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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.
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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.
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ObjectiveTo predict the incidence trend of influenza-like illness proportion （ILI%） in Shanghai using the seasonal autoregressive integrated moving average model （SARIMA）， and to provide an important reference for timely prevention and control measures. MethodsTime series analysis was performed on ILI% surveillance data of Shanghai Municipal Center for Disease Control and Prevention from the 15th week of 2015 to the 52nd week of 2019， and a prediction model was established. Seasonal autoregressive integrated moving average （SARIMA） model was established using data from the foregoing 212 weeks， and prediction effect of the model was evaluated using data from the latter 36 weeks. ResultsFrom the 15th week of 2015 to the 52nd week of 2019， the average ILI% in Shanghai was 1.494%， showing an obvious epidemic peak. SARIMA（1，0，0） （2，0，0） 52 was finally modeled. The residual of the model was white noise sequence， and the true values were all within the 95% confidence interval of the predicted values. ConclusionSARIMA（1，0，0） （2，0，0） 52 can be used for the medium term prediction of ILI% in Shanghai， and can play an early warning role for the epidemic and outbreak of influenza in Shanghai.
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Objective:To analyze the changes in the epidemiological characteristics of scarlet fever cases in Shanghai City before and after the outbreak of coronavirus disease 2019 (COVID-19), and to provide a reference for scientific prevention and control of scarlet fever.Methods:The information of scarlet fever reported cases in Shanghai City from January 2016 to June 2021 in the information system of Chinese Disease Prevention and Control was collected, and the differences in time trend, regional distribution, age and gender distribution of cases before and after the outbreak of COVID-19 in Shanghai City were analyzed by descriptive epidemiologic method.Results:The incidence rate of scarlet fever reported in 2016-2019 was (0.22-4.02)/100 000 in each month, with a median of 1.13/100 000. During January 2020 (the outbreak began in Shanghai City) and June 2021, the incidence rate of scarlet fever was (0.01-1.64)/100 000, with a median of 0.14/100 000, which was 12.39% of that before the outbreak of COVID-19. During February and June 2020, the monthly reported incidence rate of scarlet fever was (0.18-0.58)/100 000, showing an upward trend compared with the same period in 2020 ((0.01-0.05)/100 000). From 2016 to 2019, the annual reported incidence rate of each district was (0.55-65.48)/100 000, with a median of 9.57/100 000; while in 2020, the annual reported incidence rate of each district was (0.29-9.85)/100 000, with a median of 2.18/100 000, which was 22.78% of that before the outbreak of COVID-19. The incidence of scarlet fever dropped significantly. The incidence rate in Minhang District was still the highest. The cases were mainly four to eight years old, and there was no substantial difference of the proportions before and after COVID-19 pandemic, with the incidence rate of six years old group the highest. The proportion of male was more than female in reported case, while the male ratio in reported cases was not significantly different before and after COVID-19 pandemic.Conclusions:The incidence rate of scarlet fever in Shanghai City has dropped sharply after COVID-19 pandemic. The main epidemiological characteristics of the regional and population distribution of cases remain unchanged.
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Objective@#To understand the epidemiological and pathogenic characteristics of hospitalized severe acute respiratory infections (SARI) in Shanghai, China.@*Methods@#From 2015 to 2017, one Tertiary hospital and one Secondary hospital were chosen as the surveillance sites. Two respiratory tract specimens per case were collected from SARI cases aged 15 years and older. One specimen was tested for 22 respiratory pathogens by RT-PCR, and the other specimen was cultured for 6 respiratory bacteria.@*Results@#A total of 287 SARI cases were enrolled for sampling and lab testing. 70.73% of the cases were aged 60 years and older, with 41.46% (119/287) were positive for at least one pathogen. Influenza virus was the predominant pathogen, accounting for 17.77% (51/287) of all SARI cases. Human rhinovirus/Enterovirus and Coronavirus were both accounting for 7.32% (21/287), followed by Mycoplasma pneumoniae (5.57%, 16/287). The positive rates of parainfluenza virus, bocavirus, adenovirus, respiratory syncytial virus and human metapneumo virus were all less than 5%. Bacterial strains were identified in seven SARI cases, including Klebsiella pneumoniae (3 strains), Staphylococcus aureus (2 strains), Streptococcus pneumoniae (1 strain) and Pseudomonas aeruginosa (1 strain). Two or Three pathogens were co-detected from 40 cases, accounting for 33.61% of 119 positive cases. The most common co-detected pathogens were influenza virus and Mycoplasma pneumoniae (10 cases). Influenza cases peaked in winter-spring and summer. Mycoplasma pneumoniae peaked in winter-spring season and overlapped with influenza. The positive rates of pathogens were not significantly different between different age groups.@*Conclusions@#Various respiratory pathogens can be detected from SARI cases aged 15 years and older. Influenza virus was the predominant pathogen and the co-detection of influenza virus with Mycoplasma pneumoniae the most common one.
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Objective@#To analyze the etiologic and epidemiological characteristics of adult acute respiratory infections in Shanghai during 2015-2017.@*Methods@#Data was collected from outpatients with acute respiratory infections who visited the Fever Clinics in three hospitals of different levels in three administrative regions of Shanghai, from 2015 to 2017. Basic information and nasopharyngeal swabs were collected from cases in line with the inclusion criteria. Multiplex RT-PCR and bacterial cultures were performed to detect the respiratory pathogens.@*Results@#A total of 806 individuals were enrolled from 2015 to 2017. Respiratory pathogens were identified in 73.45% (592/806) of the cases, with the virus detection rate as 66.75% (538/806). It was found that the major respiratory pathogens for virus detection were influenza A in 326 (40.45%), influenza B in 116 (14.39%), rhinovirus/enterovirus in 39 (4.84%) of the cases. The overall detection rate of bacteria was 16.13% (130/806), including Klebsiella pneumoniae in 90 (11.17%) cases, Staphylococcus Aureus in 46 (5.71%) cases. Other kind of bacteria were not detected in our study. The detection rates on Mycoplasma pneumoniae was 5.33% (43/806) and on Chlamydia pneumonia was 0.37% (3/806). Co-infection with multiple pathogens was detected in 18.61% (150/806) of the cases, including 135 with double infection (accounting for 90.00%), 14 with triple infection and 1 with quadruple infection (accounted for 9.33% and 0.67%, respectively). Among the 150 cases with co-infections, the main identified pathogens were influenza A, Klebsiella pneumoniae, Staphylococcus aureus, and Mycoplasma pneumoniae. Pathogens of acute respiratory infections that identified among the outpatients from the Fever Clinics at different time, region or population, the characteristics were different (P<0.001).@*Conclusions@#In 2015-2017, outpatients with acute respiratory infections in Shanghai were mainly caused by influenza virus or other viruses, however dynamically with its composition, time, region and characteristics of the population. It is necessary to strengthen and combine related medical and preventive services and to develop the appropriate strategies regarding clinical diagnosis and treatment.
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Objective To compare the detection situation of influenza-like illnesses with different symptoms and analyze the impact on the influenza surveillance by adopting different case definitions of influenza-like illness.Methods Data was collected from 2 national influenza surveillance sentinel hospitals in Shanghai,2015.We compared the positive rate of influenza virus among patients with different symptoms (with cough and sore throat,with cough only and with sore throat only),and utilized Logistic regression model to analyze the influencing factors of the detection rate of influenza virus.Results Among 2 010 influenza-like illnesses,1 105 patients were with cough and sore throat,270 patients were with cough,635 patients were with sore throat,and the positive rate of influenza was 36.2％,39.3％ and 15.9％ respectively.The patients with cough and sore throat or with cough only had a higher positive rate of influenza than patients with sore throat (all P ＜ 0.05).For patients with specimens collected within 3 days,patients with cough and sore throat,or with cough only had a higher positive rate than patients with sore throat only (all P ＜ 0.05).Logistic regression results showed that fever (body temperature≥39 ℃) (OR =1.719,95％ CI:1.389-2.127) and cough (OR =3.046,95％ CI:2.377-3.905) were associated with the detection of influenza virus.Conclusions We suggested that we can adopt the case definition of influenza-like illness'fever (body temperature ≥38 C) and cough'in the influenza surveillance system.
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<p><b>OBJECTIVE</b>To understand the epidemiological profiles of hand, foot and mouth disease (HFMD) and the major enteroviruses causing the epidemics of HFMD in Shanghai from 2010 to 2014.</p><p><b>METHOD</b>The city-wide surveillance data between 2010 and 2014 were used to analyze the epidemiologic characteristics of the HFMD outbreaks in Shanghai. The annual incidence of HFMD was estimated based on the 2010 Shanghai Census data.</p><p><b>RESULT</b>From 2010 to 2014, the reported HFMD cases were 41 080, 37 323, 51 172, 42 198, and 65 018, respectively; the severe cases (case-severity ratio) were 469 (1.14%), 456 (1.22%), 318 (0.62%), 104 (0.25%) and 248 (0.38%), respectively. Based on Shanghai census data by the end of 2010, the attack rates of HFMD in Shanghai were 0.16%-0.28% in the entire population. In terms of the proportion of HFMD cases and severe cases in the specific population, male accounted for 59.62%-61.48% and 62.26%-73.08%, migrant population accounted for 51.86%-62.40% and 72.01%-80.38%; children aged 1.0-1.9 years comprised the highest proportion, up to 22.70%-27.00% and 32.08%-36.40%. HFMD peaked from April to July, in parallel with the peak circulation of enterovirus (EV) 71, and a small peak usually occurred in autumn and winter. All the critically severe and fatal cases were caused by EV71. The detection rates of EV71 and Coxsackievirus A (CA) 16 were 73.08%-88.09% and 1.12%-2.90% in severe HFMD cases, 19.75%-48.74% and 2.02%-23.69% in uncomplicated inpatients, and 16.78%-40.08% and 8.36%-33.39% in mild community cases, respectively. The detection rates of CA6 and CA10 in the mild community cases in 2014 were 18.38% and 1.43%, respectively. In 2013 non-EV71 and non-CA16 enteroviruses comprised 74.86% in the community cases.</p><p><b>CONCLUSION</b>The annual HFMD outbreaks occurred in Shanghai during 2010-2014. Children under 5 years of age, migrant population and male were the major susceptible population. EV71 and CA16 were the predominant pathogens causing the epidemics of HFMD except in 2013, and CA6 was prevalent in the community cases in 2014. The major peak season of HFMD usually overlapped with the peak of EV71 circulation and the majority of severe HFMD cases were associated with EV71 infection.</p>