COVID Symptom Screening at the Workplace
Georgetown McCourt Public Policy, University of Minnesota and Federal Reserve Bank of Minneapolis
Many millions of Americans currently have to participate in COVID symptom screening as a precondition for going to their workplace. Yet, there is little evidence about how these tools function. We use data from a novel, nationally-representative survey asking about labor force participation, self-reported symptoms, and medical conditions to answer some key questions about how workplace screens work and who they affect. This analysis provides insights around how many people would be screened out by COVID-related workplace screens, how differences in detection vary across various screens and populations, and whether differences in underlying health or survey response behaviors could create an unintended risk of disparate impacts by age, race, ethnicity, or gender.
Demographic groups report symptoms at different rates even after accounting for differences in likely COVID exposure, income, and household structure.
- There are no formal statistics, but broad groups of employers are required to screen workers for COVID in 34 states, and federal guidance encourages all U.S. employers to do so. This new practice, where employees have their temperature taken and/or answer questions about potential symptoms or high-risk behaviors, has emerged as a strategy to safeguard employees and customers from the spread of COVID since a fast and accurate medical test is not available to most employers. These screens, together with other non-pharmaceutical interventions – such as social distancing – are part of measures taken to balance productive interpersonal activities with contagion risk without curtailing economic activity as severely as full lockdowns. Workplace screens and related devices are likely to remain common in the medium-term, both because COVID vaccination will take time and because now that these tools have been developed, they may be leveraged to manage future outbreaks of communicable diseases.
- The COVID Impact Survey (CIS) — which combines questions about employment and financial security with questions about symptoms, underlying health, and protective behavior — provides information on what types of workers would be flagged under different screening practices. The CIS was administered to approximately 6,500 adults in a nationally representative sample over three weeks during the initial months of the pandemic in the spring of 2020. It is important to note that our analysis cannot determine the extent to which COVID screening can serve to detect actual COVID infections because the survey does not include COVID infection rates and we are not observing actual employer practices. However, the survey can provide information about the prevalence of self-reported symptoms among workers of different characteristics at a given point in time. The prevalence rates observed in the survey may be better proxies of true underlying conditions because respondents have no incentives to misreport information — the CIS is not conducted by employers and respondents do not risk being flagged for testing, being barred from entering the workplace or having to quarantine.
- Screening of common symptoms will likely classify many individuals as high-risk each day. This will limit the number of people who are able to work if reporting is truthful. Even during a period of relatively low COVID prevalence, we find that large shares of workers experience symptoms that may merit medical follow up to slow community spread. For example, 4% of respondents reported having a temperature at or above 99 degrees Fahrenheit on the day of the survey. The share of individuals flagged as high-risk ranges widely depending on the screen used: Across the seven different screens we analyze, the share of workers that could be flagged as symptomatic for COVID daily ranges from 0.4 to 7.4 percent depending on the measure used. Given the high prevalence of positive symptoms in our low-stakes setting, infrequent symptom reporting in the workplace context could indicate non-truthful reporting.
- Different screens detect different workers. Although workers who screen positive under one screen are more likely to screen positive under another screen than those who do not, there is imperfect overlap across screens. Since many respondents report any single symptom, screens that include a long list of questions flag more respondents than those that ask about fewer symptoms, as do those that require fewer symptoms for a “positive” result. In addition, survey design and question wording matters for how many, and which, workers are flagged.
- Demographic groups report symptoms at different rates, even absent fluctuations in likely COVID exposure. COVID has had a disproportionate impact on different ethnic and racial groups, which raises the question of whether these groups would face higher rates of positive symptom screens under widespread workplace screening. In addition to differences in underlying infection rates, groups may also differ in how they perceive or report symptoms. We find that survey design and the number and type of symptoms will affect who is identified as high-risk for COVID and prohibited from entering the workplace. For example, female, younger, and non-Hispanic white workers report multiple symptoms at higher rates than male, older, Black, and Hispanic workers, before and even after accounting for differences in likely COVID exposure, income, and household structure. These patterns can potentially lead to disparate impacts, and highlight the importance of monitoring and adapting screens to address concerns about equity and discrimination.
- Employers likely face a tradeoff between screens that may have a higher false negative rate but fewer disparities in detection, versus screens that have lower false negative rates but more disparities. The likelihood that a worker reports a temperature at or above 99 degrees does not vary significantly across the different groups of workers studied. But using only a reported fever to flag a worker as a potential risk for contagion is much less likely to identify an actual COVID case than when several other potential COVID symptoms are reported in addition to temperature. However, relying on the report of multiple symptoms has the potential of disproportionately flagging workers of certain groups. As reported above, there are significant differences between workers of different age, gender and ethnicity/race characteristics in the likelihood of reporting multiple symptoms. The optimal screen likely depends on local context: if case rates are surging in a firm’s area, or if the firm has known cases, it may make sense to screen more intensively at the risk of more and uneven false positives.
What this Means:
Our findings underscore the importance of monitoring how workplace screens work in practice, identify disparate impacts, weigh tradeoffs between false positive and false negative results, and change course if needed. Some populations that report symptoms less often may benefit from encouragement of symptom self-monitoring. Given the possibility of transmission of COVID by individuals when they are not experiencing symptoms, the use of self-reported symptom screening as a way to prevent contagion has limitations. Although this is not tested in the recent research paper, it is important to acknowledge that the impact of screens may go beyond direct detection of infected workers. Positive screens may lower overall disease rates by leading workers to stay home when ill or to seek medical testing, thereby reducing the spread of communicable diseases beyond COVID. In practice, the success and consequences of workplace COVID screening may depend on income support policies – such as paid sick leave – that lessen the incentive to hide symptoms in order to avoid lost income.