Background Rotavirus is a principal etiological agent of severe acute gastroenteritis in young children, for which vaccination constitutes the cornerstone of prophylactic intervention. However, to our knowledge, few studies have comprehensively assessed the differential population impacts of alternative rotavirus vaccination strategies within China. This study was therefore conducted to quantify the effect of vaccination on the epidemiological dynamics of rotavirus-associated gastroenteritis in Shanghai. Methods An age-structured Susceptible-Infected-Recovered-Susceptible (SIRS-type) compartmental model incorporating the effects of vaccine interventions was developed. Epidemiological data on reported cases were sourced from the infectious disease surveillance system. Scenario-based simulations were employed to evaluate vaccine efficacy and the prospective outcomes of strategic adjustments to the vaccination program. Results The model demonstrated a high degree of fit with observed epidemiological data over the calibration period from July 2015 to April 2024 (R2 = 0.747, RMSE = 58.55 cases/month; LOO R2 = 0.423). The implementation of the RotaTeq vaccination program resulted in an estimated cumulative reduction of 20.0% (95% CI: 18.9–21.6%) in the whole population and 24.6% (95% CI: 23.0–26.5%) among children under 5 years, relative to a no-RotaTeq counterfactual. Simulations indicated that optimizing the vaccination schedule of the Lanzhou lamb rotavirus vaccine (LLR) and augmenting coverage rates are effective strategies for outbreak mitigation. The introduction of Lanzhou lamb reassortant rotavirus vaccine, live, oral, trivalent (LLR3) and oral hexavalent reassortant rotavirus vaccine (WH-HRV) would further reduce the disease burden across all age groups, potentially controlling the epidemic to a minimal endemic level post-2029. Conclusions The incidence of rotavirus-associated gastroenteritis in Shanghai exhibited a discernible downward trend between 2015 and 2024, a decline associated with substantial contribution from the introduction of the RotaTeq vaccine. The optimization of existing vaccination protocols, in conjunction with the deployment of novel vaccines, is anticipated to be crucial for achieving more comprehensive and sustained control of rotavirus transmission in Shanghai.

PURPOSE:This prospective community-based cohort study (Acute Respiratory Infection Epidemiological Characteristics Assessment Study (ARI-ECAS)) aims to systematically monitor acute respiratory infection (ARI) incidence, characterise multiple pathogen coinfection patterns and explore microbial landscape dynamics in Shanghai's general population. By integrating syndromic surveillance, molecular diagnostics and metagenomic sequencing, the study seeks to enhance understanding of ARI epidemiology, seasonal variation and host-pathogen interactions to inform predictive modelling and optimise public health interventions in high-density urban environments. PARTICIPANTS:The study enrolled 15 199 permanent residents from all 16 districts of Shanghai, with baseline oropharyngeal swab samples across five representative districts (Xuhui, Jing'an, Jiading, Songjiang and Fengxian). Inclusion criteria required residency ≥6 months and consent for weekly follow-ups. Exclusion criteria addressed mobility limitations (planned relocation >6 months) and recent ARI history. Participants provided demographic, behavioural and clinical data via the Shanghai Health Cloud platform, with baseline and symptomatic-phase biological samples collected for analysis. FINDINGS TO DATE:During the initial 8-month surveillance period (May 2024-January 2025), the ARI-ECAS cohort demonstrated critical insights into the epidemiology of acute respiratory infections in Shanghai's urban communities. Among 15 199 participants, 10.96% reported symptomatic episodes, of whom 21.43% experienced recurrent infections. Pathogen detection using targeted next-generation sequencing (tNGS) identified microbial aetiologies in 53.52% of symptomatic cases, revealing a high prevalence of coinfections: 27.96% involved dual pathogens, while 33.01% showed polymicrobial interactions (≥3 pathogens). Notably, 85.09% of symptomatic episodes were self-managed, underscoring a low healthcare-seeking rate (14.91%) consistent with patterns observed in urban China during postpandemic transitions. FUTURE PLANS:The current phase of data collection will conclude in June 2025; however, syndromic surveillance and tNGS protocols will be sustained to capture multiyear seasonal transmission patterns. To enhance comparative rigour, future protocols will aim to collect samples from participants during asymptomatic periods in the subsequent year to serve as seasonal baseline controls. Building on this foundation, the study will integrate contact behaviour and mobility surveys to quantify parameters critical for understanding pathogen transmission dynamics (eg, household contacts and public transportation usage). Furthermore, pathogen detection and metagenomic data will be combined with transcriptomic and metabolomic profiling in selected cases to model multipathogen interaction networks and delineate host immune response pathways, thereby advancing mechanistic insights into polymicrobial cocirculation.

Objective To describe the epidemiological and clinical characteristics of a cluster of severe fever with thrombocytopenia syndrome (SFTS) cases in Shanghai and assess the potential risk of healthcare-associated transmission. Methods Epidemiological and clinical data were collected from seven patients, including the index case, four family members, and two healthcare workers. Serum samples from five patients were tested for SFTS virus (SFTSV) RNA and SFTSV-specific IgM antibodies. Results The index case developed symptoms on June 12, 2018, and died on June 23. Between June 30 and July 6, three family members and one healthcare worker developed fever, thrombocytopenia, and leukopenia; SFTSV RNA was detected in their blood samples. One family member died of multiple organ failure 11 days after symptom onset. Another family member and one doctor developed febrile symptoms and were positive for SFTSV IgM antibodies. Overall, seven cases were identified, including two deaths and two infections among healthcare workers. Conclusions This cluster suggests possible family and healthcare-associated transmission of SFTSV in Shanghai, a non-endemic area of China. Improved clinical awareness and infection prevention are needed when managing unexplained febrile hemorrhagic illnesses.

Seasonal influenza activity was disrupted due to the emergence of coronavirus disease 2019 (COVID-19) and the implementation of non-pharmaceutical interventions. In this study, we analyzed weekly influenza-like illness (ILI) cases and influenza positivity rate by subtype and age group from the Shanghai influenza surveillance system from 2015 to 2023. A wavelet analysis was conducted to explore the seasonal pattern of influenza. The average weekly ILI consultation rate was 20.28 ILI cases per 1,000 consultations, with 40,778 of 173,155 specimens (22.63 %) testing positive for influenza. During the COVID-19 pandemic, nearly no influenza viruses were detected until January 2021. Only B/Victoria was circulated for about eight months and peaked in January 2022, with a positivity rate of 47.48 %, which was lower than the peaks in each year before the COVID-19 pandemic. In 2023, the first epidemic, dominated by A(H1N1), began in week 8 (one month later than the 8-year average) and peaked at 76.89 %. The second epidemic, which was unusually not summer-based and driven by A(H3N2), started in week 38 and peaked in week 48 at 75.31 %, advancing the winter-spring epidemic by approximately one month. The age preference of influenza A changed during the era of normalized COVID-19 transmission. The seasonal patterns of influenza varied significantly across different stages of the COVID-19 pandemic, including differences in epidemic onset, peak timing, duration, periodicity, and dominant strains. Stability of seasonal changes in influenza requires longer-term surveillance, as well as further virologic and epidemiologic studies.

Introduction:The rapid evolution and symptom overlap of Coronavirus disease 2019 (COVID-19) and influenza challenge the effectiveness of current surveillance and healthcare resource planning. However, comparative evidence regarding their surveillance sensitivity and healthcare burden remains limited, particularly within concurrent community populations that capture the full spectrum of disease severity. Methods:To address this gap, data were derived from a community-based syndromic surveillance cohort in Shanghai, followed weekly between May 2024 and August 2025. We analyzed symptom profiles and illness duration, assessed the sensitivity of Influenza-Like Illness (ILI) definitions, and evaluated healthcare-seeking behaviors across both acute (0-14 days) and post-acute (>14 days) phases. Results:From May 2024 to August 2025, 382 COVID-19 and 175 influenza cases were identified. Compared with influenza, COVID-19 cases presented distinctively with upper respiratory symptoms (sore throat: 72.88% vs. 58.29%, runny or stuffy nose: 46.58% vs. 33.71%, loss of taste or smell: 3.84% vs. 0.57%; all p < 0.05), rather than fever (61.64% vs. 74.86%, p = 0.003). Consequently, standard ILI definitions failed to detect a significantly larger proportion of COVID-19 cases compared to influenza (China CDC criteria: 35.89% vs. 50.86%, p = 0.001; WHO criteria: 27.12% vs. 44.00%, p < 0.001). While illness duration was shorter for COVID-19 (6.66 ± 4.35 days vs. 8.25 ± 4.34 days, p < 0.05), influenza imposed a heavier healthcare burden, characterized by a two-fold increase in outpatient visits during the acute phase (OR = 2.12, 95% CI: 1.52-2.95) and sustained demand in the first 90 days of the post-acute phase (HR = 1.29, 95% CI: 1.03-1.61). Conclusion:COVID-19's symptom profile limits ILI surveillance sensitivity, whereas influenza imposes a higher burden extending into the post-acute phase. These differences call for adapting surveillance strategies and healthcare resource allocation to these distinct pathogen profiles.

[Objective]To investigate the current awareness and optimization recommendations on pneumonia with unknown etiology(PUE)surveillance among Shanghai healthcare professionals,and to provide evidence for the improvement of the surveillance system.[Methods]In December 2024,healthcare professional participants from diverse medical and health institutions were randomly selected within each stratum using a stratified cluster sampling method in all 16 districts of Shanghai for questionnaire surveys on their knowledge and suggestions for optimization of the PUE surveillance system.Descriptive statistics analyses,multivariate logistic regressions,and content analyses were used for data analyses.[Results]A total of 385 survey subjects were involved in the study,including 119 professional staffs from disease prevention and control centers and 266 from medical institutions.Those who understood the case definition for PUE correctly accounted for 67.01%(258/385).Multivariate regression model analyses showed that female gender(aOR=2.22,95%CI:1.36-3.66),professionals from disease control institutions(aOR=2.02,95%CI:1.12-3.72),and those who self-assessed as being familiar with the monitoring system(aOR=2.18,95%CI:1.23-3.89)had better understanding of the definition.Overall,89.61%(345/385)of the survey subjects acknowledged the necessity of the surveillance system.Small number of cases meeting the case definition(54.46%,214/379),insufficient diagnostic awareness(39.84%,151/379),and lack of incentives for case reporting(29.29%,111/379)were major problems for the current surveillance system,with variations observed across different types of institutions.Suggested segments for optimizing the surveillance system included monitoring purpose,case definition,form of monitoring and reporting procedure,organization mechanism,and epidemiological investigation and response.[Conclusion]The necessity of PUE surveillance is commonly recognized among healthcare workers.However,the existing system falls short in terms of mastery of case definition and overall surveillance adaptability.There is an urgent need for optimization and improvement to enhance the capacity for preventing and controlling emerging and sudden respiratory infectious diseases.

Background:Acute respiratory infections (ARIs) remain a major global health concern. Although long-term air pollution exposure has been linked to ARIs, prospective evidence from community-based populations remains limited. Objective:This study aimed to quantify the burden of ARIs in the community and examine the associations between long-term exposure to particulate matter 2.5 (PM2.5) and ozone (O3) and the risks of ARIs, with additional analyses using influenza-like illness (ILI) as a more specific outcome. Methods:We conducted a prospective cohort study including 3617 residents in Shanghai, China, who were followed weekly for 1 year. Individual-level exposure to PM2.5 and O3 concentrations was estimated using high-resolution datasets. Cox proportional hazards models with shared frailty were applied to assess associations with ARIs. Exposure windows of 3, 6, 9, and 12 months were evaluated, and the optimal window was selected based on the Akaike information criterion. Effect estimates were reported per IQR increase. Dose-response relationships, subgroup analyses, and multiple sensitivity analyses were performed. Results:During 3217 person-years of follow-up, 885 ARI events were documented (0.27 per person-year). In the fully adjusted model using the 12-month exposure window, each IQR increase in PM2.5 was associated with higher risks of ARIs (hazard ratio [HR] 1.594, 95% CI 1.340-1.897), with stronger associations observed for ILI (HR 1.948, 95% CI 1.484-2.557). For O3, the corresponding HRs were 1.510 (95% CI 1.135-2.007) for ARIs, with stronger associations for ILI (HR 2.229, 95% CI 1.385-3.588). PM2.5 showed a nonlinear association with ARIs, whereas linear relationships were observed for PM2.5 with ILI and O3 with both outcomes. Evidence of effect modification was observed by age, residence, and season for PM2.5 and by season for O3. Results were robust across multiple sensitivity analyses. Conclusions:Long-term exposure to PM2.5 and O3 is associated with increased risk of ARIs, with similar associations observed for ILI. These findings highlight the importance of long-term air pollution control and targeted interventions for susceptible populations, particularly during cold seasons.

Objectives The number of post-marketing studies assessing the vaccine effectiveness (VE) of the Lanzhou lamb rotavirus vaccine (LLR, licensed in 2000 exclusively in China) and the oral human attenuated pentavalent rotavirus vaccine (RotaTeq, licensed in China in 2018) in China is limited. Methods A test-negative case-control study based on prospective surveillance was conducted among diarrhea patients aged 5 years and younger at five hospitals in Shanghai, China. Cases and controls were defined based on the results of real-time fluorescent quantitative reverse transcription polymerase chain reaction (rRT-PCR) of fecal samples for rotavirus. Both matched and unmatched case-control study designs were employed using logistic regression models, with adjustments for age at onset age and the rotavirus epidemic season. Results In the LLR-specific analysis (247 cases, 2191 controls), the VE of partial LLR vaccination (2 doses) was 49.09 % (95 % CI: 1.69 % ∼ 73.64 %) in multivariate analyses. In the RotaTeq-specific analysis (42 cases and 523 controls), the VE of complete RotaTeq vaccination was 87.13 % (95 % CI: 45.87 % ∼ 96.94 %), 89.46 % (95 % CI: 55.03 % ∼ 97.53 %), and 85.69 % (95 % CI: 33.43 % ∼ 96.93 %) respectively in univariate, multivariate, and matched analyses, respectively. The vaccination coverage for any dose among 2893 patients with rotavirus-negative diarrhea born between 2011 and 2022 was 49.78 %. Following the licensure of RotaTeq in 2018, this coverage increased from 45.02 % to 61.77 %. Conclusions RotaTeq demonstrates a robust protective effectiveness, while LLR provides a certain level of protection against mild to moderate rotavirus diarrhea in children in Shanghai. For privately purchased (non-NIP) vaccines, we estimate that the coverage for rotavirus vaccines among children in Shanghai is high. Complete rotavirus vaccination is recommended for age-eligible children. Further post-marketing research on rotavirus vaccines is necessary to inform decision-making regarding the introduction of rotavirus vaccination in China.

Acute respiratory infections (ARIs) remain a major global health concern, yet evidence on the impact of long-term air pollution exposure on both incident and recurrent ARIs in the general population is still limited. This study aimed to assess the risk of ARIs among residents of a community-based cohort in Shanghai and to investigate the associations between long-term exposure to air pollutants and the risks of both incident and recurrent ARIs. We established a prospective cohort of 3,631 residents in Shanghai, China, who were followed weekly for one year. Individual-level PM2.5, PM10, NO2, and O3 concentrations were estimated using 1 km × 1 km satellite-based models at residential addresses, and exceedance days were calculated. Incident ARIs were analyzed using Cox proportional hazards models, while recurrent ARIs were examined using marginal Cox models with robust standard errors. We further fitted time-varying Cox models to estimate hazard ratio trajectories over the follow-up period. Stratified analyses were conducted to assess potential effect modification by key covariates, and sensitivity analyses were performed using alternative exposure windows, two-pollutant models, and additional models for recurrent ARIs to assess robustness. During 3,498 person-years of follow-up, a total of 874 ARIs were recorded (0.25 per person-year). For incident ARIs, each 1 μg/m3 increase in PM2.5, PM10, and O3 was associated with HRs of 1.25 (95% CI: 1.12–1.40), 1.16 (95% CI: 1.03–1.30), and 1.24 (95% CI: 1.18–1.30), respectively. Stronger associations were observed for recurrent ARIs with PM2.5 and PM10, while the effect of O3 remained stable. Time-varying Cox models revealed that the effects of PM2.5 and PM10 gradually attenuated, whereas the effect of O3 appeared later and strengthened over time. Long-term exposure to PM2.5, PM10 and O3 significantly increases the risk of both incident and recurrent ARIs, with differential time-varying patterns across pollutants.

ObjectiveTo analyze the evolutionary characteristics and genetic variations of the HA (hemagglutinin) and NA (neuraminidase) genes of influenza A(H1N1) viruses in Shanghai during 2024, to investigate their transmission patterns, and to evaluate their potential impact on vaccine effectiveness.MethodsFrom January to October 2024, throat swab specimens were collected from influenza like illness (ILI) patients at 4 hospitals in Shanghai. Real-time fluorescence ploymerase chain reaction (RT-PCR) was used for virus detection and isolation of H1N1 influenza viruses. Forty influenza A(H1N1) virus strains were sequenced using Illumina NovaSeq 6000 platform, followed by phylogenetic analyses, genetic distance analysis, and amino acid variation analyses of HA and NA genes.ResultsPhylogenetic tree of the HA and NA genes revealed that the 40 influenza A(H1N1) virus strains circulating in Shanghai in 2024 exhibited no significant geographic clustering, with a broad origin of strains and complex transmission chains. Genetic distance analyses demonstrated that the average intra-group genetic distances of HA and NA genes among the Shanghai strains were 0.005 1±0.000 6 and 0.004 6±0.000 6, respectively, which were comparable to or higher than those observed in global surveillance strains. Both HA and NA genes displayed frequent mutations. Compared to the 2023‒2024 and 2024‒2025 Northern Hemisphere A(H1N1) vaccine strains (WHO-recommended), the HA proteins of 40 Shanghai strains exhibited amino acid substitutions at positions 120, 137, 142, 169, 216, 223, 260, 277, 356 and 451, with critical mutations at positions 137 and 142 located within the Ca2 antigenic determinant. Furthermore, mutations in the NA protein were observed at positions 13, 50, 200, 257, 264, 339 and 382.ConclusionThe genetic background of the 2024 Shanghai influenza A(H1N1) virus strains is complex and diverse, and antigenic variation may affect vaccine effectiveness. Therefore, it is recommended to enhance genomic surveillance of influenza viruses, evaluate vaccine suitability, and implement more targeted prevention and control strategies against imported influenza viruses.

As COVID-19 transitions from pandemic to endemic, our prevention and control policies have shifted from broad, strict community interventions to focusing on the prevention of cluster outbreaks. Currently, information on the characteristics of cluster outbreaks remains limited. This study describes the features of COVID-19 clusters in Shanghai. It aims to provide valuable insights for managing localized outbreaks. We conducted a retrospective analysis of clusters of confirmed COVID-19 cases. Epidemiological descriptions, the transmission characteristics of clusters, and individual risk factors for contagiousness were analyzed. A total of 381 cases of COVID-19 were confirmed and 67 clusters were identified. Most clusters (58.21%, 39/67) only had two cases, with a declining proportion held by clusters of more cases. Familial transmission was predominant, accounting for 79.10% (53/67) of clusters. Although other types of cluster outbreaks, such as those in workplaces (1.49%, 1/67), occur less frequently compared to household clusters, they tend to involve larger scales and more cases. Workplaces and similar venues are more likely to experience large-scale cluster outbreaks. Contagiousness was higher among cases with runny nose (risk ratio [RR]: 4.8, 95% CI: 1.40-16.44, p-value = 0.01) and those with diabetes (RR: 3.8, 95% CI: 1.01-14.60, p-value = 0.05). In conclusion, household cluster outbreaks, in particular, are both a key priority and a foundational issue. Establishing an indicator system based on the transmissibility of cases holds significant practical value for infectious disease prevention and control. By enhancing household hygiene and developing a case classification and management system based on transmissibility, it is possible to better prevent and control regional COVID-19 outbreaks.

Introduction: This study investigated temporal changes in rotavirus group A (RVA) prevalence, epidemiological characteristics, and genotype distribution patterns among diarrhea outpatients in Shanghai Municipality, China. Methods: We conducted prospective active surveillance of diarrheal disease in pediatric and adult outpatients in Shanghai. Stool specimens were analyzed for five viral and twelve bacterial pathogens. Real-time reverse transcription polymerase chain reaction (rRT-PCR) was employed for RVA detection, followed by genotyping of RVA-positive specimens through partial amplification of VP7 and VP4 genes. Results: The study analyzed 2,331 diarrhea cases in children aged 0-14 years and 8,418 cases in individuals aged >= 15 years between January 2017 and December 2023. Overall RVA positivity rates decreased significantly from 7.43% in 2017 to 1.19% in 2023 (P=0.024). The most pronounced decline occurred in children aged 2-5 years, where positivity rates fell from 13.08% to 1.72%. Adults aged >= 30 years also showed a substantial reduction. Among RVA-positive pediatric cases (<= 14 years), the proportion of cases aged 6-14 years increased from 2.33% to 18.18%. While G9P[8] remained the predominant strain, its prevalence decreased from 77.78% to 31.25%, concurrent with the emergence of G8P[8] strains. Conclusions: RVA prevalence has shown a marked decline since 2018-2019, accompanied by a shift in age distribution toward older children. The diminishing dominance of G9P[8] strains coincided with the emergence of G8P[8] strains. Continued epidemiological and genetic surveillance of rotavirus diarrhea, coupled with real-world effectiveness evaluations of domestic vaccines, remains crucial for optimizing rotavirus immunization strategies.

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 25th 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 analyze the epidemiological characteristics of clustered vomiting and diarrhea outbreaks in Minhang District of Shanghai, to identify the influencing factors of outbreak scale and duration of epidemic, and to provide scientific evidence for further strengthening surveillance early-warning efforts in key settings and for optimizing prevention and control measures.MethodsThe data for describing epidemiological characteristics of clustered vomitting and diarrhea outbreaks in Minhang District from 2018 to 2023 were collected, multivariable logistic regression models were applied to analyze the influencing factors for epidemic scale,and Spearman rank correlation analyses were applied to analyze the factors duration.ResultsA total of 136 clustered vomiting and diarrhea outbreaks were reported in Minhang District from 2018 to 2023, all occurring in school settings, with an overall attack rate of 0.90%. The outbreaks exhibited distinct seasonality, predominantly occurring from October to December (43.38%) and March to May (32.35%). The primary settings were preschools (45.59%) and elementary schools (44.12%), with students accounted for the majority of cases (99.48%). The predominant clinical manifestation was vomiting (90.44%), with person-to-person contact being the primary transmission route (98.53%). Norovirus genogroup Ⅱ was identified as the main pathogen (71.32%). Standardized terminal disinfection of outbreak sites (OR=0.39, 95%CI=0.20‒0.74) and effective isolation of affected classes (OR=0.23, 95%CI=0.09‒0.57) were significant protective factors for reducing outbreak scale. Both response time (r=0.64, P<0.001) and the number of case generations (r=0.71, P<0.001) showed positive correlations with outbreak duration.ConclusionSchools are the key settings for the prevention and control of clustered vomiting and diarrhea outbreaks in Minhang District, with peak occurring in autumn and spring. Early detection, timely reporting, and prompt response to outbreaks are crucial. Strengthening school-based surveillance systems and standardizing outbreak management protocols are of particular importance.

IntroductionTo characterise age-mixing patterns among index cases and contacts of COVID-19, and explore when patients are most infectious during the disease process.MethodsThis study examined all initial 90 885 confirmed index cases in Shanghai and their 450 770 close contacts. A generalised additive mixed model was used to analyse the associations of the number of close contacts with different demographic and clinical characteristics. The effect of different exposure time windows on the infection of close contacts was evaluated using a modified mixed-effects Poisson regression.ResultsAnalysis of contacts indicated that 82 467 (18.29%; 95% CI 18.17%, 18.42%) were second-generation cases. Our result indicated the q-index was 0.300 (95% CI 0.298, 0.302) for overall contact matrix, and that assortativity was greatest for students (q-index=0.377; 95% CI 0.357, 0.396) and weakest for people working age not in the labour force (q-index=0.246; 95% CI 0.240, 0.252). The number of contacts was 4.96 individuals per index case (95% CI 4.86, 5.06). Contacts had a higher risk if they were exposed from 1 day before to 3 days after the onset of symptoms in the index patient, with a maximum at day 0 (adjusted relative risk (aRR)=1.52; 95% CI 1.30, 1.76). Contacts exposed from 3 days before to 3 days after an asymptomatic index case had a positive reverse transcriptase-PCR (RT-PCR) result had a higher risk, with a maximum on day 0 (aRR=1.48; 95% CI 1.37, 1.59).ConclusionsThe greatest assortativity was for students and weakest for people working age not in the labour force. Contact in the household was a significant contributor to the infection of close contacts. Contact tracing should focus on individuals who had contact soon before or soon after the onset of symptoms (or positive RT-PCR test) in the index case.

[Objective]To 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.[Methods]A 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.[Results]The 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.[Conclusion]This 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.

Background: Little is known about the characteristics of those who transmit SARS-CoV-2 infection vs those who do not, but this information could inform disease control policies. This study described the features of clusters in the first wave of COVID-19 in Shanghai and compared contagiousness by clinical and health care risk factors. Methods: In this retrospective cohort study of cases in Shanghai in January and February 2020, cases with successive generations were considered to be “contagious.” Characteristics of contagious and non-contagious cases were compared in log-binomial models that also adjusted for age and sex. Results: Between January 21 and February 17, 2020, 333 cases of COVID-19 were reported in Shanghai across 28 known infection chains. Contagiousness was higher among cases with a sore throat (risk ratio [RR]: 3.41, 95% CI: 1.59, 7.35, P=0.0051), and those with heart disease (RR: 2.06, 95% CI: 0.72, 5.90). Delays in diagnosis were also associated with higher risk of contagiousness. Having ≥2 medical visits before diagnosis was associated with 4.46 times higher risk of contagiousness (95% CI: 2.03, 9.83, P=0.0002), and there was a non-significant increase in risk with increasing numbers of days between disease onset and isolation (for each day, RR: 1.08, 95% CI: 1.01, 1.16, P=0.1734). Conclusions: Individuals with mild COVID-19 symptoms in the upper respiratory tract may still be contagious, and such individuals should be prioritized for early diagnosis and isolation to limit further chains of transmission.

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.