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Mai G, Zhang C, Lan C, Zhang J, Wang Y, Tang K, Tang J, Zeng J, Chen Y, Cheng P, Liu S, Long H, Wen Q, Li A, Liu X, Zhang R, Xu S, Liu L, Niu Y, Yang L, Wang Y, Yin D, Sun C, Chen YQ, Shen W, Zhang Z, Du X. Characterizing the dynamics of BCR repertoire from repeated influenza vaccination. Emerg Microbes Infect 2023; 12:2245931. [PMID: 37542407 PMCID: PMC10438862 DOI: 10.1080/22221751.2023.2245931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Revised: 07/12/2023] [Accepted: 08/03/2023] [Indexed: 08/06/2023]
Abstract
Yearly epidemics of seasonal influenza cause an enormous disease burden around the globe. An understanding of the rules behind the immune response with repeated vaccination still presents a significant challenge, which would be helpful for optimizing the vaccination strategy. In this study, 34 healthy volunteers with 16 vaccinated were recruited, and the dynamics of the BCR repertoire for consecutive vaccinations in two seasons were tracked. In terms of diversity, length, network, V and J gene segments usage, somatic hypermutation (SHM) rate and isotype, it was found that the overall changes were stronger in the acute phase of the first vaccination than the second vaccination. However, the V gene segments of IGHV4-39, IGHV3-9, IGHV3-7 and IGHV1-69 were amplified in the acute phase of the first vaccination, with IGHV3-7 dominant. On the other hand, for the second vaccination, the changes were dominated by IGHV1-69, with potential for coding broad neutralizing antibody. Additional analysis indicates that the application of V gene segment for IGHV3-7 in the acute phase of the first vaccination was due to the elevated usage of isotypes IgM and IgG3. While for IGHV1-69 in the second vaccination, it was contributed by isotypes IgG1 and IgG2. Finally, 41 public BCR clusters were identified in the vaccine group, with both IGHV3-7 and IGHV1-69 were involved and representative complementarity determining region 3 (CDR3) motifs were characterized. This study provides insights into the immune response dynamics following repeated influenza vaccination in humans and can inform universal vaccine design and vaccine strategies in the future.
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Affiliation(s)
- Guoqin Mai
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Chi Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Chunhong Lan
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Center for Precision Medicine, Guangdong Academy of Medical Sciences, Medical Research Institute, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, People’s Republic of China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
| | - Jie Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yuanyuan Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Kang Tang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Jing Tang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Jinfeng Zeng
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yilin Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Peiwen Cheng
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Shuning Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Haoyu Long
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Qilan Wen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Aqin Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Xuan Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Ruitong Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Shuyang Xu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Lin Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yanlan Niu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Lan Yang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yihan Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Di Yin
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Caijun Sun
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Yao-Qing Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
| | - Wei Shen
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, People’s Republic of China
| | - Zhenhai Zhang
- Department of Bioinformatics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Center for Precision Medicine, Guangdong Academy of Medical Sciences, Medical Research Institute, Guangdong Provincial People's Hospital, Southern Medical University, Guangzhou, People’s Republic of China
- Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, People’s Republic of China
- Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Southern Medical University, Guangzhou, People’s Republic of China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, People’s Republic of China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, People’s Republic of China
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, People’s Republic of China
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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: 23] [Impact Index Per Article: 23.0] [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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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: 8] [Impact Index Per Article: 4.0] [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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Sugishita Y, Sugawara T. Effectiveness and cost-effectiveness of influenza vaccination for elderly people. Vaccine 2021; 39:7531-7540. [PMID: 34857422 DOI: 10.1016/j.vaccine.2021.09.054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 09/17/2021] [Accepted: 09/21/2021] [Indexed: 10/19/2022]
Abstract
For elderly people who have low incidence of influenza, calculation of credible vaccine effectiveness (VE) sometimes becomes difficult. Currently, VE for elderly people is insufficient to ascertain the precise efficacy specifically. Cost-effectiveness of influenza vaccination of elderly people is discussed widely in terms of topics and areas. This report describes research results demonstrating influenza vaccination effectiveness among elderly people based on recent findings. Newly available influenza vaccination for elderly people appears to be cost-effective compared with that of trivalent inactiveted influenza vaccine. Overall, for all influenza virus types, it remains unclear whether influenza vaccination shows high VE. A decreasing effect of repeated vaccination was confirmed partially by test negative design and a serological study of cohorts. However, some studies have found no such decreasing effect. Measurement of VE and subsequent analysis of the cost-effectiveness of influenza vaccination for elderly people requires long-term monitoring using serological studies and test negative design.
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Martínez-Baz I, Navascués A, Casado I, Aguinaga A, Ezpeleta C, Castilla J. Simple models to include influenza vaccination history when evaluating the effect of influenza vaccination. ACTA ACUST UNITED AC 2021; 26. [PMID: 34387185 PMCID: PMC8365179 DOI: 10.2807/1560-7917.es.2021.26.32.2001099] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Background Most reports of influenza vaccine effectiveness consider current-season vaccination only. Aim We evaluated a method to estimate the effect of influenza vaccinations (EIV) considering vaccination history. Methods We used a test-negative design with well-documented vaccination history to evaluate the average EIV over eight influenza seasons (2011/12–2018/19; n = 10,356). Modifying effect was considered as difference in effects of vaccination in current and previous seasons and current-season vaccination only. We also explored differences between current-season estimates excluding from the reference category people vaccinated in any of the five previous seasons and estimates without this exclusion or only for one or three previous seasons. Results The EIV was 50%, 45% and 38% in people vaccinated in the current season who had previously received none, one to two and three to five doses, respectively, and it was 30% and 43% for one to two and three to five prior doses only. Vaccination in at least three previous seasons reduced the effect of current-season vaccination by 12 percentage points overall, 31 among outpatients, 22 in 9–65 year-olds, and 23 against influenza B. Including people vaccinated in previous seasons only in the unvaccinated category underestimated EIV by 9 percentage points on average (31% vs 40%). Estimates considering vaccination of three or five previous seasons were similar. Conclusions Vaccine effectiveness studies should consider influenza vaccination in previous seasons, as it can retain effect and is often an effect modifier. Vaccination status in three categories (current season, previous seasons only, unvaccinated) reflects the whole EIV.
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Affiliation(s)
- Iván Martínez-Baz
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Pamplona, Spain.,Instituto de Salud Pública de Navarra, Pamplona, Spain
| | - Ana Navascués
- Servicio de Microbiología Clínica, Complejo Hospitalario de Navarra, Pamplona, Spain.,Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Itziar Casado
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Pamplona, Spain.,Instituto de Salud Pública de Navarra, Pamplona, Spain
| | - Aitziber Aguinaga
- Servicio de Microbiología Clínica, Complejo Hospitalario de Navarra, Pamplona, Spain.,Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Carmen Ezpeleta
- Servicio de Microbiología Clínica, Complejo Hospitalario de Navarra, Pamplona, Spain.,Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Jesús Castilla
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Pamplona, Spain.,Instituto de Salud Pública de Navarra, Pamplona, Spain
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Kuliese M, Mickiene A, Jancoriene L, Zablockiene B, Gefenaite G. Age-Specific Seasonal Influenza Vaccine Effectiveness against Different Influenza Subtypes in the Hospitalized Population in Lithuania during the 2015-2019 Influenza Seasons. Vaccines (Basel) 2021; 9:vaccines9050455. [PMID: 34064455 PMCID: PMC8147944 DOI: 10.3390/vaccines9050455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 04/23/2021] [Accepted: 04/30/2021] [Indexed: 11/23/2022] Open
Abstract
Background: Continuous monitoring of seasonal influenza vaccine effectiveness (SIVE) is needed due to the changing nature of influenza viruses and it supports the decision on the annual update of vaccine composition. Age-specific SIVE was evaluated against different influenza subtypes in the hospitalized population in Lithuania during four influenza seasons. Methods: A test-negative case-control study design was used. SIVE and its 95% confidence intervals (95% CI) were calculated as (1 – odds ratio (OR)) × 100%. Results: Adjusted SIVE in 18–64-year-old individuals against influenza A, A(H1N1)pdm09 and B/Yamagata were 78.0% (95% CI: 1.7; 95.1%), 88.6% (95% CI: −47.4; 99.1%), and 76.8% (95% CI: −109.9; 97.4%), respectively. Adjusted SIVE in individuals aged 65 years and older against influenza A, influenza B, and B/Yamagata were 22.6% (95% CI: −36.5; 56.1%), 75.3% (95% CI: 12.2; 93.1%) and 73.1% (95% CI: 3.2; 92.5%), respectively. Unadjusted SIVE against influenza A(H3N2) among 18–64-year-old patients was 44.8% (95% CI: −171.0; 88.8%) and among those aged 65 years and older was 5.0% (95% CI: −74.5; 48.3%). Conclusions: Point estimates suggest high SIVE against influenza A in 18–64-year-old participants, and against influenza B and B/Yamagata in those 65 years old and older.
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Affiliation(s)
- Monika Kuliese
- Department of Infectious Diseases, Lithuanian University of Health Sciences, Baltijos Street 120, 47116 Kaunas, Lithuania; (A.M.); (G.G.)
- Correspondence:
| | - Aukse Mickiene
- Department of Infectious Diseases, Lithuanian University of Health Sciences, Baltijos Street 120, 47116 Kaunas, Lithuania; (A.M.); (G.G.)
| | - Ligita Jancoriene
- Clinic of Infectious Diseases and Dermatovenerology, Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, Santariskiu Street 14, 08406 Vilnius, Lithuania; (L.J.); (B.Z.)
- Center of Infectious Diseases, Vilnius University Hospital Santaros Klinikos, Santariskiu Street 14, 08406 Vilnius, Lithuania
| | - Birute Zablockiene
- Clinic of Infectious Diseases and Dermatovenerology, Faculty of Medicine, Institute of Clinical Medicine, Vilnius University, Santariskiu Street 14, 08406 Vilnius, Lithuania; (L.J.); (B.Z.)
- Center of Infectious Diseases, Vilnius University Hospital Santaros Klinikos, Santariskiu Street 14, 08406 Vilnius, Lithuania
| | - Giedre Gefenaite
- Department of Infectious Diseases, Lithuanian University of Health Sciences, Baltijos Street 120, 47116 Kaunas, Lithuania; (A.M.); (G.G.)
- Department of Health Sciences, Faculty of Medicine, Lund University, Box 157, 22100 Lund, Sweden
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Okoli GN, Racovitan F, Abdulwahid T, Hyder SK, Lansbury L, Righolt CH, Mahmud SM, Nguyen-Van-Tam JS. Decline in Seasonal Influenza Vaccine Effectiveness With Vaccination Program Maturation: A Systematic Review and Meta-analysis. Open Forum Infect Dis 2021; 8:ofab069. [PMID: 33738320 PMCID: PMC7953658 DOI: 10.1093/ofid/ofab069] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 02/03/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Evidence suggests that repeated influenza vaccination may reduce vaccine effectiveness (VE). Using influenza vaccination program maturation (PM; number of years since program inception) as a proxy for population-level repeated vaccination, we assessed the impact on pooled adjusted end-season VE estimates from outpatient test-negative design studies. METHODS We systematically searched and selected full-text publications from January 2011 to February 2020 (PROSPERO: CRD42017064595). We obtained influenza vaccination program inception year for each country and calculated PM as the difference between the year of deployment and year of program inception. We categorized PM into halves (cut at the median), tertiles, and quartiles and calculated pooled VE using an inverse-variance random-effects model. The primary outcome was pooled VE against all influenza. RESULTS We included 72 articles from 11 931 citations. Across the 3 categorizations of PM, a lower pooled VE against all influenza for all patients was observed with PM. Substantially higher reductions were observed in older adults (≥65 years). We observed similar results for A(H1N1)pdm09, A(H3N2), and influenza B. CONCLUSIONS The evidence suggests that influenza VE declines with vaccination PM. This study forms the basis for further discussions and examinations of the potential impact of vaccination PM on seasonal VE.
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Affiliation(s)
- George N Okoli
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, Manitoba, Canada
- George and Fay Yee Centre for Healthcare Innovation, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Florentin Racovitan
- Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Tiba Abdulwahid
- George and Fay Yee Centre for Healthcare Innovation, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Syed K Hyder
- Department of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, United Kingdom
| | - Louise Lansbury
- Department of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, United Kingdom
| | - Christiaan H Righolt
- Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, Manitoba, Canada
- Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Salaheddin M Mahmud
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, Manitoba, Canada
- Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Jonathan S Nguyen-Van-Tam
- Department of Epidemiology and Public Health, University of Nottingham School of Medicine, Nottingham, United Kingdom
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Okoli GN, Racovitan F, Abdulwahid T, Righolt CH, Mahmud SM. Variable seasonal influenza vaccine effectiveness across geographical regions, age groups and levels of vaccine antigenic similarity with circulating virus strains: A systematic review and meta-analysis of the evidence from test-negative design studies after the 2009/10 influenza pandemic. Vaccine 2021; 39:1225-1240. [PMID: 33494964 DOI: 10.1016/j.vaccine.2021.01.032] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 12/21/2020] [Accepted: 01/08/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND We examined the influence of some factors on seasonal influenza vaccine effectiveness (VE) from test-negative design (TND) studies. METHODS We systematically searched for full-text publications of VE against laboratory-confirmed influenza from TND studies in outpatient settings after the 2009/10 influenza pandemic. Two reviewers independently selected and extracted data from the included studies. We calculated pooled adjusted VE across geographical regions, age groups and levels of vaccine antigenic similarity with circulating virus strains, using an inverse variance, random-effects model. RESULTS We included 76 full-text articles from 11,931 citations. VE estimates against A(H1N1)pdm09, A(H3N2), influenza B, and all influenza were homogenous and point pooled VE higher in the Southern hemisphere compared with the Northern hemisphere. The difference in pooled VE between the Southern and Northern hemispheres was statistically significant for A(H3N2), influenza B, and all influenza. A consistent pattern was observed in pooled VE across both hemispheres and continents, with the highest point pooled VE being against A(H1N1)pdm09, followed by influenza B, and lowest against A(H3N2). A nearly consistent pattern was observed in pooled VE across age groups in the Northern hemisphere, with pooled VE mostly decreasing with age. Point pooled VE against A(H3N2), influenza B, and all influenza were statistically significantly higher when vaccine was antigenically similar to circulating virus strains compared with when antigenically dissimilar. Similar pattern was observed in the Northern hemisphere, but there was a lack of data from the Southern hemisphere. CONCLUSION Consistent patterns appear to exist in seasonal influenza VE across regions, age groups, and levels of vaccine antigenic similarity with circulating virus strains, with best vaccine performance against A(H1N1)pdm09 and worst against A(H3N2). The evidence highlights the need to consider geographical location, age, and vaccine antigenic similarity with circulating virus strains when designing and evaluating influenza VE studies.
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Affiliation(s)
- G N Okoli
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada; George and Fay Yee Centre for Healthcare Innovation, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada; Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, MB, Canada
| | - F Racovitan
- Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, MB, Canada
| | - T Abdulwahid
- George and Fay Yee Centre for Healthcare Innovation, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - C H Righolt
- Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, MB, Canada; Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - S M Mahmud
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada; Vaccine and Drug Evaluation Centre, University of Manitoba, Winnipeg, MB, Canada; Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
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9
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Okoli GN, Racovitan F, Righolt CH, Mahmud SM. Variations in Seasonal Influenza Vaccine Effectiveness due to Study Characteristics: A Systematic Review and Meta-analysis of Test-Negative Design Studies. Open Forum Infect Dis 2020; 7:ofaa177. [PMID: 32704509 PMCID: PMC7367680 DOI: 10.1093/ofid/ofaa177] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Accepted: 05/19/2020] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Study characteristics influence vaccine effectiveness (VE) estimation. We examined the influence of some of these on seasonal influenza VE estimates from test-negative design (TND) studies. METHODS We systematically searched bibliographic databases and websites for full-text publications of TND studies on VE against laboratory-confirmed seasonal influenza in outpatients after the 2009 pandemic influenza. We followed the Cochrane Handbook for Systematic Reviews of Interventions guidelines. We examined influence of source of vaccination information, respiratory specimen swab time, and covariate adjustment on VE. We calculated pooled adjusted VE against H1N1 and H3N2 influenza subtypes, influenza B, and all influenza using an inverse-variance random-effects model. RESULTS We included 70 full-text articles. Pooled VE against H1N1 and H3N2 influenza subtypes, influenza B, and all influenza was higher for studies that used self-reported vaccination than for those that used medical records. Pooled VE was higher with respiratory specimen collection within ≤7 days vs ≤4 days of symptom onset, but the opposite was observed for H1N1. Pooled VE was higher for studies that adjusted for age but not for medical conditions compared with those that adjusted for both. There was, however, a lack of statistical significance in almost all differences in pooled VE between compared groups. CONCLUSIONS The available evidence is not strong enough to conclude that influenza VE from TND studies varies by source of vaccination information, respiratory specimen swab time, or adjustment for age/medical conditions. The evidence is, however, indicative that these factors ought to be considered while designing or evaluating TND studies of influenza VE.
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Affiliation(s)
- George N Okoli
- George and Fay Yee Centre for Healthcare Innovation, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- College of Pharmacy, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Vaccine and Drug Evaluation Centre, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Florentin Racovitan
- Vaccine and Drug Evaluation Centre, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Christiaan H Righolt
- Vaccine and Drug Evaluation Centre, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Salaheddin M Mahmud
- Vaccine and Drug Evaluation Centre, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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Boravleva EY, Lunitsin AV, Kaplun AP, Bykova NV, Krasilnikov IV, Gambaryan AS. Immune Response and Protective Efficacy of Inactivated and Live Influenza Vaccines Against Homologous and Heterosubtypic Challenge. BIOCHEMISTRY (MOSCOW) 2020; 85:553-566. [PMID: 32571185 DOI: 10.1134/s0006297920050041] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Inactivated (whole-virion, split, subunit, and adjuvanted) vaccines and live attenuated vaccine were tested in parallel to compare their immunogenicity and protective efficacy. Homologous and heterosubtypic protection against the challenge with influenza H5N1 and H1N1 viruses in a mouse model were studied. Single immunization with live or inactivated whole-virion H5N1 vaccine elicited a high level of serum antibodies and provided complete protection against the challenge with the lethal A/Chicken/Kurgan/3/05 (H5N1) virus, whereas application of a single dose of the split vaccine was much less effective. Adjuvants increased the antibody levels. Addition of the Iso-SANP adjuvant to the split vaccine led to a paradoxical outcome: it increased the antibody levels but reduced the protective effect of the vaccine. All tested adjuvants shifted the ratio between IgG1 and IgG2a antibodies. Immunization with any of the tested heterosubtypic live viruses provided partial protection against the H5N1 challenge and significantly reduced mouse mortality, while inactivated H1N1 vaccine offered no protection at all. More severe course of illness and earlier death were observed in mice after immunization with adjuvanted subunit vaccines followed by the challenge with the heterosubtypic virus compared to challenged unvaccinated animals.
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Affiliation(s)
- E Y Boravleva
- Chumakov Federal Scientific Center for Research and Development of Immune and Biological Products, Russian Academy of Sciences, Moscow, 108819, Russia
| | - A V Lunitsin
- FSBSI Federal Research Center for Virology and Microbiology, Volginsky, Vladimir Region, 601125, Russia
| | - A P Kaplun
- Lomonosov Moscow University of Fine Chemical Technology, Moscow, 119571, Russia
| | - N V Bykova
- Lomonosov Moscow University of Fine Chemical Technology, Moscow, 119571, Russia
| | - I V Krasilnikov
- Saint Petersburg Institute of Vaccines and Sera, FMBA, St.-Petersburg, 198320, Russia
| | - A S Gambaryan
- Chumakov Federal Scientific Center for Research and Development of Immune and Biological Products, Russian Academy of Sciences, Moscow, 108819, Russia.
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11
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Negative effect on immune response of repeated influenza vaccination and waning effectiveness in interseason for elderly people. Vaccine 2020; 38:3759-3765. [PMID: 32276801 DOI: 10.1016/j.vaccine.2020.03.025] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 01/23/2020] [Accepted: 03/10/2020] [Indexed: 11/20/2022]
Abstract
BACKGROUND Through test negative designs for visiting a doctor because of influenza-like illness, many studies have found decreasing efficacy of repeated vaccination. Furthermore, waning effectiveness during interseason periods has been reported. This study was conducted to confirm negative effects of repeated vaccination in individuals with the same vaccine strain and to measure waning effects. METHODS Our cohort includes 66 participants older than 65 years old recruited from an outpatient department of one hospital. All were vaccinated, with hemagglutination inhibition (HI) antibody titers measured from 2001/02 season through the 2003/04 season. HI antibody titers were measured three times in one season: pre-vaccination, post-vaccination, and post-epidemic. To test negative effects of immune response to the repeated vaccination, differences between protection rates and differences between response rates were analyzed for individuals in the two consecutive seasons. For the test of waning effectiveness, we measured the difference in geometric mean titers of HI antibody between post-epidemic results and pre-vaccination results obtained in the following season. RESULTS Protection rates were 40-55% in A/New Caledonia/20/99 and ≥75% in A/Panama/2007/99 by repeated vaccination. In A/New Caledonia/20/99 and A/Panama/2007/99 in the 2003/04 season, significant decreases were found in protection rates from the earlier seasons, although the rate for A/Panama/2007/99 in the 2002/03 season increased significantly from that of the prior season. The respective response rates in the 2003/04 season in A/New Caledonia/20/99, and in the 2002/03 and 2003/04 seasons in A/Panama/2007/99 decreased significantly from those of earlier seasons. Regarding waning effectiveness, antibody titers for A/New Caledonia/20/99 in 2003/04 season, and A/Panama/2007/99 in 2002/03 and 2003/04 seasons decreased significantly to 37.0-66.7%. CONCLUSION Results show significant negative effects of immune response by repeated vaccination and show significant waning effectiveness during the interseason for individuals with the same strain of influenza type A. The proportion of elderly people with HI antibody titers of ≥1:40 might be maintained by repeated influenza vaccination.
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12
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Redlberger-Fritz M, Kundi M, Popow-Kraupp T. Heterogeneity of Circulating Influenza Viruses and Their Impact on Influenza Virus Vaccine Effectiveness During the Influenza Seasons 2016/17 to 2018/19 in Austria. Front Immunol 2020; 11:434. [PMID: 32256493 PMCID: PMC7092378 DOI: 10.3389/fimmu.2020.00434] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 02/25/2020] [Indexed: 11/13/2022] Open
Abstract
The constantly changing pattern in the dominance of viral strains and their evolving subclades during the seasons substantially influences influenza vaccine effectiveness (IVE). In order to further substantiate the importance of detailed data of genetic virus characterization for IVE estimates during the seasons, we performed influenza virus type and subtype specific IVE estimates. IVE estimates were assessed using a test-negative case-control design, in the context of the intraseasonal changes of the heterogeneous mix of circulating influenza virus strains for three influenza seasons (2016/17 to 2018/19) in Austria. Adjusted overall IVE over the three seasons 2016/17, 2017/18, and 2018/19 were -26, 39, and 63%, respectively. In accordance with the changing pattern of the circulating strains a broad range of overall and subtype specific IVEs was obtained: A(H3N2) specific IVE ranged between -26% for season 2016/17 to 58% in season 2018/19, A(H1N1)pdm09 specific IVE was 25% for the season 2017/18 and 65% for the season 2018/19 and Influenza B specific IVE for season 2017/18 was 45%. The results obtained in our study over the three seasons demonstrate the increasingly complex dynamic of the ever changing genetic pattern of the circulating influenza viruses and their influence on IVE estimates. This emphasizes the importance of detailed genetic virus surveillance for reliable IVE estimates.
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Affiliation(s)
| | - Michael Kundi
- Department of Environmental Health, Medical University Vienna, Vienna, Austria
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13
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Castilla J, Portillo ME, Casado I, Pozo F, Navascués A, Adelantado M, Gómez Ibáñez C, Ezpeleta C, Martínez-Baz I. Effectiveness of the current and prior influenza vaccinations in Northern Spain, 2018–2019. Vaccine 2020; 38:1925-1932. [DOI: 10.1016/j.vaccine.2020.01.028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 01/07/2020] [Accepted: 01/08/2020] [Indexed: 10/25/2022]
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Chua H, Feng S, Lewnard JA, Sullivan SG, Blyth CC, Lipsitch M, Cowling BJ. The Use of Test-negative Controls to Monitor Vaccine Effectiveness: A Systematic Review of Methodology. Epidemiology 2020; 31:43-64. [PMID: 31609860 PMCID: PMC6888869 DOI: 10.1097/ede.0000000000001116] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
BACKGROUND The test-negative design is an increasingly popular approach for estimating vaccine effectiveness (VE) due to its efficiency. This review aims to examine published test-negative design studies of VE and to explore similarities and differences in methodological choices for different diseases and vaccines. METHODS We conducted a systematic search on PubMed, Web of Science, and Medline, for studies reporting the effectiveness of any vaccines using a test-negative design. We screened titles and abstracts and reviewed full texts to identify relevant articles. We created a standardized form for each included article to extract information on the pathogen of interest, vaccine(s) being evaluated, study setting, clinical case definition, choices of cases and controls, and statistical approaches used to estimate VE. RESULTS We identified a total of 348 articles, including studies on VE against influenza virus (n = 253), rotavirus (n = 48), pneumococcus (n = 24), and nine other pathogens. Clinical case definitions used to enroll patients were similar by pathogens of interest but the sets of symptoms that defined them varied substantially. Controls could be those testing negative for the pathogen of interest, those testing positive for nonvaccine type of the pathogen of interest, or a subset of those testing positive for alternative pathogens. Most studies controlled for age, calendar time, and comorbidities. CONCLUSIONS Our review highlights similarities and differences in the application of the test-negative design that deserve further examination. If vaccination reduces disease severity in breakthrough infections, particular care must be taken in interpreting vaccine effectiveness estimates from test-negative design studies.
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Affiliation(s)
- Huiying Chua
- From the World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Shuo Feng
- From the World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Joseph A Lewnard
- Division of Epidemiology, School of Public Health, University of California, Berkeley, Berkeley, CA
| | - Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, and Doherty Department, University of Melbourne, at the Peter Doherty Institute for Infection and Immunity, Melbourne, Victoria, Australia
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, CA
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Christopher C Blyth
- Division of Paediatrics, School of Medicine, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, Perth, Western Australia, Australia
- Department of Infectious Diseases, Perth Children's Hospital, Perth, Western Australia, Australia
| | - Marc Lipsitch
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA
- Center for Communicable Disease Dynamics, Harvard T. H. Chan School of Public Health, Boston, MA
| | - Benjamin J Cowling
- From the World Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China
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Ainslie KEC, Haber M, Orenstein WA. Challenges in estimating influenza vaccine effectiveness. Expert Rev Vaccines 2019; 18:615-628. [PMID: 31116070 PMCID: PMC6594904 DOI: 10.1080/14760584.2019.1622419] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Accepted: 05/20/2019] [Indexed: 12/25/2022]
Abstract
Introduction: Influenza vaccination is regarded as the most effective way to prevent influenza infection. Due to the rapid genetic changes that influenza viruses undergo, seasonal influenza vaccines must be reformulated and re-administered annually necessitating the evaluation of influenza vaccine effectiveness (VE) each year. The estimation of influenza VE presents numerous challenges. Areas Covered: This review aims to identify, discuss, and, where possible, offer suggestions for dealing with the following challenges in estimating influenza VE: different outcomes of interest against which VE is estimated, study designs used to assess VE, sources of bias and confounding, repeat vaccination, waning immunity, population level effects of vaccination, and VE in at-risk populations. Expert Opinion: The estimation of influenza VE has improved with surveillance networks, better understanding of sources of bias and confounding, and the implementation of advanced statistical methods. Future research should focus on better estimates of the indirect effects of vaccination, the biological effects of vaccination, and how vaccines interact with the immune system. Specifically, little is known about how influenza vaccination impacts an individual's infectiousness, how vaccines wane over time, and the impact of repeated vaccination.
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Affiliation(s)
- Kylie E. C. Ainslie
- Research Associate in Influenza Disease Dynamics, MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Norfolk Place, London W2 1PG, UK
| | - Michael Haber
- Professor, Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, 1518 Clifton Rd NE, Atlanta, GA 30322, USA
| | - Walt A. Orenstein
- Professor, Division of Infectious Diseases, Department of Medicine, School of Medicine, Emory University, 1462 Clifton Rd NE, Atlanta, GA 30322, USA
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Puig-Barberà J, Mira-Iglesias A, Burtseva E, Cowling BJ, Serhat U, Ruiz-Palacios GM, Launay O, Kyncl J, Koul P, Siqueira MM, Sominina A. Influenza epidemiology and influenza vaccine effectiveness during the 2015-2016 season: results from the Global Influenza Hospital Surveillance Network. BMC Infect Dis 2019; 19:415. [PMID: 31088481 PMCID: PMC6518734 DOI: 10.1186/s12879-019-4017-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 04/24/2019] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND The Global Influenza Hospital Surveillance Network is an international platform whose primary objective is to study severe cases of influenza requiring hospitalization. METHODS During the 2015-2016 influenza season, 11 sites in the Global Influenza Hospital Surveillance Network in nine countries (Russian Federation, Czech Republic, Turkey, France, China, Spain, Mexico, India, and Brazil) participated in a prospective, active-surveillance, hospital-based epidemiological study. Influenza infection was confirmed by reverse transcription-polymerase chain reaction. Influenza vaccine effectiveness (IVE) against laboratory-confirmed influenza was estimated using a test-negative approach. RESULTS 9882 patients with laboratory results were included of which 2415 (24.4%) were positive for influenza, including 1415 (14.3%) for A(H1N1)pdm09, 235 (2.4%) for A(H3N2), 180 (1.8%) for A not subtyped, 45 (0.5%) for B/Yamagata-lineage, 532 (5.4%) for B/Victoria-lineage, and 33 (0.3%) for B not subtyped. Of included admissions, 39% were < 5 years of age and 67% had no underlying conditions. The odds of being admitted with influenza were higher among pregnant than non-pregnant women (odds ratio, 2.82 [95% confidence interval (CI), 1.90 to 4.19]). Adjusted IVE against influenza-related hospitalization was 16.3% (95% CI, 0.4 to 29.7). Among patients targeted for influenza vaccination, adjusted IVE against hospital admission with influenza was 16.2% (95% CI, - 3.6 to 32.2) overall, 23.0% (95% CI, - 3.3 to 42.6) against A(H1N1)pdm09, and - 25.6% (95% CI, - 86.3 to 15.4) against B/Victoria lineage. CONCLUSIONS The 2015-2016 influenza season was dominated by A(H1N1)pdm09 and B/Victoria-lineage. Hospitalization with influenza often occurred in healthy and young individuals, and pregnant women were at increased risk of influenza-related hospitalization. Influenza vaccines provided low to moderate protection against hospitalization with influenza and no protection against the predominant circulating B lineage, highlighting the need for more effective and broader influenza vaccines.
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Affiliation(s)
- Joan Puig-Barberà
- Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana, FISABIO, Valencia, Spain
| | - Ainara Mira-Iglesias
- Fundación para el Fomento de la Investigación Sanitaria y Biomédica de la Comunidad Valenciana, FISABIO, Valencia, Spain
| | - Elena Burtseva
- Ivanovsky Institute of Virology FSBI “N.F, Gamaleya NRCEM” Ministry of Health, Moscow, Russian Federation
| | - Benjamin J. Cowling
- School of Public Health, Li Ka Shing Faculty of Medicine, Hong Kong, Hong Kong, Special Administrative Region of China
| | - Unal Serhat
- Turkish Society of Internal Medicine, Ankara, Turkey
| | - Guillermo Miguel Ruiz-Palacios
- Salvador Zubirán National Institute of Medical Sciences and Nutrition (INCMNSZ), Vasco de Quiroga 15, Belisario Domínguez Sección 16, 14080 Tlalpan, CDMX Mexico
| | - Odile Launay
- INSERM, F-CRIN, Réseau National d’Investigation Clinique en Vaccinologie (I-REIVAC), CIC Cochin Pasteur, Paris, France and Université Paris Descartes, Sorbonne Paris Cité and Assistance Publique Hôpitaux de Paris, Hôpital Cochin, Paris, France
| | - Jan Kyncl
- National Institute of Public Health, Prague, Czech Republic
| | - Parvaiz Koul
- Department of Internal and Pulmonary Medicine, Sher-i-Kashmir Institute of Medical Sciences (SKIMS), Soura, Bemina, Srinagar, Jammu & Kashmir 190011 India
| | | | - Anna Sominina
- Research Institute of Influenza, WHO National Influenza Centre of Russia and Ministry of Healthcare of the Russian Federation, St. Petersburg, Russian Federation
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Casado I, Domínguez Á, Toledo D, Chamorro J, Astray J, Egurrola M, Fernández-Sierra MA, Martín V, Morales-Suárez-Varela M, Godoy P, Castilla J. Repeated influenza vaccination for preventing severe and fatal influenza infection in older adults: a multicentre case-control study. CMAJ 2018; 190:E3-E12. [PMID: 29311098 DOI: 10.1503/cmaj.170910] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/11/2017] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND The effectiveness of repeated vaccination for influenza to prevent severe cases remains unclear. We evaluated the effectiveness of influenza vaccination on preventing admissions to hospital for influenza and reducing disease severity. METHODS We conducted a case-control study in 20 hospitals in Spain during the 2013/14 and 2014/15 influenza seasons. Community-dwelling adults aged 65 years or older who were admitted to hospital for laboratory-confirmed influenza were matched with inpatient controls by sex, age, hospital and admission date. The effectiveness of vaccination in the current and 3 previous seasons in preventing influenza was estimated for inpatients with nonsevere influenza and for those with severe influenza who were admitted to intensive care units (ICUs) or who died. RESULTS We enrolled 130 inpatients with severe and 598 with nonsevere influenza who were matched to 333 and 1493 controls, respectively. Compared with patients who were unvaccinated in the current and 3 previous seasons, adjusted effectiveness of influenza vaccination in the current and any previous season was 31% (95% confidence interval [CI] 13%-46%) in preventing admission to hospital for nonsevere influenza, 74% (95% CI 42%-88%) in preventing admissions to ICU and 70% (95% CI 34%-87%) in preventing death. Vaccination in the current season only had no significant effect on cases of severe influenza. Among inpatients with influenza, vaccination in the current and any previous season reduced the risk of severe outcomes (adjusted odds ratio 0.45, 95% CI 0.26-0.76). INTERPRETATION Among older adults, repeated vaccination for influenza was twice as effective in preventing severe influenza compared with nonsevere influenza in patients who were admitted to hospital, which is attributable to the combination of the number of admissions to hospital for influenza that were prevented and reduced disease severity. These results reinforce recommendations for annual vaccination for influenza in older adults.
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Affiliation(s)
- Itziar Casado
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Ángela Domínguez
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Diana Toledo
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Judith Chamorro
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Jenaro Astray
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Mikel Egurrola
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - María Amelia Fernández-Sierra
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Vicente Martín
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - María Morales-Suárez-Varela
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Pere Godoy
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain
| | - Jesús Castilla
- Instituto de Salud Pública de Navarra - IdiSNA (Casado, Castilla), Pamplona, Spain; Departament de Medicina (Domínguez, Toledo), Universitat de Barcelona, Barcelona, Spain; Complejo Hospitalario de Navarra (Chamorro), Pamplona, Spain; Subdirección General de Epidemiología (Astray), Madrid, Spain; Hospital de Galdakao-Usansolo (Egurrola), Vizcaya, Spain; Complejo Hospitalario Universitario de Granada (Fernández-Sierra), Granada, Spain; Instituto de Biomedicina, Universidad de León (Martín), León, Spain; Departament de Medicina Preventiva (Morales-Suárez-Varela), Universitat de Valencia, Valencia, Spain; Agència de Salut Pública de Catalunya (Godoy), Institut de Recerca Biomèdica de Lleida, Lleida, Spain; CIBER Epidemiología y Salud Pública - CIBERESP (Casado, Domínguez, Toledo, Martín, Morales-Suárez-Varela, Godoy, Castilla), Madrid, Spain.
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