PONE-D-25-07512COVID-19 Prevention Is Shaped by Polysocial Risk: A Cross-Sectional Study of Vaccination and Testing Disparities in Underserved Populations

PLOS ONE

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Research reported in this RADx-UP publication was supported by the National Institutes of Health under Award Numbers U01DA040381, U01MD017423, and U24MD016258. This work was supported by Azure sponsorship credits granted by Microsoft’s AI for Good Research Lab. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: Yes

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3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: No

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4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

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5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Thank you for the opportunity to review this interesting work. Please find my specific feedback below:

Abstract:

• Adequate.

Introduction:

• Very well done! The Introduction clearly identifies the critical gap being addressed by this study. The significance of using the polysocial risk framework is also clearly illustrated by the authors.

Methods:

• There is inconsistency in data collection dates in the Methods section and the abstract.

Methods: Between February 3, 2020 and April 21, 2023.

Abstract: Between October 2020–June 2024.

• “This study used data from the RADx-UP Core Analytic Datasets version 1.6 collected by accessed through the CDCC on April 30, 2023 [40,43]”.

This sentence is grammatically incorrect. The date is again inconsistent; this version says April 30, 2023, while the authors previously noted April 21, 2023, in their Methods.

• Inclusion criteria: The authors note the following inclusion criteria: “Participants were adults aged 18 years and older who underwent COVID-19 testing and were enrolled in a RADx-UP project”

Later, they define one of their outcomes as COVID-19 testing.

Were participants who never tested for COVID-19 included in the study?

• Analysis: Can the authors report the extent of heterogeneity in individual projects included in the study for different outcome analyses? The authors have included Project as a clustering group in their analyses, but it may help if they can report how much heterogeneity was present as well. Just a suggestion though, the analysis in itself is adequate as well.

Results:

• “These characteristics underscore the study's focus on underserved populations disproportionately impacted by the COVID-19 pandemic.”

I believe this sentence would be more appropriate in Discussion rather than Results.

Discussion:

• “This stark difference highlights how race, age, and region compound to create barriers to prevention.”

Please note that this was a cross-sectional analysis of a dataset, which included multiple projects (with very different study designs). Since it did not entirely rely on prospective or randomized designs, it is not appropriate to establish causal inferences. The above sentence implies a cause-and-effect relationship. An alternative way to phrase this would be:

“This stark difference highlights how the compound effect of race, age, and region may potentially create barriers to prevention.”

Alternatively, you can use phrases such as “associated with”, which do not imply causality. Same feedback for further causal statements:

“This gap underscores how economic precarity directly impacts preventive health behaviors.”

“This suggests that established patterns of healthcare engagement strongly predict COVID-19 prevention behaviors.”

• The authors observed the highest disparities in vaccinations when evaluating health-related risk factors, but they also found that testing rates were similar in these groups. The provide the following interpretation:

“This likely reflects the success of widespread testing availability through community sites and at-home options [45].”

However, one may argue that vaccination was also available widespread similar to testing methods. All the other risk groups that the authors studied had consistent disparities in both vaccination and testing practices. It is interesting that the group with highest disparity in vaccination had no differences in testing practices. The authors should provide potential explanations for this.

• Social patterns in test results: Do these patterns reveal individuals with “truly” higher odds of testing positive, or do they simply reflect that these groups were tested more frequently? The patterns of people testing more often and people testing positive are concordant in the authors’ analyses, except for individuals in the Northeast region. These tested more frequently but did not test positive more frequently. What could be a potential explanation for this?

• Limitations:

Self-reported data also introduces concerns related to social desirability bias.

The authors could only study if the participants had ever been tested or not. They could not study the frequency of COVID-19 testing, which may influence the test positivity rates. Similarly, the authors studied whether the participants had ever received a COVID-19 vaccine, they did not study whether participants received all required vaccination doses (the complete series) or not.

Reviewer #2: The authors present a study linking social determinants of health and healthcare disparities to COVID-19 vaccination. Generally the study is well conducted and well reported.

Comments:

- A significant chunk of 'conclusion' can be moved to 'Public Health and Policy Implications' section.

- Authors need to update the Public health and policy implications section in discussion to include more points pertinent to their finding in this study, rather than a general importance of SDOH and Healthcare disparities.

- Details of groupings mentioned in the last paragraph of methods should be described in the methods.

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Reviewer #1: No

Reviewer #2: No

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COVID-19 Prevention Is Shaped by Polysocial Risk: A Cross-Sectional Study of Vaccination and Testing Disparities in Underserved Populations

PONE-D-25-07512R1

Dear Dr. Brown,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Kind regards,

Muhammad Muntazir Mehdi Khan, M.B.B.S.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

Reviewer #3: Yes

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3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: Yes

Reviewer #3: Yes

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4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

Reviewer #3: Yes

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5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: Authors applied polysocial risk framework to identify risk factors associated with COVID-19 prevention behaviors. They have adequately addressed all reviewer comments.

Reviewer #3: Comments by reviewer have been addressed by the author and the draft is according to journal guidelines

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy .

Reviewer #2: No

Reviewer #3: Yes:  Zainab Rustam

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