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Maurel M, Mazagatos C, Goerlitz L, Oroszi B, Hooiveld M, Machado A, Domegan L, Ilić M, Popescu R, Sève N, Martínez-Baz I, Larrauri A, Buda S, Túri G, Meijer A, Gomez V, O'Donnell J, Mlinarić I, Timnea O, Diez AO, Dürrwald R, Horváth JK, Dijkstra F, Rodrigues AP, McKenna A, Filipović SK, Lazar M, Kaczmarek M, Bacci S, Kissling E. Exploring the effect of clinical case definitions on influenza vaccine effectiveness estimation at primary care level: Results from the end-of-season 2022-23 VEBIS multicentre study in Europe. Vaccine 2024; 42:3547-3554. [PMID: 38704257 PMCID: PMC11152456 DOI: 10.1016/j.vaccine.2024.04.060] [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: 12/05/2023] [Revised: 04/03/2024] [Accepted: 04/21/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Within influenza vaccine effectiveness (VE) studies at primary care level with a laboratory-confirmed outcome, clinical case definitions for recruitment of patients can vary. We used the 2022-23 VEBIS primary care European multicentre study end-of-season data to evaluate whether the clinical case definition affected IVE estimates. METHODS We estimated VE using a multicentre test-negative case-control design. We measured VE against any influenza and influenza (sub)types, by age group (0-14, 15-64, ≥65 years) and by influenza vaccine target group, using logistic regression. We estimated IVE among patients meeting the European Union (EU) acute respiratory infection (ARI) case definition and among those meeting the EU influenza-like illness (ILI) case definition, including only sites providing information on specific symptoms and recruiting patients using an ARI case definition (as the EU ILI case definition is a subset of the EU ARI one). RESULTS We included 24 319 patients meeting the EU ARI case definition, of whom 21 804 patients (90 %) meet the EU ILI case definition, for the overall pooled VE analysis against any influenza. The overall and influenza (sub)type-specific VE varied by ≤2 % between EU ILI and EU ARI populations. DISCUSSION Among all analyses, we found similar VE estimates between the EU ILI and EU ARI populations, with few (10%) additional non-ILI ARI patients recruited. These results indicate that VE in the 2022-23 influenza season was not affected by use of a different clinical case definition for recruitment, although we recommend investigating whether this holds true for next seasons.
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Affiliation(s)
| | - Clara Mazagatos
- National Centre of Epidemiology, CIBERESP, Carlos III Health Institute, Madrid, Spain
| | - Luise Goerlitz
- Department for Infectious Disease Epidemiology, Respiratory Infections Unit, Robert Koch Institute, Berlin, Germany
| | - Beatrix Oroszi
- National Laboratory for Health Security, Epidemiology and Surveillance Centre, Semmelweis University, Budapest, Hungary
| | | | - Ausenda Machado
- Instituto Nacional de Saúde Dr. Ricardo Jorge, Lisbon, Portugal
| | - Lisa Domegan
- HSE-Health Protection Surveillance Centre, Dublin, Ireland
| | - Maja Ilić
- Croatian Institute of Public Health, Zagreb, Croatia
| | | | - Noémie Sève
- Sorbonne Université, INSERM, Institut Pierre Louis d'épidémiologie et de Santé Publique (IPLESP UMRS 1136), Paris, France
| | | | - Amparo Larrauri
- National Centre of Epidemiology, CIBERESP, Carlos III Health Institute, Madrid, Spain
| | - Silke Buda
- Department for Infectious Disease Epidemiology, Respiratory Infections Unit, Robert Koch Institute, Berlin, Germany
| | - Gergő Túri
- National Laboratory for Health Security, Epidemiology and Surveillance Centre, Semmelweis University, Budapest, Hungary
| | - Adam Meijer
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | - Verónica Gomez
- Instituto Nacional de Saúde Dr. Ricardo Jorge, Lisbon, Portugal
| | - Joan O'Donnell
- HSE-Health Protection Surveillance Centre, Dublin, Ireland
| | - Ivan Mlinarić
- Croatian Institute of Public Health, Zagreb, Croatia
| | - Olivia Timnea
- "Cantacuzino" National Military Medical Institute for Research and Development, Bucharest, Romania
| | - Ana Ordax Diez
- Instituto de Estudios de Ciencias de la Salud de Castilla y León (IECSCYL). Consejería de Sanidad. Junta de Castilla y León, Valladolid, Spain
| | - Ralf Dürrwald
- National Reference Centre for Influenza, Robert Koch Institute, Berlin, Germany
| | - Judit Krisztina Horváth
- National Laboratory for Health Security, Epidemiology and Surveillance Centre, Semmelweis University, Budapest, Hungary
| | - Frederika Dijkstra
- National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | | | - Adele McKenna
- HSE-Health Protection Surveillance Centre, Dublin, Ireland
| | | | - Mihaela Lazar
- "Cantacuzino" National Military Medical Institute for Research and Development, Bucharest, Romania
| | - Marlena Kaczmarek
- European Centre for Disease Prevention and Control, Stockholm, Sweden
| | - Sabrina Bacci
- European Centre for Disease Prevention and Control, Stockholm, Sweden
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Anoma S, Bhattarakosol P, Kowitdamrong E. Characteristics and evolution of hemagglutinin and neuraminidase genes of Influenza A(H3N2) viruses in Thailand during 2015 to 2018. PeerJ 2024; 12:e17523. [PMID: 38846750 PMCID: PMC11155671 DOI: 10.7717/peerj.17523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/16/2024] [Indexed: 06/09/2024] Open
Abstract
Background Influenza A(H3N2) virus evolves continuously. Its hemagglutinin (HA) and neuraminidase (NA) genes have high genetic variation due to the antigenic drift. This study aimed to investigate the characteristics and evolution of HA and NA genes of the influenza A(H3N2) virus in Thailand. Methods Influenza A positive respiratory samples from 2015 to 2018 were subtyped by multiplex real-time RT-PCR. Full-length HA and NA genes from the positive samples of influenza A(H3N2) were amplified and sequenced. Phylogenetic analysis with the maximum likelihood method was used to investigate the evolution of the virus compared with the WHO-recommended influenza vaccine strain. Homology modeling and N-glycosylation site prediction were also performed. Results Out of 443 samples, 147 (33.18%) were A(H1N1)pdm09 and 296 (66.82%) were A(H3N2). The A(H3N2) viruses circulating in 2015 were clade 3C.2a whereas sub-clade 3C.2a1 and 3C.2a2 dominated in 2016-2017 and 2018, respectively. Amino acid substitutions were found in all antigenic sites A, B, C, D, and E of HA but the majority of the substitutions were located at antigenic sites A and B. The S245N and N329S substitutions in the NA gene affect the N-glycosylation. None of the mutations associated with resistance to NA inhibitors were observed. Mean evolutionary rates of the HA and NA genes were 3.47 × 10 -3 and 2.98 × 10-3 substitutions per site per year. Conclusion The influenza A(H3N2) virus is very genetically diverse and is always evolving to evade host defenses. The HA and NA gene features including the evolutionary rate of the influenza A(H3N2) viruses that were circulating in Thailand between 2015 and 2018 are described. This information is useful for monitoring the genetic characteristics and evolution in HA and NA genes of influenza A(H3N2) virus in Thailand which is crucial for predicting the influenza vaccine strains resulting in high vaccine effectiveness.
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Affiliation(s)
- Sasiprapa Anoma
- Interdisciplinary Program in Medical Microbiology, Graduated School, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Applied Medical Virology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Parvapan Bhattarakosol
- Center of Excellence in Applied Medical Virology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Division of Virology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Ekasit Kowitdamrong
- Center of Excellence in Applied Medical Virology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Division of Virology, Department of Microbiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
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Perofsky AC, Huddleston J, Hansen C, Barnes JR, Rowe T, Xu X, Kondor R, Wentworth DE, Lewis N, Whittaker L, Ermetal B, Harvey R, Galiano M, Daniels RS, McCauley JW, Fujisaki S, Nakamura K, Kishida N, Watanabe S, Hasegawa H, Sullivan SG, Barr IG, Subbarao K, Krammer F, Bedford T, Viboud C. Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.02.23296453. [PMID: 37873362 PMCID: PMC10593063 DOI: 10.1101/2023.10.02.23296453] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.
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Affiliation(s)
- Amanda C Perofsky
- Fogarty International Center, National Institutes of Health, United States
- Brotman Baty Institute for Precision Medicine, University of Washington, United States
| | - John Huddleston
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, United States
| | - Chelsea Hansen
- Fogarty International Center, National Institutes of Health, United States
- Brotman Baty Institute for Precision Medicine, University of Washington, United States
| | - John R Barnes
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Thomas Rowe
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Xiyan Xu
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Rebecca Kondor
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - David E Wentworth
- Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), United States
| | - Nicola Lewis
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Lynne Whittaker
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Burcu Ermetal
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Ruth Harvey
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Monica Galiano
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Rodney Stuart Daniels
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - John W McCauley
- WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute, United Kingdom
| | - Seiichiro Fujisaki
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Kazuya Nakamura
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Noriko Kishida
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Shinji Watanabe
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Hideki Hasegawa
- Influenza Virus Research Center, National Institute of Infectious Diseases, Japan
| | - Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Australia
| | - Ian G Barr
- WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Australia
| | - Kanta Subbarao
- WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity, Australia
| | - Florian Krammer
- Center for Vaccine Research and Pandemic Preparedness (C-VaRPP), Icahn School of Medicine at Mount Sinai, United States
- Department of Pathology, Molecular and Cell-Based Medicine, Icahn School of Medicine at Mount Sinai, United States
| | - Trevor Bedford
- Brotman Baty Institute for Precision Medicine, University of Washington, United States
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, United States
- Department of Genome Sciences, University of Washington, United States
- Howard Hughes Medical Institute, Seattle, United States
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, United States
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Yang T, Tang L, Li P, Li B, Ye L, Zhou J. Effectiveness of inactivated influenza vaccine against laboratory-confirmed influenza among Chinese elderly: a test-negative design. BMC Geriatr 2024; 24:404. [PMID: 38714944 PMCID: PMC11077745 DOI: 10.1186/s12877-024-05003-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 04/22/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Evidence on the effectiveness of influenza vaccination in the elderly is limited, and results are controversial. There are also few reports from China. METHODS We conducted a test-negative case-control study design to estimate influenza vaccine effectiveness (VE) against laboratory-confirmed influenza-associated visits among elderly (aged ≥ 60 years) across four influenza seasons in Ningbo, China, from 2018 to 19 to 2021-22. Influenza-positive cases and negative controls were randomly matched in a 1:1 ratio according to age, sex, hospital, and date of influenza testing. We used logistic regression models to compare vaccination odds ratios (ORs) in cases to controls. We calculated the VE as [100% × (1-adjusted OR)] and calculated the 95% confidence interval (CI) around the estimate. RESULTS A total of 30,630 elderly patients tested for influenza with virus nucleic acid or antigen during the study period. After exclusions, we included 1 825 influenza-positive cases and 1 825 influenza-negative controls. Overall, the adjusted VE for influenza-related visits was 63.5% (95% CI, 56.3-69.5%), but varied by season. Influenza VE was 59.8% (95% CI, 51.5-66.7%) for influenza A and 89.6% (95% CI, 77.1-95.3%) for influenza B. The VE for ages 60-69 and 70-79 was 65.2% (95% CI, 55.4-72.9%) and 69.8% (95% CI, 58.7-77.9%), respectively, but only 45.4% (95% CI, 6.2-68.2%) for ages 80 and over. CONCLUSIONS Standard-dose inactivated influenza vaccine has shown good protection in the elderly in China. However, protection may not be satisfactory in people aged 80 years and older.
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Affiliation(s)
- Tianchi Yang
- Institute of Immunization and Prevention, Ningbo Municipal Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Ling Tang
- Ningbo Health Information Center, Ningbo, Zhejiang, China
| | - Pingping Li
- Jiangbei District Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Baojun Li
- Haishu District Center for Disease Control and Prevention, Ningbo, Zhejiang, China
| | - Lixia Ye
- Institute of Immunization and Prevention, Ningbo Municipal Center for Disease Control and Prevention, Ningbo, Zhejiang, China.
| | - Jifang Zhou
- School of International Pharmaceutical Business, China Pharmaceutical University, Jiangsu, China.
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Youhanna J, Tran V, Hyer R, Domnich A. Immunogenicity of Enhanced Influenza Vaccines Against Mismatched Influenza Strains in Older Adults: A Review of Randomized Controlled Trials. Influenza Other Respir Viruses 2024; 18:e13286. [PMID: 38594827 PMCID: PMC11004266 DOI: 10.1111/irv.13286] [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: 10/23/2023] [Revised: 03/15/2024] [Accepted: 03/18/2024] [Indexed: 04/11/2024] Open
Abstract
Antigenic drift is a major driver of viral evolution and a primary reason why influenza vaccines must be reformulated annually. Mismatch between vaccine and circulating viral strains negatively affects vaccine effectiveness and often contributes to higher rates of influenza-related hospitalizations and deaths, particularly in years dominated by A(H3N2). Several countries recommend enhanced influenza vaccines for older adults, who are at the highest risk of severe influenza complications and mortality. The immunogenicity of enhanced vaccines against heterologous A(H3N2) strains has been examined in nine studies to date. In six studies, an enhanced, licensed MF59-adjuvanted trivalent inactivated influenza vaccine (aIIV3) consistently increased heterologous antibody titers relative to standard influenza vaccine, with evidence of a broad heterologous immune response across multiple genetic clades. In one study, licensed high-dose trivalent inactivated influenza vaccine (HD-IIV3) also induced higher heterologous antibody titers than standard influenza vaccine. In a study comparing a higher dose licensed quadrivalent recombinant influenza vaccine (RIV4) with HD-IIV3 and aIIV3, no significant differences in antibody titers against a heterologous strain were observed, although seroconversion rates were higher with RIV4 versus comparators. With the unmet medical need for improved influenza vaccines, the paucity of studies especially with enhanced vaccines covering mismatched strains highlights a need for further investigation of cross-protection in older adults.
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Affiliation(s)
| | - Vy Tran
- CSL Seqirus LtdSummitNew JerseyUSA
| | - Randall Hyer
- Baruch S. Blumberg InstituteDoylestownPennsylvaniaUSA
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Liu F, Gross FL, Joshi S, Gaglani M, Naleway AL, Murthy K, Groom HC, Wesley MG, Edwards LJ, Grant L, Kim SS, Sambhara S, Gangappa S, Tumpey T, Thompson MG, Fry AM, Flannery B, Dawood FS, Levine MZ. Redirecting antibody responses from egg-adapted epitopes following repeat vaccination with recombinant or cell culture-based versus egg-based influenza vaccines. Nat Commun 2024; 15:254. [PMID: 38177116 PMCID: PMC10767121 DOI: 10.1038/s41467-023-44551-x] [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: 04/25/2023] [Accepted: 12/19/2023] [Indexed: 01/06/2024] Open
Abstract
Repeat vaccination with egg-based influenza vaccines could preferentially boost antibodies targeting the egg-adapted epitopes and reduce immunogenicity to circulating viruses. In this randomized trial (Clinicaltrials.gov: NCT03722589), sera pre- and post-vaccination with quadrivalent inactivated egg-based (IIV4), cell culture-based (ccIIV4), and recombinant (RIV4) influenza vaccines were collected from healthcare personnel (18-64 years) in 2018-19 (N = 723) and 2019-20 (N = 684) influenza seasons. We performed an exploratory analysis. Vaccine egg-adapted changes had the most impact on A(H3N2) immunogenicity. In year 1, RIV4 induced higher neutralizing and total HA head binding antibodies to cell- A(H3N2) virus than ccIIV4 and IIV4. In year 2, among the 7 repeat vaccination arms (IIV4-IIV4, IIV4-ccIIV4, IIV4-RIV4, RIV4-ccIIV4, RIV4-RIV4, ccIIV4-ccIIV4 and ccIIV4-RIV4), repeat vaccination with either RIV4 or ccIIV4 further improved antibody responses to circulating viruses with decreased neutralizing antibody egg/cell ratio. RIV4 also had higher post-vaccination A(H1N1)pdm09 and A(H3N2) HA stalk antibodies in year 1, but there was no significant difference in HA stalk antibody fold rise among vaccine groups in either year 1 or year 2. Multiple seasons of non-egg-based vaccination may be needed to redirect antibody responses from immune memory to egg-adapted epitopes and re-focus the immune responses towards epitopes on the circulating viruses to improve vaccine effectiveness.
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Affiliation(s)
- Feng Liu
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - F Liaini Gross
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sneha Joshi
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Temple, TX, USA
- Baylor College of Medicine, Temple, TX, USA
- Texas A & M University, College of Medicine, Temple, TX, USA
| | - Allison L Naleway
- Kaiser Permanente Northwest Center for Health Research, Portland, OR, USA
| | | | - Holly C Groom
- Kaiser Permanente Northwest Center for Health Research, Portland, OR, USA
| | - Meredith G Wesley
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Abt Associates, Atlanta, GA, USA
| | | | - Lauren Grant
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sara S Kim
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | - Terrence Tumpey
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Mark G Thompson
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Alicia M Fry
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Fatimah S Dawood
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Min Z Levine
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
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de Waure C, Gärtner BC, Lopalco PL, Puig-Barbera J, Nguyen-Van-Tam JS. Real world evidence for public health decision-making on vaccination policies: perspectives from an expert roundtable. Expert Rev Vaccines 2024; 23:27-38. [PMID: 38084895 DOI: 10.1080/14760584.2023.2290194] [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: 11/04/2023] [Accepted: 11/28/2023] [Indexed: 12/18/2023]
Abstract
INTRODUCTION Influenza causes significant morbidity and mortality, but influenza vaccine uptake remains below most countries' targets. Vaccine policy recommendations vary, as do procedures for reviewing and appraising the evidence. AREAS COVERED During a series of roundtable discussions, we reviewed procedures and methodologies used by health ministries in four European countries to inform vaccine recommendations. We review the type of evidence currently recommended by each health ministry and the range of approaches toward considering randomized controlled trials (RCTs) and real-world evidence (RWE) studies when setting influenza vaccine recommendations. EXPERT OPINION Influenza vaccine recommendations should be based on data from both RCTs and RWE studies of efficacy, effectiveness, and safety. Such data should be considered alongside health-economic, cost-effectiveness, and budgetary factors. Although RCT data are more robust and less prone to bias, well-designed RWE studies permit timely evaluation of vaccine benefits, effectiveness comparisons over multiple seasons in large populations, and detection of rare adverse events, under real-world conditions. Given the variability of vaccine effectiveness due to influenza virus mutations and increasing diversification of influenza vaccines, we argue that consideration of both RWE and RCT evidence is the best approach to more nuanced and timely updates of influenza vaccine recommendations.
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Affiliation(s)
- Chiara de Waure
- Public Health, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Barbara C Gärtner
- Department and Institute of Microbiology, Saarland University Hospital, Homburg, Germany
| | | | - Joan Puig-Barbera
- Foundation for the Promotion of Health and Biomedical Research of the Valencian Region, Valencia, Spain
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Frivold C, McCulloch DJ, Ekici S, Martin ET, Jackson ML, Chu HY. Acute respiratory infections among individuals seeking outpatient care in the states of Washington and Michigan by pregnancy status, 2011-2016. Influenza Other Respir Viruses 2023; 17:e13230. [PMID: 38076500 PMCID: PMC10700156 DOI: 10.1111/irv.13230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Revised: 11/04/2023] [Accepted: 11/11/2023] [Indexed: 12/18/2023] Open
Abstract
Background Acute respiratory infections (ARIs) during pregnancy are associated with poor maternal and fetal outcomes. Methods Using U.S. Flu Vaccine Effectiveness Network data (2011-2016) from Washington and Michigan, we tested for respiratory viruses among pregnant and non-pregnant outpatients matched on age, site, and season (n = 191). Results Among all participants, detection of human coronaviruses and rhinovirus was common. We also observed differences in virus detection by pregnancy status; human coronaviruses and respiratory syncytial virus (RSV) were detected more frequently among pregnant and non-pregnant participants, respectively. Conclusions The role of respiratory viruses in maternal ARI morbidity should be further characterized to inform implementation of prevention interventions including maternal vaccines.
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Affiliation(s)
- Collrane Frivold
- Department of MedicineUniversity of WashingtonSeattleWashingtionUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtionUSA
| | | | - Seda Ekici
- Department of PediatricsUniversity of WashingtonSeattleWashingtionUSA
| | - Emily T. Martin
- Department of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | | | - Helen Y. Chu
- Department of MedicineUniversity of WashingtonSeattleWashingtionUSA
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Chaves SS, Naeger S, Lounaci K, Zuo Y, Loiacono MM, Pilard Q, Nealon J, Genin M, Mahe C. High-Dose Influenza Vaccine Is Associated With Reduced Mortality Among Older Adults With Breakthrough Influenza Even When There Is Poor Vaccine-Strain Match. Clin Infect Dis 2023; 77:1032-1042. [PMID: 37247308 PMCID: PMC10552589 DOI: 10.1093/cid/ciad322] [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: 09/09/2022] [Revised: 05/09/2023] [Accepted: 05/24/2023] [Indexed: 05/31/2023] Open
Abstract
BACKGROUND High-dose (HD) influenza vaccine offers improved protection from influenza virus infection among older adults compared with standard-dose (SD) vaccine. Here, we explored whether HD vaccine attenuates disease severity among older adults with breakthrough influenza. METHODS This was a retrospective cohort study of US claims data for influenza seasons 2016-2017, 2017-2018, and 2018-2019, defined as 1 October through 30 April, among adults aged ≥65 years. After adjusting the different cohorts for the probability of vaccination conditional on patients' characteristics, we compared 30-day mortality rate post-influenza among older adults who experienced breakthrough infection after receipt of HD or SD influenza vaccines and among those not vaccinated (NV). RESULTS We evaluated 44 456 influenza cases: 23 109 (52%) were unvaccinated, 15 037 (33.8%) received HD vaccine, and 6310 (14.2%) received SD vaccine. Significant reductions in mortality rates among breakthrough cases were observed across all 3 seasons for HD vs NV, ranging from 17% to 29% reductions. A significant mortality reduction of 25% was associated with SD vaccination vs NV in the 2016-2017 season when there was a good match between circulating influenza viruses and selected vaccine strains. When comparing HD vs SD cohorts, mortality reductions were higher among those who received HD in the last 2 seasons when mismatch between vaccine strains and circulating H3N2 viruses was documented, albeit not significant. CONCLUSIONS HD vaccination was associated with lower post-influenza mortality among older adults with breakthrough influenza, even during seasons when antigenically drifted H3N2 circulated. Improved understanding of the impact of different vaccines on attenuating disease severity is warranted when assessing vaccine policy recommendations.
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Affiliation(s)
- Sandra S Chaves
- Modelling, Epidemiology and Data Science, Sanofi Vaccines, Lyon, France
| | - Sarah Naeger
- Modelling, Epidemiology and Data Science, Sanofi Vaccines, Lyon, France
| | | | - Yue Zuo
- Quinten Health, Lyon, France
| | | | | | - Joshua Nealon
- School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Pok Fu Lam, Hong Kong Special Administrative Region of China
| | | | - Cedric Mahe
- Modelling, Epidemiology and Data Science, Sanofi Vaccines, Lyon, France
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10
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Martins JP, Santos M, Martins A, Felgueiras M, Santos R. Seasonal Influenza Vaccine Effectiveness in Persons Aged 15-64 Years: A Systematic Review and Meta-Analysis. Vaccines (Basel) 2023; 11:1322. [PMID: 37631889 PMCID: PMC10459161 DOI: 10.3390/vaccines11081322] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/25/2023] [Accepted: 07/25/2023] [Indexed: 08/27/2023] Open
Abstract
Influenza is a respiratory disease caused by the influenza virus, which is highly transmissible in humans. This paper presents a systematic review and meta-analysis of randomized controlled trials (RCTs) and test-negative designs (TNDs) to assess the vaccine effectiveness (VE) of seasonal influenza vaccines (SIVs) in humans aged 15 to 64 years. An electronic search to identify all relevant studies was performed. The outcome measure of interest was VE on laboratory-confirmed influenza (any strain). Quality assessment was performed using the Cochrane risk-of-bias tool for RCTs and the ROBINS-I tool for TNDs. The search identified a total of 2993 records, but only 123 studies from 73 papers were included in the meta-analysis. Of these studies, 9 were RCTs and 116 were TNDs. The pooled VE was 48% (95% CI: 42-54) for RCTs, 55.4% (95% CI: 43.2-64.9) when there was a match between the vaccine and most prevalent circulating strains and 39.3% (95% CI: 23.5-51.9) otherwise. The TNDs' adjusted VE was equal to 39.9% (95% CI: 31-48), 45.1 (95% CI: 38.7-50.8) when there was a match and 35.1 (95% CI: 29.0-40.7) otherwise. The match between strains included in the vaccine and strains in circulation is the most important factor in the VE. It increases by more than 25% when there is a match with the most prevalent circulating strains. The laboratorial method for confirmation of influenza is a possible source of bias when estimating VE.
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Affiliation(s)
- João Paulo Martins
- Escola Superior de Saúde, Instituto Politécnico do Porto, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal;
- CEAUL—Centro de Estatística e Aplicações, Faculdade de Ciências, Campo Grande, Universidade de Lisboa, 1749-016 Lisboa, Portugal; (M.F.); (R.S.)
| | - Marlene Santos
- Escola Superior de Saúde, Instituto Politécnico do Porto, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal;
- Centro de Investigação em Saúde e Ambiente, Instituto Politécnico do Porto, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal;
| | - André Martins
- Centro de Investigação em Saúde e Ambiente, Instituto Politécnico do Porto, Rua Dr. António Bernardino de Almeida, 4200-072 Porto, Portugal;
| | - Miguel Felgueiras
- CEAUL—Centro de Estatística e Aplicações, Faculdade de Ciências, Campo Grande, Universidade de Lisboa, 1749-016 Lisboa, Portugal; (M.F.); (R.S.)
- Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Leiria, Campus 2, Morro do Lena—Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal
| | - Rui Santos
- CEAUL—Centro de Estatística e Aplicações, Faculdade de Ciências, Campo Grande, Universidade de Lisboa, 1749-016 Lisboa, Portugal; (M.F.); (R.S.)
- Escola Superior de Tecnologia e Gestão, Instituto Politécnico de Leiria, Campus 2, Morro do Lena—Alto do Vieiro, Apartado 4163, 2411-901 Leiria, Portugal
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11
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Kim DeLuca E, Gebremariam A, Rose A, Biggerstaff M, Meltzer MI, Prosser LA. Cost-effectiveness of routine annual influenza vaccination by age and risk status. Vaccine 2023:S0264-410X(23)00495-4. [PMID: 37291022 DOI: 10.1016/j.vaccine.2023.04.069] [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: 01/27/2023] [Revised: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 06/10/2023]
Abstract
BACKGROUND The epidemiology of circulating seasonal influenza strains changed following the 2009 pandemic influenza A(H1N1). A universal influenza vaccination recommendation has been implemented and new vaccine types have become available post-2009. The objective of this study was to evaluate the cost-effectiveness of routine annual influenza vaccination in the context of this new evidence. METHODS A state transition simulation model was constructed to estimate the health and economic outcomes of influenza vaccination compared to no vaccination for hypothetical US cohorts stratified by age and risk status. Model input parameters were derived from multiple sources, including post-2009 vaccine effectiveness data from the US Flu Vaccine Effectiveness Network. The analysis used societal and healthcare sector perspectives and a one-year time horizon, except permanent outcomes were also included. The primary outcome was the incremental cost-effectiveness ratio (ICER) in dollars per quality-adjusted life years (QALYs) gained. RESULTS Compared to no vaccination, vaccination yielded ICERs lower than $95,000/QALY for all age and risk groups, except for non-high-risk adults 18-49 years ($194,000/QALY). Vaccination was cost-saving for adults ≥50 years at higher risk for influenza-related complications. Results were most sensitive to changes in the probability of influenza illness. Performing the analysis from the healthcare sector perspective, excluding vaccination time costs, delivering vaccinations in lower-cost settings, and including productivity losses improved the cost-effectiveness of vaccination. Sensitivity analysis revealed that vaccination remains below $100,000/QALY for older persons ≥65 years at vaccine effectiveness estimates as low as 4 %. CONCLUSIONS Cost-effectiveness of influenza vaccination varied by age and risk status and was less than $95,000/QALY for all subgroups, except for non-high-risk working-age adults. Results were sensitive to the probability of influenza illness and vaccination was more favorable under certain scenarios. Vaccination for higher risk subgroups resulted in ICERs below $100,000/QALY even at low levels of vaccine effectiveness or circulating virus.
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Affiliation(s)
- Ellen Kim DeLuca
- Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor, MI, United States; Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Acham Gebremariam
- Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Angela Rose
- Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Matthew Biggerstaff
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Martin I Meltzer
- Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Lisa A Prosser
- Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor, MI, United States; Susan B. Meister Child Health Evaluation and Research Center, Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, United States.
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12
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Hood N, Flannery B, Gaglani M, Beeram M, Wernli K, Jackson ML, Martin ET, Monto AS, Zimmerman R, Raviotta J, Belongia EA, McLean HQ, Kim S, Patel MM, Chung JR. Influenza Vaccine Effectiveness Among Children: 2011-2020. Pediatrics 2023; 151:e2022059922. [PMID: 36960655 PMCID: PMC10071433 DOI: 10.1542/peds.2022-059922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/04/2023] [Indexed: 03/25/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Infants and children are at increased risk of severe influenza virus infection and its complications. Influenza vaccine effectiveness (VE) varies by age, influenza season, and influenza virus type/subtype. This study's objective was to examine the effectiveness of inactivated influenza vaccine against outpatient influenza illness in the pediatric population over 9 influenza seasons after the 2009 A(H1N1) pandemic. METHODS During the 2011-2012 through the 2019-2020 influenza seasons at outpatient clinics at 5 sites of the US Influenza Vaccine Effectiveness Network, children aged 6 months to 17 years with an acute respiratory illness were tested for influenza using real-time, reverse-transcriptase polymerase chain reaction. Vaccine effectiveness was estimated using a test-negative design. RESULTS Among 24 148 enrolled children, 28% overall tested positive for influenza, 3017 tested positive for influenza A(H3N2), 1459 for influenza A(H1N1)pdm09, and 2178 for influenza B. Among all enrollees, 39% overall were vaccinated, with 29% of influenza cases and 43% of influenza-negative controls vaccinated. Across all influenza seasons, the pooled VE for any influenza was 46% (95% confidence interval, 43-50). Overall and by type/subtype, VE against influenza illness was highest among children in the 6- to 59-month age group compared with older pediatric age groups. VE was lowest for influenza A(H3N2) virus infection. CONCLUSIONS Analysis of multiple seasons suggested substantial benefit against outpatient illness. Investigation of host-specific or virus-related mechanisms that may result in differences by age and virus type/subtype may help further efforts to promote increased vaccination coverage and other influenza-related preventative measures.
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Affiliation(s)
- Nicole Hood
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Brendan Flannery
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Manjusha Gaglani
- Texas A&M University Health Science Center College of Medicine, Temple, Texas
- Baylor Scott & White Health Research Institute, Temple, Texas
| | - Madhava Beeram
- Texas A&M University Health Science Center College of Medicine, Temple, Texas
- Baylor Scott & White Health Research Institute, Temple, Texas
| | - Karen Wernli
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Michael L. Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Emily T. Martin
- School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Arnold S. Monto
- School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Richard Zimmerman
- School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jonathan Raviotta
- School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | | | | | - Sara Kim
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Manish M. Patel
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Jessie R. Chung
- Influenza Division, US Centers for Disease Control and Prevention, Atlanta, Georgia
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13
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Currenti J, Simmons J, Oakes J, Gaudieri S, Warren CM, Gangula R, Alves E, Ram R, Leary S, Armitage JD, Smith RM, Chopra A, Halasa NB, Pilkinton MA, Kalams SA. Tracking of activated cTfh cells following sequential influenza vaccinations reveals transcriptional profile of clonotypes driving a vaccine-induced immune response. Front Immunol 2023; 14:1133781. [PMID: 37063867 PMCID: PMC10095155 DOI: 10.3389/fimmu.2023.1133781] [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: 12/29/2022] [Accepted: 03/13/2023] [Indexed: 03/30/2023] Open
Abstract
Introduction A vaccine against influenza is available seasonally but is not 100% effective. A predictor of successful seroconversion in adults is an increase in activated circulating T follicular helper (cTfh) cells after vaccination. However, the impact of repeated annual vaccinations on long-term protection and seasonal vaccine efficacy remains unclear. Methods In this study, we examined the T cell receptor (TCR) repertoire and transcriptional profile of vaccine-induced expanded cTfh cells in individuals who received sequential seasonal influenza vaccines. We measured the magnitude of cTfh and plasmablast cell activation from day 0 (d0) to d7 post-vaccination as an indicator of a vaccine response. To assess TCR diversity and T cell expansion we sorted activated and resting cTfh cells at d0 and d7 post-vaccination and performed TCR sequencing. We also single cell sorted activated and resting cTfh cells for TCR analysis and transcriptome sequencing. Results and discussion The percent of activated cTfh cells significantly increased from d0 to d7 in each of the 2016-17 (p < 0.0001) and 2017-18 (p = 0.015) vaccine seasons with the magnitude of cTfh activation increase positively correlated with the frequency of circulating plasmablast cells in the 2016-17 (p = 0.0001) and 2017-18 (p = 0.003) seasons. At d7 post-vaccination, higher magnitudes of cTfh activation were associated with increased clonality of cTfh TCR repertoire. The TCRs from vaccine-expanded clonotypes were identified and tracked longitudinally with several TCRs found to be present in both years. The transcriptomic profile of these expanded cTfh cells at the single cell level demonstrated overrepresentation of transcripts of genes involved in the type-I interferon pathway, pathways involved in gene expression, and antigen presentation and recognition. These results identify the expansion and transcriptomic profile of vaccine-induced cTfh cells important for B cell help.
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Affiliation(s)
- Jennifer Currenti
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Joshua Simmons
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jared Oakes
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Silvana Gaudieri
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Christian M. Warren
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Rama Gangula
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Eric Alves
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Ramesh Ram
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Shay Leary
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Jesse D. Armitage
- Telethon Kids Institute, University of Western Australia, Nedlands, WA, Australia
| | - Rita M. Smith
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Abha Chopra
- Institute for Immunology and Infectious Diseases, Murdoch University, Murdoch, WA, Australia
| | - Natasha B. Halasa
- Division of Pediatric Infectious Diseases, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Mark A. Pilkinton
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Spyros A. Kalams
- Division of Infectious Diseases, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, United States
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14
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Li KQ, Shi X, Miao W, Tchetgen ET. Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness. ARXIV 2023:arXiv:2203.12509v4. [PMID: 35350548 PMCID: PMC8963685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Revised: 07/07/2022] [Indexed: 10/26/2022]
Abstract
The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness against the risk of acquiring infectious diseases in real-world settings, such as Influenza, Rotavirus, Dengue fever, and more recently COVID-19. In a TND study, individuals who experience symptoms and seek care are recruited and tested for the infectious disease which defines cases and controls. Despite TND's potential to reduce unobserved differences in healthcare seeking behavior (HSB) between vaccinated and unvaccinated subjects, it remains subject to various potential biases. First, residual confounding bias may remain due to unobserved HSB, occupation as healthcare worker, or previous infection history. Second, because selection into the TND sample is a common consequence of infection and HSB, collider stratification bias may exist when conditioning the analysis on testing, which further induces confounding by latent HSB. In this paper, we present a novel approach to identify and estimate vaccine effectiveness in the target population by carefully leveraging a pair of negative control exposure and outcome variables to account for potential hidden bias in TND studies. We illustrate our proposed method with extensive simulation and an application to study COVID-19 vaccine effectiveness using data from the University of Michigan Health System.
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Affiliation(s)
| | - Xu Shi
- Department of Biostatistics, University of Michigan
| | - Wang Miao
- Department of Probability and Statistics, Peking University
| | - Eric Tchetgen Tchetgen
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania
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15
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Sahni LC, Naioti EA, Olson SM, Campbell AP, Michaels MG, Williams JV, Staat MA, Schlaudecker EP, McNeal MM, Halasa NB, Stewart LS, Chappell JD, Englund JA, Klein EJ, Szilagyi PG, Weinberg GA, Harrison CJ, Selvarangan R, Schuster JE, Azimi PH, Singer MN, Avadhanula V, Piedra PA, Munoz FM, Patel MM, Boom JA. Sustained Within-season Vaccine Effectiveness Against Influenza-associated Hospitalization in Children: Evidence From the New Vaccine Surveillance Network, 2015-2016 Through 2019-2020. Clin Infect Dis 2023; 76:e1031-e1039. [PMID: 35867698 DOI: 10.1093/cid/ciac577] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 06/29/2022] [Accepted: 07/12/2022] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Adult studies have demonstrated within-season declines in influenza vaccine effectiveness (VE); data in children are limited. METHODS We conducted a prospective, test-negative study of children 6 months through 17 years hospitalized with acute respiratory illness at 7 pediatric medical centers during the 2015-2016 through 2019-2020 influenza seasons. Case-patients were children with an influenza-positive molecular test matched by illness onset to influenza-negative control-patients. We estimated VE [100% × (1 - odds ratio)] by comparing the odds of receipt of ≥1 dose of influenza vaccine ≥14 days before illness onset among influenza-positive children to influenza-negative children. Changes in VE over time between vaccination date and illness onset date were estimated using multivariable logistic regression. RESULTS Of 8430 children, 4653 (55%) received ≥1 dose of influenza vaccine. On average, 48% were vaccinated through October and 85% through December each season. Influenza vaccine receipt was lower in case-patients than control-patients (39% vs 57%, P < .001); overall VE against hospitalization was 53% (95% confidence interval [CI]: 46, 60%). Pooling data across 5 seasons, the odds of influenza-associated hospitalization increased 4.2% (-3.2%, 12.2%) per month since vaccination, with an average VE decrease of 1.9% per month (n = 4000, P = .275). Odds of hospitalization increased 2.9% (95% CI: -5.4%, 11.8%) and 9.6% (95% CI: -7.0%, 29.1%) per month in children ≤8 years (n = 3084) and 9-17 years (n = 916), respectively. These findings were not statistically significant. CONCLUSIONS We observed minimal, not statistically significant within-season declines in VE. Vaccination following current Advisory Committee on Immunization Practices (ACIP) guidelines for timing of vaccine receipt remains the best strategy for preventing influenza-associated hospitalizations in children.
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Affiliation(s)
- Leila C Sahni
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
| | - Eric A Naioti
- Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Samantha M Olson
- Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Angela P Campbell
- Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Marian G Michaels
- UPMC Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - John V Williams
- UPMC Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Mary Allen Staat
- Department of Pediatrics, Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center Cincinnati, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Elizabeth P Schlaudecker
- Department of Pediatrics, Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center Cincinnati, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Monica M McNeal
- Department of Pediatrics, Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center Cincinnati, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Natasha B Halasa
- Vanderbilit University Medical Center, Nashville, Tennessee, USA
| | - Laura S Stewart
- Vanderbilit University Medical Center, Nashville, Tennessee, USA
| | - James D Chappell
- Vanderbilit University Medical Center, Nashville, Tennessee, USA
| | | | | | - Peter G Szilagyi
- University of California Los Angeles (UCLA) Mattel Children's Hospital, Los Angeles, California, USA
| | - Geoffrey A Weinberg
- University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Christopher J Harrison
- University of Missouri-Kansas City School of Medicine, Children's Mercy, Kansas City, Missouri, USA
| | - Rangaraj Selvarangan
- University of Missouri-Kansas City School of Medicine, Children's Mercy, Kansas City, Missouri, USA
| | - Jennifer E Schuster
- University of Missouri-Kansas City School of Medicine, Children's Mercy, Kansas City, Missouri, USA
| | - Parvin H Azimi
- University of California San Francisco (UCSF) Benioff Children's Hospital Oakland, Oakland, California, USA
| | - Monica N Singer
- University of California San Francisco (UCSF) Benioff Children's Hospital Oakland, Oakland, California, USA
| | - Vasanthi Avadhanula
- Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
| | - Pedro A Piedra
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
| | - Flor M Munoz
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
- Molecular Virology and Microbiology, Baylor College of Medicine, Houston, Texas, USA
| | - Manish M Patel
- Influenza Division, National Center for Immunization and Respiratory Disease, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Julie A Boom
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
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16
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Regan AK, Arriola CS, Couto P, Duca L, Loayza S, Nogareda F, de Almeida WAF, Antman J, Araya S, Avendaño Vigueras MA, Battaglia Paredes SC, Brstilo IF, Bustos P, Fandiño ME, Fasce R, Giovacchini CM, González Caro CI, von Horoch M, Del Valle Juarez M, Katz N, Olivares MF, da Silva DA, da Silva ET, Sotomayor V, Vergara N, Azziz-Baumgartner E, Ropero AM. Severity of influenza illness by seasonal influenza vaccination status among hospitalised patients in four South American countries, 2013-19: a surveillance-based cohort study. THE LANCET. INFECTIOUS DISEASES 2023; 23:222-232. [PMID: 36206790 PMCID: PMC9876808 DOI: 10.1016/s1473-3099(22)00493-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 07/01/2022] [Accepted: 07/08/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Although several studies have reported attenuated influenza illness following influenza vaccination, results have been inconsistent and have focused predominantly on adults in the USA. This study aimed to evaluate the severity of influenza illness by vaccination status in a broad range of influenza vaccine target groups across multiple South American countries. METHODS We analysed data from four South American countries (Argentina, Brazil, Chile, and Paraguay) participating in REVELAC-i, a multicentre, test-negative design, vaccine effectiveness network including 41 sentinel hospitals. Individuals hospitalised at one of these centres with severe acute respiratory infection were tested for influenza by real-time RT-PCR, and were included in the analysis if they had complete information about their vaccination status and outcomes of their hospital stay. We used multivariable logistic regression weighted by inverse probability of vaccination and adjusted for antiviral use, duration of illness before admission, and calendar week, to calculate the adjusted odds ratios (aORs) of intensive care unit (ICU) admission and in-hospital death (and combinations of these outcomes) among influenza-positive patients by vaccination status for three target groups: young children (aged 6-24 months), adults (aged 18-64 years) with pre-existing health conditions, and older adults (aged ≥65 years). Survival curves were used to compare length of hospital stay by vaccination status in each target group. FINDINGS 2747 patients hospitalised with PCR-confirmed influenza virus infection between Jan 1, 2013, and Dec 8, 2019, were included in the study: 649 children (70 [10·8%] fully vaccinated, 193 [29·7%] partially vaccinated) of whom 87 (13·4%) were admitted to ICU and 12 (1·8%) died in hospital; 520 adults with pre-existing medical conditions (118 [22·7%] vaccinated), of whom 139 (26·7%) were admitted to ICU and 55 (10·6%) died in hospital; and 1578 older adults (609 [38·6%] vaccinated), of whom 271 (17·2%) were admitted to ICU and 220 (13·9%) died in hospital. We observed earlier discharge among partially vaccinated children (adjusted hazard ratio 1·14 [95% CI 1·01-1·29]), fully vaccinated children (1·24 [1·04-1·47]), and vaccinated adults with pre-existing medical conditions (1·78 [1·18-2·69]) compared with their unvaccinated counterparts, but not among vaccinated older adults (0·82 [0·65-1·04]). Compared with unvaccinated individuals, lower odds of ICU admission were found for partially vaccinated children (aOR 0·64 [95% CI 0·44-0·92]) and fully vaccinated children (0·52 [0·28-0·98]), but not for adults with pre-existing conditions (1·25 [0·93-1·67]) or older adults (0·88 [0·72-1·08]). Lower odds of in-hospital death (0·62 [0·50-0·78]) were found in vaccinated versus unvaccinated older adults, with or without ICU admission, but did not differ significantly in partially vaccinated (1·35 [0·57-3·20]) or fully vaccinated young children (0·88 [0·16-4·82]) or adults with pre-existing medical conditions (1·09 [0·73-1·63]) compared with the respective unvaccinated patient groups. INTERPRETATION Influenza vaccination was associated with illness attenuation among those hospitalised with influenza, although results differed by vaccine target group. These findings might suggest that attenuation of disease severity might be specific to certain target groups, seasons, or settings. FUNDING US Centers for Disease Control and Prevention. TRANSLATIONS For the Spanish and Portuguese translations of the abstract see Supplementary Materials section.
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Affiliation(s)
- Annette K Regan
- School of Nursing and Health Professions, University of San Francisco, Orange, CA, USA; Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA.
| | - Carmen Sofia Arriola
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Paula Couto
- Health Emergencies Program, Pan American Health Organization, Washington, DC, USA
| | - Lindsey Duca
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sergio Loayza
- Department of Family, Health Promotion, and Life Course, Pan American Health Organization, Washington, DC, USA
| | - Francisco Nogareda
- Department of Family, Health Promotion, and Life Course, Pan American Health Organization, Washington, DC, USA
| | | | - Julian Antman
- Surveillance Area, Directorate of Epidemiology, Ministry of Health, Buenos Aires, Argentina; Consultant to The Task Force for Global Health, Decatur, GA, USA
| | - Soraya Araya
- Expanded Program on Immunizations, Ministry of Public Health and Social Welfare, Asunción, Paraguay
| | | | | | | | - Patricia Bustos
- Public Health Institute, Ministry of Health, Santiago, Chile
| | - Maria Eugenia Fandiño
- Surveillance Area, Directorate of Epidemiology, Ministry of Health, Buenos Aires, Argentina
| | - Rodrigo Fasce
- Public Health Institute, Ministry of Health, Santiago, Chile
| | | | | | - Marta von Horoch
- General Directorate of Health Surveillance, Ministry of Public Health and Social Welfare, Asunción, Paraguay
| | - Maria Del Valle Juarez
- Directorate for the Control of Immunopreventable Diseases, Ministry of Health, Buenos Aires, Argentina
| | - Nathalia Katz
- Directorate for the Control of Immunopreventable Diseases, Ministry of Health, Buenos Aires, Argentina
| | | | | | | | | | - Natalia Vergara
- Department of Epidemiology, Ministry of Health, Santiago, Chile
| | | | - Alba Maria Ropero
- Department of Family, Health Promotion, and Life Course, Pan American Health Organization, Washington, DC, USA
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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: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [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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18
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Rockman S, Laurie K, Ong C, Rajaram S, McGovern I, Tran V, Youhanna J. Cell-Based Manufacturing Technology Increases Antigenic Match of Influenza Vaccine and Results in Improved Effectiveness. Vaccines (Basel) 2022; 11:52. [PMID: 36679895 PMCID: PMC9861528 DOI: 10.3390/vaccines11010052] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/19/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022] Open
Abstract
To ensure that vaccination offers the best protection against an infectious disease, sequence identity between the vaccine and the circulating strain is paramount. During replication of nucleic acid, random mutations occur due to the level of polymerase fidelity. In traditional influenza vaccine manufacture, vaccine viruses are propagated in fertilized chicken eggs, which can result in egg-adaptive mutations in the antigen-encoding genes. Whilst this improves infection and replication in eggs, mutations may reduce the effectiveness of egg-based influenza vaccines against circulating human viruses. In contrast, egg-adaptive mutations are avoided when vaccine viruses are propagated in Madin-Darby canine kidney (MDCK) cell lines during manufacture of cell-based inactivated influenza vaccines. The first mammalian cell-only strain was included in Flucelvax® Quadrivalent in 2017. A sequence analysis of the viruses selected for inclusion in this vaccine (n = 15 vaccine strains, containing both hemagglutinin and neuraminidase) demonstrated that no mutations occur in the antigenic sites of either hemagglutinin or neuraminidase, indicating that cell adaptation does not occur during production of this cell-based vaccine. The development of this now entirely mammalian-based vaccine system, which incorporates both hemagglutinin and neuraminidase, ensures that the significant protective antigens are equivalent to the strains recommended by the World Health Organization (WHO) in both amino acid sequence and glycosylation pattern. The inclusion of both proteins in a vaccine may provide an advantage over recombinant vaccines containing hemagglutinin alone. Findings from real world effectiveness studies support the use of cell-based influenza vaccines.
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Affiliation(s)
- Steven Rockman
- CSL Seqirus Ltd., Parkville, VIC 3050, Australia
- Department of Immunology and Microbiology, The University of Melbourne, Parkville, VIC 3050, Australia
| | - Karen Laurie
- CSL Seqirus Ltd., Parkville, VIC 3050, Australia
| | - Chi Ong
- CSL Seqirus Ltd., Parkville, VIC 3050, Australia
| | | | | | - Vy Tran
- CSL Seqirus Ltd., Kirkland, QC H9H 4M7, Canada
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19
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Burden of medically attended influenza infection and cases averted by vaccination - United States, 2016/17 through 2018/19 influenza seasons. Vaccine 2022; 40:7703-7708. [PMID: 36379754 PMCID: PMC9732931 DOI: 10.1016/j.vaccine.2022.11.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 11/04/2022] [Accepted: 11/05/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Epidemics of seasonal influenza vary in intensity annually, and influenza vaccine effectiveness (VE) fluctuates based in part on antigenic match to circulating viruses. We estimated the incidence of influenza and influenza cases averted by vaccination in four ambulatory care sites in the United States, during seasons when overall influenza VE ranged from 29% to 40%. METHODS We conducted active surveillance for influenza at ambulatory care settings at four sites within the United States Influenza Vaccine Effectiveness Network. We extrapolated the total number of influenza cases in the source populations served by these organizations based on incidence of medically attended acute respiratory illness in the source population and influenza test results in those actively tested for influenza. We estimated the number of medically attended influenza cases averted based on incidence, vaccine coverage, and VE. RESULTS From 2016/17 through 2018/19, incidence of ambulatory visits for laboratory-confirmed influenza ranged from 31 to 51 per 1,000 population. Incidence was highest in children aged 9-17 years (range, 56 to 81 per 1,000) and lowest in adults aged 18-49 years (range, 23-32 per 1,000). Medically attended cases averted by vaccination ranged from a high of 46.6 (95 % CI, 12.1- 91.9) per 1,000 vaccinees in children aged 6 months to 8 years, to a low of 6.9 (95 % CI, -5.1- 27.3) per 1,000 vaccinees in adults aged ≥ 65 years. DISCUSSION Even in seasons with low vaccine effectiveness for a particular virus subtype, influenza vaccines can still lead to clinically meaningful reductions in ambulatory care visits for influenza.
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20
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Knowledge and perception regarding effectiveness in influenza vaccines among General Practitioners in Germany: A national survey. Vaccine X 2022; 12:100236. [DOI: 10.1016/j.jvacx.2022.100236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/27/2022] [Accepted: 10/29/2022] [Indexed: 11/06/2022] Open
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21
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Liu Y, Chen H, Duan W, Zhang X, He X, Nielsen R, Ma L, Zhai W. Predicting Egg Passage Adaptations to Design Better Vaccines for the H3N2 Influenza Virus. Viruses 2022; 14:v14092065. [PMID: 36146872 PMCID: PMC9501976 DOI: 10.3390/v14092065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 09/12/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022] Open
Abstract
Seasonal H3N2 influenza evolves rapidly, leading to an extremely poor vaccine efficacy. Substitutions employed during vaccine production using embryonated eggs (i.e., egg passage adaptation) contribute to the poor vaccine efficacy (VE), but the evolutionary mechanism remains elusive. Using an unprecedented number of hemagglutinin sequences (n = 89,853), we found that the fitness landscape of passage adaptation is dominated by pervasive epistasis between two leading residues (186 and 194) and multiple other positions. Convergent evolutionary paths driven by strong epistasis explain most of the variation in VE, which has resulted in extremely poor vaccines for the past decade. Leveraging the unique fitness landscape, we developed a novel machine learning model that can predict egg passage substitutions for any candidate vaccine strain before the passage experiment, providing a unique opportunity for the selection of optimal vaccine viruses. Our study presents one of the most comprehensive characterizations of the fitness landscape of a virus and demonstrates that evolutionary trajectories can be harnessed for improved influenza vaccines.
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Affiliation(s)
- Yunsong Liu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Hui Chen
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672, Singapore
| | - Wenyuan Duan
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Xinyi Zhang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Xionglei He
- MOE Key Laboratory of Gene Function and Regulation, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China
| | - Rasmus Nielsen
- Department of Integrative Biology, University of California-Berkeley, Berkeley, CA 94707, USA
- Department of Statistics, University of California-Berkeley, Berkeley, CA 94707, USA
- Globe Institute, University of Copenhagen, 1350 København, Copenhagen, Denmark
| | - Liang Ma
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Weiwei Zhai
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of the Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Correspondence:
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22
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Doll MK, Pettigrew SM, Ma J, Verma A. Effects of Confounding Bias in Coronavirus Disease 2019 (COVID-19) and Influenza Vaccine Effectiveness Test-Negative Designs Due to Correlated Influenza and COVID-19 Vaccination Behaviors. Clin Infect Dis 2022; 75:e564-e571. [PMID: 35325923 PMCID: PMC9129127 DOI: 10.1093/cid/ciac234] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND The test-negative design is commonly used to estimate influenza and coronavirus disease 2019 (COVID-19) vaccine effectiveness (VE). In these studies, correlated COVID-19 and influenza vaccine behaviors may introduce a confounding bias where controls are included with the other vaccine-preventable acute respiratory illness (ARI). We quantified the impact of this bias on VE estimates in studies where this bias is not addressed. METHODS We simulated study populations under varying vaccination probabilities, COVID-19 VE, influenza VE, and proportions of controls included with the other vaccine-preventable ARI. Mean bias was calculated as the difference between estimated and true VE. Absolute mean bias in VE estimates was classified as low (<10%), moderate (10% to <20%), and high (≥20%). RESULTS Where vaccination probabilities are positively correlated, COVID-19 and influenza VE test-negative studies with influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ARI controls, respectively, underestimate VE. For COVID-19 VE studies, mean bias was low for all scenarios where influenza represented ≤25% of controls. For influenza VE studies, mean bias was low for all scenarios where SARS-CoV-2 represented ≤10% of controls. Although bias was driven by the conditional probability of vaccination, low VE of the vaccine of interest and high VE of the confounding vaccine increase its magnitude. CONCLUSIONS Where a low percentage of controls is included with the other vaccine-preventable ARI, bias in COVID-19 and influenza VE estimates is low. However, influenza VE estimates are likely more susceptible to bias. Researchers should consider potential bias and its implications in their respective study settings to make informed methodological decisions in test-negative VE studies.
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Affiliation(s)
- Margaret K Doll
- Department of Population Health Sciences, Albany College of Pharmacy and Health Sciences, Albany, New York, USA
| | - Stacy M Pettigrew
- Department of Population Health Sciences, Albany College of Pharmacy and Health Sciences, Albany, New York, USA
| | - Julia Ma
- Precision Analytics, Montreal, Quebec, Canada
| | - Aman Verma
- Precision Analytics, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
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23
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Kim SS, Naioti EA, Halasa NB, Stewart LS, Williams JV, Michaels MG, Selvarangan R, Harrison CJ, Staat MA, Schlaudecker EP, Weinberg GA, Szilagyi PG, Boom JA, Sahni LC, Englund JA, Klein EJ, Ogokeh CE, Campbell AP, Patel MM. Vaccine Effectiveness Against Influenza Hospitalization and Emergency Department Visits in 2 A(H3N2) Dominant Influenza Seasons Among Children <18 Years Old-New Vaccine Surveillance Network 2016-2017 and 2017-2018. J Infect Dis 2022; 226:91-96. [PMID: 34951451 DOI: 10.1093/infdis/jiab624] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 12/21/2021] [Indexed: 11/13/2022] Open
Abstract
Studies have shown egg-adaptive mutations in influenza vaccine strains that might have impaired protection against circulating A(H3N2) influenza viruses during the 2016-2017 and 2017-2018 seasons. We used the test-negative design and multivariable models to assess vaccine effectiveness against influenza-associated hospitalization and emergency department visits among children (<18 years old) during the 2016-2017 and 2017-2018 seasons. Effectiveness was 71% (95% confidence interval, 59%-79%), 46% (35%-55%), and 45% (33%-55%) against A(H1N1)pdm09, A(H3N2), and B viruses respectively, across both seasons. During high-severity seasons with concerns for vaccine mismatch, vaccination offered substantial protection against severe influenza outcomes requiring hospitalization or emergency department visits among children.
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Affiliation(s)
- Sara S Kim
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Eric A Naioti
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | | | - Laura S Stewart
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - John V Williams
- Department of Pediatrics, University of Pittsburgh School of Medicine and UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Marian G Michaels
- Department of Pediatrics, University of Pittsburgh School of Medicine and UPMC Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Rangaraj Selvarangan
- Department of Pediatrics, Infectious Diseases Division, Children's Mercy-Kansas City and University of Missouri, Kansas City, Kansas City, Missouri, USA
- Department of Pathology and Laboratory Medicine, Children's Mercy-Kansas City and University of Missouri-Kansas City, Kansas City, Missouri, USA
| | - Christopher J Harrison
- Department of Pediatrics, Infectious Diseases Division, Children's Mercy-Kansas City and University of Missouri, Kansas City, Kansas City, Missouri, USA
| | - Mary A Staat
- Department of Pediatrics, University of Cincinnati College of Medicine, Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Elizabeth P Schlaudecker
- Department of Pediatrics, University of Cincinnati College of Medicine, Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Geoffrey A Weinberg
- University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Peter G Szilagyi
- University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- University of California at Los Angeles, Los Angeles, California, USA
| | - Julie A Boom
- Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
| | - Leila C Sahni
- Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
| | | | | | - Constance E Ogokeh
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Angela P Campbell
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Manish M Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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Pliasas VC, Menne Z, Aida V, Yin JH, Naskou MC, Neasham PJ, North JF, Wilson D, Horzmann KA, Jacob J, Skountzou I, Kyriakis CS. A Novel Neuraminidase Virus-Like Particle Vaccine Offers Protection Against Heterologous H3N2 Influenza Virus Infection in the Porcine Model. Front Immunol 2022; 13:915364. [PMID: 35874791 PMCID: PMC9300842 DOI: 10.3389/fimmu.2022.915364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 05/31/2022] [Indexed: 11/13/2022] Open
Abstract
Influenza A viruses (IAVs) pose a global health threat, contributing to hundreds of thousands of deaths and millions of hospitalizations annually. The two major surface glycoproteins of IAVs, hemagglutinin (HA) and neuraminidase (NA), are important antigens in eliciting neutralizing antibodies and protection against disease. However, NA is generally ignored in the formulation and development of influenza vaccines. In this study, we evaluate the immunogenicity and efficacy against challenge of a novel NA virus-like particles (VLPs) vaccine in the porcine model. We developed an NA2 VLP vaccine containing the NA protein from A/Perth/16/2009 (H3N2) and the matrix 1 (M1) protein from A/MI/73/2015, formulated with a water-in-oil-in-water adjuvant. Responses to NA2 VLPs were compared to a commercial adjuvanted quadrivalent whole inactivated virus (QWIV) swine IAV vaccine. Animals were prime boost vaccinated 21 days apart and challenged four weeks later with an H3N2 swine IAV field isolate, A/swine/NC/KH1552516/2016. Pigs vaccinated with the commercial QWIV vaccine demonstrated high hemagglutination inhibition (HAI) titers but very weak anti-NA antibody titers and subsequently undetectable NA inhibition (NAI) titers. Conversely, NA2 VLP vaccinated pigs demonstrated undetectable HAI titers but high anti-NA antibody titers and NAI titers. Post-challenge, NA2 VLPs and the commercial QWIV vaccine showed similar reductions in virus replication, pulmonary neutrophilic infiltration, and lung inflammation compared to unvaccinated controls. These data suggest that anti-NA immunity following NA2 VLP vaccination offers comparable protection to QWIV swine IAV vaccines inducing primarily anti-HA responses.
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Affiliation(s)
- Vasilis C. Pliasas
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
- Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta, GA, United States
| | - Zach Menne
- Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta, GA, United States
- Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Virginia Aida
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
- Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta, GA, United States
| | - Ji-Hang Yin
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
| | - Maria C. Naskou
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
| | - Peter J. Neasham
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
- Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta, GA, United States
| | - J. Fletcher North
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
- Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta, GA, United States
| | - Dylan Wilson
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
| | - Katharine A. Horzmann
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
| | - Joshy Jacob
- Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, GA, United States
| | - Ioanna Skountzou
- Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta, GA, United States
- Department of Microbiology and Immunology, School of Medicine, Emory University, Atlanta, GA, United States
- *Correspondence: Constantinos S. Kyriakis, ; Ioanna Skountzou,
| | - Constantinos S. Kyriakis
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, United States
- Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta, GA, United States
- Center for Vaccines and Immunology, University of Georgia, Athens, GA, United States
- *Correspondence: Constantinos S. Kyriakis, ; Ioanna Skountzou,
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Feng H, Zhao X, Xie J, Bai X, Fu W, Chen H, Tang H, Wang X, Dong C. Pathogen-associated T follicular helper cell plasticity is critical in anti-viral immunity. SCIENCE CHINA LIFE SCIENCES 2022; 65:1075-1090. [DOI: 10.1007/s11427-021-2055-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 09/26/2021] [Indexed: 01/12/2023]
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Noh K, Jeong EJ, An T, Shin JS, Kim H, Han SB, Kim M. The efficacy of a 2,4-diaminoquinazoline compound as an intranasal vaccine adjuvant to protect against influenza A virus infection in vivo. J Microbiol 2022; 60:550-559. [PMID: 35437625 PMCID: PMC9014970 DOI: 10.1007/s12275-022-1661-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/24/2022] [Accepted: 02/28/2022] [Indexed: 12/26/2022]
Abstract
Adjuvants are substances added to vaccines to enhance antigen-specific immune responses or to protect antigens from rapid elimination. As pattern recognition receptors, Toll-like receptors 7 (TLR7) and 8 (TLR8) activate the innate immune system by sensing endosomal single-stranded RNA of RNA viruses. Here, we investigated if a 2,4-diaminoquinazoline-based TLR7/8 agonist, (S)-3-((2-amino-8-fluoroquinazolin-4-yl)amino)hexan-1-ol (named compound 31), could be used as an adjuvant to enhance the serological and mucosal immunity of an inactivated influenza A virus vaccine. The compound induced the production of proinflammatory cytokines in macrophages. In a dose-response analysis, intranasal administration of 1 µg compound 31 together with an inactivated vaccine (0.5 µg) to mice not only enhanced virus-specific IgG and IgA production but also neutralized influenza A virus with statistical significance. Notably, in a virus-challenge model, the combination of the vaccine and compound 31 alleviated viral infection-mediated loss of body weight and increased survival rates by 40% compared with vaccine only-treated mice. We suggest that compound 31 is a promising lead compound for developing mucosal vaccine adjuvants to protect against respiratory RNA viruses such as influenza viruses and potentially coronaviruses.
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Affiliation(s)
- Kyungseob Noh
- Infectious Diseases Therapeutic Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea
- Graduate School of New Drug Discovery and Development, Chungnam National University, Daejeon, 34134, Republic of Korea
| | - Eun Ju Jeong
- Infectious Diseases Therapeutic Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea
- Medicinal Chemistry and Pharmacology, University of Science and Technology (UST), Daejeon, 34113, Republic of Korea
| | - Timothy An
- Infectious Diseases Therapeutic Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea
- Graduate School of New Drug Discovery and Development, Chungnam National University, Daejeon, 34134, Republic of Korea
| | - Jin Soo Shin
- Infectious Diseases Therapeutic Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea
| | - Hyejin Kim
- Infectious Diseases Therapeutic Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea
| | - Soo Bong Han
- Infectious Diseases Therapeutic Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea.
- Medicinal Chemistry and Pharmacology, University of Science and Technology (UST), Daejeon, 34113, Republic of Korea.
| | - Meehyein Kim
- Infectious Diseases Therapeutic Research Center, Korea Research Institute of Chemical Technology (KRICT), Daejeon, 34114, Republic of Korea.
- Graduate School of New Drug Discovery and Development, Chungnam National University, Daejeon, 34134, Republic of Korea.
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Lewnard JA, Bruxvoort KJ, Hong VX, Grant LR, Jódar L, Cané A, Gessner BD, Tartof SY. Effectiveness of Pneumococcal Conjugate Vaccination Against Virus-Associated Lower Respiratory Tract Infection Among Adults: A Case-Control Study. J Infect Dis 2022; 227:498-511. [PMID: 35323906 PMCID: PMC9383607 DOI: 10.1093/infdis/jiac098] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/21/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Interactions of Streptococcus pneumoniae with viruses feature in the pathogenesis of numerous respiratory illnesses. METHODS We undertook a case-control study among adults at Kaiser Permanente Southern California between 2015 and 2019. Case patients had diagnoses of lower respiratory tract infection (LRTI; including pneumonia or nonpneumonia LRTI diagnoses), with viral infections detected by multiplex polymerase chain reaction testing. Controls without LRTI diagnoses were matched to case patients by demographic and clinical attributes. We measured vaccine effectiveness (VE) for 13-valent (PCV13) against virus-associated LRTI by determining the adjusted odds ratio for PCV13 receipt, comparing case patients and controls. RESULTS Primary analyses included 13 856 case patients with virus-associated LRTI and 227 887 matched controls. Receipt of PCV13 was associated with a VE of 24.9% (95% confidence interval, 18.4%-30.9%) against virus-associated pneumonia and 21.5% (10.9%-30.9%) against other (nonpneumonia) virus-associated LRTIs. We estimated VEs of 26.8% (95% confidence interval, 19.9%-33.1%) and 18.6% (9.3%-27.0%) against all virus-associated LRTI episodes diagnosed in inpatient and outpatient settings, respectively. We identified statistically significant protection against LRTI episodes associated with influenza A and B viruses, endemic human coronaviruses, parainfluenza viruses, human metapneumovirus, and enteroviruses but not respiratory syncytial virus or adenoviruses. CONCLUSIONS Among adults, PCV13 conferred moderate protection against virus-associated LRTI. The impacts of pneumococcal conjugate vaccines may be mediated, in part, by effects on polymicrobial interactions between pneumococci and respiratory viruses.
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Affiliation(s)
- Joseph A Lewnard
- Correspondence: Joseph A. Lewnard, 2121 Berkeley Way, Room 5410, Berkeley, CA 94720 ()
| | - Katia J Bruxvoort
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama, USA,Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | - Vennis X Hong
- Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA
| | | | - Luis Jódar
- Pfizer Vaccines, Collegeville, Pennsylvania, USA
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Fox A, Carolan L, Leung V, Phuong HVM, Khvorov A, Auladell M, Tseng YY, Thai PQ, Barr I, Subbarao K, Mai LTQ, van Doorn HR, Sullivan SG. Opposing Effects of Prior Infection versus Prior Vaccination on Vaccine Immunogenicity against Influenza A(H3N2) Viruses. Viruses 2022; 14:v14030470. [PMID: 35336877 PMCID: PMC8949461 DOI: 10.3390/v14030470] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 11/10/2021] [Accepted: 11/28/2021] [Indexed: 02/05/2023] Open
Abstract
Prior vaccination can alternately enhance or attenuate influenza vaccine immunogenicity and effectiveness. Analogously, we found that vaccine immunogenicity was enhanced by prior A(H3N2) virus infection among participants of the Ha Nam Cohort, Viet Nam, but was attenuated by prior vaccination among Australian Health Care Workers (HCWs) vaccinated in the same year. Here, we combined these studies to directly compare antibody titers against 35 A(H3N2) viruses spanning 1968–2018. Participants received licensed inactivated vaccines containing A/HongKong/4801/2014 (H3N2). The analysis was limited to participants aged 18–65 Y, and compared those exposed to A(H3N2) viruses circulating since 2009 by infection (Ha Nam) or vaccination (HCWs) to a reference group who had no recent A(H3N2) infection or vaccination (Ha Nam). Antibody responses were compared by fitting titer/titer-rise landscapes across strains, and by estimating titer ratios to the reference group of 2009–2018 viruses. Pre-vaccination, titers were lowest against 2009–2014 viruses among the reference (no recent exposure) group. Post-vaccination, titers were, on average, two-fold higher among participants with prior infection and two-fold lower among participants with 3–5 prior vaccinations compared to the reference group. Titer rise was negligible among participants with 3–5 prior vaccinations, poor among participants with 1–2 prior vaccinations, and equivalent or better among those with prior infection compared to the reference group. The enhancing effect of prior infection versus the incrementally attenuating effect of prior vaccinations suggests that these exposures may alternately promote and constrain the generation of memory that can be recalled by a new vaccine strain.
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Affiliation(s)
- Annette Fox
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
- Correspondence: ; Tel.: +61-393-429-313
| | - Louise Carolan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
| | - Vivian Leung
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
| | - Hoang Vu Mai Phuong
- National Institute of Hygiene and Epidemiology, Ha Noi 100000, Vietnam; (H.V.M.P.); (P.Q.T.); (L.T.Q.M.)
| | - Arseniy Khvorov
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
| | - Maria Auladell
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Yeu-Yang Tseng
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
| | - Pham Quang Thai
- National Institute of Hygiene and Epidemiology, Ha Noi 100000, Vietnam; (H.V.M.P.); (P.Q.T.); (L.T.Q.M.)
| | - Ian Barr
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
| | - Kanta Subbarao
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia;
| | - Le Thi Quynh Mai
- National Institute of Hygiene and Epidemiology, Ha Noi 100000, Vietnam; (H.V.M.P.); (P.Q.T.); (L.T.Q.M.)
| | - H. Rogier van Doorn
- Oxford University Clinical Research Unit, Wellcome Africa Asia Programme, National Hospital of Tropical Diseases, Ha Noi 100000, Vietnam;
- Centre of Tropical Medicine and Global Health, Nuffield Department of Clinical Medicine, University of Oxford, Oxford OX3 7LG, UK
| | - Sheena G. Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (L.C.); (V.L.); (I.B.); (K.S.); (S.G.S.)
- Department of Infectious Diseases, University of Melbourne, Peter Doherty Institute for Infection and Immunity, Melbourne, VIC 3000, Australia; (A.K.); (Y.-Y.T.)
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Tian M, Yu J, Lillvis DF, Vexler A. Influence function methods to assess the effectiveness of influenza vaccine with survey data. Health Serv Res 2022; 57:200-211. [PMID: 34643942 PMCID: PMC8763297 DOI: 10.1111/1475-6773.13895] [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: 05/17/2021] [Revised: 06/15/2021] [Accepted: 09/30/2021] [Indexed: 02/03/2023] Open
Abstract
OBJECTIVE To examine a robust relative risk (RR) estimation for survey data analysis with ideal inferential properties under various model assumptions. DATA SOURCES We employed secondary data from the Household Component of the 2000-2016 US Medical Expenditure Panel Survey (MEPS). STUDY DESIGN We investigate a broad range of data-balancing techniques by implementing influence function (IF) methods, which allows us to easily estimate the variability for the RR estimates in the complex survey setting. We conduct a simulation study of seasonal influenza vaccine effectiveness to evaluate these approaches and discuss techniques that show robust inferential performance across model assumptions. DATA COLLECTION/EXTRACTION METHODS Demographic information, vaccine status, and self-administered questionnaire surveys were obtained from the longitudinal data files. We linked this information with medical condition files and medical event to extract the disease type and associated expenditures for each medical visit. We excluded individuals who were 18 years or younger at the beginning of each panel. PRINCIPAL FINDINGS Under various model assumptions, the IF methods show robust inferential performance when the data-balancing procedures are incorporated. Once IF methods and data-balancing techniques are implemented, contingency table-based RR estimation yields a comparable result to the generalized linear model approach. We demonstrate the applicability of the proposed methods for complex survey data using 2000-2016 MEPS data. When employing these methods, we find a significant, negative association between vaccine effectiveness (VE) estimates and influenza-incurred expenditures. CONCLUSIONS We describe and demonstrate a robust method for RR estimation and relevant inferences for influenza vaccine effectiveness using MEPS data. The proposed method is flexible and can be extended to weighted data for survey data analysis. Hence, these methods have great potential for health services research, especially when data are nonexperimental and imbalanced.
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Affiliation(s)
- Mingmei Tian
- Department of BiostatisticsUniversity at Buffalo, State University of New YorkBuffaloNew YorkUSA
| | - Jihnhee Yu
- Department of BiostatisticsUniversity at Buffalo, State University of New YorkBuffaloNew YorkUSA
| | - Denise F. Lillvis
- Department of SurgeryJacobs School of Medicine and Biomedical SciencesBuffaloNew YorkUSA,Division of Health Services Policy & Practice, School of Public Health and Health ProfessionsUniversity at Buffalo, State University of New YorkBuffaloNew YorkUSA,Trauma DepartmentJohn R. Oishei Children's HospitalBuffaloNew YorkUSA
| | - Albert Vexler
- Department of BiostatisticsUniversity at Buffalo, State University of New YorkBuffaloNew YorkUSA
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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: 2] [Impact Index Per Article: 1.0] [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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31
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Influenza Vaccine Effectiveness Estimates among US Department of Defense Adult Beneficiaries over Four Consecutive Influenza Seasons: A Test-Negative Design Study with Different Control Groups. Vaccines (Basel) 2021; 10:vaccines10010058. [PMID: 35062721 PMCID: PMC8781181 DOI: 10.3390/vaccines10010058] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 12/28/2021] [Accepted: 12/29/2021] [Indexed: 11/17/2022] Open
Abstract
A test-negative design study with different control groups (influenza test-negative controls, non-influenza virus positive controls, and pan-negative controls) was conducted to assess inactivated influenza vaccine effectiveness (VE) in adults aged ≥18 years, 2016-2017 through 2019-2020 influenza seasons. A database was developed from the US Department of Defense Global Respiratory Pathogen Surveillance Program. VE was estimated using a generalized linear mixed model with logit link and binomial distribution, adjusted for confounding effects. A total of 7114 adults including 2543 medically attended, laboratory-confirmed influenza-positive cases were identified. Using influenza test-negative controls, the adjusted VE in adults was 40% [95% confidence interval (CI): 33-46%] overall, including 46% (95% CI: 36-55%) for influenza A(H1N1)pdm09, 32% (95% CI: 19-42%) for influenza A(H3N2), and 54% (95% CI: 44-62%) for influenza B. The age-stratified analysis showed that VE estimates against influenza A(H1N1)pdm09 (34%; 95% CI: -29-66%) and influenza A(H3N2) (6%; 95% CI: -60-45%) were low and non-significant for elderly adults ≥65 years of age. Overall VE estimates against any influenza or by influenza (sub)types in adults were consistent when using influenza test-negative controls, non-influenza virus positive controls, and pan-negative controls. Inactivated influenza vaccination provided moderate protection against influenza virus infection, based on the analysis from a large number of adults aged ≥18 years over multiple influenza seasons.
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Tenforde MW, Kondor RJG, Chung JR, Zimmerman RK, Nowalk MP, Jackson ML, Jackson LA, Monto AS, Martin ET, Belongia EA, McLean HQ, Gaglani M, Rao A, Kim SS, Stark TJ, Barnes JR, Wentworth DE, Patel MM, Flannery B. Effect of Antigenic Drift on Influenza Vaccine Effectiveness in the United States-2019-2020. Clin Infect Dis 2021; 73:e4244-e4250. [PMID: 33367650 PMCID: PMC8664438 DOI: 10.1093/cid/ciaa1884] [Citation(s) in RCA: 73] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND At the start of the 2019-2020 influenza season, concern arose that circulating B/Victoria viruses of the globally emerging clade V1A.3 were antigenically drifted from the strain included in the vaccine. Intense B/Victoria activity was followed by circulation of genetically diverse A(H1N1)pdm09 viruses that were also antigenically drifted. We measured vaccine effectiveness (VE) in the United States against illness from these emerging viruses. METHODS We enrolled outpatients aged ≥6 months with acute respiratory illness at 5 sites. Respiratory specimens were tested for influenza by reverse-transcriptase polymerase chain reaction (RT-PCR). Using the test-negative design, we determined influenza VE by virus subtype/lineage and genetic subclades by comparing odds of vaccination in influenza cases versus test-negative controls. RESULTS Among 8845 enrollees, 2722 (31%) tested positive for influenza, including 1209 (44%) for B/Victoria and 1405 (51%) for A(H1N1)pdm09. Effectiveness against any influenza illness was 39% (95% confidence interval [CI]: 32-44), 45% (95% CI: 37-52) against B/Victoria and 30% (95% CI: 21-39) against A(H1N1)pdm09-associated illness. Vaccination offered no protection against A(H1N1)pdm09 viruses with antigenically drifted clade 6B.1A 183P-5A+156K HA genes (VE 7%; 95% CI: -14 to 23%) which predominated after January. CONCLUSIONS Vaccination provided protection against influenza illness, mainly due to infections from B/Victoria viruses. Vaccine protection against illness from A(H1N1)pdm09 was lower than historically observed effectiveness of 40%-60%, due to late-season vaccine mismatch following emergence of antigenically drifted viruses. The effect of drift on vaccine protection is not easy to predict and, even in drifted years, significant protection can be observed.
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Affiliation(s)
| | | | - Jessie R Chung
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | | | | | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle WA, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle WA, USA
| | | | | | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield WI, USA
| | - Manjusha Gaglani
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple TX, USA
| | - Arundhati Rao
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple TX, USA
| | - Sara S Kim
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | - Thomas J Stark
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | - John R Barnes
- Centers for Disease Control and Prevention, Atlanta GA, USA
| | | | - Manish M Patel
- Centers for Disease Control and Prevention, Atlanta GA, USA
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Human anti-neuraminidase antibodies reduce airborne transmission of clinical influenza virus isolates in the guinea pig model. J Virol 2021; 96:e0142121. [PMID: 34669506 DOI: 10.1128/jvi.01421-21] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The public health burden caused by influenza virus infections is not adequately addressed with existing vaccines and antivirals. Identifying approaches that interfere with human-to-human transmission of influenza viruses remains a pressing need. The importance of neuraminidase (NA) activity for the replication and spread of influenza viruses led us to investigate whether broadly reactive human anti-NA monoclonal antibodies (mAbs) could affect airborne transmission of the virus using the guinea pig model. In that model, infection with recent influenza virus clinical isolates resulted in 100% transmission from inoculated donors to recipients in an airborne transmission setting. Anti-NA mAbs were administered either to the inoculated animals on days 1, 2, and 4 after infection or to the naïve contacts on days 2 and 4 after donor infection. Administration of NA-1G01, a broadly cross-reactive anti-NA mAb, to either the donor or recipient reduced transmission of the A/New York City/PV02669/2019 (H1N1) and A/New York City/PV01148/2018 (H3N2) viruses. Administration of 1000-3C05, an anti-N1 mAb, to either the donor or recipient reduced transmission of A/New York City/PV02669/2019 (H1N1) virus but did not reduce transmission of A/New York City/PV01148 (H3N2) virus. Conversely, 229-2C06, an anti-N2 mAb, reduced transmission of A/New York City/PV01148 (H3N2) but did not impact transmission of A/New York City/PV02669/2019 (H1N1) virus. Our work demonstrates that anti-NA mAbs could be further developed into prophylactic or therapeutic agents to prevent influenza virus transmission and thus control viral spread. Importance The burden of influenza remains substantial despite unremitting efforts to reduce the magnitude of seasonal influenza epidemics and prepare for pandemics. While vaccination remains the mainstay of these efforts, current vaccines are designed to stimulate an immune response against the viral hemagglutinin. Interest in the role immunity against neuraminidase plays in influenza virus infection and transmission has recently surged. Human antibodies that bind broadly to neuraminidases of diverse influenza viruses and protect mice against lethal viral challenge have previously been characterized. Here, we show that three such antibodies inhibit the neuraminidase activity of recent isolates and reduce their airborne transmission in a guinea pig model. In addition to contributing to the accumulating support for incorporating neuraminidase as a vaccine antigen, these findings also demonstrate the potential of direct administration of anti-neuraminidase antibodies to individuals infected with influenza virus and to individuals for post-exposure prophylaxis to prevent the spread of influenza.
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Poor Vaccine Effectiveness against Influenza B-Related Severe Acute Respiratory Infection in a Temperate North Indian State (2019-2020): A Call for Further Data for Possible Vaccines with Closer Match. Vaccines (Basel) 2021; 9:vaccines9101094. [PMID: 34696202 PMCID: PMC8540586 DOI: 10.3390/vaccines9101094] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 09/21/2021] [Accepted: 09/21/2021] [Indexed: 01/22/2023] Open
Abstract
Background: Influenza vaccine uptake in India is poor, and scant data exist regarding the effectiveness of influenza vaccine against hospitalization. Methods: From October 2019 to March 2020, vaccination status of 1219 patients (males n = 571, aged 5–107 years; median, 50 years) hospitalized with severe acute respiratory illness (SARI) was assessed. The patients were tested for influenza viruses and their subtypes by RT PCR. Sequencing of the HA gene was performed. Vaccine effectiveness (VE) against influenza subtypes was estimated by the test negative design. Results: A total of 336 (27.5%) patients were influenza-positive, with influenza B/Victoria accounting for 49.7% (n = 167), followed by influenza A/H1N1 (47.6%; n = 155) and influenza A/H3N2 (4.4%; n = 15). About 6.8% and 8.6% of the influenza-positive and influenza-negative patients, respectively, had been vaccinated. Adjusted VE for any influenza strain was 13% (95% CI −42 to 47), which for influenza B was 0%. HA sequencing revealed that influenza B samples mainly belonged to subclade V1A.3/133R with deletion of residues 163–165, as against the 2-aa deletion in influenza B/Colorado/06/2017 strain, contained in the vaccine. VE for influenza A/H1N1 was 55%. Conclusions: Poor VE due to a genetic mismatch between the circulating strain and the vaccine strain calls for efforts to reduce the mismatch.
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Hu W, DeMarcus LS, Sjoberg PA, Robbins AS. Inactivated influenza vaccine effectiveness among department of defense beneficiaries aged 6 months-17 years, 2016-2017 through 2019-2020 influenza seasons. PLoS One 2021; 16:e0256165. [PMID: 34450617 PMCID: PMC8397503 DOI: 10.1371/journal.pone.0256165] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 07/30/2021] [Indexed: 11/18/2022] Open
Abstract
A test-negative case-control study was conducted to assess inactivated influenza vaccine effectiveness (VE) in children aged 6 months-17 years. The database was developed from the US Department of Defense Global Respiratory Pathogen Surveillance Program over four consecutive influenza seasons from 2016 to 2020. A total of 9,385 children including 4,063 medically attended, laboratory-confirmed influenza-positive cases were identified for VE analysis. A generalized linear mixed model with logit link and binomial distribution was used to estimate the VE. The adjusted VE for children was 42% [95% confidence interval (CI): 37-47%] overall, including 55% (95% CI: 47-61%) for influenza A(H1N1)pdm09, 37% (95% CI: 28-45%) for influenza A(H3N2), and 49% (95% CI: 41-55%) for influenza B. The analysis by age groups indicated that the adjusted VE in children aged 6 months-4 years was higher against influenza A(H1N1)pdm09 and influenza B, and comparable against influenza A(H3N2), compared to those in children aged 5-17 years. Further age-stratified analysis showed that the VE against any types of influenza was low and non-significant for children aged 6-11 months (33%; 95% CI:-2-56%), but it was high (54%; 95% CI: 34-67%) in children aged 12-23 months, and then declined linearly with increasing age. In conclusion, the inactivated influenza vaccination was moderately effective against influenza infection, based on the analysis from a large number of children aged 6 months-17 years over multiple influenza seasons.
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MESH Headings
- Adolescent
- Child
- Child, Preschool
- Female
- Humans
- Infant
- Influenza A Virus, H1N1 Subtype/drug effects
- Influenza A Virus, H1N1 Subtype/immunology
- Influenza A Virus, H1N1 Subtype/pathogenicity
- Influenza A Virus, H3N2 Subtype/drug effects
- Influenza A Virus, H3N2 Subtype/immunology
- Influenza A Virus, H3N2 Subtype/pathogenicity
- Influenza Vaccines/immunology
- Influenza Vaccines/therapeutic use
- Influenza, Human/epidemiology
- Influenza, Human/immunology
- Influenza, Human/prevention & control
- Influenza, Human/virology
- Male
- Seasons
- Vaccination
- Vaccine Efficacy
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Affiliation(s)
- Wenping Hu
- The Department of Defense Global Emerging Infections Surveillance Branch, Armed Forces Health Surveillance Division, WPAFB, OH, United States of America
- JYG Innovations, LLC, Dayton, OH, United States of America
- * E-mail:
| | - Laurie S. DeMarcus
- The Department of Defense Global Emerging Infections Surveillance Branch, Armed Forces Health Surveillance Division, WPAFB, OH, United States of America
- JYG Innovations, LLC, Dayton, OH, United States of America
| | - Paul A. Sjoberg
- The Department of Defense Global Emerging Infections Surveillance Branch, Armed Forces Health Surveillance Division, WPAFB, OH, United States of America
- JYG Innovations, LLC, Dayton, OH, United States of America
| | - Anthony S. Robbins
- The Department of Defense Global Emerging Infections Surveillance Branch, Armed Forces Health Surveillance Division, WPAFB, OH, United States of America
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36
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Campbell AP, Ogokeh C, Weinberg GA, Boom JA, Englund JA, Williams JV, Halasa NB, Selvarangan R, Staat MA, Klein EJ, McNeal M, Michaels MG, Sahni LC, Stewart LS, Szilagyi PG, Harrison CJ, Lively JY, Rha B, Patel M. Effect of Vaccination on Preventing Influenza-Associated Hospitalizations Among Children During a Severe Season Associated With B/Victoria Viruses, 2019-2020. Clin Infect Dis 2021; 73:e947-e954. [PMID: 33502489 DOI: 10.1093/cid/ciab060] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND The 2019-2020 influenza season was characterized by early onset with B/Victoria followed by A(H1N1)pdm09 viruses. Emergence of new B/Victoria viruses raised concerns about possible vaccine mismatch. We estimated vaccine effectiveness (VE) against influenza-associated hospitalizations and emergency department (ED) visits among children in the United States. METHODS We assessed VE among children aged 6 months-17 years with acute respiratory illness and ≤10 days of symptoms enrolled at 7 pediatric medical centers in the New Vaccine Surveillance Network. Combined midturbinate/throat swabs were tested for influenza virus using molecular assays. Vaccination history was collected from parental report, state immunization information systems, and/or provider records. We estimated VE from a test-negative design using logistic regression to compare odds of vaccination among children testing positive vs negative for influenza. RESULTS Among 2029 inpatients, 335 (17%) were influenza positive: 37% with influenza B/Victoria alone and 44% with influenza A(H1N1)pdm09 alone. VE was 62% (95% confidence interval [CI], 52%-71%) for influenza-related hospitalizations, 54% (95% CI, 33%-69%) for B/Victoria viruses, and 64% (95% CI, 49%-75%) for A(H1N1)pdm09. Among 2102 ED patients, 671 (32%) were influenza positive: 47% with influenza B/Victoria alone and 42% with influenza A(H1N1)pdm09 alone. VE was 56% (95% CI, 46%-65%) for an influenza-related ED visit, 55% (95% CI, 40%-66%) for B/Victoria viruses, and 53% (95% CI, 37%-65%) for A(H1N1)pdm09. CONCLUSIONS Influenza vaccination provided significant protection against laboratory-confirmed influenza-associated hospitalizations and ED visits associated with the 2 predominantly circulating influenza viruses among children, including against the emerging B/Victoria virus subclade.
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Affiliation(s)
- Angela P Campbell
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Constance Ogokeh
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | - Geoffrey A Weinberg
- University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Julie A Boom
- Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
| | | | - John V Williams
- Department of Pediatrics, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | - Rangaraj Selvarangan
- Children's Mercy Hospital, Kansas City, Missouri, USA
- Department of Pathology and Laboratory Medicine, University of Missouri-Kansas City, Children's Mercy Hospital, Kansas City, Missouri, USA
| | - Mary A Staat
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Division of Infectious Disease, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | | | - Monica McNeal
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
- Division of Infectious Disease, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Marian G Michaels
- Department of Pediatrics, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center Children's Hospital of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Leila C Sahni
- Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
| | - Laura S Stewart
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter G Szilagyi
- University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- University of California at Los Angeles, Los Angeles, California, USA
| | | | - Joana Y Lively
- Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- IHRC, Atlanta, Georgia, USA
| | - Brian Rha
- Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Manish Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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37
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Kim SS, Flannery B, Foppa IM, Chung JR, Nowalk MP, Zimmerman RK, Gaglani M, Monto AS, Martin ET, Belongia EA, McLean HQ, Jackson ML, Jackson LA, Patel M. Effects of Prior Season Vaccination on Current Season Vaccine Effectiveness in the United States Flu Vaccine Effectiveness Network, 2012-2013 Through 2017-2018. Clin Infect Dis 2021; 73:497-505. [PMID: 32505128 DOI: 10.1093/cid/ciaa706] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/01/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND We compared effects of prior vaccination and added or lost protection from current season vaccination among those previously vaccinated. METHODS Our analysis included data from the US Flu Vaccine Effectiveness Network among participants ≥9 years old with acute respiratory illness from 2012-2013 through 2017-2018. Vaccine protection was estimated using multivariate logistic regression with an interaction term for effect of prior season vaccination on current season vaccine effectiveness. Models were adjusted for age, calendar time, high-risk status, site, and season for combined estimates. We estimated protection by combinations of current and prior vaccination compared to unvaccinated in both seasons or current vaccination among prior vaccinated. RESULTS A total of 31 819 participants were included. Vaccine protection against any influenza averaged 42% (95% confidence interval [CI], 38%-47%) among those vaccinated only the current season, 37% (95% CI, 33-40) among those vaccinated both seasons, and 26% (95% CI, 18%-32%) among those vaccinated only the prior season, compared with participants vaccinated neither season. Current season vaccination reduced the odds of any influenza among patients unvaccinated the prior season by 42% (95% CI, 37%-46%), including 57%, 27%, and 55% against A(H1N1), A(H3N2), and influenza B, respectively. Among participants vaccinated the prior season, current season vaccination further reduced the odds of any influenza by 15% (95% CI, 7%-23%), including 29% against A(H1N1) and 26% against B viruses, but not against A(H3N2). CONCLUSIONS Our findings support Advisory Committee on Immunization Practices recommendations for annual influenza vaccination. Benefits of current season vaccination varied among participants with and without prior season vaccination, by virus type/subtype and season.
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Affiliation(s)
- Sara S Kim
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Ivo M Foppa
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jessie R Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Mary Patricia Nowalk
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Richard K Zimmerman
- University of Pittsburgh Schools of the Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | | | - Huong Q McLean
- Marshfield Clinical Research Institute, Marshfield, Wisconsin, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Manish Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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38
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Tenforde MW, Chung J, Smith ER, Talbot HK, Trabue CH, Zimmerman RK, Silveira FP, Gaglani M, Murthy K, Monto AS, Martin ET, McLean HQ, Belongia EA, Jackson LA, Jackson ML, Ferdinands JM, Flannery B, Patel MM. Influenza Vaccine Effectiveness in Inpatient and Outpatient Settings in the United States, 2015-2018. Clin Infect Dis 2021; 73:386-392. [PMID: 32270198 DOI: 10.1093/cid/ciaa407] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 04/07/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Demonstration of influenza vaccine effectiveness (VE) against hospitalized illness in addition to milder outpatient illness may strengthen vaccination messaging. Our objective was to compare patient characteristics and VE between United States (US) inpatient and outpatient VE networks. METHODS We tested adults with acute respiratory illness (ARI) for influenza within 1 outpatient-based and 1 hospital-based VE network from 2015 through 2018. We compared age, sex, and high-risk conditions. The test-negative design was used to compare vaccination odds in influenza-positive cases vs influenza-negative controls. We estimated VE using logistic regression adjusting for site, age, sex, race/ethnicity, peak influenza activity, time to testing from, season (overall VE), and underlying conditions. VE differences (ΔVE) were assessed with 95% confidence intervals (CIs) determined through bootstrapping with significance defined as excluding the null. RESULTS The networks enrolled 14 573 (4144 influenza-positive) outpatients and 6769 (1452 influenza-positive) inpatients. Inpatients were older (median, 62 years vs 49 years) and had more high-risk conditions (median, 4 vs 1). Overall VE across seasons was 31% (95% CI, 26%-37%) among outpatients and 36% (95% CI, 27%-44%) among inpatients. Strain-specific VE (95% CI) among outpatients vs inpatients was 37% (25%-47%) vs 53% (37%-64%) against H1N1pdm09; 19% (9%-27%) vs 23% (8%-35%) against H3N2; and 46% (38%-53%) vs 46% (31%-58%) against B viruses. ΔVE was not significant for any comparison across all sites. CONCLUSIONS Inpatients and outpatients with ARI represent distinct populations. Despite comparatively poor health among inpatients, influenza vaccination was effective in preventing influenza-associated hospitalizations.
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Affiliation(s)
- Mark W Tenforde
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jessie Chung
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Emily R Smith
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.,Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee, USA
| | - H Keipp Talbot
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Christopher H Trabue
- University of Tennessee Health Science Center, Saint Thomas Health, Nashville, Tennessee, USA
| | | | | | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Kempapura Murthy
- Baylor Scott and White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | | | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Jill M Ferdinands
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brendan Flannery
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Manish M Patel
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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39
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Menne Z, Pliasas VC, Compans RW, Glover S, Kyriakis CS, Skountzou I. Bivalent vaccination with NA1 and NA2 neuraminidase virus-like particles is protective against challenge with H1N1 and H3N2 influenza A viruses in a murine model. Virology 2021; 562:197-208. [PMID: 34375782 DOI: 10.1016/j.virol.2021.08.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 07/25/2021] [Accepted: 08/04/2021] [Indexed: 11/29/2022]
Abstract
Neuraminidase (NA) is the second most abundant glycoprotein on the surface of influenza A viruses (IAV). Neuraminidase type 1 (NA1) based virus-like particles (VLPs) have previously been shown to protect against challenge with H1N1 and H3N2 IAV. In this study, we produced neuraminidase type 2 (NA2) VLPs derived from the sequence of the seasonal IAV A/Perth/16/2009. Intramuscular vaccination of mice with NA2 VLPs induced high anti-NA serum IgG levels capable of inhibiting NA activity. NA2 VLP vaccination protected against mortality in a lethal A/Hong Kong/1/1968 (H3N2) virus challenge model, but not against lethal challenge with A/California/04/2009 (H1N1) virus. However, bivalent vaccination with NA1 and NA2 VLPs demonstrated no antigenic competition in anti-NA IgG responses and protected against lethal challenge with H1N1 and H3N2 viruses. Here we demonstrate that vaccination with NA VLPs is protective against influenza challenge and supports focusing on anti-NA responses in the development of future vaccination strategies.
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Affiliation(s)
- Zach Menne
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, GA, 30322, USA; Centers for Excellence in Influenza Research and Surveillance, Emory-UGA Center, Atlanta, GA, USA
| | - Vasilis C Pliasas
- Centers for Excellence in Influenza Research and Surveillance, Emory-UGA Center, Atlanta, GA, USA; Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, 36849, USA
| | - Richard W Compans
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, GA, 30322, USA; Centers for Excellence in Influenza Research and Surveillance, Emory-UGA Center, Atlanta, GA, USA
| | - Sheniqua Glover
- Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, 36849, USA
| | - Constantinos S Kyriakis
- Centers for Excellence in Influenza Research and Surveillance, Emory-UGA Center, Atlanta, GA, USA; Department of Pathobiology, College of Veterinary Medicine, Auburn University, Auburn, AL, 36849, USA
| | - Ioanna Skountzou
- Department of Microbiology and Immunology and Emory Vaccine Center, Emory University School of Medicine, Atlanta, GA, 30322, USA; Centers for Excellence in Influenza Research and Surveillance, Emory-UGA Center, Atlanta, GA, USA.
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40
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Zhang L, Wei M, Jin P, Li J, Zhu F. An evaluation of a test-negative design for EV-71 vaccine from a randomized controlled trial. Hum Vaccin Immunother 2021; 17:2101-2106. [PMID: 33529093 DOI: 10.1080/21645515.2020.1859900] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
Background: The test-negative design has been used widely in evaluation of various vaccines' effectiveness, such as influenza, rotavirus, and so on. Recently, there have been some studies about EV-71 vaccine effectiveness by using test-negative design(TND). However, the validity of the TND application in EV-71 vaccines has not been evaluated.Methods: This study is set upon prior methods to evaluate the validity of TND for influenza vaccine by using a randomized controlled clinical trial database. Vaccine effectiveness estimated by TND (VE-TND) in modified intention-to-treat population (mITT) and per-protocol-set population(PPS) was derived from a large randomized placebo-controlled clinical trial (RCT) of inactivated monovalent EV-71 vaccine in China. Derived VE-TND estimates were compared to the original vaccine efficacy results in RCT (VE-RCT).Results: We totally enrolled 7325 participants who seeked medical care for suspected EV-71 infected diseases during the surveillance. There are no significant differences between cases(test-positive) and controls(test-negative) on sex, age, height, and weight. TND vaccine effectiveness estimates were similar to original RCT vaccine efficacy estimates, both in modified intention-to-treat population and per-protocol populations.Conclusions: This study supports that TND, as an appropriate observational study design is valid to measure EV-71 vaccine effectiveness.
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Affiliation(s)
- Li Zhang
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, PR China
| | - Mingwei Wei
- Vaccine Clinical Evaluation Department, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, PR China
| | - Pengfei Jin
- Vaccine Clinical Evaluation Department, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, PR China
| | - Jingxin Li
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, PR China.,Vaccine Clinical Evaluation Department, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, PR China
| | - Fengcai Zhu
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, PR China.,NHC Key Laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention
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41
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Health Belief Model in Hospitals: Determining the Effective Factors on Influenza Vaccination. HEALTH SCOPE 2021. [DOI: 10.5812/ealthscope.113759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
: The need for extensive vaccination of health care workers (HCWs) is felt more than ever. The aim of this study was to investigate the determinants of influenza vaccination using HBM in HCWs of Jahrom hospitals. This cross-sectional study was performed by multicenter method on 614 HCWs in Jahrom, southern Iran, in 2020. Data collection tools included Demographic and researcher-made Influenza Vaccination in HCWs Based on HBM Questionnaires whose validity and reliability were measured and evaluated. Analyzes have been performed using SPSS 21. Increasing age (P < 0.001) and perceived barriers (P < 0.001) have increased influenza vaccination, but perceived benefits (P = 0.002), cues to action (P = 0.001), and self-efficacy (P < 0.001) have had a negative impact on influenza vaccination among HCWs. Perceived severity (P = 0.7) was higher in people with a history of influenza vaccination, while such a difference was not observed in perceived susceptibility. Higher mean age, previous vaccination history, and perceived barriers are predictors of influenza vaccine participation behavior.
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42
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Health Belief Model in Hospitals: Determining the Effective Factors on Influenza Vaccination. HEALTH SCOPE 2021. [DOI: 10.5812/jhealthscope.113759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
: The need for extensive vaccination of health care workers (HCWs) is felt more than ever. The aim of this study was to investigate the determinants of influenza vaccination using HBM in HCWs of Jahrom hospitals. This cross-sectional study was performed by multicenter method on 614 HCWs in Jahrom, southern Iran, in 2020. Data collection tools included Demographic and researcher-made Influenza Vaccination in HCWs Based on HBM Questionnaires whose validity and reliability were measured and evaluated. Analyzes have been performed using SPSS 21. Increasing age (P < 0.001) and perceived barriers (P < 0.001) have increased influenza vaccination, but perceived benefits (P = 0.002), cues to action (P = 0.001), and self-efficacy (P < 0.001) have had a negative impact on influenza vaccination among HCWs. Perceived severity (P = 0.7) was higher in people with a history of influenza vaccination, while such a difference was not observed in perceived susceptibility. Higher mean age, previous vaccination history, and perceived barriers are predictors of influenza vaccine participation behavior.
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43
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Martin ET, Cheng C, Petrie JG, Alyanak E, Gaglani M, Middleton DB, Ghamande S, Silveira FP, Murthy K, Zimmerman RK, Monto AS, Trabue C, Talbot HK, Ferdinands JM. Low Influenza Vaccine Effectiveness Against A(H3N2)-Associated Hospitalizations in 2016-2017 and 2017-2018 of the Hospitalized Adult Influenza Vaccine Effectiveness Network (HAIVEN). J Infect Dis 2021; 223:2062-2071. [PMID: 33140094 DOI: 10.1093/infdis/jiaa685] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 10/30/2020] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND The 2016-2017 and 2017-2018 influenza seasons were notable for the high number of hospitalizations for influenza A(H3N2) despite vaccine and circulating strain match. METHODS We evaluated vaccine effectiveness (VE) against hospitalization in the test-negative HAIVEN study. Nasal-throat swabs were tested by quantitative reverse transcription polymerase chain reaction (RT-PCR) for influenza and VE was determined based on odds of vaccination by generalized estimating equations. Vaccine-specific antibody was measured in a subset of enrollees. RESULTS A total of 6129 adults were enrolled from 10 hospitals. Adjusted VE against A(H3N2) was 22.8% (95% confidence interval [CI], 8.3% to 35.0%), pooled across both years and 49.4% (95% CI, 34.3% to 61.1%) against B/Yamagata. In 2017-2018, the A(H3N2) VE point estimate for the cell-based vaccine was 43.0% (95% CI, -36.3% to 76.1%; 56 vaccine recipients) compared to 24.0% (95% CI, 3.9% to 39.9%) for egg-based vaccines. Among 643 with serology data, hemagglutinin antibodies against the egg-based A(H3N2) vaccine strain were increased in influenza-negative individuals. CONCLUSIONS Low VE for the A/Hong Kong/4801/2014 vaccine virus in both A(H3N2) seasons emphasizes concerns for continued changes in H3N2 antigenic epitopes, including changes that may impact glycosylation and ultimately reduce VE.
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Affiliation(s)
- Emily T Martin
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Caroline Cheng
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Joshua G Petrie
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Elif Alyanak
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Manjusha Gaglani
- Baylor Scott and White Health, Texas A&M University Health Science Center College of Medicine, Temple, Texas, USA
| | | | - Shekhar Ghamande
- Baylor Scott and White Health, Texas A&M University Health Science Center College of Medicine, Temple, Texas, USA
| | | | | | | | - Arnold S Monto
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Christopher Trabue
- Ascension Saint Thomas, Nashville, Tennessee, USA.,Department of Medicine, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - H Keipp Talbot
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jill M Ferdinands
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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44
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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: 10.0] [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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45
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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: 2.3] [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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Feldstein LR, Ferdinands JM, Self WH, 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. Modeling the impacts of clinical influenza testing on influenza vaccine effectiveness estimates. J Infect Dis 2021; 224:2035-2042. [PMID: 34013330 DOI: 10.1093/infdis/jiab273] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 05/14/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Test-negative design studies for evaluating influenza vaccine effectiveness (VE) enroll patients with acute respiratory infection. Enrollment typically occurs before influenza status is determined, resulting in over-enrollment of influenza-negative patients. With availability of rapid and accurate molecular clinical testing, influenza status could be ascertained prior to enrollment, thus improving study efficiency. We estimate potential biases in VE when using clinical testing. METHODS We simulate data assuming 60% vaccinated, 25% of those vaccinated are influenza positive, and VE of 50%. We show the effect on VE in five scenarios. RESULTS VE is affected only when clinical testing preferentially targets patients based on both vaccination and influenza status. VE is overestimated by 10% if non-testing occurs in 39% of vaccinated influenza-positive patients and 24% of others; and if non-testing occurs in 8% of unvaccinated influenza-positive patients and 27% of others. VE is underestimated by 10% if non-testing occurs in 32% of unvaccinated influenza-negative patients and 18% of others. CONCLUSIONS Although differential clinical testing by vaccine receipt and influenza positivity may produce errors in estimated VE, bias in testing would have to be substantial and overall proportion of patients tested would have to be small to result in a meaningful difference in VE.
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Affiliation(s)
- Leora R Feldstein
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Jill M Ferdinands
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Wesley H Self
- Vanderbilt University Medical Center, Nashville, Tennessee, 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 & Critical Care, Oregon Health & 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 & 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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Sample size considerations for mid-season estimates from a large influenza vaccine effectiveness network in the United States. Vaccine 2021; 39:3324-3328. [PMID: 33994240 DOI: 10.1016/j.vaccine.2021.05.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/29/2021] [Accepted: 05/03/2021] [Indexed: 11/21/2022]
Abstract
INTRODUCTION Mid-season influenza vaccine effectiveness (VE) estimates are a useful tool to help guide annual influenza vaccine strain selection, vaccine policy, and public health messaging. We propose using a sample size-driven approach with data-driven inputs for publication of mid-season influenza VE. METHODS We used pooled inputs for VE by (sub)type and average vaccine coverage by age groups using data from eight seasons of the US Influenza VE Network to calculate sample sizes needed to estimate mid-season VE. RESULTS We estimate that 135 influenza-positive cases would be needed to detect an overall VE of 40% with 55% vaccine coverage among test-negative controls. Larger sample sizes would be required to produce reliable estimates specifically against influenza A/H3N2 and for older age groups. CONCLUSION Using an existing network, most of the recent influenza seasons in the US would facilitate valid mid-season VE estimates using the proposed sample sizes for broad age groupings.
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Ogokeh CE, Campbell AP, Feldstein LR, Weinberg GA, Staat MA, McNeal MM, Selvarangan R, Halasa NB, Englund JA, Boom JA, Azimi PH, Szilagyi PG, Harrison CJ, Williams JV, Klein EJ, Stewart LS, Sahni LC, Singer MN, Lively JY, Payne DC, Patel M. Comparison of Parental Report of Influenza Vaccination to Documented Records in Children Hospitalized With Acute Respiratory Illness, 2015-2016. J Pediatric Infect Dis Soc 2021; 10:389-397. [PMID: 33043965 PMCID: PMC9264279 DOI: 10.1093/jpids/piaa110] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Accepted: 09/01/2020] [Indexed: 11/13/2022]
Abstract
BACKGROUND Parent-reported influenza vaccination history may be valuable clinically and in influenza vaccine effectiveness (VE) studies. Few studies have assessed the validity of parental report among hospitalized children. METHODS Parents of 2597 hospitalized children 6 months-17 years old were interviewed from November 1, 2015 to June 30, 2016, regarding their child's sociodemographic and influenza vaccination history. Parent-reported 2015-2016 influenza vaccination history was compared with documented vaccination records (considered the gold standard for analysis) obtained from medical records, immunization information systems, and providers. Multivariable logistic regression analyses were conducted to determine potential factors associated with discordance between the 2 sources of vaccination history. Using a test-negative design, we estimated VE using vaccination history obtained through parental report and documented records. RESULTS According to parental report, 1718 (66%) children received the 2015-2016 influenza vaccine, and of those, 1432 (83%) had documentation of vaccine receipt. Percent agreement was 87%, with a sensitivity of 96% (95% confidence interval [CI], 95%-97%) and a specificity of 74% (95% CI, 72%-77%). In the multivariable logistic regression, study site and child's age 5-8 years were significant predictors of discordance. Adjusted VE among children who received ≥1 dose of the 2015-2016 influenza vaccine per parental report was 61% (95% CI, 43%-74%), whereas VE using documented records was 55% (95% CI, 33%-69%). CONCLUSIONS Parental report of influenza vaccination was sensitive but not as specific compared with documented records. However, VE against influenza-associated hospitalizations using either source of vaccination history did not differ substantially. Parental report is valuable for timely influenza VE studies.
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Affiliation(s)
- Constance E Ogokeh
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- Oak Ridge Institute for Science and Education Fellowship Program, Oak Ridge, Tennessee, USA
| | - Angela P Campbell
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Leora R Feldstein
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Geoffrey A Weinberg
- Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Mary A Staat
- Department of Pediatrics, University of Cincinnati College of Medicine, Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Monica M McNeal
- Department of Pediatrics, University of Cincinnati College of Medicine, Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Rangaraj Selvarangan
- Department of Pathology and Laboratory Medicine, University of Missouri-Kansas City, Children's Mercy Hospital, Kansas City, Missouri, USA
| | - Natasha B Halasa
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Janet A Englund
- Department of Pediatrics, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
| | - Julie A Boom
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
| | - Parvin H Azimi
- Department of Infectious Diseases, University of California, San Francisco Benioff Children's Hospital Oakland, Oakland, California, USA
| | - Peter G Szilagyi
- Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
- Department of Pediatrics, UCLA Mattel Children's Hospital, University of California, Los Angeles, Los Angeles, California, USA
| | - Christopher J Harrison
- Department of Pediatrics, University of Missouri-Kansas City; Division of Infectious Diseases, Children's Mercy Hospital, Kansas City, Missouri, USA
| | - John V Williams
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Eileen J Klein
- Department of Pediatrics, Seattle Children's Research Institute, Seattle, Washington, USA
- Department of Pediatrics, University of Washington School of Medicine, Seattle, Washington, USA
| | - Laura S Stewart
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Leila C Sahni
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Texas Children's Hospital, Houston, Texas, USA
| | - Monica N Singer
- Department of Infectious Diseases, University of California, San Francisco Benioff Children's Hospital Oakland, Oakland, California, USA
| | - Joana Y Lively
- Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- IHRC Inc, Atlanta, Georgia, USA
| | - Daniel C Payne
- Division of Viral Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Manish Patel
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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Gaglani M, Vasudevan A, Raiyani C, Murthy K, Chen W, Reis M, Belongia EA, McLean HQ, Jackson ML, Jackson LA, Zimmerman RK, Nowalk MP, Monto AS, Martin ET, Chung JR, Spencer S, Fry AM, Flannery B. Effectiveness of Trivalent and Quadrivalent Inactivated Vaccines Against Influenza B in the United States, 2011-2012 to 2016-2017. Clin Infect Dis 2021; 72:1147-1157. [PMID: 32006430 PMCID: PMC8028105 DOI: 10.1093/cid/ciaa102] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 01/30/2020] [Indexed: 11/13/2022] Open
Abstract
Background Since 2013, quadrivalent influenza vaccines containing 2 B viruses gradually replaced trivalent vaccines in the United States. We compared the vaccine effectiveness of quadrivalent to trivalent inactivated vaccines (IIV4 to IIV3, respectively) against illness due to influenza B during the transition, when IIV4 use increased rapidly. Methods The US Influenza Vaccine Effectiveness (Flu VE) Network analyzed 25 019 of 42 600 outpatients aged ≥6 months who enrolled within 7 days of illness onset during 6 seasons from 2011–2012. Upper respiratory specimens were tested for the influenza virus type and B lineage. Using logistic regression, we estimated IIV4 or IIV3 effectiveness by comparing the odds of an influenza B infection overall and the odds of B lineage among vaccinated versus unvaccinated participants. Over 4 seasons from 2013–2014, we compared the relative odds of an influenza B infection among IIV4 versus IIV3 recipients. Results Trivalent vaccines included the predominantly circulating B lineage in 4 of 6 seasons. During 4 influenza seasons when both IIV4 and IIV3 were widely used, the overall effectiveness against any influenza B was 53% (95% confidence interval [CI], 45–59) for IIV4 versus 45% (95% CI, 34–54) for IIV3. IIV4 was more effective than IIV3 against the B lineage not included in IIV3, but comparative effectiveness against illnesses related to any influenza B favored neither vaccine valency. Conclusions The uptake of quadrivalent inactivated influenza vaccines was not associated with increased protection against any influenza B illness, despite the higher effectiveness of quadrivalent vaccines against the added B virus lineage. Public health impact and cost-benefit analyses are needed globally.
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Affiliation(s)
- Manjusha Gaglani
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Anupama Vasudevan
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Chandni Raiyani
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Kempapura Murthy
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Wencong Chen
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | - Michael Reis
- Baylor Scott & White Health, Texas A&M University College of Medicine, Temple, Texas, USA
| | | | - Huong Q McLean
- Marshfield Clinic Research Institute, Marshfield, Wisconsin, USA
| | - Michael L Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Lisa A Jackson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA
| | - Richard K Zimmerman
- University of Pittsburgh, Schools of Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Mary Patricia Nowalk
- University of Pittsburgh, Schools of Health Sciences, Pittsburgh, Pennsylvania, USA
| | - Arnold S Monto
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Emily T Martin
- University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Jessie R Chung
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Sarah Spencer
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Alicia M Fry
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Brendan Flannery
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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50
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Liu F, Gross FL, Jefferson SN, Holiday C, Bai Y, Wang L, Zhou B, Levine MZ. Age-specific effects of vaccine egg adaptation and immune priming on A(H3N2) antibody responses following influenza vaccination. J Clin Invest 2021; 131:146138. [PMID: 33690218 DOI: 10.1172/jci146138] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/03/2021] [Indexed: 01/03/2023] Open
Abstract
A(H3N2) influenza vaccine effectiveness (VE) was low during the 2016-19 seasons and varied by age. We analyzed neutralizing antibody responses to egg- and cell-propagated A(H3N2) vaccine and circulating viruses following vaccination in 375 individuals (aged 7 months to 82 years) across all vaccine-eligible age groups in 3 influenza seasons. Antibody responses to cell- versus egg-propagated vaccine viruses were significantly reduced due to the egg-adapted changes T160K, D225G, and L194P in the vaccine hemagglutinins. Vaccine egg adaptation had a differential impact on antibody responses across the different age groups. Immunologically naive children immunized with egg-adapted vaccines mostly mounted antibodies targeting egg-adapted epitopes, whereas those previously primed with infection produced broader responses even when vaccinated with egg-based vaccines. In the elderly, repeated boosts of vaccine egg-adapted epitopes significantly reduced antibody responses to the WT cell-grown viruses. Analysis with reverse genetic viruses suggested that the response to each egg-adapted substitution varied by age. No differences in antibody responses were observed between male and female vaccinees. Here, the combination of age-specific responses to vaccine egg-adapted substitutions, diverse host immune priming histories, and virus antigenic drift affected antibody responses following vaccination and may have led to the low and variable VE against A(H3N2) viruses across different age groups.
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