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Identifying adverse reactions following COVID-19 vaccination in Korea using data from active surveillance: a text mining approach

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영문명
발행기관
한국역학회
저자명
Hye Ah Lee Bomi Park Chung Ho Kim Yeonjae Kim Hyunjin Park Seunghee Jun Hyelim Lee Seunghyun Lewis Kwon Yesul Heo Hyungmin Lee Hyesook Park COVID-19 Vaccine Safety Research Committee
간행물 정보
『Epidemiology and Health』47, 1~11쪽, 전체 11쪽
주제분류
의약학 > 면역학
파일형태
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발행일자
2025.01.31
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국문 초록

OBJECTIVES: Unstructured text data collected through vaccine safety surveillance systems can identify previously unreported adverse reactions and provide critical information to enhance these systems. This study explored adverse reactions using text data collected through an active surveillance system following coronavirus disease 2019 (COVID-19) vaccination. METHODS: We performed text mining on 2,608 and 2,054 records from 2 survey seasons (2023-2024 and 2024-2025), in which participants reported health conditions experienced within 7 days of vaccination using free-text responses. Frequency analysis was conducted to identify key terms, followed by subgroup analyses by sex, age, and concomitant influenza vaccination. In addition, semantic network analysis was used to examine terms reported together. RESULTS: The analysis identified several common (≥1%) adverse events, such as respiratory symptoms, sleep disturbances, lumbago, and indigestion, which had not been frequently noted in prior literature. Moreover, less frequent (≥0.1 to <1.0%) adverse reactions affecting the eyes, ears, and oral cavity were also detected. These adverse reactions did not differ significantly in frequency based on the presence or absence of simultaneous influenza vaccination. Co-occurrence analysis and estimation of correlation coefficients further revealed associations between frequently co-reported symptoms. CONCLUSIONS: This study utilized text mining to uncover previously unrecognized adverse reactions associated with COVID-19 vaccination, thereby broadening our understanding of the vaccine’s safety profile. The insights obtained may inform future investigations into vaccine-related adverse reactions and improve the processing of text data in surveillance systems.

영문 초록

목차

INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
NOTES
REFERENCES

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APA

Hye Ah Lee,Bomi Park,Chung Ho Kim,Yeonjae Kim,Hyunjin Park,Seunghee Jun,Hyelim Lee,Seunghyun Lewis Kwon,Yesul Heo,Hyungmin Lee,Hyesook Park,COVID-19 Vaccine Safety Research Committee. (2025).Identifying adverse reactions following COVID-19 vaccination in Korea using data from active surveillance: a text mining approach. Epidemiology and Health, (), 1-11

MLA

Hye Ah Lee,Bomi Park,Chung Ho Kim,Yeonjae Kim,Hyunjin Park,Seunghee Jun,Hyelim Lee,Seunghyun Lewis Kwon,Yesul Heo,Hyungmin Lee,Hyesook Park,COVID-19 Vaccine Safety Research Committee. "Identifying adverse reactions following COVID-19 vaccination in Korea using data from active surveillance: a text mining approach." Epidemiology and Health, (2025): 1-11

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