ObjectiveTo understand the epidemic characteristics of influenza in Beijing from 2023 to 2024, and to provide a scientific basis for the prevention and control of influenza. MethodsData on influenza-like illness (ILI) from secondary level and above hospitals, etiology surveillance data, and influenza clusters outbreaks data from 2023‒2024 were used to analyze the epidemic trend and pathogenic characteristics of influenza. Furthermore, an influenza comprehensive index was used to categorize the epidemic intensity at the severity level. ResultsA total of 2 065 857 ILI cases were reported in 2023‒2024 epidemic season, and the percentage of ILI was 3.67%. The age group of 5‒14 years accounted for the highest proportion of ILI (30.48%). A total of 41 766 throat swabs from ILI were detected, with a positive rate of 17.28%.A (H3N2) (51.86%) and B Victoria (41.93%) were the most prevalent subtypes of influenza virus. Clustered influenza outbreaks occurred mainly in primary schools (57.78%) and middle schools (35.55%), mainly caused by the influenza A (H3N2) subtype (85.93%). According to the influenza comprehensive index (I), the period of influenza activity and above (I>0.5) lasted for a total of 37 weeks, accounting for 71.15% of the entire influenza season. ConclusionCompared with previous years, the epidemic level of influenza in Beijing was increased in 2023‒2024, and the peak time became earlier. The comprehensive index method can objectively evaluate the level of influenza epidemic and provide suggestions for the future prevention and control of influenza in Beijing.

ObjectiveTo establish an adjusted Serfling regression model to estimate the excess cases and the excess epidemic period of hand-foot-mouth disease (HFMD) in Beijing from 2011 to 2019, so as to provide data support and decision-making basis for HFMD prevention and control. MethodsThe weekly number of HFMD cases in Beijing from 2011 to 2019 was utilized for adjusted the Serfling regression model. Then the adjusted model was used to fit the baseline and epidemic threshold of HFMD in Beijing from 2011 to 2019, calculating the excess cases and determining the excess epidemic period. ResultsA total of 279 306 cases of HFMD were reported in Beijing from 2011 to 2019, with the climax of the disease occurring in summer and autumn. After adjusting the fitting R² of the Serfling regression model to 0.773, a total of 10 excess epidemic periods totaling 92 weeks were estimated, mainly occurring in summer. The highest number of excess cases during an excess epidemic period was found in 2014 (1 272 cases, 95%CI: 990‒1 554), accounting for 65.04% of the actual cases (95%CI: 50.62%‒79.46%). ConclusionThe adjusted Serfling regression model fits well and can be utilized for early warning of HFMD and estimating the disease burden caused by HFMD.

Objective:To analyze the changes in the phylogenetic and antigenic characteristics of the hemagglutinin (HA) gene of influenza virus A(H3N2) [A(H3N2)] during the 2022-2024 influenza seasons in Beijing.Methods:The data of influenza-like cases and A(H3N2) strains from 17 network laboratories and their corresponding sentinel hospitals were collected during the 2022-2024 influenza seasons. The HA genes were amplified and sequenced after extracting nucleic acids of the chosen virus strains. BioEdit, the nucleotide and amino acid sequence identity were conducted, and the maximum likelihood method in MEGA 5.0 software was used to construct the phylogenetic tree of HA genes. Web Logo displayed the amino acid mutation, and the N-glycosylation sites of HA online were analyzed using the NetNGlyc1.0 Server online. The Datamonkey platform was utilized to analyze the positive selection pressure sites of the HA protein.Results:The 2022-2024 influenza season includes 2022-2023 and 2023-2024. During the influenza seasons of 2022-2024, the positive rates of A(H3N2) nucleic acid were 10.35% (2 127/20 543) and 10.47% (4 386/41 876), respectively. In the 2022-2023 influenza season, there were two peaks in the A(H3N2). The comparison of HA genes between all A(H3N2) strains studied with the 2022-2024 vaccine strain (A/Darwin/9/2021) revealed that all of the strains studied have the two amino acid mutations involving 186 and 225 receptor binding sites. There were 31 amino acid substitutions in the 2022-2023 influenza season, of which 18 variant sites involved antigenic determinants. There were 35 amino acid mutations during the 2023-2024 influenza season, of which 14 were related to antigenic determinants. There were changes in the genetic evolutionary subclades of A(H3N2) strains in two influenza seasons: from 2022 to 2023, three evolutionary subclades were co-prevalent together, with the 3C.2a1b.2a.2a.3a.1 accounting for 76.67% (23/30), the 3C.2a1b.2a.1a accounting for 20.00% (6/30), the 3C.2a1b.2a.2a.1 accounting for 3.33% (1/30); from 2023 to 2024, two subclades were prevalent, with 3C.2a1b.2a.2a.3a.1 accounting for 95.12% (39/41) and 3C.2a1b.2a.2a.1 accounting for 4.88% (2/41). The glycosylation site changes of the HA protein of A(H3N2) have been enhanced from 2023 to 2024. The 145 amino acid position of the HA protein of the A(H3N2) was the positive selection site for stress selection site analysis.Conclusions:The evolutionary subclades of the HA gene of A(H3N2) in Beijing showed changes from 2022 to 2024, and the glycosylation site polymorphism of the HA protein of A(H3N2) significantly increased from 2023 to 2024. Continuous monitoring of HA mutations in the A(H3N2) is crucial, providing a basis for developing influenza prevention and control strategies, as well as new strategic support for screening influenza vaccine components, vaccine design, and discovery of drug targets.

Objective:To analyze the effect of influenza vaccination on influenza cluster epidemic in primary and secondary schools in Beijing during the 2023-2024 surveillance season and provide evidence for the improvement of influenza vaccination strategies.Methods:The incidence data of influenza cluster epidemic and influenza vaccination coverage in the schools in Beijing during 2023-2024 were collected. Descriptive epidemiological methods were used to analyze cluster epidemic characteristics, and χ2 test was used to compare incidence differences between groups, and OR value and vaccine effectiveness [VE=(1- OR)×100%] were calculated. A negative binomial regression model was used to evaluate the association between school vaccination rates and cluster epidemic risk. Joinpoint regression was used to analyze trends in relative risk ( RR) with increasing vaccination coverage and to determine the optimal vaccination threshold. Results:A total of 126 influenza cluster epidemic were reported in 115 primary and secondary schools in Beijing during 2023-2024 with the median size of 15 case, the average attack rate was 36.26% (2 033/5 607). The epidemics mainly occurred in urban area (70, 55.56%). Primary schools were the main setting (78, 61.90%), and influenza A(H3N2) was the predominant subtype (108, 85.71%). The overall influenza vaccination coverage in the primary and secondary students was 54.26%, while the average vaccination in classes affected by the epidemics was 58.57%. The overall protection rate was 47.62%, the protection rate was higher in primary schools (49.65%) than in secondary schools (46.60%). The protection rates against influenza A(H1N1)pdm09 (80.93%) and influenza B (Victoria lineage) (81.65%) were significantly higher than that against influenza A(H3N2) (44.19%). When school vaccination coverage reached ≥76.00%, the epidemic risk decreased by 52.82%.Conclusions:Even the match between influenza vaccine strains and circulating strains is suboptimal, increasing influenza vaccination coverage in schools can effectively reduce the risk for influenza cluster epidemic. In the future, measures such as policy guidance and public health education should be taken to further improve vaccination coverage, thereby establishing herd immunity and reducing the transmission risk of influenza in schools.

Objective:To compare the enrichment effects of ultrafiltration, polyethylene glycol (PEG) precipitation, aluminum salt precipitation, and anionic membrane adsorption-elution on viruses in drinking water.Methods:Using phage MS2 as the target virus, three different concentrations of drinking water samples were prepared, and the samples were enriched by ultrafiltration 1, ultrafiltration 2, PEG precipitation, aluminum salt precipitation, and anionic membrane adsorption-elution method, respectively. Real-time fluorescence quantitative reverse transcription-polymerase chain reaction (RT-qPCR) was used to quantify MS2 nucleic acid in pre and post concentrated samples and the recovery rates of MS2 in samples with high, medium and low concentrations were compared among the five methods.Results:Comparing the MS2 enrichment recovery rates of individual enrichment method in water samples of different concentrations, ultrafiltration method 1, PEG precipitation method, aluminum salt precipitation method, and membrane adsorption-elution method were not affected by the sample concentration, and the differences of the recovery rates for the three concentration water samples among the four methods were not statistically significant ( P>0.05). The MS2 enrichment recovery rates of the five enrichment methods were significantly different in all concentration samples ( P<0.05). The recovery rates of ultrafiltration method 1 were higher in all three concentration samples, followed by aluminum salt precipitation and anionic membrane adsorption-elution, PEG precipitation were higher in high concentration samples, but lower in low and medium concentration samples, and the recovery rates of ultrafiltration method 2 were the lowest in all three concentration samples. Comparing the Ct values of MS2 in the enriched samples by five methods, the Ct values of ultrafiltration method 1 were the smallest in the three concentration water samples. There was no statistically significant difference in MS2 Ct values among the five enrichment methods in the medium and high concentration water samples ( P>0.05). In low concentration simulated water samples, only the difference of MS2 Ct value between ultrafiltration method 1 and ultrafiltration method 2 was statistically significant ( Z=16.000, P=0.016). Conclusions:Considering the operation simplicity, operation time and virus recovery rate after enrichment, ultrafiltration was the most effective method for virus enrichment in drinking water.

Objective:To evaluate the preservation efficacy of 7 non-inactivating virus preservation solutions.Methods:Equal amounts of H1N1 virus were added to 7 commercially available non-inactivating virus preservation solutions, and the samples were stored at -20 ℃, 4 ℃, 25 ℃ and 37 ℃ for 1 hour, 6 hours, 1 day, 3 days, and 5 days. The viral nucleic acid in each simulated sample under different storage conditions was measured using real-time quantitative PCR. The hemagglutination (HA) titer was determined through viral isolation culture and hemagglutination assay, comparing the differences in viral growth activity across different storage solutions and conditions.Results:Except for solution E, the other solutions effectively protected viral nucleic acid at the 4 storage temperatures. In terms of viral activity, solutions A, B, C, and D effectively maintained viral viability. A and B showing the best performance, E and F showed poorer performance, and G performed the worst.Conclusions:Most non-inactivating virus preservation solutions effectively protect viral nucleic acid, but there are significant differences in their ability to maintain viral viability. To ensure optimal virus preservation, it is recommended that medical institutions evaluate the effectiveness of preservation solutions before use.

Objective:To analyze the epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in Beijing in 2024, to investigate the infection status of reservoir hosts, vector organisms, and baseline human populations, and provide a scientific basis for formulating prevention and control strategies.Methods:Epidemiological surveys were conducted on all confirmed cases. Serum samples from healthy populations and reservoir hosts were collected for SFTSV antibody detection. Questing ticks were monitored using the flagging method. Real-time fluorescent quantitative PCR was employed to detect SFTSV in cases, reservoir hosts, and ticks. Positive samples underwent whole-genome sequencing and genetic evolution analysis.Results:In 2024, Beijing reported 15 locally infected cases with 4 deaths. The age of onset ranged from 50 to 80 years (median: 66 years). Cases showed a certain degree of geographical clustering, with June being the peak month of onset. The affected population was predominantly farmers, with a male-to-female ratio of 3∶2. Animal contact history emerged as a significant risk factor alongside tick bites. Parthenogenetic tick populations were identified in Pinggu district, while SFTSV-carrying ticks were detected in endemic areas (Mentougou, Shijingshan, and Fengtai Districts). Viral presence was also confirmed in ticks or dogs from non-endemic areas. Sequencing and phylogenetic analysis revealed stable clustering of strains into two distinct genotypes (A and B). Antibody-positive individuals were identified in healthy populations from non-endemic areas.Conclusions:The incidence of SFTS in Beijing is increasing, with natural viral circulation already established in non-endemic regions. Enhanced surveillance and adjusted prevention strategies are urgently needed.

A total of 1 557 cases were included in the Febrile Respiratory Syndrome (FRS) surveillance conducted in Daxing District between 2018 and 2023. Twelve respiratory pathogens were investigated: human influenza virus (HIFV), human respiratory syncytial virus (HRSV), human parainfluenza virus (HPIV), human rhinovirus (HRV), human enterovirus (HEV), human adenovirus (HadV), human metapneumovirus (HMPV), human bocavirus (HBoV), Mycoplasma pneumoniae (MP), Chlamydia pneumoniae (CP), human coronavirus (HCoV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Results demonstrated an overall pathogen detection rate of 25.31% (394/1 557), with descending prevalence as follows: HIFV, SARS-CoV-2, HRV, HPIV, MP, HCoV, HRSV, HEV, HMPV, HadV, HBoV, and CP. Temporal analysis revealed detection rates of 26.98% (150/556) for 2018-2019, 15.81% (95/601) for 2020-2022, and 37.25% (149/400) for 2023, showing statistically significant interannual variation (χ2=59.703, P<0.001). Compared with 2018-2019, 2023 exhibited significantly elevated detection rates for HIFV and HMPV ( P<0.05), while HRV, MP, HEV, and HBoV demonstrated significantly reduced rates ( P<0.05). Age-stratified analysis identified HIFV, HRSV, and HadV as the predominant pathogens in individuals aged <15 years, whereas SARS-CoV-2, HIFV, and HRV predominated in those aged ≥60 years.

Objective:To analyze the changes in the phylogenetic and antigenic characteristics of the hemagglutinin (HA) gene of influenza virus A(H3N2) [A(H3N2)] during the 2022-2024 influenza seasons in Beijing.Methods:The data of influenza-like cases and A(H3N2) strains from 17 network laboratories and their corresponding sentinel hospitals were collected during the 2022-2024 influenza seasons. The HA genes were amplified and sequenced after extracting nucleic acids of the chosen virus strains. BioEdit, the nucleotide and amino acid sequence identity were conducted, and the maximum likelihood method in MEGA 5.0 software was used to construct the phylogenetic tree of HA genes. Web Logo displayed the amino acid mutation, and the N-glycosylation sites of HA online were analyzed using the NetNGlyc1.0 Server online. The Datamonkey platform was utilized to analyze the positive selection pressure sites of the HA protein.Results:The 2022-2024 influenza season includes 2022-2023 and 2023-2024. During the influenza seasons of 2022-2024, the positive rates of A(H3N2) nucleic acid were 10.35% (2 127/20 543) and 10.47% (4 386/41 876), respectively. In the 2022-2023 influenza season, there were two peaks in the A(H3N2). The comparison of HA genes between all A(H3N2) strains studied with the 2022-2024 vaccine strain (A/Darwin/9/2021) revealed that all of the strains studied have the two amino acid mutations involving 186 and 225 receptor binding sites. There were 31 amino acid substitutions in the 2022-2023 influenza season, of which 18 variant sites involved antigenic determinants. There were 35 amino acid mutations during the 2023-2024 influenza season, of which 14 were related to antigenic determinants. There were changes in the genetic evolutionary subclades of A(H3N2) strains in two influenza seasons: from 2022 to 2023, three evolutionary subclades were co-prevalent together, with the 3C.2a1b.2a.2a.3a.1 accounting for 76.67% (23/30), the 3C.2a1b.2a.1a accounting for 20.00% (6/30), the 3C.2a1b.2a.2a.1 accounting for 3.33% (1/30); from 2023 to 2024, two subclades were prevalent, with 3C.2a1b.2a.2a.3a.1 accounting for 95.12% (39/41) and 3C.2a1b.2a.2a.1 accounting for 4.88% (2/41). The glycosylation site changes of the HA protein of A(H3N2) have been enhanced from 2023 to 2024. The 145 amino acid position of the HA protein of the A(H3N2) was the positive selection site for stress selection site analysis.Conclusions:The evolutionary subclades of the HA gene of A(H3N2) in Beijing showed changes from 2022 to 2024, and the glycosylation site polymorphism of the HA protein of A(H3N2) significantly increased from 2023 to 2024. Continuous monitoring of HA mutations in the A(H3N2) is crucial, providing a basis for developing influenza prevention and control strategies, as well as new strategic support for screening influenza vaccine components, vaccine design, and discovery of drug targets.

Objective:To analyze the effect of influenza vaccination on influenza cluster epidemic in primary and secondary schools in Beijing during the 2023-2024 surveillance season and provide evidence for the improvement of influenza vaccination strategies.Methods:The incidence data of influenza cluster epidemic and influenza vaccination coverage in the schools in Beijing during 2023-2024 were collected. Descriptive epidemiological methods were used to analyze cluster epidemic characteristics, and χ2 test was used to compare incidence differences between groups, and OR value and vaccine effectiveness [VE=(1- OR)×100%] were calculated. A negative binomial regression model was used to evaluate the association between school vaccination rates and cluster epidemic risk. Joinpoint regression was used to analyze trends in relative risk ( RR) with increasing vaccination coverage and to determine the optimal vaccination threshold. Results:A total of 126 influenza cluster epidemic were reported in 115 primary and secondary schools in Beijing during 2023-2024 with the median size of 15 case, the average attack rate was 36.26% (2 033/5 607). The epidemics mainly occurred in urban area (70, 55.56%). Primary schools were the main setting (78, 61.90%), and influenza A(H3N2) was the predominant subtype (108, 85.71%). The overall influenza vaccination coverage in the primary and secondary students was 54.26%, while the average vaccination in classes affected by the epidemics was 58.57%. The overall protection rate was 47.62%, the protection rate was higher in primary schools (49.65%) than in secondary schools (46.60%). The protection rates against influenza A(H1N1)pdm09 (80.93%) and influenza B (Victoria lineage) (81.65%) were significantly higher than that against influenza A(H3N2) (44.19%). When school vaccination coverage reached ≥76.00%, the epidemic risk decreased by 52.82%.Conclusions:Even the match between influenza vaccine strains and circulating strains is suboptimal, increasing influenza vaccination coverage in schools can effectively reduce the risk for influenza cluster epidemic. In the future, measures such as policy guidance and public health education should be taken to further improve vaccination coverage, thereby establishing herd immunity and reducing the transmission risk of influenza in schools.