RIWI Corp, Toronto, ON, Canada.
Center for Global Health Innovation, Atlanta, GA, United States.
J Med Internet Res. 2022 Jul 1;24(7):e37920. doi: 10.2196/37920.
Accurate and timely COVID-19 vaccination coverage data are vital for informing targeted, effective messaging and outreach and identifying barriers to equitable health service access. However, gathering vaccination rate data is challenging, and efforts often result in information that is either limited in scope (eg, limited to administrative data) or delayed (impeding the ability to rapidly respond). The evaluation of innovative technologies and approaches that can assist in addressing these limitations globally are needed.
The objective of this survey study was to assess the validity of Random Domain Intercept Technology (RDIT; RIWI Corp) for tracking self-reported vaccination rates in real time at the US national and state levels. RDIT-a form of online intercept sampling-has the potential to address the limitations of current vaccination tracking systems by allowing for the measurement of additional data (eg, attitudinal data) and real-time, rapid data collection anywhere there is web access.
We used RDIT from June 30 to July 26, 2021, to reach a broad sample of US adult (aged ≥18 years) web users and asked questions related to COVID-19 vaccination. Self-reported vaccination status was used as the focus of this validation exercise. National- and state-level RDIT-based vaccination rates were compared to Centers for Disease Control and Prevention (CDC)-reported national and state vaccination rates. Johns Hopkins University's and Emory University's institutional review boards designated this project as public health practice to inform message development (not human subjects research).
By using RDIT, 63,853 adult web users reported their vaccination status (6.2% of the entire 1,026,850 American web-using population that was exposed to the survey). At the national level, the RDIT-based estimate of adult COVID-19 vaccine coverage was slightly higher (44,524/63,853, 69.7%; 95% CI 69.4%-70.1%) than the CDC-reported estimate (67.9%) on July 15, 2021 (ie, midway through data collection; t=10.06; P<.001). The RDIT-based and CDC-reported state-level estimates were strongly and positively correlated (r=0.90; P<.001). RDIT-based estimates were within 5 percentage points of the CDC's estimates for 29 states.
This broad-reaching, real-time data stream may provide unique advantages for tracking the use of a range of vaccines and for the timely evaluation of vaccination interventions. Moreover, RDIT could be harnessed to rapidly assess demographic, attitudinal, and behavioral constructs that are not available in administrative data, which could allow for deeper insights into the real-time predictors of vaccine uptake-enabling targeted and timely interventions.
准确和及时的 COVID-19 疫苗接种覆盖率数据对于有针对性、有效的信息传递和外联以及识别公平获得卫生服务的障碍至关重要。然而，收集疫苗接种率数据具有挑战性，而且这些努力往往会产生范围有限（例如，仅限于行政数据）或延迟（阻碍快速响应的能力）的信息。需要评估可以在全球范围内协助解决这些限制的创新技术和方法。
本调查研究的目的是评估随机域拦截技术（RDIT；RIWI 公司）在美国国家和州一级实时跟踪自我报告的疫苗接种率的有效性。RDIT-一种在线拦截抽样形式-有可能通过允许测量额外的数据（例如，态度数据）和在任何有网络访问的地方实时、快速地收集数据，来解决当前疫苗接种跟踪系统的局限性。
我们于 2021 年 6 月 30 日至 7 月 26 日使用 RDIT 接触广泛的美国成年（年龄≥18 岁）网络用户样本，并询问与 COVID-19 疫苗接种相关的问题。自我报告的疫苗接种状况是本验证工作的重点。基于 RDIT 的全国和州级疫苗接种率与疾病控制与预防中心（CDC）报告的全国和州级疫苗接种率进行了比较。约翰霍普金斯大学和埃默里大学的机构审查委员会将该项目指定为公共卫生实践，以告知信息制定（非人体研究）。
通过使用 RDIT，63853 名成年网络用户报告了他们的疫苗接种状况（暴露于调查的 1026850 名美国网络用户总人口的 6.2%）。在全国范围内，RDIT 估计的成年人 COVID-19 疫苗覆盖率略高于（7 月 15 日，2021 年；即数据收集中途；t=10.06；P<.001）CDC 报告的估计值（67.9%）。RDIT 基础和 CDC 报告的州级估计值呈强正相关（r=0.90；P<.001）。RDIT 基础估计值与 CDC 估计值相差 5 个百分点以内的有 29 个州。
这种广泛的实时数据流可能为跟踪一系列疫苗的使用以及及时评估疫苗接种干预措施提供独特的优势。此外，RDIT 可以用于快速评估行政数据中不可用的人口统计学、态度和行为结构，从而深入了解疫苗接种的实时预测因素-实现有针对性和及时的干预。
