The new normal: Covid-19 risk perceptions and support for continuing restrictions past vaccinations

Maja Graso

Abstract
I test the possibility that over-estimating negative consequences of COVID-19 (e.g., hospitalizations, deaths, and threats to children) will be associated with stronger support the ‘new normal’ (i.e., continuation of restrictions for an undefined period starting with wide-spread access to vaccines and completed vaccinations of vulnerable people). The new normal was assessed by endorsing practices such as vaccine passports, travel restrictions, mandatory masking, continuing contact tracing, and pursuing elimination. Results are based on five samples (N = 1,233 from April 2021 and N = 264 from January 2022) and suggest that people over-estimate COVID-19 risks to children and healthy people, as evidenced by median estimates that 5% of all global deaths were children, 29% were generally healthy people under 65, and that a healthy person under the age of 65 has 5% chance of dying from COVID-19. Over-estimates observed in this study align with those based on representative samples, and they were consistently related to stronger support for the new normal.

Introduction
The nearly universal desire to ‘flatten the curve’, prevent hospitals from becoming overwhelmed, and save lives mobilized millions to embrace numerous health-minded practices and protect themselves and their fellow citizens from COVID-19. The end of the pandemic now looks closer than ever, thanks to vaccines that are continuing to be effective at preventing severe illnesses and deaths from COVID-19 [1, 2]. With the worst of the risks waning, signs of a return to pre-pandemic times are rising. Some places are dropping most of their COVID-19 restrictions entirely (e.g., Florida, Texas, and the UK), and others are adjusting in tandem with local conditions.

Materials and methods
I present the results of the central hypothesis [risk over-estimation and new normal support] tested with core percentage-based and select alternative indicators. I rely on the Supporting Information (SI) section to present additional or exploratory findings (S1 File) that are not necessarily of central relevance to this manuscript but are nonetheless beneficial for a more holistic understanding of the data at this point (e.g., ANOVAs showing differences between samples, distributions of risk estimation variables, and sample-level results). References to SI information are noted where appropriate.

Results
The underlying prediction was that people would over-estimate COVID-19 risks and that this over-estimation would be associated with stronger support of continuing restrictions. However, while determining what makes the label ‘over-estimation’ a more appropriate descriptor of this phenomenon as opposed to ‘higher estimation’ is a matter of semantics, a statistically defensible answer requires an assessment of participants’ responses against the currently available data. Therefore, the first step was to assess whether participants’ responses are over-estimates (and thus erroneous) or whether they are higher estimates but still within the expected range.

Citation: Graso M (2022) The new normal: Covid-19 risk perceptions and support for continuing restrictions past vaccinations. PLoS ONE 17(4): e0266602. https://doi.org/10.1371/journal.pone.0266602

Editor: Santosh Vijaykumar, Northumbria University, UNITED KINGDOM

Received: May 25, 2021; Accepted: March 23, 2022; Published: April 8, 2022

Copyright: © 2022 Maja Graso. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All anonymized data and syntax with basic instructions are available here: https://osf.io/87dzs/?view_only=ef9c8daf19c74e078c1c2d2abd3a06e0.

Funding: Yes. This study is funded by the University of Otago's internal grant system (University of Otago Research Grant). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The author has declared that no competing interests exist.

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