Objective: To analyze the epidemiological characteristics of varicella among nursery children in Shenzhen from 2015 to 2024, and to evaluate the impact of optimizing varicella vaccine (VarV) immunization strategies on varicella incidence. Methods: Varicella incidence data for nursery children in Shenzhen from 2015 to 2024 were obtained from the China Disease Prevention and Control Information System. The study period was divided into three phases:one dose self pay VarV (January 2015 to October 2017), two dose self pay VarV (November 2017 to October 2019), and two dose free VarV (November 2019 to December 2024). Interrupted time series (ITS) analysis was conducted to assess changes in the level and trend of varicella incidence associated with each phase of policy implementation. Results: A total of 27 517 varicella cases was reported among nursery children from 2015 to 2024, with an average annual incidence of 514.01/100 000. During the same period, 136 clustered outbreaks were reported in nursery institutions, involving a cumulative total of 1 091 cases. ITS analysis showed that during the self pay 1 dose stage, the varicella incidence among nursery children showed an upward trend, with an average monthly increase of 2.58/100 000 (95% CI =2.21/ 100 000 -2.95/100 000, P <0.01). After the implementation of the self pay 2 dose strategy, the incidence decreased, with a change in incidence of -26.12/100 000 (95% CI =-37.30/100 000 to -14.94/100 000) and a change in slope of -2.65/100 000 (95% CI = -3.38/100 000 to -1.93/100 000)(all P <0.01). After the implementation of the free 2 dose strategy, the incidence decreased further, with a change in incidence of -40.03/100 000 (95% CI =-50.39/100 000 to -29.66/100 000, P <0.01) and a change in slope of -0.56/100 000 (95% CI =-1.20/100 000-0.08/100 000, P =0.09). Conclusion The gradual optimization of the VarV vaccination strategy in Shenzhen from self pay 1 dose to free 2 dose has significantly reduced the varicella incidence among nursery children, demonstrating good short term control and long term intervention effectiveness.

Objective: To investigate the current status of hyperopic reserve among preschool children and to determine the associations with genetic and behavioral factors, so as to provide evidence for early intervention strategies and the development of working protocols for myopia prevention with a forward shift of the prevention threshold. Methods: A total of 924 preschool children (3-6 years of age) from 6 kindergartens in Jiading District of Shanghai were enrolled by stratified random sampling from March to June 2024. Cycloplegic refraction using 1% atropine eye drops was performed to obtain accurate spherical equivalent (SE) values. Questionnaires were used to collect the genetic history and daily behavioral habits of the children. Refractive status was classified into three categories based on the SE:sufficient hyperopic reserve, relatively insufficient hyperopic reserve, and pre myopia. Results: The overall detection rate of insufficient hyperopic reserve among preschool children was 82.25%, consisting of 72.29% for relatively insufficient hyperopic reserve and 9.96% for pre myopia. Multivariate Logistic regression analysis showed that parental bilateral myopia was independently and positively associated with relatively insufficient hyperopic reserve ( OR =2.13) and pre myopia ( OR =4.35) compared to children with sufficient hyperopic reserve; electronic screen exposure time ≥2 h/d on school days was an independent and positive risk factor for pre myopia ( OR =2.83); all of the above associations were statistically significant (all P <0.05). No statistically significant association was noted between outdoor activity and hyperopic reserve (all P >0.05). Conclusions The insufficient hyperopic reserve detection rate is relatively high among preschool children in Jiading District, Shanghai. Early management of electronic device use with regular screening and monitoring for preschool children with a family history of myopia should be strengthened to shift the prevention threshold earlier and prevent childhood myopia.

Objective:To analyze the spatiotemporal correlation between the surveillance data of influenza in students reported by medical institutions and school absenteeism due to illness, and evaluate the application of Bayesian Structural Time Series model (BSTS) in the prediction of school influenza epidemic.Methods:A total of 13 schools in Dapeng new district of Shenzhen were selected. The incidence data of influenza in schools in Shenzhen from January 1, 2015 to December 31, 2019 were collected from China Disease Control and Prevention Information System and the illness related school absentence data during this period were collected from Shenzhen Student Health Surveillance System, and the spatiotemporal correlation between the data from two systems was analyzed and compared. BSTS was used to make long-term predictions of the monthly incidence of influenza in students in 2019 and short-term predictions of the weekly incidence of influenza in week 1-8 and week 45-52 of 2019 by using the data from two systems.Results:There was a temporal correlation between the data from China Disease Control and Prevention Information System and the data from Shenzhen Student Health Surveillance System ( r=0.93, P<0.001), and the lag of the former one was 1 day ( r=0.73, P<0.001). Influenza outbreaks were randomly distributed in different schools in Shenzhen, and there was no spatial correlation. The root mean square error ( RMSE) and mean absolute error ( MAE) were 0.35 and 0.28, respectively, in the long-term prediction, and the RMSE was 0.33 and 0.34, and the MAE was 0.26 and 0.28, respectively, in the short-term predictions of week 1-8 and week 45-52 of 2019, respectively, showing good prediction accuracy and fitting effect. Conclusion:By analyzing the data from China Disease Control and Prevention Information System and Shenzhen Student Health Surveillance System with BSTS, the dynamics of the school influenza epidemic can be accurately predicted, and effective technical support can be provided for the early warning and prevention and control of influenza epidemic.

Objective:To analyze the temporal distribution of other infectious diarrhea (OID) in Shenzhen and provide evidence for the prevention and control of OID.Methods:The incidence data of OID in Shenzhen from 2011 to 2023 were collected. The seasonal and trend decomposition using loess (STL), seasonal index method, concentration degree and circular distribution method were used to analyze the incidence trend and temporal distribution of OID.Results:A total of 477 611 cases of OID were reported in Shenzhen from 2011 to 2023, with an average annual incidence rate of 260.19/100 000 showing a fluctuating upward trend. The seasonal index method indicated that October-January was period with high incidence of OID in Shenzhen and the seasonal intensity began to decrease in 2020. STL revealed an obvious incidence peak in winter. The concentration method showed that OID had a certain seasonality before 2018 except 2016, but the seasonality was not obvious after 2018. The circular distribution results showed that r was 0.05, mean angle ā was 1.92° and angular standard deviation s was 141.93° ( Z=1 033.37, P<0.001), with the peak on January 1 st and the high incidence period from August 11 th to May 25 th. Conclusions:OID had a certain degree of seasonality in Shenzhen, with an obvious incidence peak in winter. Since the seasonal intensity of OID decreased after 2018, the surveillance, early warning and risk assessment of OID should be continued, and prevention and control measures should be adjusted timely according to the change in the characteristics of the epidemic.

Objectives:To analyze the epidemiological characteristics and incidence trends of chronic hepatitis B in Shenzhen from 2005 to 2023, develop a prediction models with performance evaluation, explore its associations with social demographic index (SDI) and inform targeted prevention strategy development.Methods:Based on surveillance data of infectious diseases, descriptive epidemiological methods were applied to analyze the spatiotemporal and population distribution characteristics. A multifactorial prediction model integrating the SDI was established, and its predictive performance was evaluated by using data from 2020-2023. Model accuracy was evaluated by using root mean square error and mean absolute percentage error ( MAPE). The association between SDI and incidence rates was assessed through generalized linear models. Results:A total of 235 703 chronic hepatitis B cases were reported cumulatively in Shenzhen from 2005-2023, with an annual average incidence rate of 98.84/100 000. Long-term trends revealed a significant increase in the incidence from 2005 to 2019. The incidence rate was 2.48 times higher in men than in women, and the majority of cases occurred in age group 20-50 years. The cases were mainly workers in manufacturing and services. Seasonal incidence peaks were observed in March and during May to November. The overall SDI exhibited a consistent upward trend, and the positive correlation between SDI and incidence rate was observed in central urban districts (Futian and Nanshan). In contrast, industrial zones (Guangming and Bao'an) saw a significant decline in incidence rates due to intensified prevention interventions despite the increase of SDI level. Model predictions indicated that the multivariate long short-term memory (LSTM) deep learning model integrating SDI parameters outperformed both the spatiotemporal covariate- enhanced model and the augmented Bayesian structural time series model, with MAPE of 4.71%, 7.66% and 10.30%, respectively. Conclusion:SDI is a key social determinant associated with hepatitis B transmission risks, and dynamic thresholds can be established to develop tiered early warning mechanisms. It is suggested to integrate multisource SDI data into the LSTM framework, implement targeted interventions such as "rapid antibody screening in key areas + vaccination boosters for high-risk populations" and improve the timeliness of epidemic response through hybrid models to reduce disease burden level.

Objective To review the research of safe injection protocols for peripheral norepinephrine(pNE),to make clear the main contents of safe injection protocols and the compliance of clinical implementation protocols,and to provide reference for clinical nurses to use drugs safely.Methods Systematic searches were conducted in the PubMed database,the Embase database from the Netherlands,the Web of Science,the Cochrane library,CNKI,Wanfang database,VIP,and the China biomedical literature database for studies related to safe injection protocols for pNE.The search period extended from the establishment of the databases to April 30,2024.Two researchers conducted data extraction and summary analysis of the included literature.Results A total of 10 articles were incorporated,including 2 guidelines,4 observational retrospective cohort studies,2 observational prospective cohort studies,2 ambispective cohort study.All documents provide a complete safe injection scheme of pNE,and its main contents were as follows:the drug concentration should be diluted to 8～64 mg/L;the injection dose should be small,and the maximum dose should not exceed 0.5 μg·kg-1·min-1 or 25 μg/min;a short infusion time was appropriate,among which 4 schemes require≤24 hours;intravenous catheters should be large-bore models,mainly 16,18 and 20 G;selection of infusion sites with favorable venous conditions of upper limb should be selected for injection;during infusion,regular and effective monitoring was required,and the frequency of monitoring should be once an hour,not exceeding a maximum of 2 hours;observation of the puncture site,and must assess whether there was blood return to the venous pathway,develop an emergency plan for drug extravasation.Several studies provided the compliance analysis of the protocol.The items with the highest compliance were using the drug concentration specified in the protocol,with the highest implementation rate of 100.0%.The items with low compliance were:using ultrasonic catheterization or evaluation,with minimum 26.6%;monitor according to the specified time frequency,with a minimum of 36.0%;selection of infusion sites,with a minimum of 65.0%.Conclusion The pNE is safe and feasible in emergency situations,but it comes with numerous risks and limitations.Norepinephrine(NE)should be administered at low concentrations and small doses,using large-caliber venous indwelling needles,and choosing optimal injection sites.Ultrasound assessment and localization can be used if conditions permit.Short-term infusion is preferred,and effective monitoring should be conducted at regular intervals during the infusion.Emergency plans for drug extravasation should be established.Developing safe injection protocols can reduce the incidence of adverse events such as extravasation.

Objective:To report the nationwide surveillance results of pathogenic profiles and antimicrobial resistance patterns of Gram-positive bloodstream infections in China in 2023.Methods:The clinical isolates of Gram-posttive bacteria from blood cultures were collected in member hospitals of National Bloodstream Infection Bacterial Resistant Investigation Collaborative System（BRICS）during January to December 2023. Antimicrobial susceptibility testing was performed using the dilution method recommended by the Clinical and Laboratory Standards Institute（CLSI）. Statistical analyses were conducted using WHONET 5.6 and SPSS 25.0 software.Results:A total of 4 385 Gram-positive bacterial isolates were obtained from 60 participating center. The top five pathogens were Staphylococcus aureus（ n=1 544，35.2%），coagulase-negative Staphylococci（ n=1 441，32.9%）， Enterococcus faecium（ n=574，13.1%）， Enterococcus faecalis（ n=385，8.8%），and α-hemolytic Streptococci（ n=187，4.3%）. The prevalence of methicillin-resistant Staphylococcus aureus（MRSA）and methicillin-resistant coagulase-negative Staphylococci（MRCNS）was 26.2%（405/1 544）and 69.8%（1 006/1 441），respectively. Notably，all Staphylococci remained susceptible to glycopeptide or daptomycin. Staphylococcus aureus demonstrated excellent susceptibility（>97.0%）to cephalobiol，rifampicin，trimethoprim-sulfamethoxazole，linezolid，minocycline，tigecycline，and eravacycline. No Enterococcus exhibiting resistance to linezolid were detected. Glycopeptide resistance was uncommon but more frequent in Enterococcus faecium（resistance to vancomycin and teicoplanin：both 1.7%）compared to Enterococcus faecalis（both 0.3%）. The detection rates of MRSA and MRCNS exhibited significant regional variations across the country（ χ2=17.674 and 148.650，respectively，both P<0.001）. No vancomycin-resistant Enterococci were detected in central China. Institutional comparison demonstrated higher prevalence of MRSA（ χ2=14.111， P<0.001）and MRCNS（ χ2=4.828， P=0.028）in provincial hospitals than that in municipal hospitals. Socioeconomic analysis identified elevated detection rates of both MRSA（ χ2=18.986， P<0.001）and MRCNS（ χ2=4.477， P=0.034）in less developed regions（per capita GDP

Objective:To report the results of bacterial resistant investigation collaborative system（BRICS）on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2023，and provide reference for clinical tretment of bloodstream infections and prevention and control of bacterial resistance.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of BRICS were collected during January 2023 to December 2023. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 were used to analyze the data.Results:During the study period，11 492 strains of Gram-negative bacteria were collected from 60 hospitals，of which 10 098（87.9%）were Enterobacterales and 1 394（12.1%）were non-fermentative bacteria. The top 5 bacterial species were Escherichia coli（50.0%）， Klebsiella pneumoniae（26.1%）， Pseudomonas aeruginosa（5.1%）， Acinetobacter baumannii complex（5.0%）and Enterobacter cloacae complex（4.1%）. The ESBL-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus mirablilis were 46.8%（2 685/5 741），18.3%（549/2 999）and 44.0%（77/175），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（76/5 741）and 15.0%（450/2 999）；32.9%（25/76）and 78.0%（351/450）of CREC and CRKP were sensitive to ceftazidime/avibactam combination，respectively. 94.7%（72/76）and 90.2%（406/450）of CREC and CRKP were sensitive to aztreonam/avibactam combination. Furthermore，57.9%（44/76）and 79.1%（356/450）were sensitive to imipenem/relebactam combination. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 64.6%（370/573），while more than 80.0% of CRAB complex was sensitive to tigecycline，eravacycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 17.0%（99/581）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of important Gram-negative bacteria resistance among different regions in China，with statistically significant differences in the prevalence of CREC，CRKP，CRPA and CRAB complex（ χ2=10.6，28.6，10.8 and 19.3， P<0.05）. The prevalence of ESBL-producing Escherichia coli， CREC，CRAB complex and CRKP were higher in provincial hospitals than those in municipal hospitals（ χ2=12.5，9.8，12.7 and 57.8，all P<0.01）. Conclusions:Gram-negative bacteria are the main pathogens causing bloodstream infections in China，and Escherichia coli is ranked in the top，while the trend of Klebsiella pneumoniae increases continuously with time. CRKP infection shows a slow upward trend，CREC infecton maintains a low prevalence level，and CRAB complex infection continues to exhibit a high prevalence rate. The composition and resistance patterns of pathogens causing bloodstream infections vary to some extent across different regions and levels of hospitals in China.

Objective:To analyze the spatiotemporal correlation between the surveillance data of influenza in students reported by medical institutions and school absenteeism due to illness, and evaluate the application of Bayesian Structural Time Series model (BSTS) in the prediction of school influenza epidemic.Methods:A total of 13 schools in Dapeng new district of Shenzhen were selected. The incidence data of influenza in schools in Shenzhen from January 1, 2015 to December 31, 2019 were collected from China Disease Control and Prevention Information System and the illness related school absentence data during this period were collected from Shenzhen Student Health Surveillance System, and the spatiotemporal correlation between the data from two systems was analyzed and compared. BSTS was used to make long-term predictions of the monthly incidence of influenza in students in 2019 and short-term predictions of the weekly incidence of influenza in week 1-8 and week 45-52 of 2019 by using the data from two systems.Results:There was a temporal correlation between the data from China Disease Control and Prevention Information System and the data from Shenzhen Student Health Surveillance System ( r=0.93, P<0.001), and the lag of the former one was 1 day ( r=0.73, P<0.001). Influenza outbreaks were randomly distributed in different schools in Shenzhen, and there was no spatial correlation. The root mean square error ( RMSE) and mean absolute error ( MAE) were 0.35 and 0.28, respectively, in the long-term prediction, and the RMSE was 0.33 and 0.34, and the MAE was 0.26 and 0.28, respectively, in the short-term predictions of week 1-8 and week 45-52 of 2019, respectively, showing good prediction accuracy and fitting effect. Conclusion:By analyzing the data from China Disease Control and Prevention Information System and Shenzhen Student Health Surveillance System with BSTS, the dynamics of the school influenza epidemic can be accurately predicted, and effective technical support can be provided for the early warning and prevention and control of influenza epidemic.

Objective:To analyze the temporal distribution of other infectious diarrhea (OID) in Shenzhen and provide evidence for the prevention and control of OID.Methods:The incidence data of OID in Shenzhen from 2011 to 2023 were collected. The seasonal and trend decomposition using loess (STL), seasonal index method, concentration degree and circular distribution method were used to analyze the incidence trend and temporal distribution of OID.Results:A total of 477 611 cases of OID were reported in Shenzhen from 2011 to 2023, with an average annual incidence rate of 260.19/100 000 showing a fluctuating upward trend. The seasonal index method indicated that October-January was period with high incidence of OID in Shenzhen and the seasonal intensity began to decrease in 2020. STL revealed an obvious incidence peak in winter. The concentration method showed that OID had a certain seasonality before 2018 except 2016, but the seasonality was not obvious after 2018. The circular distribution results showed that r was 0.05, mean angle ā was 1.92° and angular standard deviation s was 141.93° ( Z=1 033.37, P<0.001), with the peak on January 1 st and the high incidence period from August 11 th to May 25 th. Conclusions:OID had a certain degree of seasonality in Shenzhen, with an obvious incidence peak in winter. Since the seasonal intensity of OID decreased after 2018, the surveillance, early warning and risk assessment of OID should be continued, and prevention and control measures should be adjusted timely according to the change in the characteristics of the epidemic.