Use of Random Domain Intercept Technology to Track COVID-19 Vaccination Rates in Real Time Across the United States: Survey Study.
Use of Random Domain Intercept Technology to Track COVID-19 Vaccination Rates in Real Time Across the United States: Survey Study.
复制标题
使用随机域拦截技术在美国各地真实的时间跟踪COVID-19疫苗接种率：调查研究。
DOI：
10.2196/37920
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发表时间：
2022-07-01
影响因子：
7.4
通讯作者：
Breiman, Robert F.
中科院分区：
文献类型：
--
作者：
Sargent, Rikki H.;Laurie, Shaelyn;Weakland, Leo F.;Lavery, James, V;Salmon, Daniel A.;Orenstein, Walter A.;Breiman, Robert F.
关键词：
准确和及时的COVID-19疫苗接种覆盖率数据对于提供有针对性的、有效的信息和宣传以及确定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，而且这些努力通常会导致信息范围有限（例如，仅限于行政数据）或延迟（阻碍快速反应的能力）。需要对有助于在全球范围内解决这些局限性的创新技术和办法进行评价。这项调查研究的目的是评估随机域拦截技术（RDIT; RIWI Corp）在美国国家和州一级真实的时间内跟踪自我报告的疫苗接种率的有效性。RDIT-一种在线拦截采样的形式-有可能解决当前疫苗接种跟踪系统的局限性，允许测量额外的数据（例如，态度数据）和实时，快速的数据收集任何地方有网络访问。我们于2021年6月30日至7月26日期间使用RDIT访问了美国成年（年龄≥18岁）网络用户的广泛样本，并询问了与COVID-19疫苗接种相关的问题。自我报告的疫苗接种状态被用作本验证活动的重点。国家和州一级基于RDIT的疫苗接种率与疾病控制和预防中心（CDC）报告的国家和州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指定该项目为公共卫生实践，以告知信息开发（而不是人类受试者研究）。通过使用RDIT，63，853名成年网络用户报告了他们的疫苗接种状况（占接受调查的1，026，850名美国网络用户的6.2%）。在国家层面，基于RDIT的成人COVID-19疫苗覆盖率估计值（44，524/63，853，69.7%; 95%CI 69.4%-70.1%）略高于CDC报告的2021年7月15日估计值（67.9%）（即数据收集中途; t63，852=10.06; P<.001）。基于RDIT和CDC报告的状态水平估计值之间存在强正相关（r=0.90; P<.001）。基于RDIT的估计值与CDC对29个州的估计值相差不到5个百分点。这种广泛的实时数据流可为跟踪一系列疫苗的使用情况和及时评价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无法获得的人口统计，态度和行为结构，这可以更深入地了解疫苗摄入的实时预测因素，从而实现有针对性的及时干预。
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; t63,852=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.
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