ObjectiveTo understand the seropositivity of neutralizing antibodies (NAb) and low-level NAb against SARS-CoV-2 infection in the community residents, and to explore the impact of COVID-19 vaccination and SARS-CoV-2 infection on the levels of NAb in human serum. MethodsOn the ground of surveillance cohort for acute infectious diseases in community populations in Shanghai, a proportional stratified sampling method was used to enroll the subjects at a 20% proportion for each age group (0‒14, 15‒24, 25‒59, and ≥60 years old). Blood samples collection and serum SARS-CoV-2 NAb concentration testing were conducted from March to April 2023. Low-level NAb were defined as below the 25^th percentile of NAb. ResultsA total of 2 230 participants were included, the positive rate of NAb was 97.58%, and the proportion of low-level NAb was 25.02% (558/2 230). Multivariate logistic regression analysis indicated that age, infection history and vaccination status were correlated with low-level NAb (all P<0.05). Individuals aged 60 years and above had the highest risk of low-level NAb. There was a statistically significant interaction between booster vaccination and one single infection (aOR=0.38, 95%CI: 0.19‒0.77). Compared to individuals without vaccination, among individuals infected with SARS-CoV-2 once, both primary immunization (aOR=0.23, 95%CI: 0.16‒0.35) and booster immunization (aOR=0.12, 95%CI: 0.08‒0.17) significantly reduced the risk of low-level NAb; among individuals without infections, only booster immunization (aOR=0.28, 95%CI: 0.14‒0.52) showed a negative correlation with the risk of low-level NAb. ConclusionsThe population aged 60 and above had the highest risk of low-level NAb. Regardless of infection history, a booster immunization could reduce the risk of low-level NAb. It is recommended that eligible individuals , especially the elderly, should get vaccinated in a timely manner to exert the protective role of NAb.

ObjectiveTo present the exploration and application of a prospective follow-up research method for acute infectious disease surveillance based on natural community populations， using COVID-19 infection as an example， and to provide a reference for improving the infectious disease surveillance and early warning system. MethodsA multi-stage probability proportional sampling method was employed to sample residents from all communities of 16 administrative districts in Shanghai， with households as the units. A cohort for acute infectious diseases based on natural community populations was established. The baseline survey was conducted for all cohort subjects， and COVID-19 antigen test kits were distributed. From December 21， 2022 to September 30， 2023， prospective follow-up monitoring of COVID-19 antigen and nucleic acid was carried out on the study subjects on a weekly basis. The baseline characteristics and follow-up information of the cohort subjects were described. ResultsThe cohort for acute infectious diseases included a total of 12 881 subjects， comprising 6 098 males （47.3%） and 6 783 females （52.7%）. The baseline survey revealed that 35.2% （4 540/12 881） of the subjects had a history of COVID-19 infection. During the follow-up period from December 21， 2022 to September 30， 2023， the average incidence density in the cohort was 0.61/person-year， with a higher incidence density in females （0.63/person-year） compared to males （0.59/person-year）. Individuals aged 60 and above （0.64/person-year） and those with underlying health conditions （0.67/person-year） had a higher incidence density. Healthcare workers showed a notably higher incidence density （0.84/person-year） than that in other occupational groups. As of September 30， 2023， a total of 340 subjects in the cohort experienced secondary infections， with a median interval of 170 days between the first and second infections. ConclusionThis study applies cohort study method to acute infectious disease surveillance， providing crucial data support for estimating infection rates and forecasting alerts for acute infectious diseases in the community. This method can be promoted and applied as a new approach for acute infectious disease surveillance.

Objective:To analyze the growth characteristics of different genotypes of Japanese encephalitis virus (JEV) in different cell lines, and to provide scientific basis for the selection of cell lines in the study of JEV.Methods:BHK-21, Vero, C6/36, PK-15, DF-1, N2a, SH-sy5y and MDCK cell lines were selected. The proliferation ability of genotype 1 (NX1889 strain), genotype 3 (P3 strain) and genotype 5 (XZ0934 strain) JEV in these cell lines was evaluated by plaque assay and RT-qPCR.Results:Significant cytopathogenic effects (CPE) were observed in BHK-21, Vero, C6/36, DF-1, N2a and PK-15 cell lines across all three JEV genotypes. However, no significant differences in CPE characteristics were observed within the same cell line. SH-sy5y and MDCK cell lines did not show significant CPE, but virus proliferation was detected in SH-sy5y cell line, while MDCK cell line were found to be insensitive to JEV. No significant difference was observed in the proliferation curves of G1, G3 and G5 JEV in BHK-21, Vero and SH-sy5y cell lines. In C6/36 and PK-15 cell lines, the titer of G1 JEV was higher than that of G3 and G5. In DF-1 cell line, G5 demonstrated a higher titer than the other two genotypes, whereas in N2a cell line, G5 showed a lower titer than the other two.Conclusions:There are differences in the proliferation of three different genotypes of JEV in different cell lines, which can provide reference for the study of JEV in different directions.

Objective:To elucidate the etiological and epidemiological characteristics and epidemiological patterns of viral acute respiratory infections (ARI) in Shanghai during 2023, with the aim of providing robust laboratory evidence for effective prevention and control strategies against related respiratory diseases and facilitating risk assessment.Methods:Respiratory pathogens were detected in the clinical surveillance specimens submitted by sentinel hospitals through multiplex PCR, as part of the multi-pathogen surveillance of acute respiratory infections in Shanghai during 2023. The obtained detection result were statistically analyzed in conjunction with sample information.Results:The positive detection rate of viral pathogens in 2023 was 21.17% (984/4 648), with rates of 33.53% (504/1 503) observed in ILI cases and 15.62% (480/3 145) in SARI cases. Influenza A virus (FluA) was the predominant virus detected, accounting for 13.7% (637/4 648). Other viruses identified in the surveillance samples included influenza B virus (Flu B), human rhinovirus/enterovirus (HRV/HEV), respiratory syncytial virus (RSV), human metapneumovirus (HMPV), parainfluenza virus (PIV), adenovirus (ADV) and human bocavirus (HBoV). Regarding temporal distribution, HRV/HEV and RSV exhibited the highest detection rates during the second quarter at 2.27% each (28/1 236). PIV had its peak during the third quarter at a rate of 2.49% (35/1 405), and HMPV showed prevalence mainly during the third and fourth quarters, with detection rates of 2.63% (37/1 405) and 2.35% (32/1 360), respectively.Conclusions:In acute respiratory infection surveillance cases in Shanghai in 2023, Flu A emerged as the predominant respiratory pathogen. The detection rate of HMPV ranked second only to Flu A, while other respiratory viruses such as HRV/HEV, RSV, and PIV were detected during different seasons and co-circulated. The prevalence of various respiratory viruses varied among different infected populations and over times.

Objective: To retrospectively analyze the epidemic characteristics and spatial distribution of vomiting and diarrhea outbreaks in schools and kindergartens in Shanghai from 2015 to 2019, so as to provide the scientific evidence for optimizing prevention and control of vomiting and diarrhea outbreaks in schools and kindergartens. Methods: Data collection and analysis were carried out on the vomiting and diarrhea outbreaks reported to Shanghai Municipal Center for Disease Control and Prevention from 2015 to 2019. Epidemiological characteristics were analyzed and compared. The proportion and incidence of outbreaks in schools and kindergartens were calculated, and the influencing factors of outbreaks were analyzed by multivariate Logistic regression. The index of Moran s I was used for the global and local spatial auto correlation analysis. Results: Among the 344 vomiting and diarrhea outbreaks, 98.26% occurred in kindergartens, primary schools, middle schools and other educational institutions. The median number of cases per outbreak was 15. The number of suspected outbreaks and the percentage of cases involved peaked in 2015 ( 60.00% , 84.35%) and then decreased year by year to 16.00% and 38.80% in 2019. About 86.98% of the outbreaks were transmitted by human to human contact. Among the 329 outbreaks with samples collected from cases and/or environments, the main pathogen detected was norovirus ( n =280), and sapovirus was detected in outbreak for the first time in 2016. The outbreaks showed obvious seasonality, with two peaks (November, March) and one trough (July), and the majority of outbreaks occurred in primary schools (44.38%) and kindergartens (32.84%). Compared with kindergartens, the probabilities of suspected epidemic outbreaks in primary schools, combined schools, middle schools and other educational institutions were higher (adjusted OR =6.40, 9.16, 12.64 , 5.58, P <0.01). The proportion and incidence of outbreaks in educational institutions in different districts showed no high-high aggregation areas. Conclusions Primary schools and kindergartens are key places for the prevention and control of vomiting and diarrhea outbreaks. Targeted prevention and control measures should be strengthened at the beginning of each semester and before the peak of the epidemic each year. Timely reporting of symptoms, suspension of school admissions after symptoms appear and standardized disposal of vomit are effective measures to reduce interpersonal transmission and control the scale of an outbreak.

Objective:To analyze the features of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) co-infected with other common respiratory pathogens among coronavirus disease 2019 (COVID-19) patients in Shanghai City, and to provide a reference for scientific prevention and control of COVID-19 and other respiratory infectious diseases.Methods:Descriptive epidemiological approaches were used to analyze the data of COVID-19 reported cases in Shanghai City from January 2020 to February 2021 in the information system of Chinese Disease Prevention and Control. Clinical data of the participants were collected, and their SARS-CoV-2 nucleic acid-positive respiratory specimens were collected at the time of illness onset or admission. Multiplex reverse transcription-polymerase chain reaction (RT-PCR) was performed to detect the 22 respiratory pathogens. Independent-samples t test was used for statistical analysis. Results:Of the 272 patients with COVID-19, 15(5.5%) had co-infection of SARS-CoV-2 with other respiratory pathogens, all of which were double infection. There were three cases infected with enterovirus/rhinovirus, two of each with adenovirus, human metapneumovirus and coronavirus NL63/HKU1, and one of each with coronavirus 229E, influenza A virus H1N1, parainfluenza virus 1 and respiratory syncytial virus B. Two cases infected with Mycoplasma pneumoniae. Among the 272 COVID-19 patients, 212(77.9%) had fever, 117(43.0%) had cough, 46(16.9%) had fatigue, and 35(12.9%) had sore throat. The white blood cell count of co-infection cases was higher than that of non-co-infection cases ((6.8±1.7)×10 9/L vs (5.3±1.6)×10 9/L), and the difference was statistically significant ( t=3.09, P=0.008). Conclusions:There is a certain proportion of co-infection of SARS-CoV-2 with other respiratory pathogens among the COVID-19 cases in Shanghai City, mainly viral pathogens, especially enterovirus/rhinovirus. A rational combination of drugs was recommended to improve the cure rate. Surveillance of acute respiratory infection should be further strengthened as well.

Objective:To evaluate the performance of the influenza surveillance network and compare the epidemic intensity of influenza during 2014-2020 in Shanghai.Methods:Based on the weekly reports of influenza-like illness (ILI) and laboratory-confirmed influenza cases from January 1, 2014 to December 31, 2020. This study first evaluated the data reporting and specimen collection of ILI cases for each sentinel hospital, and then calculated the percentage of ILI (ILI%), the proportion of specimens tested positive for influenza, and the incidence of influenza among all ILI outpatient and emergency visits to measure the epidemic intensity of influenza. Finally, seasonal autoregressive integrated moving average (ARIMA) model was applied to quantify the changes in epidemic intensity of influenza in 2020.Results:The proportion of influenza surveillance sentinel hospitals with a score of less than 5 in the evaluation of ILI data reporting and samples collection were 9.68% and 21.05% in 2020 in Shanghai, respectively. ILI% was estimated to be 1.51% (95% CI: 1.50%-1.51%) and 2.31% (95% CI: 2.30%-2.32%), respectively for 2014-2019 and 2020; the proportion of specimens tested positive was 24.27% (95% CI: 24.02%- 24.51%) and 7.15% (95% CI: 6.78%-7.54%), respectively; and the incidence of influenza was 3.66‰ (95% CI: 3.62‰-3.70‰) and 1.65‰ (95% CI: 1.57‰-1.74‰), respectively. ARIMA model showed that ILI% was increased by 45.25% in 2020 in Shanghai, and the proportion of specimens tested positive and the incidence of influenza were reduced by 78.45% and 51.80%, respectively. Conclusions:In 2020, the performance of influenza surveillance system has changed, ILI% has increased, the proportion of specimens tested positive and the incidence of influenza has decreased in Shanghai. The change in the quality of influenza surveillance is also a potential factor affecting the epidemic intensity of influenza. In the future, the quality control of influenza surveillance network still needs to be further strengthened.

Objective:To study the infection status and epidemiological characteristics of parainfluenza virus (PIV) in acute respiratory tract infection adult cases in Shanghai from 2015 to 2021, and to provide a scientific basis for preventing and controlling PIV.Methods:Acute respiratory tract infections were collected from 13 hospitals in Shanghai from 2015 to 2021. Relevant information was registered, and respiratory specimens were sampled to detect respiratory pathogens by multiplex PCR.Results:A total of 5 104 adult acute respiratory tract infection cases were included; the overall positive rate of the respiratory pathogens was 29.37% (1 499/5 104). The positive rate of PIV was 2.61% (133/5 104), compared with 2.32% (55/2 369) and 2.85% (78/2 735) in influenza-like cases (ILI) and severe acute respiratory infection (SARI) cases, respectively. Among them, PIV3 accounted for the highest proportion (62.41%, 83/133), followed by PIV1 (18.80%, 25/133), PIV2 (9.77%, 13/133), and PIV4 (9.02%, 12/133). The incidence of PIV-positive cases was mainly distributed in the first and second quarters, accounting for 62.41% (83/133). The difference in the incidence in each quarter was significant ( χ2=24.78, P<0.001). Mixed infection accounted for 18.80% (25/133) of 133 PIV-positive cases, the mixed infection rates of ILI and SARI were 18.18% (10/55) and 19.23% (15/78), respectively, and the main mixed pathogen of PIV was coronavirus 229E. Conclusions:There are a certain proportion of PIV-positive acute respiratory tract infection cases in Shanghai. It is necessary to strengthen the etiological surveillance in acute respiratory tract infection cases, especially the mixed infection of PIV and other pathogens.

Objective:In this study, the collected mosquito samples were subjected to viral isolation to identify the species and branch characteristics of arboviruses in five regions of Shanxi Province.Methods:Eight arboviruses in mosquito samples collected from July to September 2020 were detected by real-time fluorescent quantitative PCR, and virus isolation was carried out through cell culture. Virus isolates were identified and analyzed by molecular biology and bioinformatics method.Results:We detected 1 batch of positive samples of Japanese encephalitis virus, 2 batches of positive samples of Culex flavivirus and 8 batches of positive samples of Nam Dinh virus among 121 batches of mosquito samples. Seven virus isolates were isolated, numbered: SX-YJ-Cxp-4、SX-YJ-Ars-2、SX-YJ-Cxp-1、SX-LY-Cxp-10、SX-GP-Ars-5、SX-GP-Cxp-2、SX-GP-Cxp-4, all of which were identified as Nam Dinh virus, and the whole genome sequencing was performed on one of them, and the result showed that Shanxi Nam Dinh virus isolate and Yunnan Nam Dinh virus isolate belonged to the same evolutionary branch.Conclusions:Nam Dinh virus was isolated and identified on the specimen from Shanxi province for the first time.

In order to meet the needs of prevention and control of intestinal infectious diseases， a comprehensive surveillance for diarrheal diseases has been innovated and explored in Shanghai since 2012. The surveillance has extensive distribution of sentinel hospitals， systematic sampling， multi-pathogen collection， and hospital information system （HIS） as the basis， which has achieved “One system for surveillance of multiple diseases and one sample for detection of multiple pathogens". Continual active surveillance for the whole population has been conducted， covering demography， clinical information， epidemiology， pathogen detection， and drug sensitivity test for diarrhea cases. The surveillance has obtained preliminary achievements as follows. First， diarrheal diseases and their periodic changes have been characterized， in which the most prevalent pathogen of diarrhea is determined to be norovirus in Shanghai. Second， some rare pathogens and serotypes have been identified that may provide clues to the sources of outbreaks. Third， it facilitates the information sharing between public health institutions and clinical institutions， and provides scientific evidence for clinical diagnosis and treatment. In the future， Shanghai diarrhea comprehensive surveillance will be improved for expanding range and depth of surveillance， artificial intelligence assisted diagnosis and treatment， early warning of outbreaks， prediction of epidemic trends， and application of new detection technologies.