The characteristics and trend of adverse events following immunization reported by information system in Jiangsu province, China, 2015–2018

BMC PUBLIC HEALTH(2021)

引用 6|浏览15
暂无评分
摘要
Objective Adverse events following immunization is an important factor influencing public trust in vaccination. Publicizing its incidence timely can increase public trust. The aim of this study is to describe the incidence and characteristics of adverse events following immunization in Jiangsu province of China from 2015 to 2018. Methods All information of adverse events following immunization (AEFIs) was gained from Jiangsu Province Vaccination Integrated Service Management Information System. The reported AEFI trend was analyzed using Chi-square test. Results A total of 77,980 AEFI cases were reported through the AEFI system; Among which, 77,731 were classified as non-serious AEFI cases and 249 were serious AEFI cases. The male to female ratio was 1.31:1, cases less than 7 years old accounted for 97.7%. The total estimated AEFI rate was 62.70/100,000 doses. By severity, 60.75/100,000, 4.46/100,000 and 0.11/100,000 AEFI cases were common vaccine reaction, rare vaccine reaction, and serious rare vaccine reaction, respectively. The top two serious AEFI were thrombocytopenic purpura and febrile. The incidence rates showed the increasing trend and the linear trend of the increasing incidence rates passed the significant test at 0.05 levels. Conclusion The sensitivity of AEFI monitoring in Jiangsu Province is increasing and higher than the national average and most countries. The majority of AEFI cases were common adverse reactions, while the serious vaccine reactions caused by vaccines were extremely low. To elevate the sensitivity of AEFI surveillance may reduce the incidence of developing serious AEFI cases.
更多
查看译文
关键词
Adverse events following immunization, Incidence of adverse events following immunization, Serious vaccine reaction, Common vaccine reaction, Vaccine, Categories of vaccine reaction
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要