Identification of the spatial-temporal cluster and risk factors of hepatitis E from 2017 to 2022 in Shanghai, China

Hepatitis E, caused by the Hepatitis E virus (HEV), is a global infectious liver disease primarily transmitted through fecal-oral and zoonotic routes. Our study aimed to identify the potential case clusters and risk events at the community level in Shanghai to inform tailored strategies. Data on HEV cases from 2017 to 2022 in Shanghai were collected from the National Notifiable Disease Reporting System (NNDRS) and supplemented with population and socio-economic data from Shanghai’s communities. Descriptive and temporal analyses were applied to describe the epidemiological patterns, spatial-temporal scan analysis was used to identify potential case clusters, and binary logistic regression was conducted to explore the associations between risk factors and potential clusters. A total of 4,668 HEV cases were analyzed, with an average annual notification rate of 3.14 per 100,000 population in Shanghai from 2017 to 2022. Temporal analysis identified a significant temporal cluster from January 1 st , 2017 to May 31 st , 2019 (RR = 1.35, LLR = 52.18, p < 0.001), and a seasonal cluster from December to May. Spatial-temporal analysis over a 6-year span revealed one statistically significant cluster with a time frame from Jan 1 st , 2017 to Jun 30th (RR = 1.73, LLR = 135.74, p < 0.001). Spatial-temporal analysis per year revealed the most likely cluster in urban areas, with additional clusters in suburban towns. Binary logistic regression indicated positive associations between the risk rank of the clusters and population density (OR PD = 7.367, p PD < 0.001), and the count of malls (OR COM = 1.531, p COM = 0.050), and a negative association with the distance to river (OR DTR = 0.742, p DTR = 0.048). The spatial-temporal pattern of HEV in Shanghai during 2017 to 2022 suggested that although the communities with higher notification rates were observed in the southeastern communities of Shanghai, the most likely cluster identified by yearly spatial-temporal analysis was located in urban areas, consistent with the cluster detected over the 6-year period. The associations found in this study should be interpreted as ecological and hypothesis-generating. Confirmation of the potential transmission routes of HEV infection requires individual-level studies to inform more focused strategies for HEV prevention.

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Publication Details

Journal
BMC Infectious Diseases
Published
2026-09-24
DOI
https://doi.org/10.1186/s12879-026-14463-4
Primary Topic
Hepatitis Viruses Studies and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Identification of the spatial-temporal cluster and risk factors of hepatitis E from 2017 to 2022 in Shanghai, China

Lin Jing, Ren Hong, Di Xu, Ma Zhi-Tao et al.
BMC Infectious Diseases
Hepatitis Viruses Studies and Epidemiology
article

Identification of the spatial-temporal cluster and risk factors of hepatitis E from 2017 to 2022 in Shanghai, China

Lin Jing, Ren Hong, Di Xu, Ma Zhi-Tao, Qu Ling-Xiao, Lu Yi-Han, Li Zhao-He, Chen Kai-Yun, Shen Xin, Chen Kang
article en

Abstract

Hepatitis E, caused by the Hepatitis E virus (HEV), is a global infectious liver disease primarily transmitted through fecal-oral and zoonotic routes. Our study aimed to identify the potential case clusters and risk events at the community level in Shanghai to inform tailored strategies. Data on HEV cases from 2017 to 2022 in Shanghai were collected from the National Notifiable Disease Reporting System (NNDRS) and supplemented with population and socio-economic data from Shanghai’s communities. Descriptive and temporal analyses were applied to describe the epidemiological patterns, spatial-temporal scan analysis was used to identify potential case clusters, and binary logistic regression was conducted to explore the associations between risk factors and potential clusters. A total of 4,668 HEV cases were analyzed, with an average annual notification rate of 3.14 per 100,000 population in Shanghai from 2017 to 2022. Temporal analysis identified a significant temporal cluster from January 1 st , 2017 to May 31 st , 2019 (RR = 1.35, LLR = 52.18, p < 0.001), and a seasonal cluster from December to May. Spatial-temporal analysis over a 6-year span revealed one statistically significant cluster with a time frame from Jan 1 st , 2017 to Jun 30th (RR = 1.73, LLR = 135.74, p < 0.001). Spatial-temporal analysis per year revealed the most likely cluster in urban areas, with additional clusters in suburban towns. Binary logistic regression indicated positive associations between the risk rank of the clusters and population density (OR PD = 7.367, p PD < 0.001), and the count of malls (OR COM = 1.531, p COM = 0.050), and a negative association with the distance to river (OR DTR = 0.742, p DTR = 0.048). The spatial-temporal pattern of HEV in Shanghai during 2017 to 2022 suggested that although the communities with higher notification rates were observed in the southeastern communities of Shanghai, the most likely cluster identified by yearly spatial-temporal analysis was located in urban areas, consistent with the cluster detected over the 6-year period. The associations found in this study should be interpreted as ecological and hypothesis-generating. Confirmation of the potential transmission routes of HEV infection requires individual-level studies to inform more focused strategies for HEV prevention.

BMC Infectious Diseases
Shanghai Jiao Tong University (CN), Chinese Center For Disease Control and Prevention (CN), Fudan University (CN), Shanghai Public Health Clinical Center (CN), Tongren Hospital (CN), Beijing Center for Disease Prevention and Control (CN), Shanghai Municipal Center For Disease Control Prevention (CN)
Sustainable cities and communities
Openalex Percentile: Top 13%
Hepatitis Viruses Studies and Epidemiology
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