Incidence, circulation, and spatiotemporal analysis of seasonal influenza in Shandong, China, 2008-2019: A retrospective study

Analysis of seasonal H3N2 influenza virus epidemic characteristics and whole genome features in Jining City from 2018 to 2023

Seasonal H3N2 influenza virus, known for its rapid evolution, poses a serious threat to human health. This study focuses on analyzing the influenza virus trends in Jining City (2018-2023) and understanding the evolving nature of H3N2 strains. Data on influenza-like cases were gathered from Jining City's sentinel hospitals: Jining First People's Hospital and Rencheng Maternal and Child Health Hospital, using the Chinese Influenza Surveillance Information System. Over the period from 2018 to 2023, 7844 throat swab specimens were assessed using real-time fluorescence quantitative PCR for influenza virus nucleic acid detection. For cases positive for seasonal H3N2 influenza virus, virus isolation was followed by whole genome sequencing. Evolutionary trees were built for the eight gene segments, and protein variation analysis was performed. From 2018 to 2023, influenza-like cases in Jining City represented 6.99% (237 299/3 397 247) of outpatient visits, peaking in December and January. Influenza virus was detected in 15.67% (1229/7844) of cases, primarily from December to February. Notably, no cases were found in the 2020-2021 season. Full genome sequencing was conducted on 70 seasonal H3N2 strains, revealing distinct evolutionary branches across seasons. Significant antigenic site variations in the HA protein were noted. No resistance mutations to inhibitors were found, but some strains exhibited mutations in PA, NS1, PA-X, and PB1-F2. Influenza trends in Jining City saw significant shifts in the 2020-2021 and 2022-2023 seasons. Seasonal H3N2 exhibited rapid evolution. Sustained vigilance is imperative for vaccine updates and antiviral selection.

Heterogeneity of influenza infection at precise scale in Yinchuan, Northwest China, 2012-2022: evidence from Joinpoint regression and spatiotemporal analysis

Identifying high-risk regions and turning points of influenza with a precise spatiotemporal scale may provide effective prevention strategies. In this study, epidemiological characteristics and spatiotemporal clustering analysis at the township level were performed. A descriptive study and a Joinpoint regression analysis were used to explore the epidemiological characteristics and the time trend of influenza. Spatiotemporal autocorrelation and clustering analyses were carried out to explore the spatiotemporal distribution characteristics and aggregation. Furthermore, the hotspot regions were analyzed by spatiotemporal scan analysis. A total of 4025 influenza cases were reported in Yinchuan showing an overall increasing trend. The tendency of influenza in Yinchuan consisted of three stages: increased from 2012 to the first peak in 2019 (32.62/100,000) with a slight decrease in 2016; during 2019 and 2020, the trend was downwards; then it increased sharply again and reached another peak in 2022. The Joinpoint regression analysis found that there were three turning points from January 2012 to December 2022, namely January 2020, April 2020, and February 2022. The children under ten displayed an upward trend and were statistically significant. The trend surface analysis indicated that there was a shifting trend from northern to central and southern. A significant positive spatial auto-correlation was observed at the township level and four high-incidence clusters of influenza were detected. These results suggested that children under 10 years old deserve more attention and the spatiotemporal distribution of high-risk regions of influenza in Yinchuan varies every year at the township level. Thus, more monitoring and resource allocation should be prone to the four high-incidence clusters, which may benefit the public health authorities to carry out the vaccination and health promotion timely.

Genetic characterization and whole-genome sequencing-based genetic analysis of influenza virus in Jining City during 2021-2022

Background

The influenza virus poses a significant threat to global public health due to its high mutation rate. Continuous surveillance, development of new vaccines, and public health measures are crucial in managing and mitigating the impact of influenza outbreaks.

Methods

Nasal swabs were collected from individuals with influenza-like symptoms in Jining City during 2021-2022. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to detect influenza A viruses, followed by isolation using MDCK cells. Additionally, nucleic acid detection was performed to identify influenza A H1N1, seasonal H3N2, B/Victoria, and B/Yamagata strains. Whole-genome sequencing was conducted on 24 influenza virus strains, and subsequent analyses included characterization, phylogenetic construction, mutation analysis, and assessment of nucleotide diversity.

Results

A total of 1,543 throat swab samples were collected. The study revealed the dominance of the B/Victoria influenza virus in Jining during 2021-2022. Whole-genome sequencing showed co-prevalence of B/Victoria influenza viruses in the branches of Victoria clade 1A.3a.1 and Victoria clade 1A.3a.2, with a higher incidence observed in winter and spring. Comparative analysis demonstrated lower similarity in the HA, MP, and PB2 gene segments of the 24 sequenced influenza virus strains compared to the Northern Hemisphere vaccine strain B/Washington/02/2019. Mutations were identified in all antigenic epitopes of the HA protein at R133G, N150K, and N197D, and the 17-sequence antigenic epitopes exhibited more than 4 amino acid variation sites, resulting in antigenic drift. Moreover, one sequence had a D197N mutation in the NA protein, while seven sequences had a K338R mutation in the PA protein.

Conclusion

This study highlights the predominant presence of B/Victoria influenza strain in Jining from 2021 to 2022. The analysis also identified amino acid site variations in the antigenic epitopes, contributing to antigenic drift.

Dynamics of influenza-like illness under urbanization procedure and COVID-19 pandemic in the sub-center of Beijing during 2013-2021

Influenza‐like illness (ILI) varies in intensity year by year, generally keeping a stable pattern except for great changes of its epidemic pattern. Of the most impacting factors, urbanization has been suggested as shaping the intensity of influenza epidemics. Besides, growing evidence indicates the nonpharmaceutical interventions (NPIs) to severe acute respiratory syndrome coronavirus 2 offer great advantages in controlling infectious diseases. The present study aimed to evaluate the impact of urbanization and NPIs on the dynamic of ILI in Tongzhou, Beijing, during January 2013 to March 2021. ILI epidemiological surveillance data in Tongzhou district were obtained from Beijing Influenza Surveillance Network and separated into three periods of urbanization and four intervals of coronavirus disease 2019 pandemic. Standardized average incidence rates of ILI in each separate stages were calculated and compared by using Wilson method and time series model of seasonal ARIMA. Influenza seasonal outbreaks showed similar epidemic size and intensity before urbanization during 2013–2016. Increased ILI activity was found during the process of Tongzhou's urbanization during 2017–2019, with the rate difference of 2.48 (95% confidence interva [CI]: 2.44, 2.52) and the rate ratio of 1.75 (95% CI: 1.74, 1.76) of ILI incidence between preurbanization and urbanization periods. ILI activity abruptly decreased from the beginning of 2020 and kept at the bottom level almost in every epidemic interval. The top decrease in ILI activity by NPIs was shown in 5–14 years group in 2020–2021 influenza season, as 92.2% (95% CI: 78.3%, 95.2%). The results indicated that both urbanization and NPIs interrupted the epidemic pattern of ILI. We should pay more attention to public health when facing increasing population density, human contact, population mobility, and migration in the process of urbanization. NPIs and influenza vaccination should be implemented as necessary measures to protect people from common infectious diseases like ILI.