본문 바로가기
KERD
논문KCI 등재

Barriers to COVID-19 vaccine surveillance: the issue of under-reporting adverse events

신주영|Choe Young June|Choe Seung Ah|Ko Hwa Yeon|Yoon Dongwon|Kim Ju Hwan|Noh Yunha|Jung Jaehun
한국역학회 (Korean Society of Epidemiology)|2023.01|Epidemiology and Health|제45권 |pp. 1-7|DOI 10.4178/epih.e2023054

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

COVID-19PharmacovigilanceVaccineCross-sectional survey

초록

OBJECTIVES: This study investigated the reporting rates of adverse events following immunization (AEFIs) to the spontaneous reporting system (SRS) and its predictors among individuals with AEFIs after coronavirus disease 2019 (COVID-19) vaccination. METHODS: A cross-sectional, web-based survey was conducted from December 2, 2021 to December 20, 2021, recruiting participants >14 days after completion of a primary COVID-19 vaccination series. Reporting rates were calculated by dividing the number of participants who reported AEFIs to the SRS by the total number of participants who experienced AEFIs. We estimated adjusted odds ratios (aORs) using multivariate logistic regression to determine factors associated with spontaneous AEFIs reporting. RESULTS: Among 2,993 participants, 90.9% and 88.7% experienced AEFIs after the first and second vaccine doses, respectively (reporting rates, 11.6 and 12.7%). Furthermore, 3.3% and 4.2% suffered moderate to severe AEFIs, respectively (reporting rates, 50.5 and 50.0%). Spontaneous reporting was more prevalent in female (aOR, 1.54; 95% confidence interval [CI], 1.31 to 1.81); those with moderate to severe AEFIs (aOR, 5.47; 95% CI, 4.45 to 6.73), comorbidities (aOR, 1.31; 95% CI, 1.09 to 1.57), a history of severe allergic reactions (aOR, 2.02; 95% CI, 1.47 to 2.77); and those who had received mRNA-1273 (aOR, 1.25; 95% CI, 1.05 to 1.49) or ChAdOx1 (aOR, 1.62; 95% CI, 1.15 to 2.30) vaccines versus BNT162b2. Reporting was less likely in older individuals (aOR, 0.98; 95% CI, 0.98 to 0.99 per 1-year age increment). CONCLUSIONS: Spontaneous reporting of AEFIs after COVID-19 vaccination was associated with younger age, female sex, moderate to severe AEFIs, comorbidities, history of allergic reactions, and vaccine type. AEFIs under-reporting should be considered when delivering information to the community and in public health decision-making.

Abstract

OBJECTIVES: This study investigated the reporting rates of adverse events following immunization (AEFIs) to the spontaneous reporting system (SRS) and its predictors among individuals with AEFIs after coronavirus disease 2019 (COVID-19) vaccination. METHODS: A cross-sectional, web-based survey was conducted from December 2, 2021 to December 20, 2021, recruiting participants >14 days after completion of a primary COVID-19 vaccination series. Reporting rates were calculated by dividing the number of participants who reported AEFIs to the SRS by the total number of participants who experienced AEFIs. We estimated adjusted odds ratios (aORs) using multivariate logistic regression to determine factors associated with spontaneous AEFIs reporting. RESULTS: Among 2,993 participants, 90.9% and 88.7% experienced AEFIs after the first and second vaccine doses, respectively (reporting rates, 11.6 and 12.7%). Furthermore, 3.3% and 4.2% suffered moderate to severe AEFIs, respectively (reporting rates, 50.5 and 50.0%). Spontaneous reporting was more prevalent in female (aOR, 1.54; 95% confidence interval [CI], 1.31 to 1.81); those with moderate to severe AEFIs (aOR, 5.47; 95% CI, 4.45 to 6.73), comorbidities (aOR, 1.31; 95% CI, 1.09 to 1.57), a history of severe allergic reactions (aOR, 2.02; 95% CI, 1.47 to 2.77); and those who had received mRNA-1273 (aOR, 1.25; 95% CI, 1.05 to 1.49) or ChAdOx1 (aOR, 1.62; 95% CI, 1.15 to 2.30) vaccines versus BNT162b2. Reporting was less likely in older individuals (aOR, 0.98; 95% CI, 0.98 to 0.99 per 1-year age increment). CONCLUSIONS: Spontaneous reporting of AEFIs after COVID-19 vaccination was associated with younger age, female sex, moderate to severe AEFIs, comorbidities, history of allergic reactions, and vaccine type. AEFIs under-reporting should be considered when delivering information to the community and in public health decision-making.

참고문헌 (32)

  1. Nikfarjam A, "Early detection of adverse drug reactions in social health networks : a natural language processing pipeline for signal detection", JMIR Public Health Surveill, 5, pp.e11264~ (2019)
  2. Luo C, "Comparability of clinical trials and spontaneous reporting data regarding COVID-19 vaccine safety", Sci Rep, 12, pp.10946~ (2022)
  3. Dhodapkar MM, "Characterization and corroboration of safety signals identified from the US Food and Drug Administration Adverse Event Reporting System, 2008-19 : cross sectional study", BMJ, 379, pp.e071752~ (2022)
  4. "COVID-19 vaccines: safety surveillance manual" (2021)[URL]
  5. Petousis-Harris H, "Assessing the safety of COVID-19 vaccines : a primer", Drug Saf, 43, pp.1205~1210 (2020)
  6. Paul E, "Attitudes towards vaccines and intention to vaccinate against COVID-19 : implications for public health communications", Lancet Reg Health Eur, 1, pp.100012~ (2021)
  7. Wan EY, "Bell’s palsy following vaccination with mRNA(BNT162b2)and inactivated(CoronaVac)SARS-CoV-2 vaccines : a case series and nested case-control study", Lancet Infect Dis, 22, pp.64~72 (2022)
  8. See I, "Case series of thrombosis with thrombocytopenia syndrome after COVID-19 vaccination-United States, December 2020 to August 2021", Ann Intern Med, 175, pp.513~522 (2022)
  9. Hazell L, "Under-reporting of adverse drug reactions : a systematic review", Drug Saf, 29, pp.385~396 (2006)
  10. Kim S, "A cross-sectional survey of knowledge, attitude, and willingness to engage in spontaneous reporting of adverse drug reactions by Korean consumers", BMC Public Health, 20, pp.1527~ (2020)
  11. Beatty AL, "Analysis of COVID-19 vaccine type and adverse effects following vaccination", JAMA Netw Open, 4, pp.e2140364~ (2021)
  12. Ganesan S, "Vaccine side effects following COVID-19 vaccination among the residents of the UAE-an observational study", Front Public Health, 10, pp.876336~ (2022)
  13. Etikan I, "Sampling and sampling methods", Biom Biostat Int J, 5, pp.00149~ (2017)
  14. Polack FP, "Safety and efficacy of the BNT162b2 mRNA Covid-19 vaccine", N Engl J Med, 383, pp.2603~2615 (2020)
  15. Sadoff J, "Safety and efficacy of single-dose Ad26. COV2. S vaccine against Covid-19", N Engl J Med, 384, pp.2187~2201 (2021)
  16. "Monitoring of adverse events following COVID-19 immunization in South Korea 2023"[URL]
  17. Reinfeld S, "Can new onset psychosis occur after mRNA based COVID-19 vaccine administration? A case report", Psychiatry Res, 304, pp.114165~ (2021)
  18. Ameratunga R, "SARS-CoV-2 the ASIA virus(Autoimmune", autoinflammatory Syndrome Induced by Adjuvants), the risk of infertility and vaccine hesitancy, 2022, pp.21, 1177~1184
  19. von Elm E, "The Strengthening the Reporting of Observational Studies in Epidemiology(STROBE)statement : guidelines for reporting observational studies", J Clin Epidemiol, 61, pp.344~349 (2008)
  20. Hervé C, "The how’s and what’s of vaccine reactogenicity", NPJ Vaccines, 4, pp.39~ (2019)
  21. Male V, "COVID-19 vaccination and menstruation", Science, 378, pp.704~706 (2022)
  22. Grover S, "First episode psychosis following receipt of first dose of COVID-19 vaccine : a case report", Schizophr Res, 241, pp.70~71 (2022)
  23. Davies MJ, "The attitudes of pharmacists, students and the general public on mHealth applications for medication adherence", Pharm Pract(Granada), 13, pp.644~ (2015)
  24. Klein SL, "Sex differences in immune responses", Nat Rev Immunol, 16, pp.626~638 (2016)
  25. Sedgwick P, "Non-response bias versus response bias", BMJ, 348, pp.g2573~ (2014)
  26. Mosnier-Pudar H, "How do patients with type 2 diabetes perceive their disease? Insights from the French DIABASIS survey", Diabetes Metab, 35, pp.220~227 (2009)
  27. Martel MO, "Self-reports of medication side effects and pain-related activity interference in patients with chronic pain : a longitudinal cohort study", Pain, 156, pp.1092~1100 (2015)
  28. Urakawa R, "Impact of age, sex and medical history on adverse reactions to the first and second dose of BNT162b2 mRNA COVID-19 vaccine in Japan : a cross-sectional study", BMC Infect Dis, 22, pp.179~ (2022)
  29. Kitagawa H, "Adverse reactions to the BNT162b2 and mRNA-1273 mRNA COVID-19 vaccines in Japan", J Infect Chemother, 28, pp.576~581 (2022)
  30. Kant A, "Description of frequencies of reported adverse events following immunization among four different COVID-19 vaccine brands", Drug Saf, 45, pp.319~331 (2022)
  31. Merkley E, "The correlates and dynamics of COVID-19 vaccine-specific hesitancy", Vaccine, 40, pp.2020~2027 (2022)
  32. Hughes MT, "Opinion : the importance of offering vaccine choice in the fight against COVID-19", Proc Natl Acad Sci U S A, 118, pp.e2117185118~ (2021)

관련 논문AI추천

지역 약사의 자발적 부작용 보고에 대한 인식 및 태도와 영향요인 조사: 설문조사 결과를 중심으로김나영, 신주영, 이모세, 이정민, 장보현, 전하림, 최아형한국임상약학회 · 한국임상약학회지2019 · 제29권 제2호Self-reported adverse events after 2 doses of COVID-19 vaccine in Korea고미정, 김형준, 황인섭, Cho Enhi, Kim Seontae, Kwon Yunhyung, Seo Soon-Young, Yeon-Kyeng Lee한국역학회 · Epidemiology and Health2023 · 제45권 Identifying adverse reactions following COVID-19 vaccination in Korea using data from active surveillance: a text mining approachHeo Yesul, Jun Seunghee, Kim Chung Ho, Kim Yeonjae, Kwon Seunghyun Lewis, Lee Hye Ah, Lee Hyelim, Lee Hyungmin, Park Bomi, Park Hyesook, Park Hyunjin한국역학회 · Epidemiology and Health2025 · 제47권 Updates on Vaccine Safety and Post-Licensure Surveillance for Adverse Events Following Immunization in South Korea, 2005–2017김주환, 신주영, 윤동원, 이혜성연세대학교의과대학 · Yonsei Medical Journal2020 · 제61권 제7호A Comparison of Active Surveillance Programs Including a Spontaneous Reporting Model for Phamacovigilance of Adverse Drug Events in a Hospital구명진, 김성은, 박은혜, 박중원, 윤일선, 이재현, 홍천수대한내과학회 · The Korean Journal of Internal Medicine2012 · 제27권 제4호Signal Detection of Adverse Events Following Pneumococcal Vaccines from the Korea Adverse Event Reporting System Database, 2005–2016김관수, 김현정, 박민수, 송인명, 신주영, 오인선연세대학교의과대학 · Yonsei Medical Journal2020 · 제61권 제3호

이 간행물의 다른 논문 (102건)

Changes in health behaviors and obesity of Korean adolescents before and during the COVID-19 pandemic: a special report using the Korea Youth Risk Behavior SurveyChoi Sunhye, Oh Kyungwon, 오창모, Kim Yangha, Yang Ji Eunpp. 1-8Korea Seroprevalence Study of Monitoring of SARS-COV-2 Antibody Retention and Transmission (K-SEROSMART): findings from national representative sample황태윤, 오경재, 홍영습, Kim Su Young, 이계오, 윤규현, 김정애, 이혁민, 신민호, 이순영, 이원영, 김동현, 박재현, 이훈재, 조성일, 남해성, 이무식, Lee June-Woo, Kim Sung Soon, 설로마, Kim Byoungguk, 이중정, 오창모, Jung Sun Jae, 오성수, Yim Hyeon Woo, 한미아, 김유미, 조희숙, Lee Ju-Hyung, Jung Jaehun, Kim Ah-Ra, Han Jina, Baek Hye Jin, Noh Eunbi, Ryu Sukhyun, 박노례, Jung Eunok, Kim Sang Il, Hwang Yoo-Sung, Oh Sangcheol, Kim Migyeong, Yu Byengchul, Kim Keonyeop, Hwangbo Young, Lee Joongyub, Kim Hyeongsu, Kang Gilwon, Ryu So Yeon, Park Soon-Woo, Kim Sang Kyu, Park Ki Soo, Kwon Jun-wook, Jang Eun Young, Nam Jeonghyunpp. 1-13Genetically determined alcohol consumption and cancer risk in Korea지선하, 정금지, 백지우, Shin Sang Yoppp. 1-7Self-reported adverse events after 2 doses of COVID-19 vaccine in Korea고미정, 김형준, 황인섭, Kwon Yunhyung, Kim Seontae, Seo Soon-Young, Cho Enhi, Yeon-Kyeng Leepp. 1-7Detecting mpox infection in the early epidemic: an epidemiologic investigation of the third and fourth cases in KoreaChoi Jihyun, Choi Yunsang, Kim Jong Mu, 박숙경, Kim Taeyoung, Park Eonjoo, Eun Juk Suk, Lee Eun-young, Mun Ji Won, Lee Sinyoung, Yeom Hansol, Kim Eun Kyoung, Ha Jinhopp. 1-7
원문 보기