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Clothier HJ, Shetty AN, Mesfin Y, Mackie M, Pearce C, Buttery JP. What would have happened anyway? Population data source considerations when estimating background incident rates of adverse events following immunisation to inform vaccine safety. Vaccine 2024; 42:1108-1115. [PMID: 38262811 DOI: 10.1016/j.vaccine.2024.01.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 01/05/2024] [Accepted: 01/08/2024] [Indexed: 01/25/2024]
Abstract
INTRODUCTION Understanding background incident rates of adverse events following immunisation (AEFI) is essential to rapidly detect, evaluate, respond to, and communicate about vaccine safety concerns, especially for new vaccines. Creating estimates based on geographic specific population level data is increasingly important, as new AEFI presentations will be subject to the same local influences of population demography, exposures, health system variations and level of health care sought. METHODS We conducted a retrospective cohort analysis of hospital admissions, emergency department presentations and general practice consultations from 2015 to 2019-before introduction of COVID-19, Mpox or Shingrix vaccination-to estimate background incident rates for 37 conditions considered potential AEFI of special interest (AESI). Background incident rates per 100,000 population were calculated and presented as cases expected to occur coincidentally 1 day, 1 week and 6 weeks post-vaccination, by life-stage age-groups and presenting healthcare setting. We then assessed the proportional contribution of each data source to inform each AESI background rate estimate. RESULTS 16,437,156 episodes of the 37 AESI were identified. Hospital admissions predominantly informed 19 (51%) of AESI, including exclusively ADEM and CVST; 8 AESI (22%) by primary care, and 10 (27%) a mix. Four AESI (allergic urticaria, Bell's palsy, erythema multiform and sudden death) were better informed by emergency presentations than admissions, but conversely 11 AESI (30%) were not captured in ICD-10 coded emergency presentations at all. CONCLUSIONS Emergent safety concerns are inevitable in population-wide implementation of new vaccines, therefore understanding local background rates aids both safety signal detection as well as maintaining public confidence in vaccination. Hospital and primary care data sources can be interrogated to inform expected background incident rates of adverse events that may occur following vaccination. However, it is necessary to understand which data-source provides best intelligence according to nature of condition and presenting healthcare setting.
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Affiliation(s)
- Hazel J Clothier
- Health Informatics, Centre for Health Analytics, Melbourne Children's Campus, 50 Flemington Road, Parkville, Victoria, Australia; SAEFVIC, Infection and Immunity, Murdoch Children's Research Institute, 50 Flemington Road, Parkville, Victoria, Australia; Melbourne School of Population & Global Health, University of Melbourne, Grattan Street, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Grattan Street, Parkville, Victoria, Australia.
| | - Aishwarya N Shetty
- Health Informatics, Centre for Health Analytics, Melbourne Children's Campus, 50 Flemington Road, Parkville, Victoria, Australia; SAEFVIC, Infection and Immunity, Murdoch Children's Research Institute, 50 Flemington Road, Parkville, Victoria, Australia.
| | - Yonatan Mesfin
- SAEFVIC, Infection and Immunity, Murdoch Children's Research Institute, 50 Flemington Road, Parkville, Victoria, Australia
| | - Michael Mackie
- Victorian Agency for Health Information, Victorian Government Department of Health, 50 Lonsdale Street, Melbourne, Victoria, Australia.
| | | | - Jim P Buttery
- Health Informatics, Centre for Health Analytics, Melbourne Children's Campus, 50 Flemington Road, Parkville, Victoria, Australia; SAEFVIC, Infection and Immunity, Murdoch Children's Research Institute, 50 Flemington Road, Parkville, Victoria, Australia; Department of Paediatrics, University of Melbourne, Grattan Street, Parkville, Victoria, Australia; Department of General Medicine, The Royal Children's Hospital, 50 Flemington Road, Parkville, Victoria, Australia.
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Lin CH, Chen TA, Chiang PH, Hsieh AR, Wu BJ, Chen PY, Lin KC, Tsai ZS, Lin MH, Chen TJ, Chen YC. Incidence and Nature of Short-Term Adverse Events following COVID-19 Second Boosters: Insights from Taiwan's Universal Vaccination Strategy. Vaccines (Basel) 2024; 12:149. [PMID: 38400133 PMCID: PMC10892656 DOI: 10.3390/vaccines12020149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 01/27/2024] [Accepted: 01/28/2024] [Indexed: 02/25/2024] Open
Abstract
This study evaluates the incidence and characteristics of adverse events (AEs) following the second COVID-19 booster dose, leveraging Taiwan's distinctive approach of extending booster vaccinations to all citizens, unlike the targeted high-risk group strategies in other countries. Utilizing data from Taipei Veterans General Hospital's Vaccine Adverse Event Reporting System (VAERS) from 27 October 2022 to 19 January 2023, this research examines AEs in 441 out of 1711 booster recipients, considering factors like age, vaccine brands, and booster combinations. The findings revealed incidence rates (IRs) of 25.6% (95% CI: 21.1-30.8) after the first booster and 24.9% (95% CI: 20.5-30.0) after the second, mostly non-serious, with those having AEs post-first booster being five times more likely to report them again (incidence rate ratio, 5.02, p < 0.001). Significantly, switching from the mRNA1273 vaccine to another brand reduced AE risk by 18%. This study underscores that AEs are more repetitive than cumulative with additional booster doses, advocating for personalized vaccination strategies based on individual medical histories and previous vaccine reactions. These insights are valuable for healthcare providers in discussing potential AEs with patients, thereby improving vaccine compliance and public trust, and for policymakers in planning future booster vaccination strategies.
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Affiliation(s)
- Ching-Hao Lin
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan; (C.-H.L.); (T.-A.C.); (K.-C.L.); (M.-H.L.); (T.-J.C.)
| | - Tsung-An Chen
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan; (C.-H.L.); (T.-A.C.); (K.-C.L.); (M.-H.L.); (T.-J.C.)
| | - Pin-Hsuan Chiang
- Big Data Center, Taipei Veterans General Hospital, Taipei 112, Taiwan; (P.-H.C.); (Z.-S.T.)
| | - Ai-Ru Hsieh
- Department of Statistics, Tamkang University, New Taipei City 251, Taiwan;
| | - Bih-Ju Wu
- Department of Nursing, Taipei Veterans General Hospital, Taipei 112, Taiwan;
| | - Po-Yu Chen
- Department of Family Medicine, Cheng Hsin General Hospital, Taipei 112, Taiwan;
| | - Kuan-Chen Lin
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan; (C.-H.L.); (T.-A.C.); (K.-C.L.); (M.-H.L.); (T.-J.C.)
| | - Zih-Syun Tsai
- Big Data Center, Taipei Veterans General Hospital, Taipei 112, Taiwan; (P.-H.C.); (Z.-S.T.)
| | - Ming-Hwai Lin
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan; (C.-H.L.); (T.-A.C.); (K.-C.L.); (M.-H.L.); (T.-J.C.)
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
| | - Tzeng-Ji Chen
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan; (C.-H.L.); (T.-A.C.); (K.-C.L.); (M.-H.L.); (T.-J.C.)
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
- Department of Family Medicine, Taipei Veterans General Hospital, Hsinchu Branch, Hsinchu 31064, Taiwan
| | - Yu-Chun Chen
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei 112, Taiwan; (C.-H.L.); (T.-A.C.); (K.-C.L.); (M.-H.L.); (T.-J.C.)
- Big Data Center, Taipei Veterans General Hospital, Taipei 112, Taiwan; (P.-H.C.); (Z.-S.T.)
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112, Taiwan
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Phillips A, Jiang Y, Walsh D, Andrews N, Artama M, Clothier H, Cullen L, Deng L, Escolano S, Gentile A, Gidding G, Giglio N, Junker T, Huang W, Janjua N, Kwong J, Li J, Nasreen S, Naus M, Naveed Z, Pillsbury A, Stowe J, Vo T, Buttery J, Petousis-Harris H, Black S, Hviid A. Background rates of adverse events of special interest for COVID-19 vaccines: A multinational Global Vaccine Data Network (GVDN) analysis. Vaccine 2023; 41:6227-6238. [PMID: 37673715 DOI: 10.1016/j.vaccine.2023.08.079] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND The Global COVID Vaccine Safety (GCoVS) project was established in 2021 under the multinational Global Vaccine Data Network (GVDN) consortium to facilitate the rapid assessment of the safety of newly introduced vaccines. This study analyzed data from GVDN member sites on the background incidence rates of conditions designated as adverse events of special interest (AESI) for COVID-19 vaccine safety monitoring. METHODS Eleven GVDN global sites obtained data from national or regional healthcare databases using standardized methods. Incident events of 13 pre-defined AESI were included for a pre-pandemic period (2015-19) and the first pandemic year (2020). Background incidence rates (IR) and 95% confidence intervals (CI) were calculated for inpatient and emergency department encounters, stratified by age and sex, and compared between pre-pandemic and pandemic periods using incidence rate ratios. RESULTS An estimated 197 million people contributed 1,189,652,926 person-years of follow-up time. Among inpatients in the pre-pandemic period (2015-19), generalized seizures were the most common neurological AESI (IR ranged from 22.15 [95% CI 19.01-25.65] to 278.82 [278.20-279.44] per 100,000 person-years); acute disseminated encephalomyelitis was the least common (<0.5 per 100,000 person-years at most sites). Pulmonary embolism was the most common thrombotic event (IR 45.34 [95% CI 44.85-45.84] to 93.77 [95% CI 93.46-94.08] per 100,000 person-years). The IR of myocarditis ranged from 1.60 [(95% CI 1.45-1.76) to 7.76 (95% CI 7.46-8.08) per 100,000 person-years. The IR of several AESI varied by site, healthcare setting, age and sex. The IR of some AESI were notably different in 2020 compared to 2015-19. CONCLUSION Background incidence of AESIs exhibited some variability across study sites and between pre-pandemic and pandemic periods. These findings will contribute to global vaccine safety surveillance and research.
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Affiliation(s)
- A Phillips
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia
| | - Y Jiang
- Department of Statistics, University of Auckland, New Zealand; Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand
| | - D Walsh
- Department of Statistics, University of Auckland, New Zealand; Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand
| | - N Andrews
- UK Health Security Agency, London, UK
| | - M Artama
- Faculty of Social Sciences, Tampere University, Finland
| | - H Clothier
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - L Cullen
- Public Health Scotland, Edinburgh, Scotland, UK
| | - L Deng
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia
| | - S Escolano
- Université Paris-Saclay, UVSQ, Inserm, CESP, High Dimensional Biostatistics for Drug Safety and Genomics, Villejuif, France
| | - A Gentile
- Hospital de Niños Ricardo Gutierrez Epidemiology Department Buenos Aires City, Argentina
| | - G Gidding
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia; The University of Sydney Northern Clinical School, Australia
| | - N Giglio
- Hospital de Niños Ricardo Gutierrez Epidemiology Department Buenos Aires City, Argentina
| | - T Junker
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - W Huang
- Global Health Program, College of Public Health, National Taiwan University, Taipei, Taiwan; National Taiwan University Children's Hospital, Taipei, Taiwan
| | - N Janjua
- British Columbia Centre for Disease Control, Vancouver, Canada; School of Population and Public Health, University of British Columbia, Vancouver, Canada; Centre for Health Evaluation and Outcome Sciences, St Paul's Hospital, Vancouver, Canada
| | - J Kwong
- ICES, Toronto, Ontario, Canada; Public Health Ontario, Toronto, Ontario, Canada; Department of Family and Community Medicine, Temerty Faculty of Medicine and the Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - J Li
- British Columbia Centre for Disease Control, Vancouver, Canada
| | - S Nasreen
- ICES, Toronto, Ontario, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - M Naus
- British Columbia Centre for Disease Control, Vancouver, Canada; School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - Z Naveed
- School of Population and Public Health, University of British Columbia, Vancouver, Canada
| | - A Pillsbury
- National Centre for Immunisation Research and Surveillance, Westmead, New South Wales, Australia
| | - J Stowe
- UK Health Security Agency, London, UK
| | - T Vo
- Faculty of Social Sciences, Tampere University, Finland; Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - J Buttery
- Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand; Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - H Petousis-Harris
- Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand; Associate Professor, School of Population Health, University of Auckland, New Zealand
| | - S Black
- Global Vaccine Data Network, Global Coordinating Centre, Auckland, New Zealand
| | - A Hviid
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark; Pharmacovigilance Research Center, Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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