d4l Data4Life gGmbH, Potsdam, Germany.
Institute of Medical Informatics, Charité University Medicine Berlin, Berlin, Germany.
J Med Internet Res. 2024 Jun 4;26:e47070. doi: 10.2196/47070.
The COVID-19 pandemic posed significant challenges to global health systems. Efficient public health responses required a rapid and secure collection of health data to improve the understanding of SARS-CoV-2 and examine the vaccine effectiveness (VE) and drug safety of the novel COVID-19 vaccines.
This study (COVID-19 study on vaccinated and unvaccinated subjects over 16 years; eCOV study) aims to (1) evaluate the real-world effectiveness of COVID-19 vaccines through a digital participatory surveillance tool and (2) assess the potential of self-reported data for monitoring key parameters of the COVID-19 pandemic in Germany.
Using a digital study web application, we collected self-reported data between May 1, 2021, and August 1, 2022, to assess VE, test positivity rates, COVID-19 incidence rates, and adverse events after COVID-19 vaccination. Our primary outcome measure was the VE of SARS-CoV-2 vaccines against laboratory-confirmed SARS-CoV-2 infection. The secondary outcome measures included VE against hospitalization and across different SARS-CoV-2 variants, adverse events after vaccination, and symptoms during infection. Logistic regression models adjusted for confounders were used to estimate VE 4 to 48 weeks after the primary vaccination series and after third-dose vaccination. Unvaccinated participants were compared with age- and gender-matched participants who had received 2 doses of BNT162b2 (Pfizer-BioNTech) and those who had received 3 doses of BNT162b2 and were not infected before the last vaccination. To assess the potential of self-reported digital data, the data were compared with official data from public health authorities.
We enrolled 10,077 participants (aged ≥16 y) who contributed 44,786 tests and 5530 symptoms. In this young, primarily female, and digital-literate cohort, VE against infections of any severity waned from 91.2% (95% CI 70.4%-97.4%) at week 4 to 37.2% (95% CI 23.5%-48.5%) at week 48 after the second dose of BNT162b2. A third dose of BNT162b2 increased VE to 67.6% (95% CI 50.3%-78.8%) after 4 weeks. The low number of reported hospitalizations limited our ability to calculate VE against hospitalization. Adverse events after vaccination were consistent with previously published research. Seven-day incidences and test positivity rates reflected the course of the pandemic in Germany when compared with official numbers from the national infectious disease surveillance system.
Our data indicate that COVID-19 vaccinations are safe and effective, and third-dose vaccinations partially restore protection against SARS-CoV-2 infection. The study showcased the successful use of a digital study web application for COVID-19 surveillance and continuous monitoring of VE in Germany, highlighting its potential to accelerate public health decision-making. Addressing biases in digital data collection is vital to ensure the accuracy and reliability of digital solutions as public health tools.
COVID-19 大流行对全球卫生系统构成了重大挑战。有效的公共卫生应对措施需要快速、安全地收集卫生数据，以提高对 SARS-CoV-2 的认识，并检查新型 COVID-19 疫苗的疫苗有效性 (VE) 和药物安全性。
本研究（接种和未接种 16 岁以上人群的 COVID-19 研究；eCOV 研究）旨在 (1) 通过数字参与式监测工具评估 COVID-19 疫苗的真实世界效果，(2) 评估自我报告数据在监测德国 COVID-19 大流行关键参数方面的潜力。
我们使用数字研究网络应用程序，于 2021 年 5 月 1 日至 2022 年 8 月 1 日期间收集自我报告数据，以评估 VE、检测阳性率、COVID-19 发病率和 COVID-19 疫苗接种后的不良事件。我们的主要结局指标是 SARS-CoV-2 疫苗对实验室确诊的 SARS-CoV-2 感染的 VE。次要结局指标包括对住院和不同 SARS-CoV-2 变体的 VE、疫苗接种后不良事件以及感染期间的症状。使用调整混杂因素的逻辑回归模型来估计初次接种系列后 4 至 48 周以及第三剂接种后的 VE。未接种疫苗的参与者与年龄和性别匹配的、已接种 2 剂 BNT162b2（辉瑞-生物科技）的参与者和已接种 3 剂 BNT162b2 且最后一次接种前未感染的参与者进行比较。为了评估自我报告的数字数据的潜力，将数据与公共卫生当局的官方数据进行了比较。
我们招募了 10077 名（年龄≥16 岁）参与者，他们提供了 44786 次检测和 5530 次症状。在这个年轻、主要是女性且精通数字技术的队列中，BNT162b2 第二剂接种后 4 周时，对任何严重程度的感染的 VE 从 91.2%（95%CI 70.4%-97.4%）下降到 48 周时的 37.2%（95%CI 23.5%-48.5%）。第三剂 BNT162b2 接种后 4 周时，VE 增加至 67.6%（95%CI 50.3%-78.8%）。报告的住院人数较少，限制了我们计算针对住院的 VE 的能力。疫苗接种后的不良事件与先前发表的研究一致。与国家传染病监测系统的官方数据相比，7 天发病率和检测阳性率反映了德国大流行的进程。
我们的数据表明，COVID-19 疫苗安全有效，第三剂疫苗部分恢复了对 SARS-CoV-2 感染的保护。该研究展示了数字研究网络应用程序在 COVID-19 监测和德国 VE 持续监测中的成功应用，突出了其加速公共卫生决策的潜力。解决数字数据收集的偏差对于确保数字解决方案作为公共卫生工具的准确性和可靠性至关重要。
