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McGovern I, Chastek B, Bancroft T, Webb N, Imran M, Pelton SI, Haag MDM. Relative vaccine effectiveness of MF59®-adjuvanted vs high-dose trivalent inactivated influenza vaccines for prevention of test-confirmed influenza hospitalizations during the 2017-2020 influenza seasons. Int J Infect Dis 2024:107160. [PMID: 38969330 DOI: 10.1016/j.ijid.2024.107160] [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: 03/19/2024] [Revised: 06/27/2024] [Accepted: 06/28/2024] [Indexed: 07/07/2024] Open
Abstract
OBJECTIVES This study evaluated relative vaccine effectiveness (rVE) of MF59-adjuvanted trivalent inactivated influenza vaccine (aTIV) vs high-dose trivalent inactivated influenza vaccine (HD-TIV) for prevention of test-confirmed influenza emergency department visits and/or inpatient admissions ("ED/IP") and for IP admissions alone pooled across the 2017-2020 influenza seasons. Exploratory individual season analyses were also performed. METHODS This retrospective test-negative design study included US adults age ≥65 years vaccinated with aTIV or HD-TIV who presented to an ED or IP setting with acute respiratory or febrile illness during the 2017-2020 influenza seasons. Test-positive cases and test-negative controls were grouped by vaccine received. The rVE of aTIV vs HD-TIV was evaluated using a combination of inverse probability of treatment weighting and logistic regression to adjust for potential confounders. RESULTS Pooled analyses over the 3 seasons found no significant differences in the rVE of aTIV vs HD-TIV for prevention of test-confirmed influenza ED/IP (-2.5% [-19.6, 12.2]) visits and admissions or IP admissions alone (-1.6% [-22.5, 15.7]). The exploratory individual season analyses also showed no significant differences. CONCLUSIONS Evidence from the 2017-2020 influenza seasons indicates aTIV and HD-TIV are comparable for prevention of test-confirmed influenza ED/IP visits in US adults age ≥65 years.
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Stein AN, Mills CW, McGovern I, McDermott KW, Dean A, Bogdanov AN, Sullivan SG, Haag MDM. Relative Vaccine Effectiveness of Cell- vs Egg-Based Quadrivalent Influenza Vaccine Against Test-Confirmed Influenza Over 3 Seasons Between 2017 and 2020 in the United States. Open Forum Infect Dis 2024; 11:ofae175. [PMID: 38698895 PMCID: PMC11064727 DOI: 10.1093/ofid/ofae175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 03/20/2024] [Indexed: 05/05/2024] Open
Abstract
Background Influenza vaccine viruses grown in eggs may acquire egg-adaptive mutations that may reduce antigenic similarity between vaccine and circulating influenza viruses and decrease vaccine effectiveness. We compared cell- and egg-based quadrivalent influenza vaccines (QIVc and QIVe, respectively) for preventing test-confirmed influenza over 3 US influenza seasons (2017-2020). Methods Using a retrospective test-negative design, we estimated the relative vaccine effectiveness (rVE) of QIVc vs QIVe among individuals aged 4 to 64 years who had an acute respiratory or febrile illness and were tested for influenza in routine outpatient care. Exposure, outcome, and covariate data were obtained from electronic health records linked to pharmacy and medical claims. Season-specific rVE was estimated by comparing the odds of testing positive for influenza among QIVc vs QIVe recipients. Models were adjusted for age, sex, geographic region, influenza test date, and additional unbalanced covariates. A doubly robust approach was used combining inverse probability of treatment weights with multivariable regression. Results The study included 31 824, 33 388, and 34 398 patients in the 2017-2018, 2018-2019, and 2019-2020 seasons, respectively; ∼10% received QIVc and ∼90% received QIVe. QIVc demonstrated superior effectiveness vs QIVe in prevention of test-confirmed influenza: rVEs were 14.8% (95% CI, 7.0%-22.0%) in 2017-2018, 12.5% (95% CI, 4.7%-19.6%) in 2018-2019, and 10.0% (95% CI, 2.7%-16.7%) in 2019-2020. Conclusions This study demonstrated consistently superior effectiveness of QIVc vs QIVe in preventing test-confirmed influenza over 3 seasons characterized by different circulating viruses and degrees of egg adaptation.
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Affiliation(s)
- Alicia N Stein
- Centre for Outcomes Research and Epidemiology, CSL Seqirus, Melbourne, Australia
| | | | - Ian McGovern
- Centre for Outcomes Research and Epidemiology, CSL Seqirus, Waltham, Massachusetts, USA
| | | | - Alex Dean
- Real World Evidence, Veradigm, Chicago, Illinois, USA
| | | | - Sheena G Sullivan
- WHO Collaborating Centre for Reference and Research on Influenza, Royal Melbourne Hospital, and Department of Infectious Diseases, University of Melbourne, at the Peter Doherty Institute of Infection and Immunity, Melbourne, Australia
- Department of Epidemiology, University of California, Los Angeles, California, USA
| | - Mendel D M Haag
- Centre for Outcomes Research and Epidemiology, CSL Seqirus, Amsterdam, Netherlands
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Chung H, Campitelli MA, Buchan SA, Campigotto A, Crowcroft NS, Gubbay JB, Jung JK, Karnauchow T, Katz K, McGeer AJ, McNally JD, Richardson DC, Richardson SE, Rosella LC, Russell ML, Schwartz KL, Simor A, Smieja M, Sundaram ME, Warshawsky BF, Zahariadis G, Kwong JC. Measuring waning protection from seasonal influenza vaccination during nine influenza seasons, Ontario, Canada, 2010/11 to 2018/19. Euro Surveill 2024; 29. [PMID: 38390652 PMCID: PMC10899815 DOI: 10.2807/1560-7917.es.2024.29.8.2300239] [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] [Indexed: 02/24/2024] Open
Abstract
BackgroundWaning immunity from seasonal influenza vaccination can cause suboptimal protection during peak influenza activity. However, vaccine effectiveness studies assessing waning immunity using vaccinated and unvaccinated individuals are subject to biases.AimWe examined the association between time since vaccination and laboratory-confirmed influenza to assess the change in influenza vaccine protection over time.MethodsUsing linked laboratory and health administrative databases in Ontario, Canada, we identified community-dwelling individuals aged ≥ 6 months who received an influenza vaccine before being tested for influenza by RT-PCR during the 2010/11 to 2018/19 influenza seasons. We estimated the adjusted odds ratio (aOR) for laboratory-confirmed influenza by time since vaccination (categorised into intervals) and for every 28 days.ResultsThere were 53,065 individuals who were vaccinated before testing for influenza, with 10,264 (19%) influenza-positive cases. The odds of influenza increased from 1.05 (95% CI: 0.91-1.22) at 42-69 days after vaccination and peaked at 1.27 (95% CI: 1.04-1.55) at 126-153 days when compared with the reference interval (14-41 days). This corresponded to 1.09-times increased odds of influenza every 28 days (aOR = 1.09; 95% CI: 1.04-1.15). Individuals aged 18-64 years showed the greatest decline in protection against influenza A(H1N1) (aORper 28 days = 1.26; 95% CI: 0.97-1.64), whereas for individuals aged ≥ 65 years, it was against influenza A(H3N2) (aORper 28 days = 1.20; 95% CI: 1.08-1.33). We did not observe evidence of waning vaccine protection for individuals aged < 18 years.ConclusionsInfluenza vaccine protection wanes during an influenza season. Understanding the optimal timing of vaccination could ensure robust protection during seasonal influenza activity.
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Affiliation(s)
| | | | - Sarah A Buchan
- Public Health Ontario, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
| | - Aaron Campigotto
- London Health Sciences Centre, London, Canada
- Hospital for Sick Children, Toronto, Canada
| | - Natasha S Crowcroft
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Canada
- Public Health Ontario, Toronto, Canada
- ICES, Toronto, Canada
| | - Jonathan B Gubbay
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
- Hospital for Sick Children, Toronto, Canada
- Public Health Ontario, Toronto, Canada
| | | | - Timothy Karnauchow
- Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Canada
- Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Kevin Katz
- North York General Hospital, Toronto, Canada
| | - Allison J McGeer
- Sinai Health System, Toronto, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | | | | | - Susan E Richardson
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
- Hospital for Sick Children, Toronto, Canada
| | - Laura C Rosella
- Public Health Ontario, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
| | | | - Kevin L Schwartz
- Public Health Ontario, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
| | - Andrew Simor
- Sunnybrook Health Sciences Centre, Toronto, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | | | - Maria E Sundaram
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, United States
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- ICES, Toronto, Canada
| | - Bryna F Warshawsky
- Western University, London, Canada
- Public Health Ontario, Toronto, Canada
| | - George Zahariadis
- Newfoundland and Labrador Public Health Laboratory, St. John's, Canada
- London Health Sciences Centre, London, Canada
| | - Jeffrey C Kwong
- ICES, Toronto, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Canada
- University Health Network, Toronto, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Canada
- Public Health Ontario, Toronto, Canada
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4
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Smolarchuk C, Ickert C, Zelyas N, Kwong JC, Buchan SA. Early influenza vaccine effectiveness estimates using routinely collected data, Alberta, Canada, 2023/24 season. Euro Surveill 2024; 29:2300709. [PMID: 38214082 PMCID: PMC10785209 DOI: 10.2807/1560-7917.es.2024.29.2.2300709] [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: 12/16/2023] [Accepted: 01/10/2024] [Indexed: 01/13/2024] Open
Abstract
Timely and precise influenza vaccine effectiveness (VE) estimates are needed to guide public health messaging and impact vaccine uptake immediately. Using routinely collected laboratory, vaccination and health administrative data from Alberta, Canada, we estimated influenza VE against infection for the 2023/24 season on a near real-time basis, to late December, at 61% (95% CI: 58-64) against influenza A(H1N1), 49% (95% CI: 28-63) against influenza A(H3N2) and 75% (95% CI: 58-85) against influenza B.
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Affiliation(s)
- Christa Smolarchuk
- Public Health Analytics, Alberta Health, Edmonton, Alberta
- These authors contributed equally to this work and share first authorship
| | - Carla Ickert
- Public Health Analytics, Alberta Health, Edmonton, Alberta
- These authors contributed equally to this work and share first authorship
| | - Nathan Zelyas
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Canada
| | - Jeffrey C Kwong
- ICES, Toronto, Canada
- Public Health Ontario, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Canada
- University Health Network, Toronto, Canada
| | - Sarah A Buchan
- ICES, Toronto, Canada
- Public Health Ontario, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
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5
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Jorgensen SCJ, Hernandez A, Fell DB, Austin PC, D'Souza R, Guttmann A, Brown KA, Buchan SA, Gubbay JB, Nasreen S, Schwartz KL, Tadrous M, Wilson K, Kwong JC. Maternal mRNA covid-19 vaccination during pregnancy and delta or omicron infection or hospital admission in infants: test negative design study. BMJ 2023; 380:e074035. [PMID: 36754426 PMCID: PMC9903336 DOI: 10.1136/bmj-2022-074035] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
OBJECTIVE To estimate the effectiveness of maternal mRNA covid-19 vaccination during pregnancy against delta and omicron severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection and hospital admission in infants. DESIGN Test negative design study. SETTING Community and hospital testing in Ontario, Canada. PARTICIPANTS Infants younger than six months of age, born between 7 May 2021 and 31 March 2022, who were tested for SARS-CoV-2 between 7 May 2021 and 5 September 2022. INTERVENTION Maternal mRNA covid-19 vaccination during pregnancy. MAIN OUTCOME MEASURES Laboratory confirmed delta or omicron infection or hospital admission of the infant. Multivariable logistic regression estimated vaccine effectiveness, with adjustments for clinical and sociodemographic characteristics associated with vaccination and infection. RESULTS 8809 infants met eligibility criteria, including 99 delta cases (4365 controls) and 1501 omicron cases (4847 controls). Infant vaccine effectiveness from two maternal doses was 95% (95% confidence interval 88% to 98%) against delta infection and 97% (73% to 100%) against infant hospital admission due to delta and 45% (37% to 53%) against omicron infection and 53% (39% to 64%) against hospital admission due to omicron. Vaccine effectiveness for three doses was 73% (61% to 80%) against omicron infection and 80% (64% to 89%) against hospital admission due to omicron. Vaccine effectiveness for two doses against infant omicron infection was highest with the second dose in the third trimester (53% (42% to 62%)) compared with the first (47% (31% to 59%)) or second (37% (24% to 47%)) trimesters. Vaccine effectiveness for two doses against infant omicron infection decreased from 57% (44% to 66%) between birth and eight weeks to 40% (21% to 54%) after 16 weeks of age. CONCLUSIONS Maternal covid-19 vaccination with a second dose during pregnancy was highly effective against delta and moderately effective against omicron infection and hospital admission in infants during the first six months of life. A third vaccine dose bolstered protection against omicron. Effectiveness for two doses was highest with maternal vaccination in the third trimester, and effectiveness decreased in infants beyond eight weeks of age.
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Affiliation(s)
- Sarah C J Jorgensen
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Deshayne B Fell
- ICES, Toronto, ON, Canada
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
| | - Peter C Austin
- ICES, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Rohan D'Souza
- Departments of Obstetrics and Gynecology and Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
- School of Graduate Studies, University of Toronto, Toronto, ON, Canada
| | - Astrid Guttmann
- ICES, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Pediatrics, Hospital for Sick Children, Toronto, ON, Canada
- The Edwin SH Leong Centre for Healthy Children, University of Toronto, Toronto, ON, Canada
| | - Kevin A Brown
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Public Health Ontario, Toronto, ON, Canada
| | - Sarah A Buchan
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada
| | - Jonathan B Gubbay
- Public Health Ontario, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Sharifa Nasreen
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Kevin L Schwartz
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Public Health Ontario, Toronto, ON, Canada
| | - Mina Tadrous
- ICES, Toronto, ON, Canada
- Women's College Hospital, Toronto, ON, Canada
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada
| | - Kumanan Wilson
- Department of Medicine, University of Ottawa, Ottawa, ON, Canada
- Bruyère Research Institute, Ottawa, ON, Canada
- Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Jeffrey C Kwong
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada
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6
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Kim P, Coleman B, Kwong JC, Plevneshi A, Hassan K, Green K, McNeil SA, Armstrong I, Gold WL, Gubbay J, Katz K, Kuster SP, Lovinsky R, Matukas L, Ostrowska K, Richardson D, McGeer A. Burden of Severe Illness Associated With Laboratory-Confirmed Influenza in Adults Aged 50-64 Years, 2010-2011 to 2016-2017. Open Forum Infect Dis 2022; 10:ofac664. [PMID: 36632417 PMCID: PMC9830541 DOI: 10.1093/ofid/ofac664] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Indexed: 12/28/2022] Open
Abstract
Background Understanding the burden of influenza is necessary to optimize recommendations for influenza vaccination. We describe the epidemiology of severe influenza in 50- to 64-year-old residents of metropolitan Toronto and Peel region, Canada, over 7 influenza seasons. Methods Prospective population-based surveillance for hospitalization associated with laboratory-confirmed influenza was conducted from September 2010 to August 2017. Conditions increasing risk of influenza complications were as defined by Canada's National Advisory Committee on Immunization. Age-specific prevalence of medical conditions was estimated using Ontario health administrative data. Population rates were estimated using Statistics Canada data. Results Over 7 seasons, 1228 hospitalizations occurred in patients aged 50-64 years: 40% due to A(H3N2), 30% A(H1N1), and 22% influenza B. The average annual hospitalization rate was 15.6, 20.9, and 33.2 per 100 000 in patients aged 50-54, 55-59, and 60-64 years, respectively; average annual mortality was 0.9/100 000. Overall, 33% of patients had received current season influenza vaccine; 963 (86%) had ≥1 underlying condition increasing influenza complication risk. The most common underlying medical conditions were chronic lung disease (38%) and diabetes mellitus (31%); 25% of patients were immunocompromised. The average annual hospitalization rate was 6.1/100 000 in those without and 41/100 000 in those with any underlying condition, and highest in those with renal disease or immunocompromise (138 and 281 per 100 000, respectively). The case fatality rate in hospitalized patients was 4.4%; median length of stay was 4 days (interquartile range, 2-8 days). Conclusions The burden of severe influenza in 50- to 64-year-olds remains significant despite our universal publicly funded vaccination program. These data may assist in improving estimates of the cost-effectiveness of new strategies to reduce this burden.
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Affiliation(s)
- Philip Kim
- Department of Microbiology, Sinai Health System, Toronto, Canada
| | - Brenda Coleman
- Department of Microbiology, Sinai Health System, Toronto, Canada,Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Jeffrey C Kwong
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada,Department of Family and Community Medicine, University of Toronto, Toronto, Canada,ICES, Toronto, Canada,Public Health Ontario, Toronto, Canada
| | - Agron Plevneshi
- Department of Microbiology, Sinai Health System, Toronto, Canada
| | - Kazi Hassan
- Department of Microbiology, Sinai Health System, Toronto, Canada
| | - Karen Green
- Department of Microbiology, Sinai Health System, Toronto, Canada
| | - Shelly A McNeil
- Department of Medicine, Dalhousie University, Halifax, Canada
| | | | - Wayne L Gold
- Department of Medicine, University Health Network, University of Toronto, Toronto, Canada
| | - Jonathan Gubbay
- Public Health Ontario, Toronto, Canada,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | - Kevin Katz
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada,Department of Microbiology, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Stefan P Kuster
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St Gallen, St Gallen, Switzerland
| | | | - Larissa Matukas
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada,Division of Microbiology, Unity Health, Toronto, Canada
| | | | - David Richardson
- Department of Medical Microbiology and Infectious Diseases, William Osler Health System, Brampton, Canada
| | - Allison McGeer
- Correspondence: Allison McGeer, Mount Sinai Hospital, 600 University Ave, Room 171, Toronto, ON, Canada M5G 1X5 ()
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7
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Jones RP, Ponomarenko A. Roles for Pathogen Interference in Influenza Vaccination, with Implications to Vaccine Effectiveness (VE) and Attribution of Influenza Deaths. Infect Dis Rep 2022; 14:710-758. [PMID: 36286197 PMCID: PMC9602062 DOI: 10.3390/idr14050076] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/15/2022] [Accepted: 09/15/2022] [Indexed: 08/29/2023] Open
Abstract
Pathogen interference is the ability of one pathogen to alter the course and clinical outcomes of infection by another. With up to 3000 species of human pathogens the potential combinations are vast. These combinations operate within further immune complexity induced by infection with multiple persistent pathogens, and by the role which the human microbiome plays in maintaining health, immune function, and resistance to infection. All the above are further complicated by malnutrition in children and the elderly. Influenza vaccination offers a measure of protection for elderly individuals subsequently infected with influenza. However, all vaccines induce both specific and non-specific effects. The specific effects involve stimulation of humoral and cellular immunity, while the nonspecific effects are far more nuanced including changes in gene expression patterns and production of small RNAs which contribute to pathogen interference. Little is known about the outcomes of vaccinated elderly not subsequently infected with influenza but infected with multiple other non-influenza winter pathogens. In this review we propose that in certain years the specific antigen mix in the seasonal influenza vaccine inadvertently increases the risk of infection from other non-influenza pathogens. The possibility that vaccination could upset the pathogen balance, and that the timing of vaccination relative to the pathogen balance was critical to success, was proposed in 2010 but was seemingly ignored. Persons vaccinated early in the winter are more likely to experience higher pathogen interference. Implications to the estimation of vaccine effectiveness and influenza deaths are discussed.
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Affiliation(s)
- Rodney P Jones
- Healthcare Analysis and Forecasting, Wantage OX12 0NE, UK
| | - Andrey Ponomarenko
- Department of Biophysics, Informatics and Medical Instrumentation, Odessa National Medical University, Valikhovsky Lane 2, 65082 Odessa, Ukraine
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8
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Nasreen S, Chung H, He S, Brown KA, Gubbay JB, Buchan SA, Fell DB, Austin PC, Schwartz KL, Sundaram ME, Calzavara A, Chen B, Tadrous M, Wilson K, Wilson SE, Kwong JC. Effectiveness of COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe outcomes with variants of concern in Ontario. Nat Microbiol 2022; 7:379-385. [PMID: 35132198 DOI: 10.1101/2021.06.28.21259420] [Citation(s) in RCA: 66] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 12/16/2021] [Indexed: 05/26/2023]
Abstract
SARS-CoV-2 variants of concern (VOC) are more transmissible and may have the potential for increased disease severity and decreased vaccine effectiveness. We estimated the effectiveness of BNT162b2 (Pfizer-BioNTech Comirnaty), mRNA-1273 (Moderna Spikevax) and ChAdOx1 (AstraZeneca Vaxzevria) vaccines against symptomatic SARS-CoV-2 infection and COVID-19 hospitalization or death caused by the Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1) and Delta (B.1.617.2) VOC in Ontario, Canada, using a test-negative design study. We identified 682,071 symptomatic community-dwelling individuals who were tested for SARS-CoV-2, and 15,269 individuals with a COVID-19 hospitalization or death. Effectiveness against symptomatic infection ≥7 d after two doses was 89-92% against Alpha, 87% against Beta, 88% against Gamma, 82-89% against Beta/Gamma and 87-95% against Delta across vaccine products. The corresponding estimates ≥14 d after one dose were lower. Effectiveness estimates against hospitalization or death were similar to or higher than against symptomatic infection. Effectiveness against symptomatic infection was generally lower for older adults (≥60 years) than for younger adults (<60 years) for most of the VOC-vaccine combinations. Our findings suggest that jurisdictions facing vaccine supply constraints may benefit from delaying the second dose in younger individuals to more rapidly achieve greater overall population protection; however, older adults would likely benefit most from minimizing the delay in receiving the second dose to achieve adequate protection against VOC.
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Affiliation(s)
- Sharifa Nasreen
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | | | - Siyi He
- ICES, Toronto, Ontario, Canada
| | - Kevin A Brown
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Public Health Ontario, Toronto, Ontario, Canada
| | | | - Sarah A Buchan
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Public Health Ontario, Toronto, Ontario, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Ontario, Canada
| | - Deshayne B Fell
- ICES, Toronto, Ontario, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, Ontario, Canada
| | - Peter C Austin
- ICES, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Kevin L Schwartz
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Public Health Ontario, Toronto, Ontario, Canada
| | - Maria E Sundaram
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | | | | | - Mina Tadrous
- ICES, Toronto, Ontario, Canada
- Women's College Hospital, Toronto, Ontario, Canada
| | - Kumanan Wilson
- Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada
- Bruyere and Ottawa Hospital Research Institutes, Ottawa, Ontario, Canada
| | - Sarah E Wilson
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Public Health Ontario, Toronto, Ontario, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Ontario, Canada
| | - Jeffrey C Kwong
- ICES, Toronto, Ontario, Canada.
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
- Public Health Ontario, Toronto, Ontario, Canada.
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Ontario, Canada.
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
- University Health Network, Toronto, Ontario, Canada.
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9
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Nasreen S, Chung H, He S, Brown KA, Gubbay JB, Buchan SA, Fell DB, Austin PC, Schwartz KL, Sundaram ME, Calzavara A, Chen B, Tadrous M, Wilson K, Wilson SE, Kwong JC. Effectiveness of COVID-19 vaccines against symptomatic SARS-CoV-2 infection and severe outcomes with variants of concern in Ontario. Nat Microbiol 2022; 7:379-385. [DOI: 10.1038/s41564-021-01053-0] [Citation(s) in RCA: 78] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 12/16/2021] [Indexed: 12/22/2022]
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10
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Chung H, He S, Nasreen S, Sundaram ME, Buchan SA, Wilson SE, Chen B, Calzavara A, Fell DB, Austin PC, Wilson K, Schwartz KL, Brown KA, Gubbay JB, Basta NE, Mahmud SM, Righolt CH, Svenson LW, MacDonald SE, Janjua NZ, Tadrous M, Kwong JC. Effectiveness of BNT162b2 and mRNA-1273 covid-19 vaccines against symptomatic SARS-CoV-2 infection and severe covid-19 outcomes in Ontario, Canada: test negative design study. BMJ 2021; 374:n1943. [PMID: 34417165 PMCID: PMC8377789 DOI: 10.1136/bmj.n1943] [Citation(s) in RCA: 181] [Impact Index Per Article: 60.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/02/2021] [Indexed: 01/19/2023]
Abstract
OBJECTIVE To estimate the effectiveness of mRNA covid-19 vaccines against symptomatic infection and severe outcomes (hospital admission or death). DESIGN Test negative design study. SETTING Ontario, Canada between 14 December 2020 and 19 April 2021. PARTICIPANTS 324 033 community dwelling people aged ≥16 years who had symptoms of covid-19 and were tested for SARS-CoV-2. INTERVENTIONS BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) vaccine. MAIN OUTCOME MEASURES Laboratory confirmed SARS-CoV-2 by reverse transcription polymerase chain reaction (RT-PCR) and hospital admissions and deaths associated with SARS-CoV-2 infection. Multivariable logistic regression was adjusted for personal and clinical characteristics associated with SARS-CoV-2 and vaccine receipt to estimate vaccine effectiveness against symptomatic infection and severe outcomes. RESULTS Of 324 033 people with symptoms, 53 270 (16.4%) were positive for SARS-CoV-2 and 21 272 (6.6%) received at least one dose of vaccine. Among participants who tested positive, 2479 (4.7%) were admitted to hospital or died. Vaccine effectiveness against symptomatic infection observed ≥14 days after one dose was 60% (95% confidence interval 57% to 64%), increasing from 48% (41% to 54%) at 14-20 days after one dose to 71% (63% to 78%) at 35-41 days. Vaccine effectiveness observed ≥7 days after two doses was 91% (89% to 93%). Vaccine effectiveness against hospital admission or death observed ≥14 days after one dose was 70% (60% to 77%), increasing from 62% (44% to 75%) at 14-20 days to 91% (73% to 97%) at ≥35 days, whereas vaccine effectiveness observed ≥7 days after two doses was 98% (88% to 100%). For adults aged ≥70 years, vaccine effectiveness estimates were observed to be lower for intervals shortly after one dose but were comparable to those for younger people for all intervals after 28 days. After two doses, high vaccine effectiveness was observed against variants with the E484K mutation. CONCLUSIONS Two doses of mRNA covid-19 vaccines were observed to be highly effective against symptomatic infection and severe outcomes. Vaccine effectiveness of one dose was observed to be lower, particularly for older adults shortly after the first dose.
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Affiliation(s)
| | | | | | - Maria E Sundaram
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Sarah A Buchan
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Public Health Ontario, ON, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada
| | - Sarah E Wilson
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Public Health Ontario, ON, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada
| | | | | | - Deshayne B Fell
- ICES, Toronto, ON, Canada
- School of Epidemiology and Public Health, University of Ottawa, ON, Canada
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, Canada
| | - Peter C Austin
- ICES, Toronto, ON, Canada
- Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Kumanan Wilson
- School of Epidemiology and Public Health, University of Ottawa, ON, Canada
- Bruyère and Ottawa Hospital Research Institutes, Ottawa, ON, Canada
- Department of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Kevin L Schwartz
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Public Health Ontario, ON, Canada
| | - Kevin A Brown
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Public Health Ontario, ON, Canada
| | - Jonathan B Gubbay
- Public Health Ontario, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Nicole E Basta
- Department of Epidemiology, Biostatistics, and Occupational Health, School of Population and Global Health, McGill University, Montreal, QC, Canada
| | - Salaheddin M Mahmud
- Vaccine and Drug Evaluation Centre, Department of Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Christiaan H Righolt
- Vaccine and Drug Evaluation Centre, Department of Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Lawrence W Svenson
- Analytics and Performance Reporting Branch, Alberta Health, Edmonton, AB, Canada
- Division of Preventive Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB, Canada
- School of Public Health, University of Alberta, Edmonton, AB, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Shannon E MacDonald
- School of Public Health, University of Alberta, Edmonton, AB, Canada
- Faculty of Nursing, University of Alberta, Edmonton, AB, Canada
| | - Naveed Z Janjua
- British Columbia Centre for Disease Control, Vancouver, BC, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Mina Tadrous
- ICES, Toronto, ON, Canada
- Women's College Hospital, Toronto, ON, Canada
- Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON, Canada
| | - Jeffrey C Kwong
- ICES, Toronto, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Public Health Ontario, ON, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
- University Health Network, Toronto, ON, Canada
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11
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Crowcroft NS, Schwartz KL, Savage RD, Chen C, Johnson C, Li Y, Marchand-Austin A, Bolotin S, Deeks SL, Jamieson FB, Drews SJ, Russell ML, Svenson LW, Simmonds K, Righolt CH, Bell C, Mahmud SM, Kwong JC. A Call for Caution in Use of Pertussis Vaccine Effectiveness Studies to Estimate Waning Immunity: A Canadian Immunization Research Network Study. Clin Infect Dis 2021; 73:83-90. [PMID: 32384142 DOI: 10.1093/cid/ciaa518] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Vaccine effectiveness (VE) studies provide essential evidence on waning vaccine-derived immunity, a major threat to pertussis control. We evaluated how study design affects estimates by comparing 2 case-control studies conducted in Ontario, Canada. METHODS We compared results from a test-negative design (TND) with a frequency-matched design (FMD) case-control study using pertussis cases from 2005-2015. In the first study, we identified test-negative controls from the public health laboratory that diagnosed cases and, in the second, randomly selected controls from patients attending the same physicians that reported cases, frequency matched on age and year. We compared characteristics of cases and controls using standardized differences. RESULTS In both designs, VE estimates for the early years postimmunization were consistent with clinical trials (TND, 84%; FMD, 89% at 1-3 years postvaccination) but diverged as time since last vaccination increased (TND, 41%; FMD, 74% by 8 years postvaccination). Overall, we observed lower VE and faster waning in the TND than the FMD. In the TND but not FMD, controls differed from cases in important confounders, being younger, having more comorbidities, and higher healthcare use. Differences between the controls of each design were greater than differences between cases. TND controls were more likely to be unvaccinated or incompletely vaccinated than FMD controls (P < .001). CONCLUSIONS The FMD adjusted better for healthcare-seeking behavior than the TND. Duration of protection from pertussis vaccines is unclear because estimates vary by study design. Caution should be exercised by experts, researchers, and decision makers when evaluating evidence on optimal timing of boosters.
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Affiliation(s)
- Natasha S Crowcroft
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Centre for Vaccine Preventable Diseases, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada
| | - Kevin L Schwartz
- Centre for Vaccine Preventable Diseases, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada.,St Joseph's Health Centre, Toronto, Ontario, Canada
| | - Rachel D Savage
- Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.,Women's College Research Institute, Women's College Hospital, Toronto, Ontario, Canada
| | | | | | - Ye Li
- Centre for Vaccine Preventable Diseases, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada
| | | | - Shelly Bolotin
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Centre for Vaccine Preventable Diseases, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada
| | - Shelley L Deeks
- Centre for Vaccine Preventable Diseases, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada
| | - Frances B Jamieson
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada
| | - Steven J Drews
- Medical Microbiology, Canadian Blood Service, Edmonton, Alberta, Canada.,Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Margaret L Russell
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Lawrence W Svenson
- Alberta Health, Edmonton, Alberta, Canada.,Division of Preventive Medicine, University of Alberta, Edmonton, Alberta, Canada.,School of Public Health, University of Alberta, Edmonton, Alberta, Canada
| | - Kimberley Simmonds
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.,Alberta Health, Edmonton, Alberta, Canada.,School of Public Health, University of Alberta, Edmonton, Alberta, Canada
| | - Christiaan H Righolt
- Vaccine and Drug Evaluation Centre, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Christopher Bell
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Salaheddin M Mahmud
- Vaccine and Drug Evaluation Centre, Department of Community Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Jeffrey C Kwong
- Centre for Vaccine Preventable Diseases, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada.,Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
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12
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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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13
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Petersen JM, Ranker LR, Barnard-Mayers R, MacLehose RF, Fox MP. A systematic review of quantitative bias analysis applied to epidemiological research. Int J Epidemiol 2021; 50:1708-1730. [PMID: 33880532 DOI: 10.1093/ije/dyab061] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/05/2021] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Quantitative bias analysis (QBA) measures study errors in terms of direction, magnitude and uncertainty. This systematic review aimed to describe how QBA has been applied in epidemiological research in 2006-19. METHODS We searched PubMed for English peer-reviewed studies applying QBA to real-data applications. We also included studies citing selected sources or which were identified in a previous QBA review in pharmacoepidemiology. For each study, we extracted the rationale, methodology, bias-adjusted results and interpretation and assessed factors associated with reproducibility. RESULTS Of the 238 studies, the majority were embedded within papers whose main inferences were drawn from conventional approaches as secondary (sensitivity) analyses to quantity-specific biases (52%) or to assess the extent of bias required to shift the point estimate to the null (25%); 10% were standalone papers. The most common approach was probabilistic (57%). Misclassification was modelled in 57%, uncontrolled confounder(s) in 40% and selection bias in 17%. Most did not consider multiple biases or correlations between errors. When specified, bias parameters came from the literature (48%) more often than internal validation studies (29%). The majority (60%) of analyses resulted in >10% change from the conventional point estimate; however, most investigators (63%) did not alter their original interpretation. Degree of reproducibility related to inclusion of code, formulas, sensitivity analyses and supplementary materials, as well as the QBA rationale. CONCLUSIONS QBA applications were rare though increased over time. Future investigators should reference good practices and include details to promote transparency and to serve as a reference for other researchers.
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Affiliation(s)
- Julie M Petersen
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Lynsie R Ranker
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Ruby Barnard-Mayers
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Richard F MacLehose
- Division of Epidemiology and Community Health, University of Minnesota, School of Public Health, Minneapolis, MN, USA
| | - Matthew P Fox
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.,Department of Global Health, Boston University School of Public Health, Boston, MA, USA
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14
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Fitzpatrick T, McNally JD, Stukel TA, Lu H, Fisman D, Kwong JC, Guttmann A. Family and Child Risk Factors for Early-Life RSV Illness. Pediatrics 2021; 147:peds.2020-029090. [PMID: 33737374 DOI: 10.1542/peds.2020-029090] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/30/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Most infants hospitalized with respiratory syncytial virus (RSV) do not meet common "high-risk" criteria and are otherwise healthy. The objective of this study was to quantify the risks and relative importance of socioeconomic factors for severe, early-life RSV-related illness. We hypothesized several of these factors, particularly those indicating severe social vulnerability, would have statistically significant associations with increased RSV hospitalization rates and may offer impactful targets for population-based RSV prevention strategies, such as prophylaxis programs. METHODS We used linked health, laboratory, and sociodemographic administrative data for all children born in Ontario (2012-2018) to identify all RSV-related hospitalizations occurring before the third birthday or end of follow-up (March 31, 2019). We estimated rate ratios and population attributable fractions using a fully adjusted model. RESULTS A total of 11 782 RSV-related hospitalizations were identified among 789 484 children. Multiple socioeconomic factors were independently associated with increased RSV-related admissions, including young maternal age, maternal criminal involvement, and maternal history of serious mental health and/or addiction concerns. For example, an estimated 4.1% (95% confidence interval: 2.2 to 5.9) of RSV-related admissions could be prevented by eliminating the increased admissions risks among children whose mothers used welfare-based drug insurance. Notably, 41.6% (95% confidence interval: 39.6 to 43.5) of admissions may be prevented by targeting older siblings (eg, through vaccination). CONCLUSIONS Many social factors were independently associated with early-life RSV-related hospitalization. Existing RSV prophylaxis and emerging vaccination programs should consider the importance of both clinical and social risk factors when determining eligibility and promoting compliance.
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Affiliation(s)
- Tiffany Fitzpatrick
- ICES, Toronto, Ontario, Canada.,Dalla Lana School of Public Health.,Child Health Evaluative Sciences, Hospital for Sick Children, Toronto, Ontario, Canada
| | - J Dayre McNally
- Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | - Thérèse A Stukel
- ICES, Toronto, Ontario, Canada.,Dalla Lana School of Public Health.,Institute for Health Policy, Management and Evaluation
| | - Hong Lu
- ICES, Toronto, Ontario, Canada
| | | | - Jeffrey C Kwong
- ICES, Toronto, Ontario, Canada.,Dalla Lana School of Public Health.,Institute for Health Policy, Management and Evaluation.,Public Health Ontario, Toronto, Ontario, Canada; and.,Department of Family and Community Medicine.,Centre for Vaccine Preventable Diseases, and.,University Health Network, Toronto, Ontario, Canada.,Contributed equally as co-senior authors
| | - Astrid Guttmann
- ICES, Toronto, Ontario, Canada; .,Dalla Lana School of Public Health.,Child Health Evaluative Sciences, Hospital for Sick Children, Toronto, Ontario, Canada.,Institute for Health Policy, Management and Evaluation.,Division of Pediatric Medicine and.,Edwin S.H. Leong Centre for Healthy Children, University of Toronto, Toronto, Ontario, Canada.,Contributed equally as co-senior authors
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15
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Balasubramani GK, Zimmerman RK, Eng H, Lyons J, Clarke L, Nowalk MP. Comparison of local influenza vaccine effectiveness using two methods. Vaccine 2021; 39:1283-1289. [PMID: 33485643 PMCID: PMC7825890 DOI: 10.1016/j.vaccine.2021.01.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 12/04/2020] [Accepted: 01/04/2021] [Indexed: 11/19/2022]
Abstract
Background In some settings, research methods to determine influenza vaccine effectiveness (VE) may not be appropriate because of cost, time constraints, or other factors. Administrative database analysis of viral testing results and vaccination history may be a viable alternative. This study compared VE estimates from outpatient research and administrative databases. Methods Using the test-negative, case-control design, data for 2017–2018 and 2018–2019 influenza seasons were collected using: 1) consent, specimen collection, RT-PCR testing and vaccine verification using multiple methods; and 2) an administrative database of outpatients with a clinical respiratory viral panel combined with electronic immunization records. Odds ratios for likelihood of influenza infection by vaccination status were calculated using multivariable logistic regression. VE = (1 − aOR) × 100. Results Research participants were significantly younger (P < 0.001), more often white (69% vs. 59%; P < 0.001) than non-white and less frequently enrolled through the emergency department (35% vs. 72%; P < 0.001) than administrative database participants. VE was significant against all influenza and influenza A in each season and both seasons combined (37–49%). Point estimate differences between methods were evident, with higher VE in the research database, but insignificant due to low sample sizes. When enrollment sites were separately analyzed, there were significant differences in VE estimates for all influenza (66% research vs. 46% administrative P < 0.001) and influenza A (67% research vs. 49% administrative; P < 0.001) in the emergency department. Conclusions: The selection of the appropriate method for determining influenza vaccine effectiveness depends on many factors, including sample size, subgroups of interest, etc., suggesting that research estimates may be more generalizable. Other advantages of research databases for VE estimates include lack of clinician-related selection bias for testing and less misclassification of vaccination status. The advantages of the administrative databases are potentially shorter time to VE results and lower cost.
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Affiliation(s)
- G K Balasubramani
- University of Pittsburgh Department of Epidemiology, Suite 600 Schenley Place, 4420 Bayard St., Pittsburgh, PA 15260 USA.
| | - Richard K Zimmerman
- University of Pittsburgh Department of Family Medicine, Suite 520 Schenley Place, 4420 Bayard St., Pittsburgh, PA 15260 USA.
| | - Heather Eng
- University of Pittsburgh Department of Epidemiology, Suite 600 Schenley Place, 4420 Bayard St., Pittsburgh, PA 15260 USA.
| | - Jason Lyons
- University of Pittsburgh Department of Epidemiology, Suite 600 Schenley Place, 4420 Bayard St., Pittsburgh, PA 15260 USA.
| | - Lloyd Clarke
- UPMC Health System Department of Pharmacy, Division of Infectious Diseases/Pharmacy Department - AMP 5th Floor Falk Medical Building, 3601 Fifth Ave, Pittsburgh, PA, USA.
| | - Mary Patricia Nowalk
- University of Pittsburgh Department of Family Medicine, Suite 520 Schenley Place, 4420 Bayard St., Pittsburgh, PA 15260 USA.
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16
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Baum U, Kulathinal S, Auranen K. Mitigation of biases in estimating hazard ratios under non-sensitive and non-specific observation of outcomes-applications to influenza vaccine effectiveness. Emerg Themes Epidemiol 2021; 18:1. [PMID: 33446220 PMCID: PMC7807790 DOI: 10.1186/s12982-020-00091-z] [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: 02/03/2020] [Accepted: 12/17/2020] [Indexed: 11/10/2022] Open
Abstract
Background Non-sensitive and non-specific observation of outcomes in time-to-event data affects event counts as well as the risk sets, thus, biasing the estimation of hazard ratios. We investigate how imperfect observation of incident events affects the estimation of vaccine effectiveness based on hazard ratios. Methods Imperfect time-to-event data contain two classes of events: a portion of the true events of interest; and false-positive events mistakenly recorded as events of interest. We develop an estimation method utilising a weighted partial likelihood and probabilistic deletion of false-positive events and assuming the sensitivity and the false-positive rate are known. The performance of the method is evaluated using simulated and Finnish register data. Results The novel method enables unbiased semiparametric estimation of hazard ratios from imperfect time-to-event data. False-positive rates that are small can be approximated to be zero without inducing bias. The method is robust to misspecification of the sensitivity as long as the ratio of the sensitivity in the vaccinated and the unvaccinated is specified correctly and the cumulative risk of the true event is small. Conclusions The weighted partial likelihood can be used to adjust for outcome measurement errors in the estimation of hazard ratios and effectiveness but requires specifying the sensitivity and the false-positive rate. In absence of exact information about these parameters, the method works as a tool for assessing the potential magnitude of bias given a range of likely parameter values.
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Affiliation(s)
- Ulrike Baum
- Department of Public Health Solutions, Finnish Institute for Health and Welfare, Mannerheimintie 166, 00300, Helsinki, Finland.
| | - Sangita Kulathinal
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Kari Auranen
- Department of Mathematics and Statistics, University of Turku, Turku, Finland.,Department of Clinical Medicine, University of Turku, Turku, Finland
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17
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Hamilton MA, Calzavara A, Emerson SD, Djebli M, Sundaram ME, Chan AK, Kustra R, Baral SD, Mishra S, Kwong JC. Validating International Classification of Disease 10th Revision algorithms for identifying influenza and respiratory syncytial virus hospitalizations. PLoS One 2021; 16:e0244746. [PMID: 33411792 PMCID: PMC7790248 DOI: 10.1371/journal.pone.0244746] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Accepted: 12/15/2020] [Indexed: 11/18/2022] Open
Abstract
Objective Routinely collected health administrative data can be used to efficiently assess disease burden in large populations, but it is important to evaluate the validity of these data. The objective of this study was to develop and validate International Classification of Disease 10th revision (ICD -10) algorithms that identify laboratory-confirmed influenza or laboratory-confirmed respiratory syncytial virus (RSV) hospitalizations using population-based health administrative data from Ontario, Canada. Study design and setting Influenza and RSV laboratory data from the 2014–15, 2015–16, 2016–17 and 2017–18 respiratory virus seasons were obtained from the Ontario Laboratories Information System (OLIS) and were linked to hospital discharge abstract data to generate influenza and RSV reference cohorts. These reference cohorts were used to assess the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of the ICD-10 algorithms. To minimize misclassification in future studies, we prioritized specificity and PPV in selecting top-performing algorithms. Results 83,638 and 61,117 hospitalized patients were included in the influenza and RSV reference cohorts, respectively. The best influenza algorithm had a sensitivity of 73% (95% CI 72% to 74%), specificity of 99% (95% CI 99% to 99%), PPV of 94% (95% CI 94% to 95%), and NPV of 94% (95% CI 94% to 95%). The best RSV algorithm had a sensitivity of 69% (95% CI 68% to 70%), specificity of 99% (95% CI 99% to 99%), PPV of 91% (95% CI 90% to 91%) and NPV of 97% (95% CI 97% to 97%). Conclusion We identified two highly specific algorithms that best ascertain patients hospitalized with influenza or RSV. These algorithms may be applied to hospitalized patients if data on laboratory tests are not available, and will thereby improve the power of future epidemiologic studies of influenza, RSV, and potentially other severe acute respiratory infections.
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Affiliation(s)
- Mackenzie A. Hamilton
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | | | | | - Mohamed Djebli
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | | | - Adrienne K. Chan
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Division of Infectious Diseases, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Rafal Kustra
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Stefan D. Baral
- Department of Epidemiology, John Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Sharmistha Mishra
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, St. Michael’s Hospital, University of Toronto, Toronto, Ontario, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
- MAP Centre for Urban Health Solutions, St. Michael’s Hospital, Li Ka Shing Knowledge Institute, Toronto, Ontario, Canada
| | - Jeffrey C. Kwong
- ICES, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Public Health Ontario, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
- University Health Network, Toronto, Ontario, Canada
- Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Ontario, Canada
- * E-mail:
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18
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Chung H, Buchan SA, Campigotto A, Campitelli MA, Crowcroft NS, Dubey V, Gubbay JB, Karnauchow T, Katz K, McGeer AJ, McNally JD, Mubareka S, Murti M, Richardson DC, Rosella LC, Schwartz KL, Smieja M, Zahariadis G, Kwong JC. Influenza vaccine effectiveness against all-cause mortality following laboratory-confirmed influenza in older adults, 2010-2011 to 2015-2016 seasons in Ontario, Canada. Clin Infect Dis 2020; 73:e1191-e1199. [PMID: 33354709 PMCID: PMC8423473 DOI: 10.1093/cid/ciaa1862] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Accepted: 12/21/2020] [Indexed: 12/22/2022] Open
Abstract
Background Older adults are at increased risk of mortality from influenza infections. We estimated influenza vaccine effectiveness (VE) against mortality following laboratory-confirmed influenza. Methods Using a test-negative design study and linked laboratory and health administrative databases in Ontario, Canada, we estimated VE against all-cause mortality following laboratory-confirmed influenza for community-dwelling adults aged >65 years during the 2010–2011 to 2015–2016 influenza seasons. Results Among 54 116 older adults tested for influenza across the 6 seasons, 6837 died within 30 days of specimen collection. Thirteen percent (925 individuals) tested positive for influenza, and 50.6% were considered vaccinated for that season. Only 23.2% of influenza test-positive cases had influenza recorded as their underlying cause of death. Before and after multivariable adjustment, we estimated VE against all-cause mortality following laboratory-confirmed influenza to be 20% (95% confidence interval [CI], 8%–30%) and 20% (95% CI, 7%–30%), respectively. This estimate increased to 34% after correcting for influenza vaccination exposure misclassification. We observed significant VE against deaths following influenza confirmation during 2014–2015 (VE = 26% [95% CI, 5%–42%]). We also observed significant VE against deaths following confirmation of influenza A/H1N1 and A/H3N2, and against deaths with COPD as the underlying cause. Conclusions These results support the importance of influenza vaccination in older adults, who account for most influenza-associated deaths annually.
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Affiliation(s)
| | - Sarah A Buchan
- ICES, Toronto, ON, Canada.,Public Health Ontario, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Aaron Campigotto
- Hospital for Sick Children, Toronto, ON, Canada.,London Health Sciences Centre, London, ON, Canada
| | | | - Natasha S Crowcroft
- ICES, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.,Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Vinita Dubey
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.,Toronto Public Health
| | - Jonathan B Gubbay
- Public Health Ontario, Toronto, ON, Canada.,Hospital for Sick Children, Toronto, ON, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Timothy Karnauchow
- Children's Hospital of Eastern Ontario, Ottawa, ON, Canada.,Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Kevin Katz
- North York General Hospital, Toronto, ON, Canada
| | - Allison J McGeer
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada.,Sinai Health System, Toronto, ON, Canada
| | | | | | - Michelle Murti
- Public Health Ontario, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | | | - Laura C Rosella
- ICES, Toronto, ON, Canada.,Public Health Ontario, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Kevin L Schwartz
- ICES, Toronto, ON, Canada.,Public Health Ontario, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | | | - George Zahariadis
- London Health Sciences Centre, London, ON, Canada.,Newfoundland & Labrador Public Health Laboratory, St. John's, NF&L, Canada
| | - Jeffrey C Kwong
- ICES, Toronto, ON, Canada.,Public Health Ontario, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.,Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON, Canada.,Department of Family & Community Medicine, University of Toronto, Toronto, ON, Canada.,University Health Network, Toronto, ON, Canada
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19
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Kwong JC, Chung H, Jung JK, Buchan SA, Campigotto A, Campitelli MA, Crowcroft NS, Gubbay JB, Karnauchow T, Katz K, McGeer AJ, McNally JD, Richardson DC, Richardson SE, Rosella LC, Schwartz KL, Simor A, Smieja M, Zahariadis G, On Behalf Of The Canadian Immunization Research Network Cirn Investigators. The impact of repeated vaccination using 10-year vaccination history on protection against influenza in older adults: a test-negative design study across the 2010/11 to 2015/16 influenza seasons in Ontario, Canada. ACTA ACUST UNITED AC 2020; 25. [PMID: 31937397 PMCID: PMC6961264 DOI: 10.2807/1560-7917.es.2020.25.1.1900245] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Introduction Annual influenza vaccination is recommended for older adults, but evidence regarding the impact of repeated vaccination has been inconclusive. Aim We investigated vaccine effectiveness (VE) against laboratory-confirmed influenza and the impact of repeated vaccination over 10 previous seasons on current season VE among older adults. Methods We conducted an observational test-negative study in community-dwelling adults aged > 65 years in Ontario, Canada for the 2010/11 to 2015/16 seasons by linking laboratory and health administrative data. We estimated VE using multivariable logistic regression. We assessed the impact of repeated vaccination by stratifying by previous vaccination history. Results We included 58,304 testing episodes for respiratory viruses, with 11,496 (20%) testing positive for influenza and 31,004 (53%) vaccinated. Adjusted VE against laboratory-confirmed influenza for the six seasons combined was 21% (95% confidence interval (CI): 18 to 24%). Patients who were vaccinated in the current season, but had received no vaccinations in the previous 10 seasons, had higher current season VE (34%; 95%CI: 9 to 52%) than patients who had received 1–3 (26%; 95%CI: 13 to 37%), 4–6 (24%; 95%CI: 15 to 33%), 7–8 (13%; 95%CI: 2 to 22%), or 9–10 (7%; 95%CI: −4 to 16%) vaccinations (trend test p = 0.001). All estimates were higher after correcting for misclassification of current season vaccination status. For patients who were not vaccinated in the current season, residual protection rose significantly with increasing numbers of vaccinations received previously. Conclusions Although VE appeared to decrease with increasing numbers of previous vaccinations, current season vaccination likely provides some protection against influenza regardless of the number of vaccinations received over the previous 10 influenza seasons.
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Affiliation(s)
- Jeffrey C Kwong
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada.,Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Ontario, Canada.,Department of Family & Community Medicine, University of Toronto, Toronto, Ontario, Canada.,ICES, Toronto, Ontario, Canada
| | | | | | - Sarah A Buchan
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada.,ICES, Toronto, Ontario, Canada
| | - Aaron Campigotto
- Hospital for Sick Children, Toronto, Ontario, Canada.,University Health Network, Toronto, Ontario, Canada
| | | | - Natasha S Crowcroft
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,ICES, Toronto, Ontario, Canada
| | - Jonathan B Gubbay
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Hospital for Sick Children, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada
| | - Timothy Karnauchow
- Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Ontario, Canada.,Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | - Kevin Katz
- North York General Hospital, Toronto, Ontario, Canada
| | - Allison J McGeer
- Sinai Health System, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - J Dayre McNally
- Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada
| | | | - Susan E Richardson
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada.,Hospital for Sick Children, Toronto, Ontario, Canada
| | - Laura C Rosella
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada.,ICES, Toronto, Ontario, Canada
| | - Kevin L Schwartz
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.,Public Health Ontario, Toronto, Ontario, Canada.,ICES, Toronto, Ontario, Canada
| | - Andrew Simor
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.,Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | | | - George Zahariadis
- Newfoundland & Labrador Public Health Laboratory, St. John's, Newfoundland and Labrador, Canada.,London Health Sciences Centre, London, Ontario, Canada
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20
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Mouratidou E, Lambrou A, Andreopoulou A, Gioula G, Exindari M, Kossyvakis A, Pogka V, Mentis A, Georgakopoulou T, Lytras T. Influenza vaccine effectiveness against hospitalization with laboratory-confirmed influenza in Greece: A pooled analysis across six seasons, 2013-2014 to 2018-2019. Vaccine 2020; 38:2715-2724. [PMID: 32033848 DOI: 10.1016/j.vaccine.2020.01.083] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 01/24/2020] [Accepted: 01/27/2020] [Indexed: 11/24/2022]
Abstract
BACKGROUND Monitoring seasonal influenza Vaccine Effectiveness (VE) is key to inform vaccination strategies and sustain uptake. Pooling data across multiple seasons increases precision and allows for subgroup analyses, providing more conclusive evidence. Our aim was to assess VE against hospitalization with laboratory-confirmed influenza in Greece over six seasons, from 2013 to 2014 to 2018-2019, using routinely collected surveillance data. METHODS Swab samples from hospitalized patients across the country were tested for influenza by RT-PCR. We used the test-negative design, with patients testing positive for influenza serving as cases and those testing negative serving as controls. VE was calculated as one minus the Odds Ratio (OR) for influenza vaccination, estimated by mixed-effects logistic regression and adjusted for age, sex, hospitalization type (being in intensive care or not), time from symptom onset to swabbing, and calendar time. Stratified estimates by age and hospitalization type were obtained, and also subgroup estimates by influenza type/subtype and season. Antigenic and genetic characterization of a subset of circulating influenza strains was performed. RESULTS A total of 3,882 test-positive cases and 5,895 test-negative controls were analyzed. Across all seasons, adjusted VE was 45.5% (95% CI: 31.6-56.6) against all influenza, 62.8% against A(H1N1)pdm09 (95% CI: 40.7-76.7), 28.2% against A(H3N2) (95% CI: 12.0-41.3) and 45.5% against influenza B (95% CI: 29.1-58.1). VE was slightly lower for patients aged 60 years and over, and similar between patients hospitalized inside or outside intensive care. Circulating A(H1N1)pdm09 and B strains were antigenically similar to the vaccine strains, whereas A(H3N2) were not. CONCLUSION Our results confirm the public health benefits from seasonal influenza vaccination, despite the suboptimal effectiveness against A(H3N2) strains. Continued monitoring of VE is essential, and routinely collected surveillance data can be valuable in this regard.
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Affiliation(s)
- Elisavet Mouratidou
- National Public Health Organization, Athens, Greece; European Programme for Intervention Epidemiology Training (EPIET), European Centre for Disease Prevention and Control (ECDC), Stockholm, Sweden.
| | | | | | - Georgia Gioula
- National Influenza Centre for Northern Greece, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Maria Exindari
- National Influenza Centre for Northern Greece, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Athanasios Kossyvakis
- National Influenza Centre for Southern Greece, Hellenic Pasteur Institute, Athens, Greece
| | - Vasiliki Pogka
- National Influenza Centre for Southern Greece, Hellenic Pasteur Institute, Athens, Greece
| | - Andreas Mentis
- National Influenza Centre for Southern Greece, Hellenic Pasteur Institute, Athens, Greece
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21
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Scott AN, Buchan SA, Kwong JC, Drews SJ, Simmonds KA, Svenson LW. Using population-wide administrative and laboratory data to estimate type- and subtype-specific influenza vaccine effectiveness: a surveillance protocol. BMJ Open 2019; 9:e029708. [PMID: 31575570 PMCID: PMC6773297 DOI: 10.1136/bmjopen-2019-029708] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
INTRODUCTION The appropriateness of using routinely collected laboratory data combined with administrative data for estimating influenza vaccine effectiveness (VE) is still being explored. This paper outlines a protocol to estimate influenza VE using linked laboratory and administrative data which could act as a companion to estimates derived from other methods. METHODS AND ANALYSIS We will use the test-negative design to estimate VE for each influenza type/subtype and season. Province-wide individual-level records of positive and negative influenza tests at the Provincial Laboratory for Public Health in Alberta will be linked, by unique personal health numbers, to administrative databases and vaccination records held at the Ministry of Health in Alberta to determine covariates and influenza vaccination status, respectively. Covariates of interests include age, sex, immunocompromising chronic conditions and healthcare setting. Cases will be defined based on an individual's first positive influenza test during the season, and potential controls will be defined based on an individual's first negative influenza test during the season. One control for each case will be randomly selected based on the week the specimen was collected. We will estimate VE using multivariable logistic regression. ETHICS AND DISSEMINATION Ethics approval was obtained from the University of Alberta's Health Research Ethics Board-Health Panel under study ID Pro00075997. Results will be disseminated by public health officials in Alberta.
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Affiliation(s)
- Allison Nicole Scott
- Ministry of Health, Government of Alberta, Edmonton, Alberta, Canada
- Department of Public Health, Concordia University of Edmonton, Edmonton, Alberta, Canada
| | - Sarah A Buchan
- Populations and Public Health Research Program, ICES, Toronto, Ontario, Canada
- Public Health Sciences, Public Health Ontario, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Jeffrey C Kwong
- Populations and Public Health Research Program, ICES, Toronto, Ontario, Canada
- Public Health Sciences, Public Health Ontario, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
| | | | - Kimberley A Simmonds
- Ministry of Health, Government of Alberta, Edmonton, Alberta, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Lawrence W Svenson
- Ministry of Health, Government of Alberta, Edmonton, Alberta, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Division of Preventive Medicine, University of Alberta, Edmonton, Alberta, Canada
- School of Public Health, University of Alberta, Edmonton, Alberta, Canada
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