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Objective@#To assess the risk of public health emergencies in Zhejiang Province, March 2021. @*Methods@#An expert counsel was conducted to assess the risk of coronavirus disease 2019 ( COVID-19 ) , enteritis due to norovirus, chicken pox and influenza by professionals in Zhejiang CDC, based on the information from infectious disease and public health emergency surveillance in Zhejiang Province, domestic health administrative departments, World Health Organization, and European CDC. @*Results@#In March 2021, the risk of imported COVID-19 epidemic will be high in Zhejiang Province, and the possibility of local spread could not be ruled out. The possibility of a large-scale outbreak of enteritis due to norovirus and a small-scale outbreak of chickenpox in schools and kindergartens could not be ruled out after the new term begins. An increased risk of influenza epidemic is predicted in collective units such as schools and kindergartens, yet the risk of a large-scale one will be low.@*Conclusion@#High attention should be paid to COVID-19 and enteritis due to norovirus, and general attention should be paid to chicken pox and influenza outbreak.
RESUMO
Objective@#To analyze the epidemiological characteristics of notifiable infectious diseases reported in Zhejiang Province in 2020 for prevention and control.@*Methods@#Data of notifiable infectious diseases reported in Zhejiang Province in 2020 were extracted from China Information System for Disease Control and Prevention. The incidence and death of notifiable infectious diseases were analyzed and compared with the averages from 2015 to 2019; then the characteristics of some key diseases such as coronavirus disease 2019 ( COVID-19 ), influenza and other infectious diarrhea were summarized. @*Results@#Totally 487 271 cases of 30 kinds of infectious diseases were reported. The incidence and mortality rate was 832.94/100 000 and 0.615 4/100 000, which were 7.05% and 14.60% lower than the average value of 2015-2019.The weekly morbidity of Class A and Class B infectious diseases fluctuated between 1.24/100 000 and 3.68/100 000, and hit the bottom in the sixth to eighth week. The morbidity of Class C infectious diseases was 154.19/100 000 in the first week, then dropped to 4.83/100 000 in the second to sixth week and maintained at a low level. High morbidity of infectious diseases were reported in Hangzhou ( 1 412.62/100 000 ), Jinhua ( 960.35/100 000 ) and Ningbo ( 921.25/100 000 ). The morbidity of class C infectious diseases in Hangzhou was 1 248.80/100 000, which was far higher than that of other ten prefecture-level cities. The diseases with high reported morbidity were influenza (438.45/100 000), other infectious diarrhea (140.29/100 000 ), hand-foot-and-mouth disease ( 99.64/100 000 ), pulmonary tuberculosis ( 41.92/100 000 ), syphilis (41.37/100 000) and viral hepatitis ( 30.48/100 000 ). More deaths were reported in AIDS and pulmonary tuberculosis, and the mortality were 0.482 1/100 000 and 0.116 2/100 000. A total of 1 306 confirmed cases, 302 asymptomatic infections and 1 death of COVID-19 were reported. @*Conclusion@#In 2020, the incidence rate of notifiable infectious diseases in Zhejiang decreased compared with the average value of 2015-2019. Pulmonary tuberculosis, syphilis and hepatitis B still have high morbidity, and the COVID-19 epidemic spread widely. The morbidity of some respiratory infectious diseases and imported infectious diseases have dropped significantly compared with previous years.
RESUMO
OBJECTIVE: To analyze and evaluate the application of China Infectious Diseases Automated-alert and Response System(CIDARS)in Zhejiang province. METHODS: Data through the monitoring program in 2012 was analyzed descriptively and compared with the incidence data in the same period as well information related to public health emergency events. RESULTS: A total of 14 292 signals were generated on 28 kinds of infectious diseases in the system, in Zhejiang province. 100% of the signals had been responded and the median time to response was 0.81 hours. 123 signals (0.86%)were preliminarily verified as suspected outbreaks and 33 outbreaks were finally confirmed by further field investigation, with a positive ratio of 0.23% . Information related to regional distribution showed significant differences which reflecting a positive correlation between the numbers of diseases and the time of early-warning(r = 0. 97, P < 0.01). Distribution of information related to different types of diseases was also significantly different, showing a positive correlation between the prevalent strength of the disease and the amount of information in a specific area(r = 0.80, P < 0.01). CONCLUSION: CIDARS had a good performance which could be used to assist the local public health institutions on early detection of possible outbreaks at the early stage. However, the effectiveness was different for different regions and diseases.
