Representativeness of a national, probability-based panel survey of COVID-19 isolation practices—United States, 2020–2022

TL;DR

This study shows that a national survey on isolation practices after a positive COVID-19 test aligns well with CDC data, making it a useful tool for public health decisions.

Contribution

The study demonstrates the representativeness of a probability-based panel survey for tracking post-diagnosis isolation behaviors.

Findings

Survey data estimates correlated highly with CDC case counts (r: +0.94; p < 0.05).

High correlations were maintained across demographic subgroups.

The survey data reflects real-world behavior and supports its use in public health decision-making.

Abstract

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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