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Sun H, Wang Y, Wei Y, Hu W, Zhou J, Nama N, Ma Y, Liu G, Hao Y. Effect of Current-Season-Only Versus Continuous Two-Season Influenza Vaccination on Mortality in Older Adults: A Propensity-Score-Matched Retrospective Cohort Study. Vaccines (Basel) 2025; 13:164. [PMID: 40006711 PMCID: PMC11860298 DOI: 10.3390/vaccines13020164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2025] [Revised: 02/01/2025] [Accepted: 02/06/2025] [Indexed: 02/27/2025] Open
Abstract
BACKGROUND/OBJECTIVES This study evaluated the impact of influenza vaccination on mortality using real-world data and compared the effect of current-season-only vaccination versus continuous two-season vaccination. METHODS The 2017-2019 data from the Center for Disease Control and Prevention of Shenzhen, Guangdong, China, included 880,119 individuals aged ≥65 years. The participants were divided into vaccinated and unvaccinated groups and matched using propensity scores with a 1:4 nearest-neighbor approach. Vaccinated individuals were further divided into current-season-only and continuous two-season vaccination groups, matched 1:1. Cox's multivariable proportional hazards regression models were used to assess the effect of vaccination on all-cause mortality, with Firth's penalized likelihood method applied to correct for a few events. The Fine-Gray competing risk models were used to assess the effect of vaccination on cardio-cerebral vascular disease (CCVD) mortality. Sensitivity analyses, including caliper matching, a nested case-control design, and Poisson's regression, were performed to test the robustness of the results. RESULTS Influenza vaccination reduced all-cause mortality by 39% (HR = 0.61, 95% CI: 0.47-0.80) and 55% (HR = 0.45, 95% CI: 0.33-0.60) in 2017-2018 and 2018-2019, respectively. Current-season-only vaccination showed stronger protective effects than continuous two-season vaccination (HR = 0.56, 95% CI: 0.31-0.99). Influenza vaccination reduced CCVD mortality by 46% (HR = 0.54, 95% CI: 0.34-0.84) in 2018-2019. The results were consistent across the sensitivity analyses. CONCLUSIONS Influenza vaccination was associated with a reduced risk of all-cause and CCVD mortality in older adults, underscoring the importance of routine influenza vaccination in older populations. Stronger effects were observed for current-season-only vaccination, warranting further research to confirm the association and explore mechanisms.
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Affiliation(s)
- Huimin Sun
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.W.); (W.H.); (J.Z.); (N.N.); (Y.M.)
| | - Yijing Wang
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China;
| | - Yongyue Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.W.); (W.H.); (J.Z.); (N.N.); (Y.M.)
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
| | - Weihua Hu
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.W.); (W.H.); (J.Z.); (N.N.); (Y.M.)
| | - Junwen Zhou
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.W.); (W.H.); (J.Z.); (N.N.); (Y.M.)
| | - Nuosu Nama
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.W.); (W.H.); (J.Z.); (N.N.); (Y.M.)
| | - Yujie Ma
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.W.); (W.H.); (J.Z.); (N.N.); (Y.M.)
| | - Gang Liu
- Shenzhen Center for Disease Control and Prevention, Shenzhen 518055, China;
| | - Yuantao Hao
- Department of Epidemiology and Health Statistics, School of Public Health, Peking University, Beijing 100191, China; (H.S.); (Y.W.); (W.H.); (J.Z.); (N.N.); (Y.M.)
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing 100191, China
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Yang T, Tong F, Tang L, Li P, Li B, Ye L, Zhou J. Repeated vaccination does not appear to significantly weaken the protective effect of influenza vaccine in the elderly: A test-negative case-control study in China. Vaccine 2024; 42:125986. [PMID: 38762359 DOI: 10.1016/j.vaccine.2024.05.034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 05/02/2024] [Accepted: 05/15/2024] [Indexed: 05/20/2024]
Abstract
BACKGROUND The impact of repeated influenza vaccination on vaccine effectiveness has been a topic of debate. Conducting more multinational, multicenter studies in different influenza seasons is crucial for a better understanding of this issue. There is a lack of comprehensive related research reports in China. METHODS Using the Regional Health Information Platform, we conducted a test-negative case-control study to evaluate the impact of repeated vaccination on the prevention of laboratory-confirmed influenza in individuals aged 60 and above in Ningbo during four influenza seasons from 2018-19 to 2021-22. Influenza-positive cases and negative controls were matched in a 1:1 ratio based on the visiting hospital and the date of influenza testing. Propensity score adjustment and multivariable logistic regression were used to estimate risk and address confounding effects. RESULTS During the study period, a total of 30,630 elderly patients underwent influenza virus nucleic acid or antigen testing. After exclusions, we included 1976 cases of influenza-positive and 1976 cases of influenza-negative controls. Multivariable logistic regression analysis revealed that individuals receiving the vaccine in two consecutive seasons did not exhibit a significantly increased risk of influenza illness compared to those receiving the vaccine only in the current season (adjusted odds ratio: 1.22, 95% confidence interval: 0.94-1.58). However, the risk of influenza illness was found to be elevated in individuals who received the vaccine only in the previous season (adjusted odds ratio: 1.56, 95% confidence interval: 1.15-2.10) and even further elevated in those who had not received the vaccine in either of the consecutive two seasons (adjusted odds ratio: 3.39, 95% confidence interval: 2.80-4.09). CONCLUSIONS Regardless of the vaccination history in the previous season, receiving the current season influenza vaccine is the best choice for the elderly population. Our study supports the initiative to vaccinate elderly individuals against influenza annually.
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Affiliation(s)
- Tianchi Yang
- Institute of Immunization and Prevention, Ningbo Municipal Center for Disease Control and Prevention, Zhejiang, China
| | - Feng Tong
- Ningbo Municipal Center for Disease Control and Prevention, Zhejiang, China
| | - Ling Tang
- Ningbo Health Information Center, Zhejiang, China
| | - Pingping Li
- Jiangbei District Center for Disease Control and Prevention, Zhejiang, China
| | - Baojun Li
- Haishu District Center for Disease Control and Prevention, Zhejiang, China
| | - Lixia Ye
- Institute of Immunization and Prevention, Ningbo Municipal Center for Disease Control and Prevention, Zhejiang, China.
| | - Jifang Zhou
- School of International Pharmaceutical Business, China Pharmaceutical University, Jiangsu, China.
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Zhang T, Han Y, Huang W, Wei H, Zhao Y, Shu L, Guo Y, Ye B, Zhou J, Liu J. Neutralizing antibody responses against contemporary and future influenza A(H3N2) viruses in paradoxical clades elicited by repeated and single vaccinations. J Med Virol 2024; 96:e29743. [PMID: 38884419 DOI: 10.1002/jmv.29743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 05/16/2024] [Accepted: 06/05/2024] [Indexed: 06/18/2024]
Abstract
As one of the most effective measures to prevent seasonal influenza viruses, annual influenza vaccination is globally recommended. Nevertheless, evidence regarding the impact of repeated vaccination to contemporary and future influenza has been inconclusive. A total of 100 subjects singly or repeatedly immunized with influenza vaccines including 3C.2a1 or 3C.3a1 A(H3N2) during 2018-2019 and 2019-2020 influenza season were recruited. We investigated neutralization antibody by microneutralization assay using four antigenically distinct A(H3N2) viruses circulating from 2018 to 2023, and tracked the dynamics of B cell receptor (BCR) repertoire for consecutive vaccinations. We found that vaccination elicited cross-reactive antibody responses against future emerging strains. Broader neutralizing antibodies to A(H3N2) viruses and more diverse BCR repertoires were observed in the repeated vaccination. Meanwhile, a higher frequency of BCR sequences shared among the repeated-vaccinated individuals with consistently boosting antibody response was found than those with a reduced antibody response. Our findings suggest that repeated seasonal vaccination could broaden the breadth of antibody responses, which may improve vaccine protection against future emerging viruses.
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MESH Headings
- Humans
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza Vaccines/immunology
- Influenza Vaccines/administration & dosage
- Antibodies, Neutralizing/blood
- Antibodies, Neutralizing/immunology
- Antibodies, Viral/blood
- Antibodies, Viral/immunology
- Influenza, Human/prevention & control
- Influenza, Human/immunology
- Influenza, Human/virology
- Adult
- Cross Reactions/immunology
- Male
- Female
- Vaccination
- Middle Aged
- Young Adult
- Neutralization Tests
- Receptors, Antigen, B-Cell/immunology
- Receptors, Antigen, B-Cell/genetics
- Adolescent
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Affiliation(s)
- Ting Zhang
- Collaborative Innovation Centre of Regenerative Medicine and Medical Bioresource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Yang Han
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
- National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, China
- State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, China
| | - Weijuan Huang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Hejiang Wei
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yingze Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Liumei Shu
- Department of Health Care, Beijing Daxing District Hospital, Beijing, China
| | - Yaxin Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Beiwei Ye
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
| | - Jianfang Zhou
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jun Liu
- Collaborative Innovation Centre of Regenerative Medicine and Medical Bioresource Development and Application Co-constructed by the Province and Ministry, Guangxi Medical University, Nanning, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases (NITFID), National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- Research Unit of Adaptive Evolution and Control of Emerging Viruses (2018RU009), Chinese Academy of Medical Sciences, Beijing, China
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Mai G, Zhang C, Lan C, Zhang J, Wang Y, Tang K, Tang J, Zeng J, Chen Y, Cheng P, Liu S, Long H, Wen Q, Li A, Liu X, Zhang R, Xu S, Liu L, Niu Y, Yang L, Wang Y, Yin D, Sun C, Chen YQ, Shen W, Zhang Z, Du X. Characterizing the dynamics of BCR repertoire from repeated influenza vaccination. Emerg Microbes Infect 2023; 12:2245931. [PMID: 37542407 PMCID: PMC10438862 DOI: 10.1080/22221751.2023.2245931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 07/12/2023] [Accepted: 08/03/2023] [Indexed: 08/06/2023]
Abstract
Yearly epidemics of seasonal influenza cause an enormous disease burden around the globe. An understanding of the rules behind the immune response with repeated vaccination still presents a significant challenge, which would be helpful for optimizing the vaccination strategy. In this study, 34 healthy volunteers with 16 vaccinated were recruited, and the dynamics of the BCR repertoire for consecutive vaccinations in two seasons were tracked. In terms of diversity, length, network, V and J gene segments usage, somatic hypermutation (SHM) rate and isotype, it was found that the overall changes were stronger in the acute phase of the first vaccination than the second vaccination. However, the V gene segments of IGHV4-39, IGHV3-9, IGHV3-7 and IGHV1-69 were amplified in the acute phase of the first vaccination, with IGHV3-7 dominant. On the other hand, for the second vaccination, the changes were dominated by IGHV1-69, with potential for coding broad neutralizing antibody. Additional analysis indicates that the application of V gene segment for IGHV3-7 in the acute phase of the first vaccination was due to the elevated usage of isotypes IgM and IgG3. While for IGHV1-69 in the second vaccination, it was contributed by isotypes IgG1 and IgG2. Finally, 41 public BCR clusters were identified in the vaccine group, with both IGHV3-7 and IGHV1-69 were involved and representative complementarity determining region 3 (CDR3) motifs were characterized. This study provides insights into the immune response dynamics following repeated influenza vaccination in humans and can inform universal vaccine design and vaccine strategies in the future.
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Affiliation(s)
- Guoqin Mai
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Chi Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Chunhong Lan
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Center for Precision Medicine, Guangdong Academy of Medical Sciences, Medical Research Institute, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, People’s Republic of China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Jie Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yuanyuan Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Kang Tang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Jing Tang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Jinfeng Zeng
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yilin Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Peiwen Cheng
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Shuning Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Haoyu Long
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Qilan Wen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Aqin Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Xuan Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Ruitong Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Shuyang Xu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Lin Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yanlan Niu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Lan Yang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yihan Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Di Yin
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Caijun Sun
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yao-Qing Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Wei Shen
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Zhenhai Zhang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Center for Precision Medicine, Guangdong Academy of Medical Sciences, Medical Research Institute, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, People’s Republic of China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, People’s Republic of China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, People’s Republic of China
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6
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Shi Y, Yang W, Li X, Chu K, Wang J, Tang R, Xu L, Li L, Hu Y, Zhao C, Pan H. Immunogenicity and Safety of One versus Two Doses of Quadrivalent Inactivated Influenza Vaccine (IIV4) in Vaccine-Unprimed Children and One Dose of IIV4 in Vaccine-Primed Children Aged 3-8 Years. Vaccines (Basel) 2023; 11:1586. [PMID: 37896989 PMCID: PMC10611167 DOI: 10.3390/vaccines11101586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 09/26/2023] [Accepted: 09/27/2023] [Indexed: 10/29/2023] Open
Abstract
Two doses of the inactivated influenza vaccine (IIV) are generally recommended for children under 9 years old. This study assessed the necessity for a second dose of quadrivalent IIV (IIV4) in children aged 3-8 years. In this randomized, open-label, paralleled-controlled study, 400 children aged 3-8 years who were vaccine-unprimed were randomly assigned at a 1:1 ratio to receive a two-dose (Group 1) or one-dose (Group 2) regimen of IIV4, and 200 who were vaccine-primed received one dose of IIV4 (Group 3). A serum sample was collected before and 28 days after the last dose to determine the hemagglutination inhibition (HI) antibody level. Adverse events were collected within 28 days after each dose. One-dose or two-doses of IIV4 were well tolerated and safe in children aged 3-8 years, and no serious adverse events related to the vaccine were reported. The seroconversion rates (SCRs) of HI antibody ranged from 61.86% to 95.86%, and the post-vaccination seroprotection rates (SPRs) were all >70% in three groups against the four virus strains. The two-dose regimen in vaccine-unprimed participants (Group 1) achieved similar SPRs in comparison with the one-dose in the vaccine-primed group (Group 3), and the SPRs in Group 1 and Group 3 were higher in vaccine-unprimed participants of the one-dose regimen (Group 2). The present study supports the recommendations of a two-dose regimen for IIV4 use in children aged 3-8 years.
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Affiliation(s)
- Yunfeng Shi
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009,China
| | - Wanqi Yang
- Sinovac Biotech Co., Ltd., Beijing 100085, China
| | - Xiaoyu Li
- National Institutes for Food and Drug Control, Beijing 102629, China
| | - Kai Chu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009,China
| | | | - Rong Tang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009,China
| | - Li Xu
- Sinovac Biotech Co., Ltd., Beijing 100085, China
| | - Lanshu Li
- National Institutes for Food and Drug Control, Beijing 102629, China
| | - Yuansheng Hu
- Sinovac Biotech Co., Ltd., Beijing 100085, China
| | - Chenyan Zhao
- National Institutes for Food and Drug Control, Beijing 102629, China
| | - Hongxing Pan
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009,China
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