Ottawa Hospital Research Institute, Clinical Epidemiology Program, Ottawa, Canada.
School of Population and Public Health, University of British Columbia, Vancouver, Canada.
Vaccine. 2022 Jul 29;40(31):4065-4080. doi: 10.1016/j.vaccine.2022.04.103. Epub 2022 Jun 6.
Post-licensure adverse events following immunization (AEFI) surveillance is conducted to monitor vaccine safety, such as identifying batch/brand issues and rare reactions, which consequently improves community confidence. The integration of technology has been proposed to improve AEFI surveillance, however, there is an absence of description regarding which digital solutions are successfully being used and their unique characteristics.
The objectives of this scoping review were to 1) map the research landscape on digital systems used for active, participant-centred, AEFI surveillance and 2) describe their core components.
We conducted a scoping review informed by the PRISMA Extension for Scoping Reviews (PRSIMA-ScR) guideline. OVID-Medline, Embase Classic + Embase, and Medrxiv were searched by a medical librarian from January 1, 2000 to January 28th, 2021. Two independent reviewers determined which studies met inclusion based on pre-specified eligibility criteria. Data extraction was conducted using pre-made tables with specific variables by one investigator and verified by a second.
Twenty-seven publications met inclusion, the majority of which came from Australia (n = 15) and Canada (n = 6). The most studied active, participant-centred, digital AEFI surveillance systems were SmartVax (n = 8) (Australia), Vaxtracker (n = 7) (Australia), and Canadian National Vaccine Safety (CANVAS) Network (Canada) (n = 6). The two most common methods of communicating with vaccinees reported were short-message-service (SMS) (n = 15) and e-mail (n = 14), with online questionnaires being the primary method of data collection (n = 20).
Active, participant-centred, digital AEFI surveillance is an area actively being researched as depicted by the literature landscape mapped by this scoping reviewWe hypothesize that the AEFI surveillance approach herein described could become a primary method of collecting self-reported subjective symptoms and reactogenicity from vaccinees, complementing existing systems. Future evaluation of identified digital solutions is necessary to bring about improvements to current vaccine surveillance systems to meet contemporary and future public health needs.
疫苗接种后不良事件（AEFI）监测是为了监测疫苗安全性而进行的，例如识别批次/品牌问题和罕见反应，从而提高社区信心。已经提出了整合技术以改善 AEFI 监测，但是，关于哪些数字解决方案正在成功使用以及它们的独特特征，缺乏描述。
本范围综述的目的是 1）绘制用于主动、以参与者为中心的 AEFI 监测的数字系统的研究图景，2）描述它们的核心组成部分。
我们根据 PRISMA 扩展用于范围综述（PRISMA-ScR）指南进行了范围综述。一名医学图书管理员从 2000 年 1 月 1 日至 2021 年 1 月 28 日在 OVID-Medline、Embase Classic + Embase 和 Medrxiv 上进行了搜索。两名独立审查员根据预先规定的纳入标准确定了哪些研究符合纳入标准。使用预先制作的表格和特定变量由一名调查员进行数据提取，并由第二名调查员进行验证。
27 篇出版物符合纳入标准，其中大多数来自澳大利亚（n=15）和加拿大（n=6）。研究最多的主动、以参与者为中心的数字 AEFI 监测系统是 SmartVax（n=8）（澳大利亚）、Vaxtracker（n=7）（澳大利亚）和加拿大国家疫苗安全（CANVAS）网络（加拿大）（n=6）。报告的与疫苗接种者最常见的两种沟通方式是短消息服务（SMS）（n=15）和电子邮件（n=14），在线问卷调查是主要的数据收集方法（n=20）。
如本范围综述所描绘的，主动、以参与者为中心的数字 AEFI 监测是一个积极研究的领域。我们假设，本文所述的 AEFI 监测方法可以成为从疫苗接种者那里收集自我报告的主观症状和反应原性的主要方法，补充现有的系统。需要对已确定的数字解决方案进行进一步评估，以改进当前的疫苗监测系统，以满足当代和未来的公共卫生需求。
