiangprovincechina20162020
AT wangjikai descriptivestudyoffoodbornediseaseusingdiseasemonitoringdatainzhejiangprovincechina20162020
AT yuyunxian descriptivestudyoffoodbornediseaseusingdiseasemonitoringdatainzhejiangprovincechina20162020
AT zhangronghua descriptivestudyoffoodbornediseaseusingdiseasemonitoringdatainzhejiangprovincechina20162020