ABSTRACT
Objective@#To investigate the spatio-temporal clustering characteristics of influenza in Yinzhou District, Ningbo City, Zhejiang Province from 2017 to 2021, so as to provide insights into prevention and control of influenza. Methods Data of influenza in Yinzhou District from 2017 to 2021 were collected from the Chinese Disease Prevention and Control Information System. The software ArcGIS 10.8 was employed for spatial autocorrelation analysis, and SaTScan 10.1 was employed for spatio-temporal scanning to analyze the temporal and spatial clustering characteristics of influenza incidence in Yinzhou District. @*Methods@#Data of influenza in Yinzhou District from 2017 to 2021 were collected from the Chinese Disease Prevention and Control Information System. The software ArcGIS 10.8 was employed for spatial autocorrelation analysis, and SaTScan 10.1 was employed for spatio-temporal scanning to analyze the temporal and spatial clustering characteristics of influenza incidence in Yinzhou District.@*Results@#Totally 60 543 influenza cases were reported in Yinzhou District from 2017 to 2021, with an incidence of 0.76%. The incidence of influenza peaked in December 2019 (9.35%) and January 2020 (9.28%) during the period between 2017 and 2021. Spatial autocorrelation analysis showed that there was a positive spatial correlation of influenza incidence in Yinzhou District from 2018 to 2021 (all P<0.05), and a high clustering in 2019 and 2021. Zhonghe Street showed a low-high clustering from 2017 to 2020; Jiangshan Town showed a low-high clustering in 2017 and 2020, and a high-high clustering in 2019 and 2021; Shounan Street showed a high-high clustering from 2018 to 2020; Yunlong Street showed a high-high clustering in 2021. Spatio-temporal scanning analysis showed that the class Ⅰ clusters were located in the central region which centered in Dongqianhu Town, with aggregation time in August 2017, in the northwest region with aggregation time in December and January from 2018 to 2020, and in the west region with aggregation time in August 2021.@* Conclusion @#The incidence of influenza in Yinzhou District from 2017 to 2021 showed a spatio-temporal clustering in the northwestern region in winter and summer.
ABSTRACT
Objective@#To learn the level of resilience among community health emergency staff in Zhejiang Province and its influencing factors under the epidemic situation of coronavirus disease 2019. @*Methods@#Using stratified cluster sampling method, the community health emergency workers from six counties in Zhejiang Province were recruited in this study. A self-designed questionnaire, a scale for core emergency response capability of medical workers and 10 Items Connor-Davidson Resilience Scale ( CD-RISC-10 ) were employed. The multivariate linear regression model was used to analyze the influencing factors for resilience. @*Results@#A total of 749 people were surveyed, with 699 valid questionnaires ( effective rate 93.32% ). Among the 699 community health emergency staffs, the total scores of resistance and core emergency response capability were 34.97±7.95 and 118.38±27.60. The multivariate linear regression analysis showed that core emergency response capability ( β＇=0.410 ), education background (diploma: β＇=0.158; bachelor: β＇=0.196), position ( top: β＇=0.083 ) and self-rated physical fitness ( not qualified: β＇=-0.152; less qualified: β＇=-0.235; generally qualified: β＇=-0.219; more qualified: β＇=-0.107 ) were the influencing factors for resilience of community health emergency staff. @*Conclusion@#The resilience of community health emergency staff in Zhejiang Province is at a medium level, and is associated with education background, physical fitnes and position.