COVID-19 risk perceptions of social interaction and essential activities and inequity in the USA: results from a nationally representative survey

  1. Daniel J Erchick
  2. Alexander J Zapf
  3. Prativa Baral
  4. Jeffrey Edwards
  5. Shruti H Mehta
  6. Sunil S Solomon
  7. Dustin G Gibson
  8. Smisha Agarwal
  9. Alain B Labrique

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Abstract

SARS-CoV-2 has disproportionately affected disadvantaged communities across the USA. Risk perceptions for social interactions and essential activities during the COVID-19 pandemic may vary by sociodemographic factors.

Methods

We conducted a nationally representative online survey of 1592 adults in the USA to understand risk perceptions related to transmission of COVID-19 for social (eg, visiting friends) and essential activities (eg, medical visits or returning to work). We assessed relationships for activities using bivariate comparisons and multivariable logistic regression modelling, between responses of safe and unsafe, and participant characteristics. Data were collected and analysed in 2020.

Results

Among 1592 participants, risk perceptions of unsafe for 13 activities ranged from 29.2% to 73.5%. Large gatherings, indoor dining and visits with elderly relatives had the highest proportion of unsafe responses (>58%), while activities outdoor, accessing healthcare and going to the grocery store had the lowest (<36%). Older respondents were more likely to view social gatherings and indoor activities as unsafe but less likely for other activities, such as going to the grocery store and accessing healthcare. Compared with white/Caucasian respondents, black/African-American and Hispanic/Latino respondents were more likely to view activities such as dining and visiting friends outdoor as unsafe. Generally, men versus women, Republicans versus Democrats and independents, and individuals with higher versus lower income were more likely to view activities as safe.

Conclusion

Evidence-based interventions should be tailored to sociodemographic differences in risk perception, access to information and health behaviours when implementing efforts to control the COVID-19 pandemic.

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  1. Version published to 10.1136/bmjopen-2021-051882
  2. ScreenIT

    SciScore for 10.1101/2021.01.30.21250705: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: Survey responses were excluded for the following reasons: age less than 18 (n=47), residence outside United States (n=3), ethnicity/race for which sample quota was already filled (n=171), refusal of consent (n=72), and partial interview (n=77).
    IRB: The study received ethical approval from the Institutional Review Board at Johns Hopkins Bloomberg School of Public Health, Baltimore, USA.
    RandomizationDynata – a market research firm (https://www.dynata.com) that maintains a large first-party global data platform, including 62 million panelists with accompanying demographic information – selected a random sample from their database to match the U.S. Census estimates.
    Blindingnot detected.
    Power AnalysisThis sample allowed for detection of a 10% difference in proportions between White, Black, and Hispanic ethnicity/race groups assuming power of 80%, type I error rate of 0.05, and a baseline prevalence of 40%-60%.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical analyses were conducted in Stata 16.1 (StataCorp, College Station, Texas, USA).
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    This study had limitations. Selection bias associated with online surveys is well established, for example, underrepresenting individuals who are older, without internet access, have lower income, and have less formal education; this effect is difficult to quantify, in either direction or magnitude, and may limit the generalizability of our results. However, the digital divide in internet access has shrunk over time.25 Despite our large sample size, samples for strata of important participant characteristics, including certain racial and ethnic minorities, were too small to provide sufficient statistical power for our analyses; still, we had sufficient statistical power to examine racial and ethnic differences between Black/African American, Hispanic/Latino, and White/Caucasian groups, which very few studies have done. Our questionnaire did not collect data on some characteristics that could affect risk perceptions, including presence of underlying health conditions, type of employment, or whether the respondent knew someone who had been infected with COVID-19.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2021.01.30.21250705v1 on medRxiv