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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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2
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Zhu L, Han Y, Lu J, Tan J, Liao C, Guo C, He Q, Qiu Y, Lu H, Zhou Y, Wei J, Hu D. Evaluation of Influenza Vaccine Effectiveness from 2021 to 2024: A Guangdong-Based Test-Negative Case-Control Study. Vaccines (Basel) 2024; 13:4. [PMID: 39852783 PMCID: PMC11768588 DOI: 10.3390/vaccines13010004] [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: 11/29/2024] [Revised: 12/18/2024] [Accepted: 12/21/2024] [Indexed: 01/26/2025] Open
Abstract
BACKGROUND The influenza virus's high mutation rate requires the annual reformulation and administration of the vaccine. Therefore, its vaccine effectiveness (VE) must be evaluated annually. AIM Estimate the effectiveness of the influenza vaccine and analyze the impact of age, seasonal variations, and the vaccination to sample collection interval on VE. METHODS The study used a test-negative case-control (TNCC) design to collect data from patients under 18 years of age who presented with acute respiratory infection (ARI) symptoms and underwent influenza virus testing at a national children's regional medical center in Guangdong Province between October 2021 and January 2024, spanning three influenza seasons. VE was estimated using unconditional logistic regression. RESULTS A total of 27,670 patient data entries were analyzed. The VE against all influenza viruses across the three seasons was 37% (95% CI: 31-43), with the lowest VE of 24% (95% CI: 8-37) observed in the 2021-2022 season. In children aged 0.5 to <3 years, the VE was 32% (95% CI: 19-43). The effectiveness for samples collected at intervals of 0.5-2 months, 3-6 months, and over 6 months after vaccination was 39% (95% CI: 32-46), 30% (95% CI: 19-40), and 28% (95% CI: 5-46). CONCLUSIONS Across three influenza seasons, at least one-third of vaccinated individuals were protected from influenza in outpatient settings. Given that children are at high risk, improving vaccination management is recommended, and parents should be encouraged to vaccinate their children before each influenza season.
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Affiliation(s)
- Liyan Zhu
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
| | - Ying Han
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
| | - Jiahai Lu
- School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; (J.L.); (C.L.); (C.G.)
- National Medical Products Administration Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou 510080, China
- One Health Center of Excellence for Research & Training, Sun Yat-Sen University, Guangzhou 510080, China
- School of Laboratory Medicine and Life Science, Wenzhou Medical University, Wenzhou 325000, China
- Hainan Key Novel Thinktank “Hainan Medical University ‘One Health’ Research Center”, Haikou 571199, China
- Research Institute of Sun Yat-Sen University in Shenzhen, Shenzhen 518057, China
- Key Laboratory of Tropical Diseases Control, Sun Yat-Sen University, Ministry of Education, Guangzhou 510080, China
- Institute of One Health, Wenzhou Medical University, Wenzhou 325000, China
| | - Jianhao Tan
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
| | - Conghui Liao
- School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; (J.L.); (C.L.); (C.G.)
| | - Cheng Guo
- School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China; (J.L.); (C.L.); (C.G.)
- National Medical Products Administration Key Laboratory for Quality Monitoring and Evaluation of Vaccines and Biological Products, Guangzhou 510080, China
| | - Qing He
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
| | - Yajie Qiu
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
| | - Huahua Lu
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
| | - Yue Zhou
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
| | - Jianrui Wei
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
- Guangzhou Key Laboratory of Child Neurodevelopment, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China
| | - Dandan Hu
- Department of Child Healthcare, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China; (L.Z.); (Y.H.); (J.T.); (Q.H.); (Y.Q.); (H.L.); (Y.Z.)
- Guangzhou Key Laboratory of Child Neurodevelopment, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangzhou 510623, China
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3
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Sajkov D, Woodman R, Honda-Okubo Y, Barbara J, Chew D, Toson B, Petrovsky N. A Multiseason Randomized Controlled Trial of Advax-Adjuvanted Seasonal Influenza Vaccine in Participants With Chronic Disease or Older Age. J Infect Dis 2024; 230:444-454. [PMID: 38157402 PMCID: PMC11326838 DOI: 10.1093/infdis/jiad589] [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: 07/22/2023] [Revised: 12/07/2023] [Accepted: 12/19/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND The aim of the current study was to determine the safety and immunogenicity of trivalent inactivated influenza vaccine (TIV) alone or formulated with Advax delta inulin adjuvant in those who were older (aged >60 years) or had chronic disease. METHODS Over 4 consecutive years from 2008 through 2011, adult participants with chronic disease or >60 years of age were recruited into a randomized controlled study to assess the safety, tolerability and immunogenicity of Advax-adjuvanted TIV (TIV + Adj) versus standard TIV. The per-protocol population with ≥1 postbaseline measurement of influenza antibodies comprised 1297 participants, 447 in the TIV and 850 in the TIV + Adj) group. RESULTS No safety issues were identified. Variables negatively affecting vaccine responses included obesity and diabetes mellitus. Advax adjuvant had a positive impact on anti-influenza immunoglobulin M responses and on H3N2 and B strain seropositivity as assessed by hemagglutination inhibition. CONCLUSIONS TIV + Adj was safe and well tolerated in individuals with chronic disease. There is an ongoing need for research into improved influenza vaccines for high-risk populations. CLINICAL TRIALS REGISTRATION Australia New Zealand Clinical Trial Registry: ACTRN 12608000364370.
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Affiliation(s)
- Dimitar Sajkov
- Australian Respiratory and Sleep Medicine Institute Ltd, Clovelly Park, South Australia, Australia
- Respiratory Department, Flinders University, Bedford Park, South Australia, Australia
| | - Richard Woodman
- Epidemiology and Biostatistics, Flinders University, Bedford Park, South Australia, Australia
| | - Yoshikazu Honda-Okubo
- Vaxine Pty Ltd, Warradale, South Australia, Australia
- College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
| | - Jeffrey Barbara
- Renal Department, Flinders University, Bedford Park, South Australia, Australia
| | - Derek Chew
- Cardiology Department, Flinders University, Bedford Park, South Australia, Australia
| | - Barbara Toson
- College of Medicine and Public Health, Flinders University, Bedford Park, South Australia, Australia
| | - Nikolai Petrovsky
- Australian Respiratory and Sleep Medicine Institute Ltd, Clovelly Park, South Australia, Australia
- Vaxine Pty Ltd, Warradale, South Australia, Australia
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4
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Pott H, LeBlanc JJ, ElSherif M, Hatchette TF, McNeil SA, Andrew MK. Predicting major clinical events among Canadian adults with laboratory-confirmed influenza infection using the influenza severity scale. Sci Rep 2024; 14:18378. [PMID: 39112632 PMCID: PMC11306731 DOI: 10.1038/s41598-024-67931-9] [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: 10/16/2023] [Accepted: 07/17/2024] [Indexed: 08/10/2024] Open
Abstract
We developed and validated the Influenza Severity Scale (ISS), a standardized risk assessment for influenza, to estimate and predict the probability of major clinical events in patients with laboratory-confirmed infection. Data from the Canadian Immunization Research Network's Serious Outcomes Surveillance Network (2011/2012-2018/2019 influenza seasons) enabled the selecting of all laboratory-confirmed influenza patients. A machine learning-based approach then identified variables, generated weighted scores, and evaluated model performance. This study included 12,954 patients with laboratory-confirmed influenza infections. The optimal scale encompassed ten variables: demographic (age and sex), health history (smoking status, chronic pulmonary disease, diabetes mellitus, and influenza vaccination status), clinical presentation (cough, sputum production, and shortness of breath), and function (need for regular support for activities of daily living). As a continuous variable, the scale had an AU-ROC of 0.73 (95% CI, 0.71-0.74). Aggregated scores classified participants into three risk categories: low (ISS < 30; 79.9% sensitivity, 51% specificity), moderate (ISS ≥ 30 but < 50; 54.5% sensitivity, 55.9% specificity), and high (ISS ≥ 50; 51.4% sensitivity, 80.5% specificity). ISS demonstrated a solid ability to identify patients with hospitalized laboratory-confirmed influenza at increased risk for Major Clinical Events, potentially impacting clinical practice and research.
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Affiliation(s)
- Henrique Pott
- Canadian Centre for Vaccinology, Dalhousie University, Halifax, Canada.
- Department of Medicine, Universidade Federal de São Carlos, Rod. Washington Luis, km 235, São Carlos, SP, 13656-905, Brazil.
| | - Jason J LeBlanc
- Canadian Centre for Vaccinology, Dalhousie University, Halifax, Canada
- Department of Pathology, Dalhousie University, Halifax, Canada
| | - May ElSherif
- Canadian Centre for Vaccinology, Dalhousie University, Halifax, Canada
| | - Todd F Hatchette
- Canadian Centre for Vaccinology, Dalhousie University, Halifax, Canada
- Department of Pathology, Dalhousie University, Halifax, Canada
| | - Shelly A McNeil
- Canadian Centre for Vaccinology, Dalhousie University, Halifax, Canada
- Department of Medicine (Infectious Diseases), Dalhousie University, Halifax, Canada
| | - Melissa K Andrew
- Canadian Centre for Vaccinology, Dalhousie University, Halifax, Canada
- Department of Medicine (Geriatrics), Dalhousie University, Halifax, Canada
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5
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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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ElSherif M, Andrew MK, Ye L, Ambrose A, Boivin G, Bowie W, David MP, Gruselle O, Halperin SA, Hatchette TF, Johnstone J, Katz K, Langley JM, Loeb M, MacKinnon-Cameron D, McCarthy A, McElhaney JE, McGeer A, Poirier A, Pirçon JY, Powis J, Richardson D, Semret M, Smith S, Smyth D, Trottier S, Valiquette L, Webster D, McNeil SA, LeBlanc JJ. Leveraging Influenza Virus Surveillance From 2012 to 2015 to Characterize the Burden of Respiratory Syncytial Virus Disease in Canadian Adults ≥50 Years of Age Hospitalized With Acute Respiratory Illness. Open Forum Infect Dis 2023; 10:ofad315. [PMID: 37441353 PMCID: PMC10334379 DOI: 10.1093/ofid/ofad315] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Accepted: 06/12/2023] [Indexed: 07/15/2023] Open
Abstract
Background Respiratory syncytial virus (RSV) disease in older adults is undercharacterized. To help inform future immunization policies, this study aimed to describe the disease burden in Canadian adults aged ≥50 years hospitalized with RSV. Methods Using administrative data and nasopharyngeal swabs collected from active surveillance among adults aged ≥50 years hospitalized with an acute respiratory illness (ARI) during the 2012-2013, 2013-2014, and 2014-2015 influenza seasons, RSV was identified using a respiratory virus multiplex polymerase chain reaction test to describe the associated disease burden, incidence, and healthcare costs. Results Of 7797 patients tested, 371 (4.8%) were RSV positive (2.2% RSV-A and 2.6% RSV-B). RSV prevalence varied by season from 4.2% to 6.2%. Respiratory virus coinfection was observed in 11.6% (43/371) of RSV cases, with influenza A being the most common. RSV hospitalization rates varied between seasons and increased with age, from 8-12 per 100 000 population in adults aged 50-59 years to 174-487 per 100 000 in adults aged ≥80 years. The median age of RSV cases was 74.9 years, 63.7% were female, and 98.1% of cases had ≥1 comorbidity. Among RSV cases, the mean length of hospital stay was 10.6 days, 13.7% were admitted to the intensive care unit, 6.4% required mechanical ventilation, and 6.1% died. The mean cost per RSV case was $13 602 (Canadian dollars) but varied by age and Canadian province. Conclusions This study adds to the growing literature on adult RSV burden by showing considerable morbidity, mortality, and healthcare costs in hospitalized adults aged ≥50 years with ARIs such as influenza.
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Affiliation(s)
- May ElSherif
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Melissa K Andrew
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Lingyun Ye
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Ardith Ambrose
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Guy Boivin
- Centre de Recherche du Centre hospitalier universitaire de Québec-Université Laval, Québec City, Québec, Canada
| | - William Bowie
- University of British Columbia, Vancouver, British Columbia, Canada
| | | | | | - Scott A Halperin
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Todd F Hatchette
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | | | - Kevin Katz
- North York General Hospital, Toronto, Ontario, Canada
| | - Joanne M Langley
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Mark Loeb
- McMaster University, Hamilton, Ontario, Canada
| | - Donna MacKinnon-Cameron
- Canadian Center for Vaccinology, IWK Health Centre and Nova Scotia Health Authority, Dalhousie University, Halifax, Nova Scotia, Canada
| | | | | | | | - Andre Poirier
- Centre intégré universitaire de santé et services sociaux de la Mauricie et du Centre du Québec, Québec City, Québec, Canada
| | | | - Jeff Powis
- Michael Garron Hospital, Toronto, Ontario, Canada
| | | | | | | | - Daniel Smyth
- The Moncton Hospital, Moncton, New Brunswick, Canada
| | - Sylvie Trottier
- Centre de Recherche du Centre hospitalier universitaire de Québec-Université Laval, Québec City, Québec, Canada
| | | | - Duncan Webster
- Saint John Regional Hospital, Saint John, New Brunswick, Canada
| | - Shelly A McNeil
- Correspondence: Jason J. LeBlanc, PhD, FCCM, D(ABMM), Division of Microbiology, Nova Scotia Health, Queen Elizabeth II Health Sciences Centre, Room 404B, Mackenzie Bldg, 5788 University Ave, Halifax, NS B3H 1V8, Canada (); Shelly McNeil, MD, FRCPC, FIDSA, Canadian Center for Vaccinology, IWK Health Centre, 4th Floor Goldbloom Pavilion, 5850/5980 University Ave, Halifax, NS B3K 6R8, Canada ()
| | - Jason J LeBlanc
- Correspondence: Jason J. LeBlanc, PhD, FCCM, D(ABMM), Division of Microbiology, Nova Scotia Health, Queen Elizabeth II Health Sciences Centre, Room 404B, Mackenzie Bldg, 5788 University Ave, Halifax, NS B3H 1V8, Canada (); Shelly McNeil, MD, FRCPC, FIDSA, Canadian Center for Vaccinology, IWK Health Centre, 4th Floor Goldbloom Pavilion, 5850/5980 University Ave, Halifax, NS B3K 6R8, Canada ()
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7
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Uemura K, Ono S, Michihata N, Yamana H, Yasunaga H. Duration of influenza vaccine effectiveness in the elderly in Japan: A retrospective cohort study using large-scale population-based registry data. Vaccine 2023; 41:3092-3098. [PMID: 37045684 DOI: 10.1016/j.vaccine.2023.03.066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 03/27/2023] [Accepted: 03/29/2023] [Indexed: 04/14/2023]
Abstract
BACKGROUND The immune response to influenza vaccination in the elderly is likely to be lower than that in young adults. Clinical protection may not persist year-round in the elderly. However, the effectiveness of influenza vaccine in the elderly has not been adequately studied, especially in terms of the duration of effectiveness. METHODS We used a linked database of healthcare administrative claims data and vaccination records maintained by the municipality of a city in Kanto region of Japan. We studied individuals who were aged 65 years or older at baseline and were followed up between April 1, 2014 to March 31, 2020. The duration of influenza vaccine effectiveness by age category was analyzed using a time-dependent piecewise Cox proportional hazard model with time-dependent vaccine status, prior season vaccination and covariates confirmed in the baseline period (age, sex, cancer, diabetes, chronic obstructive pulmonary diseases, asthma, chronic kidney diseases, and cardiovascular diseases). RESULTS We identified an analysis population of 83,146 individuals, of which 7,401 (8.9%) had experienced influenza and 270 (0.32%) underwent influenza-related hospitalization. Individuals who were vaccinated during the first season (n = 47,338) were older than non-vaccinated individuals (n = 35,808) (average age, 75.8 vs. 74.1 years, respectively). The multivariable analysis showed a lower incidence of influenza in vaccinated individuals (hazard ratio [HR], 0.47; 95% confidence interval [CI], 0.43-0.51; P < 0.001), while the incidence of hospitalization for influenza did not differ significantly by vaccination status (HR, 0.79; 95% CI, 0.53-1.18; P = 0.249). Protective effectiveness against incidence was maintained for 4 or 5 months after vaccination in those aged 65-69 and 80-years, 5 months in 70-79 years. CONCLUSIONS Our study identified moderate vaccine effectiveness in preventing the incidence of influenza in the Japanese elderly. Vaccine effectiveness showed a trend of gradual attenuation. Clinicians should suspect influenza infection even in those vaccinated, especially in elderly individuals who had received vaccination more than 4 or 5 months previously.
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Affiliation(s)
- Kohei Uemura
- Department of Biostatistics & Bioinformatics, Interfaculty Initiative in Information Studies, The University of Tokyo, Tokyo, Japan.
| | - Sachiko Ono
- Department of Eat-loss Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Nobuaki Michihata
- Department of Health Services Research, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hayato Yamana
- Department of Health Services Research, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hideo Yasunaga
- Department of Clinical Epidemiology & Health Economics, School of Public Health, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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8
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Jones-Gray E, Robinson EJ, Kucharski AJ, Fox A, Sullivan SG. Does repeated influenza vaccination attenuate effectiveness? A systematic review and meta-analysis. THE LANCET. RESPIRATORY MEDICINE 2023; 11:27-44. [PMID: 36152673 PMCID: PMC9780123 DOI: 10.1016/s2213-2600(22)00266-1] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 07/13/2022] [Accepted: 07/13/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Influenza vaccines require annual readministration; however, several reports have suggested that repeated vaccination might attenuate the vaccine's effectiveness. We aimed to estimate the reduction in vaccine effectiveness associated with repeated influenza vaccination. METHODS In this systematic review and meta-analysis, we searched MEDLINE, EMBASE, and CINAHL Complete databases for articles published from Jan 1, 2016, to June 13, 2022, and Web of Science for studies published from database inception to June 13, 2022. For studies published before Jan 1, 2016, we consulted published systematic reviews. Two reviewers (EJ-G and EJR) independently screened, extracted data using a data collection form, assessed studies' risk of bias using the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) and evaluated the weight of evidence by Grading of Recommendations Assessment, Development, and Evaluation (GRADE). We included observational studies and randomised controlled trials that reported vaccine effectiveness against influenza A(H1N1)pdm09, influenza A(H3N2), or influenza B using four vaccination groups: current season; previous season; current and previous seasons; and neither season (reference). For each study, we calculated the absolute difference in vaccine effectiveness (ΔVE) for current season only and previous season only versus current and previous season vaccination to estimate attenuation associated with repeated vaccination. Pooled vaccine effectiveness and ∆VE were calculated by season, age group, and overall. This study is registered with PROSPERO, CRD42021260242. FINDINGS We identified 4979 publications, selected 681 for full review, and included 83 in the systematic review and 41 in meta-analyses. ΔVE for vaccination in both seasons compared with the current season was -9% (95% CI -16 to -1, I2=0%; low certainty) for influenza A(H1N1)pdm09, -18% (-26 to -11, I2=7%; low certainty) for influenza A(H3N2), and -7% (-14 to 0, I2=0%; low certainty) for influenza B, indicating lower protection with consecutive vaccination. However, for all types, A subtypes and B lineages, vaccination in both seasons afforded better protection than not being vaccinated. INTERPRETATION Our estimates suggest that, although vaccination in the previous year attenuates vaccine effectiveness, vaccination in two consecutive years provides better protection than does no vaccination. The estimated effects of vaccination in the previous year are concerning and warrant additional investigation, but are not consistent or severe enough to support an alternative vaccination regimen at this time. FUNDING WHO and the US National Institutes of Health.
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Affiliation(s)
- Elenor Jones-Gray
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia
| | - Elizabeth J Robinson
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia
| | - Adam J Kucharski
- Centre for the Mathematical Modelling of Infectious Diseases (CMMID), London School of Hygiene and Tropical Medicine, London, UK
| | - Annette Fox
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia
| | - Sheena G Sullivan
- Department of Infectious Diseases, University of Melbourne, Melbourne, VIC, Australia; WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC, Australia; Department of Epidemiology, University of California, Los Angeles, CA, USA.
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9
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Zhang Y, Wang Y, Jia C, Li G, Zhang W, Li Q, Chen X, Leng W, Huang L, Xie Z, Zhang H, You W, An R, Jiang H, Zhao X, Cheng S, Tan J, Cui W, Gao F, Lu W, Wang Y, Yang Y, Xia S, Wang S. Immunogenicity and safety of an egg culture-based quadrivalent inactivated non-adjuvanted subunit influenza vaccine in subjects ≥3 years: A randomized, multicenter, double-blind, active-controlled phase III, non-inferiority trial. Vaccine 2022; 40:4933-4941. [PMID: 35810063 DOI: 10.1016/j.vaccine.2022.06.078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Revised: 06/21/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022]
Abstract
Subunit influenza vaccine only formulated with surface antigen proteins has better safety profiles relative to split-virion influenza vaccine. Compared to the traditional quadrivalent split-virion influenza vaccine, a novel quadrivalent subunit influenza vaccine is urgently needed in China. We completed a phase 3, randomized, double-blind, active-controlled, non-inferiority clinical study at two sites in Henan Province, China. Eligible volunteers were split into four age cohorts (3-8 years, 9-17 years, 18-64 years, and ≥ 65 years, based on their dates of birth) and randomly assigned (1:1) to the subunit and the split-virion ecNAIIV4 groups. All volunteers were intramuscularly administered a single vaccine dose at baseline, and children aged 3-8 years received a boosting dose at day 28. And the immune response was evaluated by measuring hemagglutinin-inhibition antibody titers against the four vaccine strains in blood samples. Safety profiles had nonsignificant differences between the study groups in ≥ 3 years cohort. Most adverse reactions post-vaccination, both local and systemic, were mild to moderate and resolved within 3 days. And no serious adverse events occurred. The immunogenicity of the trial vaccine was non-inferior to the comparator. Further, a two-dose vaccine series can provide better seroprotection than that of a one-dose series in children aged 3-8 years, with clinically acceptable safety profiles. Clinical Trials Registration. ChiCTR2100049934.
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Affiliation(s)
| | - Yanxia Wang
- Henan Provincial Centre for Disease Control and Prevention, Zhenzhou, China.
| | | | | | - Wei Zhang
- Henan Provincial Centre for Disease Control and Prevention, Zhenzhou, China.
| | - Qin Li
- Ab&b Biotec Co., Ltd, Taizhou, China.
| | | | | | - Lili Huang
- Henan Provincial Centre for Disease Control and Prevention, Zhenzhou, China.
| | - Zhiqiang Xie
- Henan Provincial Centre for Disease Control and Prevention, Zhenzhou, China.
| | | | - Wangyang You
- Henan Provincial Centre for Disease Control and Prevention, Zhenzhou, China.
| | - Rui An
- Ab&b Biotec Co., Ltd, Taizhou, China.
| | | | - Xue Zhao
- Ab&b Biotec Co., Ltd, Taizhou, China.
| | | | - Jiebing Tan
- Henan Provincial Centre for Disease Control and Prevention, Zhenzhou, China.
| | - Weiyang Cui
- Puyang Centre for Disease Control and Prevention, Henan, China.
| | - Feilong Gao
- Kaifeng Municipal Centre for Disease Control and Prevention, Henan, China.
| | - Weifeng Lu
- Kaifeng Municipal Centre for Disease Control and Prevention, Henan, China.
| | - Yuping Wang
- Puyang Centre for Disease Control and Prevention, Henan, China.
| | - Yongli Yang
- Department of Epidemiology and Public Health, College of Public Health, Zhengzhou University, Zhenzhou, China.
| | - Shengli Xia
- Henan Provincial Centre for Disease Control and Prevention, Zhenzhou, China.
| | - Shuai Wang
- Ab&b Biotec Co., Ltd, Taizhou, China; Yither Biotech Co., Ltd, Shanghai, China.
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10
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Kang M, Zanin M, Wong SS. Subtype H3N2 Influenza A Viruses: An Unmet Challenge in the Western Pacific. Vaccines (Basel) 2022; 10:vaccines10010112. [PMID: 35062773 PMCID: PMC8778411 DOI: 10.3390/vaccines10010112] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/07/2022] [Accepted: 01/07/2022] [Indexed: 02/04/2023] Open
Abstract
Subtype H3N2 influenza A viruses (A(H3N2)) have been the dominant strain in some countries in the Western Pacific region since the 2009 influenza A(H1N1) pandemic. Vaccination is the most effective way to prevent influenza; however, low vaccine effectiveness has been reported in some influenza seasons, especially for A(H3N2). Antigenic mismatch introduced by egg-adaptation during vaccine production between the vaccine and circulating viral stains is one of the reasons for low vaccine effectiveness. Here we review the extent of this phenomenon, the underlying molecular mechanisms and discuss recent strategies to ameliorate this, including new vaccine platforms that may provide better protection and should be considered to reduce the impact of A(H3N2) in the Western Pacific region.
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Affiliation(s)
- Min Kang
- School of Public Health, Southern Medical University, Guangzhou 510515, China;
- Guangdong Center for Disease Control and Prevention, Guangzhou 511430, China
| | - Mark Zanin
- State Key Laboratory for Respiratory Diseases and National Clinical Research Centre for Respiratory Disease, Guangzhou Medical University, 195 Dongfengxi Road, Guangzhou 511436, China;
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, China
| | - Sook-San Wong
- State Key Laboratory for Respiratory Diseases and National Clinical Research Centre for Respiratory Disease, Guangzhou Medical University, 195 Dongfengxi Road, Guangzhou 511436, China;
- School of Public Health, The University of Hong Kong, 7 Sassoon Road, Pokfulam, Hong Kong, China
- Correspondence: ; Tel.: +86-178-2584-6078
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11
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Martínez-Baz I, Navascués A, Casado I, Aguinaga A, Ezpeleta C, Castilla J. Simple models to include influenza vaccination history when evaluating the effect of influenza vaccination. ACTA ACUST UNITED AC 2021; 26. [PMID: 34387185 PMCID: PMC8365179 DOI: 10.2807/1560-7917.es.2021.26.32.2001099] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Background Most reports of influenza vaccine effectiveness consider current-season vaccination only. Aim We evaluated a method to estimate the effect of influenza vaccinations (EIV) considering vaccination history. Methods We used a test-negative design with well-documented vaccination history to evaluate the average EIV over eight influenza seasons (2011/12–2018/19; n = 10,356). Modifying effect was considered as difference in effects of vaccination in current and previous seasons and current-season vaccination only. We also explored differences between current-season estimates excluding from the reference category people vaccinated in any of the five previous seasons and estimates without this exclusion or only for one or three previous seasons. Results The EIV was 50%, 45% and 38% in people vaccinated in the current season who had previously received none, one to two and three to five doses, respectively, and it was 30% and 43% for one to two and three to five prior doses only. Vaccination in at least three previous seasons reduced the effect of current-season vaccination by 12 percentage points overall, 31 among outpatients, 22 in 9–65 year-olds, and 23 against influenza B. Including people vaccinated in previous seasons only in the unvaccinated category underestimated EIV by 9 percentage points on average (31% vs 40%). Estimates considering vaccination of three or five previous seasons were similar. Conclusions Vaccine effectiveness studies should consider influenza vaccination in previous seasons, as it can retain effect and is often an effect modifier. Vaccination status in three categories (current season, previous seasons only, unvaccinated) reflects the whole EIV.
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Affiliation(s)
- Iván Martínez-Baz
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Pamplona, Spain.,Instituto de Salud Pública de Navarra, Pamplona, Spain
| | - Ana Navascués
- Servicio de Microbiología Clínica, Complejo Hospitalario de Navarra, Pamplona, Spain.,Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Itziar Casado
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Pamplona, Spain.,Instituto de Salud Pública de Navarra, Pamplona, Spain
| | - Aitziber Aguinaga
- Servicio de Microbiología Clínica, Complejo Hospitalario de Navarra, Pamplona, Spain.,Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Carmen Ezpeleta
- Servicio de Microbiología Clínica, Complejo Hospitalario de Navarra, Pamplona, Spain.,Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Jesús Castilla
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Pamplona, Spain.,Instituto de Salud Pública de Navarra, Pamplona, Spain
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12
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Safiabadi Tali SH, LeBlanc JJ, Sadiq Z, Oyewunmi OD, Camargo C, Nikpour B, Armanfard N, Sagan SM, Jahanshahi-Anbuhi S. Tools and Techniques for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/COVID-19 Detection. Clin Microbiol Rev 2021; 34:e00228-20. [PMID: 33980687 PMCID: PMC8142517 DOI: 10.1128/cmr.00228-20] [Citation(s) in RCA: 199] [Impact Index Per Article: 49.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory disease coronavirus 2 (SARS-CoV-2), has led to millions of confirmed cases and deaths worldwide. Efficient diagnostic tools are in high demand, as rapid and large-scale testing plays a pivotal role in patient management and decelerating disease spread. This paper reviews current technologies used to detect SARS-CoV-2 in clinical laboratories as well as advances made for molecular, antigen-based, and immunological point-of-care testing, including recent developments in sensor and biosensor devices. The importance of the timing and type of specimen collection is discussed, along with factors such as disease prevalence, setting, and methods. Details of the mechanisms of action of the various methodologies are presented, along with their application span and known performance characteristics. Diagnostic imaging techniques and biomarkers are also covered, with an emphasis on their use for assessing COVID-19 or monitoring disease severity or complications. While the SARS-CoV-2 literature is rapidly evolving, this review highlights topics of interest that have occurred during the pandemic and the lessons learned throughout. Exploring a broad armamentarium of techniques for detecting SARS-CoV-2 will ensure continued diagnostic support for clinicians, public health, and infection prevention and control for this pandemic and provide advice for future pandemic preparedness.
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Affiliation(s)
- Seyed Hamid Safiabadi Tali
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
- Department of Mechanical, Industrial, and Aerospace Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
| | - Jason J LeBlanc
- Department of Pathology, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Microbiology and Immunology, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Medicine (Infectious Diseases), Dalhousie University, Halifax, Nova Scotia, Canada
- Division of Microbiology, Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada
| | - Zubi Sadiq
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
| | - Oyejide Damilola Oyewunmi
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
| | - Carolina Camargo
- Department of Microbiology and Immunology, McGill University, Montréal, Québec, Canada
| | - Bahareh Nikpour
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec, Canada
| | - Narges Armanfard
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec, Canada
- Mila-Quebec AI Institute, Montréal, Québec, Canada
| | - Selena M Sagan
- Department of Microbiology and Immunology, McGill University, Montréal, Québec, Canada
- Department of Biochemistry, McGill University, Montréal, Québec, Canada
| | - Sana Jahanshahi-Anbuhi
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
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13
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McLean HQ, Belongia EA. Influenza Vaccine Effectiveness: New Insights and Challenges. Cold Spring Harb Perspect Med 2021; 11:cshperspect.a038315. [PMID: 31988202 DOI: 10.1101/cshperspect.a038315] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Methods for assessing influenza vaccine efficacy and effectiveness have evolved over six decades. Randomized trials remain the gold standard for licensure, but observational studies are needed for annual assessment of vaccine effectiveness (VE). The test-negative design (TND) has become the de facto standard for these field studies. Patients who seek medical care with acute respiratory illness are tested for influenza, and VE is estimated from the odds of vaccination among influenza cases versus test-negative controls. VE varies across seasons, populations, age groups, and products, but VE estimates are consistently higher for A(H1N1)pdm09 and type B compared with A(H3N2). VE studies are increasingly used in combination with molecular epidemiology to understand the viral and immune system factors that drive clinical efficacy and effectiveness. The emerging field of immunoepidemiology offers the potential to understand complex host-virus interactions that affect vaccine protection, and this knowledge will contribute to universal vaccine development.
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Affiliation(s)
- Huong Q McLean
- Center for Clinical Epidemiology & Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin 54449, USA
| | - Edward A Belongia
- Center for Clinical Epidemiology & Population Health, Marshfield Clinic Research Institute, Marshfield, Wisconsin 54449, USA
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14
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Verschoor CP, Haynes L, Pawelec G, Loeb M, Andrew MK, Kuchel GA, McElhaney JE. Key Determinants of Cell-Mediated Immune Responses: A Randomized Trial of High Dose Vs. Standard Dose Split-Virus Influenza Vaccine in Older Adults. FRONTIERS IN AGING 2021; 2. [PMID: 35128529 PMCID: PMC8813165 DOI: 10.3389/fragi.2021.649110] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Background: Efforts to improve influenza vaccine effectiveness in older adults have resulted in some successes, such as the introduction of high-dose split-virus influenza vaccine (HD-SVV), yet studies of cell-mediated immune responses to these vaccines remain limited. We have shown that granzyme B (GrB) activity in influenza A/H3N2 challenged peripheral blood mononuclear cells (PBMC) correlates with protection against influenza following standard dose vaccination (SD-SVV) in older adults. Further, the interferon-γ (IFNγ) to interleukin-10 (IL-10) ratio can be a correlate of protection. Methods: In a double-blind trial (ClinicalTrials.gov NCT02297542) older adults (≥65 years, n = 582) were randomized to receive SD-SVV or HD-SVV (Fluzone®) from 2014/15 to 2017/18. Young adults (20–40 years, n = 79) received SD-SVV. At 0, 4, 10, and 20 weeks post-vaccination, serum antibody titers, IFNγ, IL-10, and inducible GrB (iGrB) were measured in ex vivo influenza-challenged PBMC. iGrB is defined as the fold change in GrB activity from baseline levels (bGrB) in circulating T cells. Responses of older adults were compared to younger controls, and in older adults, we analyzed effects of age, sex, cytomegalovirus (CMV) serostatus, frailty, and vaccine dose. Results: Prior to vaccination, younger compared to older adults produced significantly higher IFNγ, IL-10, and iGrB levels. Relative to SD-SVV recipients, older HD-SVV recipients exhibited significantly lower IFNγ:IL-10 ratios at 4 weeks post-vaccination. In contrast, IFNγ and iGrB levels were higher in younger SD vs. older SD or HD recipients; only the HD group showed a significant IFNγ response to vaccination compared to the SD groups; all three groups showed a significant iGrB response to vaccination. In a regression analysis, frailty was associated with lower IFNγ levels, whereas female sex and HD-SVV with higher IL-10 levels. Age and SD-SVV were associated with lower iGrB levels. The effect of prior season influenza vaccination was decreased iGrB levels, and increased IFNγ and IL-10 levels, which correlated with influenza A/H3N2 hemagglutination inhibition antibody titers. Conclusion: Overall, HD-SVV amplified the IL-10 response consistent with enhanced antibody responses, with little effect on the iGrB response relative to SD-SVV in either younger or older adults. These results suggest that enhanced protection with HD-SVV is largely antibody-mediated. Clinical Trial Registration: ClinicalTrials.gov (NCT02297542).
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Affiliation(s)
- Chris P. Verschoor
- Health Sciences North Research Institute, Sudbury, ON, Canada
- Northern Ontario School of Medicine, Sudbury, ON, Canada
| | - Laura Haynes
- UConn Center on Aging, University of Connecticut School of Medicine, Farmington, CT, United States
| | - Graham Pawelec
- Health Sciences North Research Institute, Sudbury, ON, Canada
- Department of Immunology, University of Tübingen, Tübingen, Germany
| | - Mark Loeb
- Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON, Canada
| | - Melissa K. Andrew
- Department of Medicine (Geriatrics), Dalhousie University, Halifax, NS, Canada
| | - George A. Kuchel
- UConn Center on Aging, University of Connecticut School of Medicine, Farmington, CT, United States
| | - Janet E. McElhaney
- Health Sciences North Research Institute, Sudbury, ON, Canada
- Northern Ontario School of Medicine, Sudbury, ON, Canada
- *Correspondence: Janet E. McElhaney,
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15
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Feldstein LR, Self WH, Ferdinands JM, Randolph AG, Aboodi M, Baughman AH, Brown SM, Exline MC, Files DC, Gibbs K, Ginde AA, Gong MN, Grijalva CG, Halasa N, Khan A, Lindsell CJ, Newhams M, Peltan ID, Prekker ME, Rice TW, Shapiro NI, Steingrub J, Talbot HK, Halloran ME, Patel M. Incorporating Real-time Influenza Detection Into the Test-negative Design for Estimating Influenza Vaccine Effectiveness: The Real-time Test-negative Design (rtTND). Clin Infect Dis 2021; 72:1669-1675. [PMID: 32974644 DOI: 10.1093/cid/ciaa1453] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 09/21/2020] [Indexed: 01/17/2023] Open
Abstract
With rapid and accurate molecular influenza testing now widely available in clinical settings, influenza vaccine effectiveness (VE) studies can prospectively select participants for enrollment based on real-time results rather than enrolling all eligible patients regardless of influenza status, as in the traditional test-negative design (TND). Thus, we explore advantages and disadvantages of modifying the TND for estimating VE by using real-time, clinically available viral testing results paired with acute respiratory infection eligibility criteria for identifying influenza cases and test-negative controls prior to enrollment. This modification, which we have called the real-time test-negative design (rtTND), has the potential to improve influenza VE studies by optimizing the case-to-test-negative control ratio, more accurately classifying influenza status, improving study efficiency, reducing study cost, and increasing study power to adequately estimate VE. Important considerations for limiting biases in the rtTND include the need for comprehensive clinical influenza testing at study sites and accurate influenza tests.
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Affiliation(s)
- Leora R Feldstein
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Wesley H Self
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jill M Ferdinands
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Adrienne G Randolph
- Department of Anesthesiology, Critical Care, and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.,Departments of Anesthesia and Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - Michael Aboodi
- Division of Critical Care Medicine, Albert Einstein College of Medicine, Bronx, New York, USA
| | | | - Samuel M Brown
- Division of Pulmonary/Critical Care, Department of Medicine, Intermountain Medical Center and University of Utah, Murray, Utah, USA
| | - Matthew C Exline
- The Ohio State University, College of Nursing, Columbus, Ohio, USA
| | - D Clark Files
- Pulmonary Critical Care Allergy and Immunological Diseases, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Kevin Gibbs
- Pulmonary Critical Care Allergy and Immunological Diseases, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Adit A Ginde
- Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Michelle N Gong
- Division of Critical Care Medicine, Division of Pulmonary Medicine, Department of Medicine, Department of Epidemiology and Population Health, Montefiore Healthcare System, Albert Einstein College of Medicine, Bronx, New York, USA
| | | | - Natasha Halasa
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Akram Khan
- Department of Pulmonary and Critical Care, Oregon Health and Science University, Portland, Oregon, USA
| | | | - Margaret Newhams
- Department of Anesthesiology, Critical Care, and Pain Medicine, Boston Children's Hospital, Boston, Massachusetts, USA.,Departments of Anesthesia and Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - Ithan D Peltan
- Division of Pulmonary/Critical Care, Department of Medicine, Intermountain Medical Center and University of Utah, Murray, Utah, USA
| | - Matthew E Prekker
- Department of Medicine, Division of Pulmonary and Critical Care and Department of Emergency Medicine, Hennepin County Medical Center and the University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Todd W Rice
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Nathan I Shapiro
- Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Jay Steingrub
- Division of Critical Care Pulmonary Medicine, Baystate Medical Center, Springfield, Massachusetts, USA
| | - H Keipp Talbot
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - M Elizabeth Halloran
- Department of Biostatistics, University of Washington, Seattle, Washington, USA.,Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Manish Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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16
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Hollingsworth R, El Guerche-Séblain C, Tsai T, Vasiliev Y, Lee S, Bright H, Barbosa P. Assessment of the benefits of seasonal influenza vaccination: Elements of a framework to interpret estimates of vaccine effectiveness and support robust decision-making and communication. Influenza Other Respir Viruses 2020; 15:164-174. [PMID: 32885610 PMCID: PMC7767949 DOI: 10.1111/irv.12786] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 06/26/2020] [Accepted: 06/29/2020] [Indexed: 12/03/2022] Open
Abstract
Systematic reviews and meta‐analyses confirm that influenza vaccination reduces the risk of influenza illness by between about 40% and 60% in seasons when circulating influenza stains are well matched to vaccine strains. Influenza vaccine effectiveness (IVE) estimates, however, are often discordant and a source of confusion for decision makers. IVE assessments are increasingly publicized and are often used by policy makers to make decisions about the value of seasonal influenza vaccination. But there is limited guidance on how IVE should be interpreted or used to inform policy. There are several limitations to the use of IVE for decision‐making: (a) IVE studies have methodological issues that often complicate the interpretation of their value; and (b) the full impact of vaccination will almost always be greater than the impact assessed by a point estimate of IVE in specific populations or settings. Understanding the strengths and weaknesses of study methodologies and the fundamental limitations of IVE estimates is important for the accuracy of interpretations and support of policy makers’ decisions. Here, we review a comprehensive set of issues that need to be considered when interpreting IVE and determining the full benefits of influenza vaccination. We propose that published IVE values should be assessed using an evaluative framework that includes influenza‐specific outcomes, types of VE study design, and confounders, among other factors. Better interpretation of IVE will improve the broader assessment of the value of influenza vaccination and ultimately optimize the public health benefits in seasonal influenza vaccination.
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Affiliation(s)
| | | | | | - Yuri Vasiliev
- St. Petersburg Research Institute of Vaccines and Sera, Krasnoe Selo, Russian Federation
| | - Sam Lee
- Sanofi Pasteur, Swiftwater, PA, USA
| | | | - Paula Barbosa
- International Federation of Pharmaceutical Manufacturers and Associations, Geneva, Switzerland
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17
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Abstract
Seasonal influenza remains a major public health problem, responsible for hundreds of thousands of deaths every year, mostly of elderly people. Despite the wide availability of vaccines, there are multiple problems decreasing the effectiveness of vaccination programs. These include viral variability and hence the requirement to match strains by estimating which will become prevalent each season, problems associated with vaccine and adjuvant production, and the route of administration as well as the perceived lower vaccine efficiency in older adults. Clinical protection is still suboptimal for all of these reasons, and vaccine uptake remains too low in most countries. Efforts to improve the effectiveness of influenza vaccines include developing universal vaccines independent of the circulating strains in any particular season and stimulating cellular as well as humoral responses, especially in the elderly. This commentary assesses progress over the last 3 years towards achieving these aims. Since the beginning of 2020, an unprecedented international academic and industrial effort to develop effective vaccines against the new coronavirus SARS-CoV-2 has diverted attention away from influenza, but many of the lessons learned for the one will synergize with the other to mutual advantage. And, unlike the SARS-1 epidemic and, we hope, the SARS-CoV-2 pandemic, influenza will not be eliminated and thus efforts to improve influenza vaccines will remain of crucial importance.
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Affiliation(s)
- Graham Pawelec
- Department of Immunology, University of Tübingen, Tübingen, Germany.,Health Sciences North Research Institute, Ontario, Canada
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18
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Glatman-Freedman A, Pando R, Sefty H, Omer I, Rosenberg A, Drori Y, Nemet I, Mendelson E, Keinan-Boker L, Mandelboim M. Predominance of a Drifted Influenza A (H3N2) Clade and its Association with Age-specific Influenza Vaccine Effectiveness Variations, Influenza Season 2018-2019. Vaccines (Basel) 2020; 8:vaccines8010078. [PMID: 32050460 PMCID: PMC7157661 DOI: 10.3390/vaccines8010078] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 01/24/2020] [Accepted: 01/29/2020] [Indexed: 12/20/2022] Open
Abstract
Background: Influenza A (H3N2) clade 3C.3a was the predominant influenza virus in Israel throughout the 2018-2019 season, constituting a drift from the influenza A (H3N2) vaccine. We estimated the end-of season vaccine effectiveness (VE) by age, among community patients with influenza-like illness (ILI), considering the hemagglutinin (HA) gene mutations and amino acid substitutions of influenza A (H3N2) viruses detected. Methods: Nose-throat samples were analyzed for the presence of influenza virus, type/subtype, and HA gene sequence. HA gene sequences and amino acid substitutions were compared to the influenza A/Singapore/INFIMH-16-0019/2016 (H3N2)-like 2018-2019 vaccine virus, and a phylogenetic tree was generated. Influenza VE against influenza A (H3N2) was estimated using the test-negative design. VE was estimated by age group and by 15 year moving age intervals. Results: In total, 90% of the influenza A (H3N2) viruses belonged to the 3C.3a clade, constituting a unique situation in the northern hemisphere. Adjusted all-age influenza A (H3N2) VE was −3.5% (95% CI: −51.2 to 29.1). Although adjusted VEs were very low among infants, children, and young adults, a VE of 45% (95% CI: −19.2 to 74.6) was estimated among adults aged ≥45 years old. Conclusions: The higher VE point estimates among older adults may be related to previous exposure to similar influenza viruses.
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Affiliation(s)
- Aharona Glatman-Freedman
- Israel Center for Disease Control, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
- School of Public Health, Tel Aviv University Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Correspondence:
| | - Rakefet Pando
- Israel Center for Disease Control, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
- Central Virology Laboratory, Sheba Medical Center, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
| | - Hanna Sefty
- Israel Center for Disease Control, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
| | - Itay Omer
- School of Public Health, Tel Aviv University Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Alina Rosenberg
- Israel Center for Disease Control, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
| | - Yaron Drori
- School of Public Health, Tel Aviv University Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Central Virology Laboratory, Sheba Medical Center, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
| | - Ital Nemet
- Central Virology Laboratory, Sheba Medical Center, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
| | - Ella Mendelson
- School of Public Health, Tel Aviv University Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Central Virology Laboratory, Sheba Medical Center, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
| | - Lital Keinan-Boker
- Israel Center for Disease Control, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
- School of Public Health, University of Haifa, Haifa 3498838, Israel
| | - Michal Mandelboim
- School of Public Health, Tel Aviv University Faculty of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Central Virology Laboratory, Sheba Medical Center, Israel Ministry of Health, Tel Hashomer, Ramat Gan 5265601, Israel
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19
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LeBlanc JJ, ElSherif M, Mulpuru S, Warhuus M, Ambrose A, Andrew M, Boivin G, Bowie W, Chit A, Dos Santos G, Green K, Halperin SA, Hatchette TF, Ibarguchi B, Johnstone J, Katz K, Langley JM, Lagacé-Wiens P, Loeb M, Lund A, MacKinnon-Cameron D, McCarthy A, McElhaney JE, McGeer A, Poirier A, Powis J, Richardson D, Semret M, Shinde V, Smyth D, Trottier S, Valiquette L, Webster D, Ye L, McNeil S. Validation of the Seegene RV15 multiplex PCR for the detection of influenza A subtypes and influenza B lineages during national influenza surveillance in hospitalized adults. J Med Microbiol 2020; 69:256-264. [PMID: 31264957 PMCID: PMC7431100 DOI: 10.1099/jmm.0.001032] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 06/16/2019] [Indexed: 01/04/2023] Open
Abstract
Background. The Serious Outcomes Surveillance Network of the Canadian Immunization Research Network (CIRN SOS) has been performing active influenza surveillance since 2009 (ClinicalTrials.gov identifier: NCT01517191). Influenza A and B viruses are identified and characterized using real-time reverse-transcriptase polymerase chain reaction (RT-PCR), and multiplex testing has been performed on a subset of patients to identify other respiratory virus aetiologies. Since both methods can identify influenza A and B, a direct comparison was performed.Methods. Validated real-time RT-PCRs from the World Health Organization (WHO) to identify influenza A and B viruses, characterize influenza A viruses into the H1N1 or H3N2 subtypes and describe influenza B viruses belonging to the Yamagata or Victoria lineages. In a subset of patients, the Seeplex RV15 One-Step ACE Detection assay (RV15) kit was also used for the detection of other respiratory viruses.Results. In total, 1111 nasopharyngeal swabs were tested by RV15 and real-time RT-PCRs for influenza A and B identification and characterization. For influenza A, RV15 showed 98.0 % sensitivity, 100 % specificity and 99.7 % accuracy. The performance characteristics of RV15 were similar for influenza A subtypes H1N1 and H3N2. For influenza B, RV15 had 99.2 % sensitivity, 100 % specificity and 99.8 % accuracy, with similar assay performance being shown for both the Yamagata and Victoria lineages.Conclusions. Overall, the detection of circulating subtypes of influenza A and lineages of influenza B by RV15 was similar to detection by real-time RT-PCR. Multiplex testing with RV15 allows for a more comprehensive respiratory virus surveillance in hospitalized adults, without significantly compromising the reliability of influenza A or B virus detection.
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Affiliation(s)
- J. J. LeBlanc
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - M. ElSherif
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - S. Mulpuru
- Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
| | - M. Warhuus
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - A. Ambrose
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - M. Andrew
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - G. Boivin
- Centre Hospitalier Universitaire de Québec, QC, Canada
| | - W. Bowie
- University of British Columbia, Vancouver, BC, Canada
| | - A. Chit
- Sanofi Pasteur, Swiftwater, PA, USA
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada
| | - G. Dos Santos
- Business & Decision Life Sciences (on behalf of GSK), Bruxelles, Belgium
- Present address: GSK, Wavre, Belgium
| | - K. Green
- Mount Sinai Hospital, Toronto, ON, Canada
| | - S. A. Halperin
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - T. F. Hatchette
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - B. Ibarguchi
- GSK, Mississauga, ON, Canada
- Present address: Bayer, Inc., Mississauga, Ontario, Canada
| | - J. Johnstone
- Public Health Ontario and University of Toronto, Toronto, ON, Canada
| | - K. Katz
- North York General Hospital, Toronto, ON, Canada
| | - J. M. Langley
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | | | - M. Loeb
- Public Health Ontario and University of Toronto, Toronto, ON, Canada
| | - A. Lund
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - D. MacKinnon-Cameron
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - A. McCarthy
- Ottawa Hospital General, Ottawa, Ontario, Canada
| | - J. E. McElhaney
- Health Sciences North Research Institute, Sudbury, ON, Canada
| | - A. McGeer
- Mount Sinai Hospital, Toronto, ON, Canada
| | - A. Poirier
- Centre Intégré Universitaire de Santé et Services Sociaux, Quebec, QC, Canada
| | - J. Powis
- Toronto East General Hospital, Toronto, ON, Canada
| | | | - M. Semret
- McGill University, Montreal, QC, Canada
| | - V. Shinde
- GSK, King of Prussia, PA, USA
- Present address: Novavax Vaccines, Washington, DC, USA
| | - D. Smyth
- The Moncton Hospital, Moncton, NB, Canada
| | - S. Trottier
- Centre Hospitalier Universitaire de Québec, QC, Canada
| | | | | | - L. Ye
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre, and Nova Scotia Health Authority, Halifax, NS, Canada
| | - S. A. McNeil
- Ottawa Hospital Research Institute, University of Ottawa, Ottawa, ON, Canada
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20
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Christiansen CF, Thomsen RW, Schmidt M, Pedersen L, Sørensen HT. Influenza vaccination and 1-year risk of myocardial infarction, stroke, heart failure, pneumonia, and mortality among intensive care unit survivors aged 65 years or older: a nationwide population-based cohort study. Intensive Care Med 2019; 45:957-967. [PMID: 31187170 DOI: 10.1007/s00134-019-05648-4] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Accepted: 05/13/2019] [Indexed: 10/26/2022]
Abstract
PURPOSE We examined whether influenza vaccination affects 1-year risk of myocardial infarction, stroke, heart failure, pneumonia, and death among intensive care unit (ICU) survivors aged ≥ 65 years. METHODS Danish Intensive Care Database data on all elderly ( ≥ 65 years) patients hospitalized in Danish ICUs in the period 2005-2015, and subsequently discharged, were linked with data from other medical registries, including data on uptake of the seasonal influenza vaccine. We computed these patients' 1-year risk of hospitalization for myocardial infarction, stroke, heart failure, or pneumonia, and their 1-year risk of all-cause mortality. Hazard ratios (HRs) with 95% confidence intervals (CIs) were computed using Cox proportional hazards regression, with adjustment and propensity score matching applied to handle confounding. RESULTS The study included 89,818 ICU survivors. The influenza vaccinated patients (n = 34,871, 39%) were older, had more chronic diseases, and used more prescription medications than the unvaccinated patients. Adjusted 1-year mortality was decreased among the vaccinated versus the unvaccinated patients (19.3% versus 18.8%; adjusted HR, 0.92; 95% CI 0.89-0.95). Influenza vaccination was also associated with a decreased risk of stroke (adjusted HR, 0.84; 95% CI 0.78-0.92), but only a small, non-significantly decreased risk of myocardial infarction (adjusted HR, 0.93; 95% CI 0.83-1.03). There was no association between vaccination and subsequent hospitalization for heart failure or pneumonia. Propensity score matched analyses confirmed these findings. CONCLUSIONS Compared with the unvaccinated ICU survivors, the influenza vaccinated ICU survivors had a lower 1-year risk of stroke and a lower 1-year risk of death, whereas no substantial association was observed for the risk of hospitalization for myocardial infarction, heart failure, or pneumonia. Our findings support influenza vaccination of individuals aged ≥ 65 years.
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Affiliation(s)
- Christian Fynbo Christiansen
- Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus N, Denmark.
| | - Reimar Wernich Thomsen
- Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus N, Denmark
| | - Morten Schmidt
- Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus N, Denmark.,Department of Cardiology, Regional Hospital West Jutland, Herning, Denmark
| | - Lars Pedersen
- Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus N, Denmark
| | - Henrik Toft Sørensen
- Department of Clinical Epidemiology, Aarhus University Hospital, Olof Palmes Alle 43-45, 8200, Aarhus N, Denmark.,Department of Health Research and Policy (Epidemiology), Stanford University, Stanford, CA, USA
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