PONE-D-21-21612

Patterns and predictors of sick leave among non-hospitalized healthcare and residential care workers with Covid-19 during the early phase of the pandemic

PLOS ONE

Dear Dr. Kisiel,

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Academic Editor

PLOS ONE

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Additional Editor Comments:

The methodological issues raised by the reviewers should be appropriately addressed in your revised manuscript. Please note that additional reviewer comments could be found in the attached document.

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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: Partly

Reviewer #3: Yes

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

Reviewer #1: Yes

Reviewer #2: I Don't Know

Reviewer #3: 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: Yes

Reviewer #3: 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: No

Reviewer #3: 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 allowing me to review your study, “Patterns and predictors of sick leave among non-hospitalized healthcare and residential care workers with Covid-19 during the early phase of the pandemic”. The study examined predictors of sick leave among non-hospitalized healthcare & residential care workers from March to August 2020.

Overall, my impressions of this paper are positive. It offers meaningful data on a population exposed to various health risks and, naturally, higher than average sickness absence rates. I have included some remarks to help ensure the success of this paper.

• To improve this paper, I believe that more editing is required. I list some examples below.

++ “The study from the US and Spain showed that healthcare workers also had increased prevalence of sick leave during the pandemic….” It is unclear by stating “the study” that it was one study or several studies.

++ Issues with the structure of the sentence beginning with “A recent editorial by Gohar…”, specifically with “job support employees.” Do you mean “employee job support?”

++ Inconsistencies “healthcare” and “health care.”

++ “However, a limitation is that there might be a bias by collecting sick leave information in this way as Swedish inhabitants are free to seek health care in different regions that have distinct patients records BMI was missing in the substantial part of the study population.” I am unclear if these are supposed to be two separate sentences. If not, please clarify your point.

• It is indicated that multiple sick leave periods were summed together and later categorized based on total duration. Were there any measures taken for sick leaves that were uncommon (e.g., car accident)?

• How updated are medical records concerning variables such as BMI? If not updated regularly, I believe this should be described in the limitation section. Also, is BMI self-reported in these records? If it is self-reported, it is an important consideration to add as individuals typically underestimate their weight or BMI (which further magnifies the role of BMI and sick leave).

• It was mentioned that BMI was missing in a substantial part of the study population. Could this have compromised the integrity of the results?

• Age in previous studies showed inconsistencies with its relationship to sickness absence. However, some evidence suggests that sex (females) have higher rates of sick leaves. It might be worthy of hypothesizing why there was not a relationship. Could it be that COVID-19 affects male and female healthcare workers evenly? I would draw on the statistics (sex) of patients infected with COVID in the Uppsala region and contrast accordingly.

• Also missing from this study is its implications. By having this information, what should be done in terms of future research or from a practical standpoint?

• Mentioning the region or at least the country in the title is beneficial

My best wishes!

Reviewer #2: This is an interesting, important and generally well structured study. However, there is a fair amount of copy editing and revision for clarity of language that needs to be done before it can be published, in my opinion. I have attempted to make some suggestions along these lines in the attached document. My grammatical and wording edits are only suggestions, but I think they will add to the readability of the paper.

I also had some concerns about the description of the statistical methods and presentation of the results which I have also detailed in the attached document. These, I think, must be addressed.

Thanks you for sharing your work; I enjoyed reading it.

Reviewer #3: This is an interesting study. The manuscript is well-written. However, some methodologic issues should be further clarified. My specific comments are as follows:

1. The authors only mentioned that BMI data are missing for 206 subjects. How about the missing data regarding other variables (listed in Table 1) used in the prediction model? Please also clarify this in the manuscript.

2. The definitions of the variables (predictors) or how they were identified were not clearly described in the Method section. For instance, how the symptoms at onset were defined or identified (e.g., what GI symptoms? How to define fatigue?)? How were the comorbidities defined (e.g., using diagnostic codes only? any criteria for diagnosis times or the time period to identify the comorbidities?)? This section should be revised to provide more details.

3. The study sample size is only 433 (≤ 3 weeks, n=373; >3 weeks, n=60). The patient no. of many predictors is low; some were < 10 (as shown in Table 1). Whether the statistical power was enough to evaluate the effect of those predictors should be doubted.

4. According to the Statistical analysis section, the regression models only adjusted for age, gender, and comorbidities, but not other variables in Table 1, based on clinical and theoretical reasoning. However, to me, the reasons for choosing only age, gender, and comorbidities for adjustment seem arbitrary. Is it possible to perform additional analyses (sensitivity analyses) that applied other variable selection methods (e.g., stepwise selection method, LASSO regression)?

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Reviewer #1: No

Reviewer #2: Yes: Matthew Groenewold

Reviewer #3: No

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Attachments

Attachment

Submitted filename: PONE-D-21-21612_mrg_review.docx

Patterns and predictors of sick leave among Swedish non-hospitalized healthcare and residential care workers with Covid-19 during the early phase of the pandemic

PONE-D-21-21612R1

Dear Dr. Kisiel,

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.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

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Kind regards,

Huei-Kai Huang, M.D.

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 #1: All comments have been addressed

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 #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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

Reviewer #1: I Don't Know

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 #1: Yes

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 #1: Yes

Reviewer #2: Yes

Reviewer #3: Yes

**********

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 #1: The authors have adequately resolved all my comments in their resubmission. I believe that the paper is worthy of publication.

Reviewer #2: (No Response)

Reviewer #3: (No Response)

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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 #1: No

Reviewer #2: No

Reviewer #3: No