|
|
|
| Etiological surveillance for influenza-like illness cases in Jiangsu Province |
| SHI Chunlei1, DAI Qigang2, DONG Yanhui3, LIU Dongsheng1, ZHOU Shengnan1
|
1. Xuzhou Center for Disease Control and Prevention, Xuzhou, Jiangsu 221006, China;
2. Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu 210009, China;
3. Institute of Child and Adolescent Health, Peking University, Beijing 100191, China |
|
|
|
|
Abstract Objective To analyze the etiological surveillance results of influenza-like illness (ILI) cases in Jiangsu Province, and investigate the distribution characteristics of different influenza virus types, so as to provide the evidence for improving influenza prevention and control measures. Methods Influenza laboratory testing data for sentinel surveillance of ILI cases in Jiangsu Province from 2019 to 2024 were collected through the China Influenza Surveillance Information System. The positive detection rate of influenza virus was calculated, and descriptive analysis was performed to characterize the distribution of different influenza virus types. Using the farthest neighbor linkage method, influenza virus positive detection rates clustering was analyzed by year and week. Clusters were defined based on inter-cluster distance, and the intensity of the positive detection rate was visualized through color gradients in the clustering heatmap. Results From 2019 to 2024, a total of 183 878 ILI specimens were collected in Jiangsu Province. Among them, 20 059 specimens tested positive for influenza virus, corresponding to an overall positive detection rate of 10.91%, and an average annual positive detection rate of 10.89%. The primary circulating influenza virus types were influenza A H3N2 subtype, accounting for 40.92%, followed by influenza B Victoria linage at 34.00%, and influenza A H1N1 subtype at 24.80%. Influenza B Yamagata linage was not detected throughout the five-year period. Influenza A H3N2 subtype predominated during two distinct periods: from January to March 2019, and from June 2022 to December 2023. Influenz B Victoria linage was the dominant type from April 2019 to May 2022 and again from January to April 2024. Influenza A H1N1 subtype emerged as the primary type from May to December 2024. Year-based clustering analysis grouped the annual positive detection rates from 2019 to 2024 into three clusters. The closest cluster distance was observed between 2019 and 2024. The highest annual positive detection rate occurred in 2023. Both influenza A H3N2 and H1N1 subtype each formed a single cluster, with their peak positive detection rates also recorded in 2023. Influenza B Victoria lineage was separated into two clusters, with its highest positive detection rate occurring in 2020. Week-based clustering analysis revealed that influenza virus detection was concentrated in weeks 47 to 52 and weeks 1 to 15. More specifically, the positive detection rates for influenza A H3N2 subtype peaked during weeks 30 to 34 and weeks 42 to 52; for influenza A H1N1 subtype, during weeks 9 to 15 and weeks 51 to 52; and for influenza B Victoria lineage, during weeks 1 to 11 and weeks 50 to 52. Conclusions From 2019 to 2024, the average annual positive detection rate of influenza virus in Jiangsu Province remained relatively low. Influenza activity characterized by the alternating circulation of influenza A H1N1 subtype, influenza A H3N2 subtype, and influenza B Victoria linage. It is necessary to maintain the surveillance sensitivity for the influenza B Yamagata lineage.
|
|
Received: 02 December 2025
Revised: 01 February 2026
Published: 11 February 2026
|
|
|
|
|
|
[1] 王若琳,张奕,黎晓蕾,等.家长对学生流感疫苗接种的知信行特征及决定因素分析:一项基于多城市的调查[J].中国校医,2025,39(4):259-264,274.
[2] PENG J L,XU K,TONG Y,et al.Epidemiological characteristics of influenza outbreaks in schools in Jiangsu Province,China,2020-2023 post-COVID-19 pandemic[J/OL].BMC Infect Dis,2024,24(1)[2026-02-01].https://doi.org/10.1186/s12879-024-10079-8.
[3] 马春娜,吴双胜,张莉,等.北京市2015—2020年流感流行季流感样病例和流感病原学分析[J].中华实验和临床病毒学杂志,2021,35(1):44-48.
[4] 国家免疫规划技术工作组流感疫苗工作组.中国流感疫苗预防接种技术指南(2023—2024)[J].中华流行病学杂志,2023,44(10):1507-1530.
[5] 王铭韩,胡泽鑫,冯录召,等.新型冠状病毒感染疫情后我国季节性流感的流行趋势与防控建议[J].中华医学杂志,2024,104(8):559-565.
[6] DHANASEKARAN V,SULLIVAN S,EDWARDS K M,et al.Human seasonal influenza under COVID-19 and the potential consequences of influenza lineage elimination[J/OL].Nat Commun,2022,13(1)[2026-02-01].https://doi.org/10.1038/s41467-022-29402-5.
[7] OLSEN S J,AZZIZ-BAUMGARTNER E,BUDD A P,et al.Decreased influenza activity during the COVID-19 pandemic-United States,Australia,Chile,and South Africa,2020[J].MMWR Morb Mortal Wkly Rep,2020,69(37):1305-1309.
[8] 中华人民共和国国家卫生计划生育委员会办公厅.国家卫生计生委办公厅关于印发全国流感监测方案(2017年版)的通知[EB/OL].[2026-02-01].https://ivdc.chinacdc.cn/cnic/fascc/201802/P020180202290930853917.pdf.
[9] 石鑫,许军,舒畅,等.黑龙江省老年人群流行性感冒流行特征[J].预防医学,2023,35(3):250-252,261.
[10] 魏宇翔. 组学大数据的热图可视化[D].武汉:华中科技大学,2024.
[11] HUANG W J,CHENG Y H,TAN M J,et al.Epidemiological and virological surveillance of influenza viruses in China during2020-2021[J/OL].Infect Dis Poverty,2022,11(1)[2026-02-01].https://doi.org/10.1186/s40249-022-01002-x.
[12] CHEN Z Y,TSUI J L,GUTIERREZ B,et al.COVID-19 pandemic interventions reshaped the global dispersal of seasonal influenza viruses[J/OL].Science,2024,386(6722)[2026-02-01].https://doii.org/10.1126/science.adq3003.
[13] ACHANGWA C,PARK H,RYU S,et al.Collateral impact of public health and social measures on respiratory virus activity during the COVID-19 pandemic2020-2021[J/OL].Viruses,2022,14(5)[2026-02-01].https://doi.org/10.3390/v14051071.
[14] ADLHOCH C,SNEIDERMAN M,MARTINUKA O,et al.Spotlight influenza:the2019/20 influenza season and the impact of COVID-19 on influenza surveillance in the WHO European Region[J/OL].Euro Surveill,2021,26(40)[2026-02-01].https://doi.org/10.2807/1560-7917.ES.2021.26.40.2100077.
[15] 余宏杰,舒跃龙.流感大流行的威胁及中国的应对[J].疾病监测,2005,20(10):505-507.
[16] FU X Q,LONG J,XIONG Y,et al.Epidemic patterns of the different influenza virus types and subtypes/lineages for 10 years in Chongqing,China,2010-2019[J/OL].Hum Vaccin Immunother,2024,20(1)[2026-02-01].https://doi.org/10.1080/21645515.2024.2363076.
[17] SOMININA A,DANILENKO D,KOMISSAROV A B,et al.Assessing the intense influenza a(H1N1)pdm09 epidemic and vaccine effectiveness in the post-COVID season in the Russian federation[J/OL].Viruses,2023,15(8)[2026-02-01].https://doi.org/10.3390/v15081780.
[18] DESHEVA Y,KUDAR P,SERGEEVA M,et al.The persistence of cross-reactive immunity to influenza B/Yamagata neuraminidase despite the disappearance of the lineage:structural and serological evidence[J/OL].Int J Mol Sci,2025,26(15)[2026-02-01].https://doi.org/10.3390/ijms26157476.
[19] 辛丽,王大燕.乙型流感病毒Yamagata系毒株的消失及其疫苗株更换的思考及讨论[J].中国生物制品学杂志,2024,37(8):1014-1019.
[20] 傅俊杰,戴启刚,霍翔.2011—2019年江苏省不同型别流感病毒流行特征差异分析[J].疾病监测,2020,35(11):992-997.
[21] CHEN L,GUO Y C,LÓPEZ-GÜELL K,et al.Immunity debt for seasonal influenza after the COVID-19 pandemic and as a result of nonpharmaceutical interventions:an ecological analysis and cohort study[J/OL].Adv Sci,2025,12(20)[2026-02-01].https://doi.org/10.1002/advs.202410513.
[22] DAVE K,LEE P C.Global geographical and temporal patterns of seasonal influenza and associated climatic factors[J].Epidemiol Rev,2019,41(1):51-68.
[23] YU H J,ALONSO W J,FENG L Z,et al.Characterization of regional influenza seasonality patterns in China and implications for vaccination strategies:spatio-temporal modeling of surveillance data[J/OL].PLoS Med,2013,10(11)[2026-02-01].https://doi.org/10.1371/journal.pmed.1001552. |
|
|
|
