Seasonal characteristics and virus strain variation of influenza epidemics in Guangzhou city, 2015 – 2022: seasonal-trend decomposition-based analysis

Abstract

Objective To study prevalence characteristics and change pattern of dominant virus strain of influenza epidemics in Guangzhou city and to provide evidence for formulating region-specific prevention and control measures. Methods Weekly influenza surveillance data of Guangzhou city, Guangdong province from 2015 to 2022 were collected from China Influenza Surveillance Information System. The positive rate series of influenza virus and its pathogen subtype were decomposed into trend/season/remainder component by using the seasonal-trend decomposition procedure based on locally weighted regression. By calculating covariance, the contribution rate of the obtained components to the fluctuation of positive rate was analyzed. Results Of 39 198 surveillance specimens sampled in the city during the 8-year period, 3 632 (9.27%) were positive for influenza virus nucleic acid. Trend series analysis showed that the positive rate fluctuated from 4.57% to 16.07%, with an increasing trend, during 2015 – 2019 and varied with a U-shape trajectory during 2020 – 2022. Winter-spring and spring-summer peaks of the positive rate were observed in season series analysis and the remainder component analysis revealed the highest fluctuation range of 48.96% for the positive rate in 2022. The positive rate of influenza A (H3N2) presented a similar season series to that of influenza B (Victoria), with winter and summer peaks, but the summer peaks of influenza A (H3N2) was later than that of influenza B (Victoria); the peak shape and prevalence duration (single peaks mainly in winter-spring season) of influenza A (H1N1) pdm09 positivity were similar to those of influenza B (Yamagata). In general, the remainder component was the main contributor to the fluctuation of the total positive rate, accounting for 59.16% of overall fluctuation (covariance of remainder component versus that of original series: 80.81/136.60), followed by season and trend component, accounting for 25.19% (34.41/136.60) and 15.68% (21.38/136.60) of overall fluctuation, respectively. Conclusion There were virus subtype-specific differences in seasonal peak and prevalence duration of influenza infection and random fluctuation exerted a greater effect than long-term trend and seasonal variation on influenza epidemic pattern in Guangzhou city.

Keywords

• influenza
• subtype
• seasonal-trend decomposition
• time series