2020-2022 年美国 COVID-19 隔离做法全国概率小组调查的代表性。

Frontiers in epidemiology Pub Date : 2024-04-26 eCollection Date: 2024-01-01 DOI:10.3389/fepid.2024.1379256
Holly H Matulewicz, Divya Vohra, Willow Crawford-Crudell, John E Oeltmann, Patrick K Moonan, Melanie M Taylor, Chandra Couzens, Andy Weiss
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引用次数: 0

摘要

美国疾病控制和预防中心(CDC)收到了关于有多少人SARS-CoV-2检测结果呈阳性的监测数据,但关于个人如何减少传播的信息却很少。为了填补这一信息空白,我们对居住在美国的具有全国代表性的成年人进行了一次基于概率的在线调查,以更好地了解个人在 SARS-CoV-2 检测结果呈阳性后的行为。鉴于小组调查的回复率通常较低,我们评估了调查数据与疾病预防控制中心 2020 年 3 月至 2022 年 3 月监测数据的吻合程度。我们使用疾病预防控制中心的监控数据计算每月的 COVID-19 病例总数,并将其与我们的调查在同一时期捕获的每月 COVID-19 病例总数进行比较。我们发现,我们的总体调查数据估计值与分析期间向疾病预防控制中心报告的每月病例数之间存在高度相关性(r:+0.94; p
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Representativeness of a national, probability-based panel survey of COVID-19 isolation practices-United States, 2020-2022.

The U.S. Centers for Disease Control and Prevention (CDC) received surveillance data on how many people tested positive for SARS-CoV-2, but there was little information about what individuals did to mitigate transmission. To fill the information gap, we conducted an online, probability-based survey among a nationally representative panel of adults living in the United States to better understand the behaviors of individuals following a positive SARS-CoV-2 test result. Given the low response rates commonly associated with panel surveys, we assessed how well the survey data aligned with CDC surveillance data from March, 2020 to March, 2022. We used CDC surveillance data to calculate monthly aggregated COVID-19 case counts and compared these to monthly COVID-19 case counts captured by our survey during the same period. We found high correlation between our overall survey data estimates and monthly case counts reported to the CDC during the analytic period (r: +0.94; p < 0.05). When stratified according to demographic characteristics, correlations remained high. These correlations strengthened our confidence that the panel survey participants were reflective of the cases reported to CDC and demonstrated the potential value of panel surveys to inform decision making.

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