Department of Public Health Sciences, Dalla Lana School of Public Health, University of Toronto, 155 College St, Toronto, ON, M5T 3M7, Canada.
MAP Centre for Urban Health Solutions, St. Michael's Hospital, Unity Health Toronto, 30 Bond St, Toronto, ON, M5B 1W8, Canada.
Can J Public Health. 2021 Oct;112(5):867-871. doi: 10.17269/s41997-021-00554-z. Epub 2021 Jun 23.
Although clinical trials are necessary for vaccine approval, observational epidemiology will be required to evaluate the long-term effectiveness, safety, and population impacts of newly approved COVID-19 vaccines under real-world field conditions. In this commentary, I argue that a hybrid approach that combines new data sources and tools, including COVID-19 vaccine registries, with traditional epidemiological methods will be needed to evaluate COVID-19 vaccines using observational epidemiology. Wherever possible, primary data collection, active surveillance, and linkage with existing population-based cohorts should be leveraged to supplement secondary data sources and passive surveillance systems. Evidence-informed public health decision making around provincial COVID-19 immunization programs will need to account for potential biases, incomplete or conflicting information, and heterogeneity across subpopulations.
虽然临床试验对于疫苗批准是必要的，但为了评估新批准的 COVID-19 疫苗在真实环境下的长期效果、安全性和人群影响，还需要进行观察性流行病学研究。在这篇评论中，我认为需要一种混合方法，将包括 COVID-19 疫苗登记处在内的新数据源和工具与传统流行病学方法相结合，以利用观察性流行病学来评估 COVID-19 疫苗。只要有可能，就应利用原始数据收集、主动监测以及与现有人群队列的链接来补充二手数据源和被动监测系统。在制定省级 COVID-19 免疫计划的循证公共卫生决策时，需要考虑潜在的偏倚、信息不完整或相互矛盾以及亚人群之间的异质性。
