[Epidemiological characteristics and influencing factors of public health emergency events of varicella in the Beijing-Tianjin-Hebei region, 2006-2021].

To explore the epidemiological characteristics of public health emergency events (PHEE) of varicella in the Beijing-Tianjin-Hebei region and analyze its related influencing factors. Excel was used to organize the varicella data in the Beijing-Tianjin-Hebei region from 2006 to 2021, reported by the management information system of PHEE, to describe the epidemiological characteristics of varicella events. Spatial autocorrelation and spatial scanning methods were used to test and determine its spatial clusters. Geographic detectors were used to analyze the impact of socio-economic factors. From 2006 to 2021, there were 644 reported varicella events in the Beijing-Tianjin-Hebei region, with a total of 18 052 cases and an incidence rate of 2.78%. The number, duration and response time <i>M</i> (<i>Q</i><sub>1</sub>, <i>Q</i><sub>3</sub>) of each reported event were 22 (15, 35) cases, 19 (7, 34) days and 7 (4, 17) days, respectively. Hebei Province had a shorter response time and duration of events compared to Beijing and Tianjin. The most reported varicella events were in 2006 and 2007, with 112 and 106 events, respectively. By 2014, the number of events had decreased yearly, and there was a small peak from 2017 to 2019 between 2014 and 2021. From 2006 to 2021, the PHEE of varicella showed a seasonal bimodal distribution from March to June and from October to January of the following year, with peaks in May and December. There was a total of 500 reported varicella events in primary schools, including 218 events in rural primary schools (34%), 142 events in county and town primary schools (22%) and 140 events in urban primary schools (22%). The distribution of varicella events showed a positive spatial autocorrelation and strong spatial clustering, with <i>Moran's I</i> of 0.31. The Class 1 clustering area was centered in Kuancheng Manchu Autonomous County, Chengde City, with a radius of 207 km and included 58 districts (<i>LLR</i>=3 550.23, <i>RR</i>=3.78). The most explanatory factor among socio-economic factors was the proportion of the population aged 0-24 years old (<i>q</i>=0.22), and the interaction effect between each factor was stronger than the independent effect. Overall, there are differences in the level of handling varicella events across Beijing, Tianjin and Hebei. The main occurrence of varicella events is in primary schools, especially in rural areas. Varicella events exhibit spatial clustering. Population structure-related factors have a strong impact on the risk of the incidence of varicella events.

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Journal
PubMed
Published
2024-12-06
DOI
https://doi.org/10.3760/cma.j.cn112150-20240301-00171
Primary Topic
Healthcare and Venom Research
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article
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article

[Epidemiological characteristics and influencing factors of public health emergency events of varicella in the Beijing-Tianjin-Hebei region, 2006-2021].

M M Wang, X D Li, Chengdong Xu, Lingling Wang et al.
PubMed
Healthcare and Venom Research
article

[Epidemiological characteristics and influencing factors of public health emergency events of varicella in the Beijing-Tianjin-Hebei region, 2006-2021].

M M Wang, X D Li, Chengdong Xu, Lingling Wang, Xiao‐Ming Chen, Peng‐Hui Wang, Tianqi Wang, Xingyuan Liu, Y H Hu, M Y You, D P Yin
article en

Abstract

To explore the epidemiological characteristics of public health emergency events (PHEE) of varicella in the Beijing-Tianjin-Hebei region and analyze its related influencing factors. Excel was used to organize the varicella data in the Beijing-Tianjin-Hebei region from 2006 to 2021, reported by the management information system of PHEE, to describe the epidemiological characteristics of varicella events. Spatial autocorrelation and spatial scanning methods were used to test and determine its spatial clusters. Geographic detectors were used to analyze the impact of socio-economic factors. From 2006 to 2021, there were 644 reported varicella events in the Beijing-Tianjin-Hebei region, with a total of 18 052 cases and an incidence rate of 2.78%. The number, duration and response time <i>M</i> (<i>Q</i><sub>1</sub>, <i>Q</i><sub>3</sub>) of each reported event were 22 (15, 35) cases, 19 (7, 34) days and 7 (4, 17) days, respectively. Hebei Province had a shorter response time and duration of events compared to Beijing and Tianjin. The most reported varicella events were in 2006 and 2007, with 112 and 106 events, respectively. By 2014, the number of events had decreased yearly, and there was a small peak from 2017 to 2019 between 2014 and 2021. From 2006 to 2021, the PHEE of varicella showed a seasonal bimodal distribution from March to June and from October to January of the following year, with peaks in May and December. There was a total of 500 reported varicella events in primary schools, including 218 events in rural primary schools (34%), 142 events in county and town primary schools (22%) and 140 events in urban primary schools (22%). The distribution of varicella events showed a positive spatial autocorrelation and strong spatial clustering, with <i>Moran's I</i> of 0.31. The Class 1 clustering area was centered in Kuancheng Manchu Autonomous County, Chengde City, with a radius of 207 km and included 58 districts (<i>LLR</i>=3 550.23, <i>RR</i>=3.78). The most explanatory factor among socio-economic factors was the proportion of the population aged 0-24 years old (<i>q</i>=0.22), and the interaction effect between each factor was stronger than the independent effect. Overall, there are differences in the level of handling varicella events across Beijing, Tianjin and Hebei. The main occurrence of varicella events is in primary schools, especially in rural areas. Varicella events exhibit spatial clustering. Population structure-related factors have a strong impact on the risk of the incidence of varicella events.

PubMedVol. 58(12)
Henan University (CN), Chinese Center For Disease Control and Prevention (CN), Beijing Institute of Big Data Research (CN), Hainan Center for Disease Control & Prevention (CN), Institute of Geographic Sciences and Natural Resources Research (CN)
Healthcare and Venom Research
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