Estimating the trend of COVID-19 in Norway by combining multiple surveillance indicators

Gunnar Rø; Trude Marie Lyngstad; Elina Seppälä; Siri Nærland Skodvin; Lill Trogstad; Richard Aubrey White; Arve Paulsen; Trine Hessevik Paulsen; Trine Skogset Ofitserova; Petter Langlete; Elisabeth Henie Madslien; Karin Nygård; Birgitte Freisleben de Blasio

doi:10.1371/journal.pone.0317105

Peer Review History

Original SubmissionOctober 12, 2024
29 Nov 2024 Decision Letter - Yury E Khudyakov, Editor PONE-D-24-45734Estimating the trend of COVID-19 in Norway by combining multiple surveillance indicatorsPLOS ONE Dear Dr. Rø, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Your manuscript was reviewed by two experts in the field. Both identified several problems in your submission which require your attention. Please provide point-by-point responses to the attached comments. Please submit your revised manuscript by Jan 13 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. 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If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. [Note: HTML markup is below. Please do not edit.] 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 ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? 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Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 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: This paper is methodologically interesting, but I have some concerns about these points: - The authors characterize the Proportion Positive as an Incidence Indicator, but the definition they provide seems more like a Prevalence indicator, except they refer only to Positive tests in new cases. The definition in the paper states only positive tests divided by total tests, but as it has been seen later, one test can remain positive through different periods of time and ithe authors do not specify how they treat repeated tests. -Relating to Figure 4 trhe authors should make it clear why some correlations are not included (seemingly because there are no data for those indicators in the same period) - In the Results section the authors write: "When comparing the overall growth rate to the rates for 226 cases and hospitalisations we can see multiple times of disagreement, especially around 227 early 2022. The heterogeneity between the growth rates from the different indicators 228 varies significantly over the time with both early 2020 and early 2022 being examples of 229 periods with high heterogeneity". Nevertheless they conclude "that estimating and visualising growth rates from many 234 different surveillance indicators can provide a more complete picture of the spread of 235 COVID-19 than only considering laboratory confirmed cases or hospitalisations". As a public health specialist I would prefer to know which of the differente indicators should be included in a robust model for estimating growth rates, as it seems that some of the indiocators are not suitable for a robust model. Reviewer #2: Really I found a problem to understand the title of the article. It doesn't reflects the aim exactly. It should be more obvious. Also the estimate methods are not equivalent in time factor and area distribution which may cause some bias in comparison of data. Also you didn't mention other causes that could affect the growth rate at the same time. Although you said that the ethical approval is not needed. But I think there should be. ****** 6. 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If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0317105.r001
Revision 1
19 Dec 2024 Author Response Response to the reviewers We thank the reviewers for insightful comments and provide a point-by-point answer below. Reviewer 1 This paper is methodologically interesting, but I have some concerns about these points: Reviewer Point P 1.1 — The authors characterize the Proportion Positive as an Incidence Indicator, but the definition they provide seems more like a Prevalence indicator, except they refer only to Positive tests in new cases. The definition in the paper states only positive tests divided by total tests, but as it has been seen later, one test can remain positive through different periods of time and ithe authors do not specify how they treat repeated tests. Reply: The proportion positive PCR tests was classified as an incidence indicator as it is directly related to the number of new confirmed PCR cases by dividing by the total number of ”test-events” per day. Since it is just a rescaling of new cases which is an incidence indicator, we consider proportion positive to also be an incidence indicator. Both the numerator, number of positive cases, and the test-event denominator are defined to remove the effect of the same person being tested multiple times. As described in line 93 (in the manuscript with track changes), test-events only consider one test per person in a 7 day period and for the number of positive tests we only consider a persons first positive test within a 60-day period, so repeated positive tests within this period are not included. We have updated the text in line 89-91 and a minor update in the ”Proportion Positive” row in the table to clarify this aspect of positive tests. Reviewer Point P 1.2 — Relating to Figure 4 trhe authors should make it clear why some correlations are not included (seemingly because there are no data for those indicators in the same period) Reply: This is a good point, we have updated the caption for figure 4. Reviewer Point P 1.3 — In the Results section the authors write: ”When comparing the overall growth rate to the rates for 226 cases and hospitalisations we can see multiple times of disagreement, especially around 227 early 2022. The heterogeneity between the growth rates from the different indicators 228 varies significantly over the time with both early 2020 and early 2022 being examples of 229 periods with high heterogeneity”. Nevertheless they conclude ”that estimating and visualising growth rates from many 234 different surveillance indicators can provide a more complete picture of the spread of 235 COVID-19 than only considering laboratory confirmed cases or hospitalisations”. As a public health specialist I would prefer to know which of the different indicators should be included in a robust model for estimating growth rates, as it seems that some of the indicators are not suitable for a robust model. Reply: This is a good questions and while it would indeed have been useful to be able to determine which indicators are robust, our aim is instead to try to use all the available surveillance indicators to understand the underlying transmission process. Even less robust surveillance indicators can provide important information. During the pandemic all indicators had a changing relationship with the underlying infections, and that the best solution therefore is to consider all available indicators holistically as we show in figure 3 with all the growth rates. Using the meta-analysis model also allows us to combine the different growth rates into one when the heterogeneity is low, and gives us a signal that interpretation is more difficult when heterogeneity is high. In these situations, one needs real epidemiological and public health insight into the disease processes, and the data collection and interpretation of each individual indicator to determine which indicator provides the best description of the underlying transmission. We have tried to clarify our aims in line 58-73, a minor edit in the abstract in line 5 and in the discussion in line 312-315. Reviewer 2 Reviewer Point P 2.1 — Really I found a problem to understand the title of the article. It doesn’t reflects the aim exactly. It should be more obvious. Reply: We apologies if the aim was not described well enough. The aim is to use multiple surveillance indicators to provide a more comprehensive and robust estimate the underlying trend of new COVID19 infections in Norway. We have tried to highlight this in line 58-73 (In the manuscript with track changes) and with a minor edit in the abstract in line 5. We hope that this makes it clear that the title corresponds to our aims in the article. Reviewer Point P 2.2 — Also the estimate methods are not equivalent in time factor and area distribution which may cause some bias in comparison of data. Also you didn’t mention other causes that could affect the growth rate at the same time. Reply: We completely agree that there are differences in geographical area, age of participants and many other characteristics between the different surveillance indicators. This is discussed in line 302- 310. As we commented on above, the goal of the paper is not to compare and contrast the different indicators, but to extract useful estimates of the overall trend in new infections. The high correlation between the indicators clearly show that even if there are differences between the different indicators, they also all provide information about the trend in the underlying transmission process. We have clarified this further in the lines 312-315. Reviewer Point P 2.3 — Although you said that the ethical approval is not needed. But I think there should be. Reply: The data we have used contain no identifiable data and only consist of the aggregated number of events (cases/admission/deaths/etc) on a national level. The data has been collected and prepared for surveillance purposes and have already been published in weekly reports by the Norwegian Public Health Institute(https://www.fhi.no/publ/statusrapporter/luftveisinfeksjoner/) and in part in many other publications(i.e https://github.com/folkehelseinstituttet/surveillance data). Since this is just a reanalysis of data already collected, used and published for public health surveillance purposes, no additional ethical approval is needed. We have clarified this in line 208. Attachments Attachment Submitted filename: ResponseToReviewers.pdf https://doi.org/10.1371/journal.pone.0317105.r002
22 Dec 2024 Decision Letter - Yury E Khudyakov, Editor Estimating the trend of COVID-19 in Norway by combining multiple surveillance indicators PONE-D-24-45734R1 Dear Dr. Rø, 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. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Yury E Khudyakov, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0317105.r003
Formally Accepted
20 Jan 2025 Acceptance Letter - Yury E Khudyakov, Editor PONE-D-24-45734R1 PLOS ONE Dear Dr. Rø, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Yury E Khudyakov Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0317105.r004

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