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• The seasonality of influenza activity in Shanghai, China after the 2009 A/H1N1 pandemic is complex. • Annual winter epidemics were found and lasted into spring in some years. • Co-circulation of A/H3N2, A/H1N1, and two lineages of influenza B contributed to the annual winter epidemics. • Semiannual epidemics in the summer, which were found in four of the six surveillance years, were only attributable to A/H3N2. • The current one-season vaccination program in Shanghai, China should be carefully reconsidered. Understanding the complexity of influenza subtype seasonality is critical to promoting a suitable vaccination program. The aim of this study was to identify and compare the seasonality and epidemiological features of seasonal influenza subtypes after the 2009 A/H1N1 pandemic and to lay a foundation for further investigation into the social and environmental factors affecting seasonal influenza virus transmission. Influenza-like illness (ILI) case surveillance was conducted in two sentinel hospitals in Pudong New Area, Shanghai between 2012 and 2018. Weekly data on ILI cases were analyzed. A time-series seasonal decomposition analysis was used to reveal the seasonality of influenza and epidemiological features among different subtypes. In total, 10 977 ILI patients were enrolled of whom 2385 (21.7%) had laboratory-confirmed influenza. Compared to influenza A (16.3%), influenza B (5.4%) was less frequently detected among the ILI patients (p < 0.001). Semiannual epidemic peaks were identified in four of the years during the 6-year study period, while only one annual epidemic peak was found in the other two years. An epidemic peak occurred in each winter season, and a secondary peak also occasionally occurred in summer or spring. A/H3N2 predominated in both summer and winter, while A/H1N1, B/Yamagata, and B/Victoria circulated almost exclusively in winter or spring. Two lineages of influenza B seemed to predominate in alternating years. This study highlights the complexity of seasonal influenza virus activity in a subtropical region of China, presenting both semiannual and annual epidemic peaks in different years. The results of this study may provide further insight into possible improvements in the timing of influenza vaccination in Shanghai, China. [ABSTRACT FROM AUTHOR]

We aimed to understand the temporal dynamics of SARS‐CoV‐2 reinfection risk and assess the impact of inactivated vaccination on the occurrence of reinfection. We investigated the reinfection risk of SARS‐CoV‐2 from November 1, 2022, to February 12, 2023, when China rapidly lifted the zero‐COVID policy. The study subjects were those who were first infected during the zero‐COVID period between January 1, 2020, and October 31, 2022, in Dalian city, China. Among the 1961 previous infections, 126 (6.4%, 95% CI: 5.4, 7.5) were reinfected. The risk of reinfection increased over time since initial infection. Compared with those who did not receive or received one dose of inactivated vaccine, receiving two or three doses was associated with additional protection against reinfection among individuals who were infected with pre‐Omicron more than a year earlier, with the OR ranged from 0.33 (95% CI: 0.03, 1.83) to 0.91 (95% CI: 0.22, 3.27). In contrast, no protective effect from two or three doses of vaccines against reinfection was observed among those who were first infected with Omicron variants within a year. Primary or booster vaccination contributed to limited protection against reinfection or symptomatic reinfection among individuals infected with Omicron SARS‐CoV‐2 within a year. However, a booster dose after 1 year of natural infection may provide additional protection against reinfection. [ABSTRACT FROM AUTHOR]

X-axis: The value of climate variable; Y-axis: 2-weeks lagged cumulative relative risk (RR), indicating the number of times more likely to have influenza compared to reference value (Ref); Solid line: RR value; Grey shadow: 95% confidence interval (95% CI). • High temperature only associated with influenza A occurrence. • High diurnal temperature range (DTR) causes more influenza A cases. • Low DTR causes more influenza B cases. • High DTR and low temperature were the key drivers for influenza A and B separately. Most previous studies focused on the association between climate variables and seasonal influenza activity in tropical or temperate zones, little is known about the associations in different influenza types in subtropical China. The study aimed to explore the associations of multiple climate variables with influenza A (Flu-A) and B virus (Flu-B) transmissions in Shanghai, China. Weekly influenza virus and climate data (mean temperature (MeanT), diurnal temperature range (DTR), relative humidity (RH) and wind velocity (Wv)) were collected between June 2012 and December 2018. Generalized linear models (GLMs), distributed lag non-linear models (DLNMs) and regression tree models were developed to assess such associations. MeanT exerted the peaking risk of Flu-A at 1.4 °C (2-weeks' cumulative relative risk (RR): 14.88, 95% confidence interval (CI): 8.67–23.31) and 25.8 °C (RR: 12.21, 95%CI: 6.64–19.83), Flu-B had the peak at 1.4 °C (RR: 26.44, 95%CI: 11.52–51.86). The highest RR of Flu-A was 23.05 (95%CI: 5.12–88.45) at DTR of 15.8 °C, that of Flu-B was 38.25 (95%CI: 15.82–87.61) at 3.2 °C. RH of 51.5% had the highest RR of Flu-A (9.98, 95%CI: 4.03–26.28) and Flu-B (4.63, 95%CI: 1.95–11.27). Wv of 3.5 m/s exerted the peaking RR of Flu-A (7.48, 95%CI: 2.73–30.04) and Flu-B (7.87, 95%CI: 5.53–11.91). DTR ≥ 12 °C and MeanT <22 °C were the key drivers for Flu-A and Flu-B, separately. The study found complex non-linear relationships between climate variability and different influenza types in Shanghai. We suggest the careful use of meteorological variables in influenza prediction in subtropical regions, considering such complex associations, which may facilitate government and health authorities to better minimize the impacts of seasonal influenza. [ABSTRACT FROM AUTHOR]

Background: A variety of viruses can cause acute respiratory infections (ARIs), resulting in a high disease burden worldwide. To explore the dominant viruses and their prevalence characteristics in children with ARIs, comprehensive surveillance was carried out in the Pudong New Area of Shanghai. Methods: Between January 2013 and December 2022, the basic and clinical information, and respiratory tract specimens of 0–14 years old children with ARIs were collected in five sentinel hospitals in Shanghai Pudong. Each specimen was tested for eight respiratory viruses, and the positive rates of different age groups, case types (inpatient or outpatient) were analyzed. Results: In our study, 30.67% (1294/4219) children with ARIs were positive for at least one virus. Influenza virus (IFV) was the most commonly detected respiratory virus (349/4219, 8.27%), followed by respiratory syncytial virus (RSV) (217/4219, 5.14%), para‐influenza virus (PIV) (215/4219, 5.10%), and human coronavirus (HCoV, including 229E, OC43, NL63, and HKU1) (184/4219, 4.36%). IFV was the leading respiratory virus in outpatients aged 5–14 years (201/1673, 12.01%); RSV was the most prevalent respiratory virus in both inpatients (61/238, 25.63%) and outpatients (4/50, 8.00%) for ARI patients aged <6 months old. For PIV, HMPV, HCoV, and HRV, the risk of infection usually was higher among young children. Co‐infection with more than two viruses was seen in 3.25% (137/4219). Conclusions: IFV and RSV played important roles in ARIs among children, but the risk populations were different. There are needs for targeted diagnosis and treatment and necessary immunization and non‐pharmaceutical interventions. [ABSTRACT FROM AUTHOR]

Previous studies have provided evidence of seasonal influenza transmission linked to various meteorological and environmental factors. However, the joint effect from both air pollutant exposure and meteorological factors that modify the seasonal influenza incidence is not well discussed. Data on weekly laboratory-confirmed influenza positive case numbers were obtained from Pudong New Area, Shanghai, China between January 1, 2011 and December 31, 2019. Weekly average weather data (absolute humidity (AH), minimum temperature (Min Temp) and particulate matter <2.5 μm (PM 2.5) concentration levels) at the same period were collected from Copernicus Atmosphere Monitoring Services (CAMS). A General additive model (GAM) and distributed lag nonlinear model (DLNM) with Quasi-Poisson likelihood were used to evaluate the independent and interaction effect of weather factors and PM 2.5 on seasonal influenza transmission along with lag effects. Our research showed that both AH and Min Temp had U-shape interactive relationships with PM 2.5 at high PM 2.5 concentration level. Interaction between PM 2.5 and AH had positive relative risk (RR) effect at lag of 5 weeks when AH = 5 g/m3and 15 g/m3, as well as the same lag period when Min Temp = 5 °C and 20 °C. Our study found that an interactive effect between air pollutant and weather factors exists and significantly affects influenza transmission. For future studies, lag interactive effects among air pollutant and temperature or humidity should be considered in the evaluation of the environment-influenza association, as such interactions might change the disease response to short-term effects. [Display omitted] • Dry, cold weather and high PM 2.5 level increase the seasonal influenza transmission. • Interactive effects among PM 2.5 and weather factors affect influenza at over lag 4 weeks. • PM 2.5 interaction with humidity had a non-linear relationship with influenza. • The interaction of PM 2.5 with temperature had a U-shape effect on influenza. [ABSTRACT FROM AUTHOR]

International travel may facilitate the spread of the novel coronavirus disease (COVID‐19). The study describes clusters of COVID‐19 cases within Chinese tour groups travelling in Europe January 16–28. We compared characteristics of cases and non‐cases to determine transmission dynamics. The index case travelled from Wuhan, China, to Europe on 16 January 2020, and to Shanghai, China, on 27 January 2020, within a tour group (group A). Tour groups with the same outbound flight (group B) or the same tourism venue (group D) and all Chinese passengers on the inbound flight (group C) were investigated. The outbreak involved 11 confirmed cases, 10 suspected cases and six tourists who remained healthy. Group A, involving seven confirmed cases and six suspected cases, consisted of familial transmission followed by propagative transmission. There was less pathogenicity with propagative transmission than with familial transmission. Disease was transmitted in shared outbound flights, shopping venues within Europe and inbound flight back to China. The novel coronavirus caused clustered cases of COVID‐19 in tour groups. When tourism and travel opens up, governments will need to improve screening at airports and consider increased surveillance of tour groups—particularly those with older tour members. [ABSTRACT FROM AUTHOR]

We conducted sentinel-based surveillance for norovirus in the Pudong area of Shanghai, China, during 2012-2013, by analyzing 5,324 community surveys, 408,024 medical records, and 771 laboratory-confirmed norovirus infections among 3,877 diarrhea cases. Our analysis indicated an outpatient incidence of 1.5/100 person-years and a community incidence of 8.9/100 person-years for norovirus-associated diarrhea. [ABSTRACT FROM AUTHOR]

Introduction: Clinical and etiological characteristics of influenza-like illness (ILI) in outpatients is poorly understood in the southern temperate region of China. We conducted laboratory-based surveillance of viral etiology for ILI outpatients in Shanghai from January 2011 to December 2013. Materials and Methods: Clinical and epidemiological data from ILI outpatients, both children and adults, were collected. A total of 1970 nasopharyngeal swabs were collected and tested for 12 respiratory viruses using multiplex RT-PCR, and the data were analyzed anonymously. Results: All 12 respiratory viruses were detected in the specimens. At least one virus was detected in 32.4% of 1970 specimens analyzed, with 1.1% showing co-infections. The most frequently detected agents were influenza A (11.7%), influenza B (9.6%), and rhinoviruses (3.1%).Other viruses were present at a frequency less than 3.0%. We observed a winter peak in the detection rate in ILI patients during 3 years of surveillance and a summer peak in 2012. HCoV, HADV, and HMPV were detected more frequently in children than in adults. Patients infected with influenza virus experienced higher temperatures, more coughs, running noses, headaches and fatigue than patients infected with other viruses and virus-free patients (p<0.001). Conclusions: The spectrum, seasonality, age distribution and clinical associations of respiratory virus infections in children and adults with influenza-like illness were analyzed in this study for the first time. To a certain extent, the findings can provide baseline data for evaluating the burden of respiratory virus infection in children and adults in Shanghai. It will also provide clinicians with helpful information about the etiological patterns of outpatients presenting with complaints of acute respiratory syndrome, but further studies should be conducted, and longer-term laboratory-based surveillance would give a better picture of the etiology of ILI. [ABSTRACT FROM AUTHOR]