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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]

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]