Molecular epidemiological analysis of Influenza viruses in Influenza-like illness cases: a retrospective study in Chongqing Hi-Tech Zone, China (2021-2024)
Listed in
This article is not in any list yet, why not save it to one of your lists.Abstract
The seasonal epidemiology and high variability of influenza viruses result in yearly differentiation of main pandemic strains. Effective prevention and control of influenza epidemics require enhanced surveillance, timely updates of vaccine components.Therefore, it is crucial to establish a continuous surveillance system to track epidemiological trends and develop appropriate vaccination and preventive measures.A retrospective analysis was conducted on the molecular epidemiological characteristics of influenza viruses in influenza-like cases at a hospital in Chongqing Hi-Tech Zone from 2021 to 2024. Among 39,986 ILI specimens tested using the immunocolloid gold method, 6,616 influenza viruses were detected, with a detection rate of 16.54%. Infections included 4,464 influenza A viruses (67.50%), 2,033 influenza B viruses (30.73%), and 119 co-infections of influenza A and B viruses (1.77%). From November 2021 to September 2022, the peak detection of influenza A virus occurred in January 2022, and influenza B virus peaked in April 2022. From July 2022 to March 2023, the influenza A virus peaked in December 2022, while the influenza B virus peaked in January 2023. Influenza B virus detection lagged behind influenza A virus detection. In this region, H3N2 was the predominant subtype of influenza A, and Victoria was the main subtype of influenza B. The "H1" subtype of influenza A did not appear throughout 2023 but accounted for 82% in January 2024 and 16% in February 2024. The "Yamagata" subtype of influenza B did not appear from 2023 to 2024. Influenza epidemics in the winter and spring seasons in Chongqing Hi-Tech Zone were predominantly caused by influenza A, with influenza B also circulating. Influenza A strains were mainly H3N2, while influenza B strains were primarily Victoria. This study provides essential data and a scientific basis for developing and optimizing influenza prevention and control strategies.