Inclusion of environmentally themed search terms improves Elastic net regression nowcasts of regional Lyme disease rates

Eric Kontowicz; Grant Brown; James Torner; Margaret Carrel; Kelly K. Baker; Christine A. Petersen

doi:10.1371/journal.pone.0251165

Peer Review History

Original SubmissionApril 6, 2021
18 Jun 2021 Decision Letter - Sam R. Telford III, Editor PONE-D-21-11338 Inclusion of environmentally themed search terms improved Elastic Net regression nowcasts of regional Lyme disease rates PLOS ONE Dear Christy: 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. One of the reviewers does not think that infodemiology has any utility and rejected it. I had to find reviewers who had actually done this kind of work before. One of them had substantive comments that need to be addressed in a revision. In comments to me, it was suggested that the authors needed more familiarity with infodemiology, particularly GoogleTrends analyses, and that there was a good literature on its applications, limitations, and standards of practice. The other comment was that the database was at least 2 years old and it was likely that there was additional data that could be used. I Please submit your revised manuscript by Aug 02 2021 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. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Best regards, Sam Sam R. Telford III Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please confirm in your manuscript that you have adhered to the Terms and Use/Terms of Service of Google Correlate. 3. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide. 4. Thank you for stating the following financial disclosure: "The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." At this time, please address the following queries: a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution. b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.” c) If any authors received a salary from any of your funders, please state which authors and which funders. d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.” Please include your amended statements within your cover letter; we will change the online submission form on your behalf. [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: No Reviewer #2: Yes Reviewer #3: Yes ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: Yes Reviewer #3: Yes ****** 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 ****** 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 Reviewer #3: 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 manuscript proposes a method to forecast Lyme disease incidence using regressions methods with Google search history data. I believe that the application of machine learning/Big Data methods is misguided for ecologically complex phenomena like the incidence tick-borne diseases. This manuscript does not provide any compelling evidence for the contribution of these techniques to the understand-ing of Lyme disease incidence. As an exquisitely seasonal process, Lyme disease perpetuation and zo-onotic transmission will be powerfully correlated to Google search terms. The same would be true for indicators of “nice weather” (not obtained from Google!). Reviewer #2: General comments This is a paper on inclusion of environmentally themed search terms improved Elastic Net regression nowcasts of regional Lyme disease rates. I have some comments on your manuscript. Specific comments 1. Abstract and Introduction: ”…with 95% of human cases occurring…” Please provide the absolute numbers of cases (n/N), showing where this percentage is coming from. 2. Introduction: “CDC”. Please write this out when mentioned for the first time in the main text. 3. Introduction: “LASSO”. Please write this out when mentioned for the first in the text. 4. Material and Methods: “erythema migrans”. You may consider briefly describing what this is, you may put this description in the parentheses, for example. 5. Please check up the capital letters concerning Google, United States, Table, for example. Also, some words are lowercased instead of capital letters. 6. Both abbreviations are used: “US” and U.S.”. Please consider choosing one of them. 7. Figure 7: If you use color lines in the figures, please tell the readers which color indicates which line. 8. Please check up the reference list concerning the links and make sure that they are updated. Reviewer #3: This is an interesting approach in modeling Lyme Disease with Google Trends data. However, there are some issues that need to be addressed before this manuscript can be reconsidered for publication. The authors mention that “High correlation was determined when the correlation value was greater than 0.8, moderate if correlation value was between 0.5 and 0.8, and poor when less than 0.5”. Shouldn’t the significance of a correlation be measured by, for example, the p-values (or CIs)? Also, “high” and “moderate” should be defined (I assume the authors mean that high is p<0.01 and that moderate is p<0.05; however, a correlation with a p-value less than .05 is considered quite strong). There is no description of the Google Trends data selection criteria and collection procedure. This is an important drawback of this manuscript. All methodology steps should be reported in detail (e.g., period, region, category, web search, use of quotes for keywords with more than one word, individual searches, comparisons, etc.). This is an information epidemiology (infodemiology) study. I suggest that the authors study the relevant literature in order to gain insight and enhance their literature review. An introductory paragraph could be added in the Introduction Section. The analysis (data collection) was conducted in September 2019, considering data up to December 2018. It is now 2021, and there are two more years’ data available. I believe it would add to the value of this manuscript if the analysis was updated. ****** 6. 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: Yes: Ivo M Foppa Reviewer #2: Yes:** Samuli Pesälä Reviewer #3: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". 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.0251165.r001
Revision 1
24 Aug 2021 Author Response We thank our reviewers for their thoughtful comments. By responding to them, we believe that we have greatly strengthened the manuscript. Our responses will appear below in Garamond. a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution. There were no sources of funding for this research b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.” The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. c) If any authors received a salary from any of your funders, please state which authors and which funders. No authors received a salary from any of our funders. d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.” The authors received no specific funding for this work. 5. Review Comments to the Author Reviewer #1: This manuscript proposes a method to forecast Lyme disease incidence using regressions methods with Google search history data. I believe that the application of machine learning/Big Data methods is misguided for ecologically complex phenomena like the incidence tick-borne diseases. This manuscript does not provide any compelling evidence for the contribution of these techniques to the understanding of Lyme disease incidence. As an exquisitely seasonal process, Lyme disease perpetuation and zoonotic transmission will be powerfully correlated to Google search terms. The same would be true for indicators of “nice weather” (not obtained from Google!). We appreciate the considerations of this reviewer and completely agree that the ecological system of Borrelia is complex. This exercise was to determine how well these computational methods could reproduce and “nowcast” trends of reported Lyme Disease, and surprisingly it did quite well and found trends even if the weather was not nice… like the fall adult Ixodes transmission “bump”. That is why we feel this should be reported through this work. Reviewer #2: General comments This is a paper on inclusion of environmentally themed search terms improved Elastic Net regression nowcasts of regional Lyme disease rates. I have some comments on your manuscript. Specific comments 1. Abstract and Introduction: ”…with 95% of human cases occurring…” Please provide the absolute numbers of cases (n/N), showing where this percentage is coming from. We have now included the total number of confirmed positive cases (n) from northeast and upper Midwest states and the total number of confirmed positive cases for the United states (N). 2. Introduction: “CDC”. Please write this out when mentioned for the first time in the main text. We have included the full name (Center for Disease Control and Prevention) of the CDC before its first mention in the introduction 3. Introduction: “LASSO”. Please write this out when mentioned for the first in the text. We have included the full name (Least Absolute Shrinkage and Selection Operator) of the LASSO before its first mention in the introduction. 4. Material and Methods: “erythema migrans”. You may consider briefly describing what this is, you may put this description in the parentheses, for example. We have added “bullseye rash” as a parenthetical comment in this section. 5. Please check up the capital letters concerning Google, United States, Table, for example. Also, some words are lowercased instead of capital letters. We have made edits throughout the manuscript to maintain consistency of capitalization and apologize for these errors. 6. Both abbreviations are used: “US” and U.S.”. Please consider choosing one of them. We have edited the manuscript to maintain consistency of US throughout. 7. Figure 7: If you use color lines in the figures, please tell the readers which color indicates which line. We have included text into the legend of Figure 7 to make clear that the black lines are regional incidence and the colored lines are model predictions. 8. Please check up the reference list concerning the links and make sure that they are updated. We have updated the reference list to ensure that the all links are active and functioning. Reviewer #3: This is an interesting approach in modeling Lyme Disease with Google Trends data. However, there are some issues that need to be addressed before this manuscript can be reconsidered for publication. 1. The authors mention that “High correlation was determined when the correlation value was greater than 0.8, moderate if correlation value was between 0.5 and 0.8, and poor when less than 0.5”. Shouldn’t the significance of a correlation be measured by, for example, the p-values (or CIs)? Also, “high” and “moderate” should be defined (I assume the authors mean that high is p<0.01 and that moderate is p<0.05; however, a correlation with a p-value less than .05 is considered quite strong). We thank the reviewer for this comment, and indicated when p-values were significant in Supplemental Table 2 to accompany the correlation values. We feel that reporting the correlation value directly is important, as this measures the strength of the linear relationship directly. P-values (and by extension confidence intervals) measure the strength of evidence for the presence of nonzero correlation, but do not give any indication of the strength of correlation itself. In a large sample with multiple comparisons, one could obtain very strong evidence for nonzero correlation when the linear relationship is actually quite weak, while in a small sample a high correlation might not reach significance. 2. There is no description of the Google Trends data selection criteria and collection procedure. This is an important drawback of this manuscript. All methodology steps should be reported in detail (e.g., period, region, category, web search, use of quotes for keywords with more than one word, individual searches, comparisons, etc.). We have added to the methods section to make this clear. We state in the methods that we use the terms identified via Google Correlate to collect search hit data on. We have added more language to make it clear that terms identified from Google Correlate were inputted into Google Trends unaltered to collect search term hit data for each region. I also included text to make it clear that gtrendsR is an R interface for Google Trends that allows for an automated process of collecting search term data. 3. This is an information epidemiology (infodemiology) study. I suggest that the authors study the relevant literature in order to gain insight and enhance their literature review. An introductory paragraph could be added in the Introduction Section. We have included a paragraph, lines 93-102, to the introduction outlining infodemiology and its use in predicting disease and better informing the general public about health-related outcomes. 4. The analysis (data collection) was conducted in September 2019, considering data up to December 2018. It is now 2021, and there are two more years’ data available. I believe it would add to the value of this manuscript if the analysis was updated. We appreciate and understand the reviewers concern for having recent data for publication. However, the authors’ intention of this work is to show that value of including environmentally related features when nowcasting with Google Search terms, which does not require all recent data. This manuscript highlights the importance of considering environmental factors when creating prediction models for vector borne diseases. To this end, the models have also been posted on Eric Kontowicz’s Github (https://github.com/ekontowicz/Lyme-disease-Elastic-Net-regression-Nowcasting) for further use by other researchers and additional updates. Lastly, given the time it takes to have rigorous peer review, particularly during this COVID-19 pandemic these findings will lag all surveillance data available. Attachments Attachment Submitted filename: PLOSOne_response to ReviewerComments final.docx https://doi.org/10.1371/journal.pone.0251165.r002
29 Sep 2021 Decision Letter - Sam R. Telford III, Editor PONE-D-21-11338R1Inclusion of environmentally themed search terms improved Elastic Net regression nowcasts of regional Lyme disease ratesPLOS ONE Dear Christy, 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. Please submit your revised manuscript by Nov 13 2021 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. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Sam R. Telford III Academic Editor PLOS ONE Journal Requirements: Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. 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. Additional Editor Comments (if provided): Reviewer 2 makes the point that these kinds of studies should follow a standard methodology, e.g., Mavragani and Ochoa 2019 JMIR Public Health and Surveillance. I have examined this reference and believe that if you have a table in the methods or at lines 380 et seq that summarize the 4 critical aspects of this kind of work, as recommended by Mavragani and Ochoa (keywords, region, period, category) this concern would be satisfied. Citing this reference as informing your study reinforces the fact that standardized methods should be the basis for analyses using GT. At the very least, because it is suggested that GT might be used by local health departments in a predictive manner, it might be good to make it easy for them to test it out by having a very simple set of search terms provided. It is clear that you spent much time analyzing keywords; in the end, what were they? (Table S1 is very comprehensive but can the most high-value keywords be highlighted in a summary table?) For region, was it overall, including metropolitan, urban, suburban and rural? For period, it looks like the specific searches were monthly from 2004-2015. According to Mavragani and Ochoa, search term category does not need to be specified if the keywords are very specific and you provided much analysis on selecting the useful keywords. I would prefer not to send this back to the one reviewer and delay a decision. If you can provide such a table, the ms could be accepted without a third round of review. [Note: HTML markup is below. Please do not edit.] 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: (No Response) ******** 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 ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes Reviewer #3: Yes ****** 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 ****** 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 ****** 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 have revised the text as requested. This manuscript has definitely improved after revisions. Reviewer #3: The GT methodology is still not properly reported. Please see relevant representative literature to understand how to report the methodology (like this one for example: https://www.jmir.org/2020/8/e19611/). ****** 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: Yes:** Samuli Pesälä Reviewer #3: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". 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.0251165.r003
Revision 2
21 Nov 2021 Author Response We thank Dr. Telford, the editor, and our reviewers for their thoughtful comments. We agree that the rigorous context of Mavragani and Ochoa, 2019, and in a new summary table, containing what they emphasize as the four key components for this type of computational epidemiology adds great strength to this method and specifically our manuscript. We have added this summary table at line 293 containing the five regions, the top 10, focused, keywords (so categories not needed) over the critical training period, 2004-2012. Our responses will appear below in Garamond. a) Please clarify the sources of funding (financial or material support) for your study. List the grants or organizations that supported your study, including funding received from your institution. There were no sources of funding for this research b) State what role the funders took in the study. If the funders had no role in your study, please state: “The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.” The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. c) If any authors received a salary from any of your funders, please state which authors and which funders. No authors received a salary from any of our funders. d) If you did not receive any funding for this study, please state: “The authors received no specific funding for this work.” The authors received no specific funding for this work. 5. Review Comments to the Author Reviewer #1: This manuscript proposes a method to forecast Lyme disease incidence using regressions methods with Google search history data. I believe that the application of machine learning/Big Data methods is misguided for ecologically complex phenomena like the incidence tick-borne diseases. This manuscript does not provide any compelling evidence for the contribution of these techniques to the understanding of Lyme disease incidence. As an exquisitely seasonal process, Lyme disease perpetuation and zoonotic transmission will be powerfully correlated to Google search terms. The same would be true for indicators of “nice weather” (not obtained from Google!). We appreciate the considerations of this reviewer and completely agree that the ecological system of Borrelia is complex. This exercise was to determine how well these computational methods could reproduce and “nowcast” trends of reported Lyme Disease, and surprisingly it did quite well and found trends even if the weather was not nice… like the fall adult Ixodes transmission “bump”. That is why we feel this should be reported through this work. Reviewer #2: General comments This is a paper on inclusion of environmentally themed search terms improved Elastic Net regression nowcasts of regional Lyme disease rates. I have some comments on your manuscript. Specific comments 1. Abstract and Introduction: ”…with 95% of human cases occurring…” Please provide the absolute numbers of cases (n/N), showing where this percentage is coming from. We have now included the total number of confirmed positive cases (n) from northeast and upper Midwest states and the total number of confirmed positive cases for the United states (N). 2. Introduction: “CDC”. Please write this out when mentioned for the first time in the main text. We have included the full name (Center for Disease Control and Prevention) of the CDC before its first mention in the introduction 3. Introduction: “LASSO”. Please write this out when mentioned for the first in the text. We have included the full name (Least Absolute Shrinkage and Selection Operator) of the LASSO before its first mention in the introduction. 4. Material and Methods: “erythema migrans”. You may consider briefly describing what this is, you may put this description in the parentheses, for example. We have added “bullseye rash” as a parenthetical comment in this section. 5. Please check up the capital letters concerning Google, United States, Table, for example. Also, some words are lowercased instead of capital letters. We have made edits throughout the manuscript to maintain consistency of capitalization and apologize for these errors. 6. Both abbreviations are used: “US” and U.S.”. Please consider choosing one of them. We have edited the manuscript to maintain consistency of US throughout. 7. Figure 7: If you use color lines in the figures, please tell the readers which color indicates which line. We have included text into the legend of Figure 7 to make clear that the black lines are regional incidence and the colored lines are model predictions. 8. Please check up the reference list concerning the links and make sure that they are updated. We have updated the reference list to ensure that the all links are active and functioning. Reviewer #3: This is an interesting approach in modeling Lyme Disease with Google Trends data. However, there are some issues that need to be addressed before this manuscript can be reconsidered for publication. 1. The authors mention that “High correlation was determined when the correlation value was greater than 0.8, moderate if correlation value was between 0.5 and 0.8, and poor when less than 0.5”. Shouldn’t the significance of a correlation be measured by, for example, the p-values (or CIs)? Also, “high” and “moderate” should be defined (I assume the authors mean that high is p<0.01 and that moderate is p<0.05; however, a correlation with a p-value less than .05 is considered quite strong). We thank the reviewer for this comment, and indicated when p-values were significant in Supplemental Table 2 to accompany the correlation values. We feel that reporting the correlation value directly is important, as this measures the strength of the linear relationship directly. P-values (and by extension confidence intervals) measure the strength of evidence for the presence of nonzero correlation, but do not give any indication of the strength of correlation itself. In a large sample with multiple comparisons, one could obtain very strong evidence for nonzero correlation when the linear relationship is actually quite weak, while in a small sample a high correlation might not reach significance. 2. There is no description of the Google Trends data selection criteria and collection procedure. This is an important drawback of this manuscript. All methodology steps should be reported in detail (e.g., period, region, category, web search, use of quotes for keywords with more than one word, individual searches, comparisons, etc.). We have added to the methods section to make this clear. We state in the methods that we use the terms identified via Google Correlate to collect search hit data on. We have added more language to make it clear that terms identified from Google Correlate were inputted into Google Trends unaltered to collect search term hit data for each region. I also included text to make it clear that gtrendsR is an R interface for Google Trends that allows for an automated process of collecting search term data. 3. This is an information epidemiology (infodemiology) study. I suggest that the authors study the relevant literature in order to gain insight and enhance their literature review. An introductory paragraph could be added in the Introduction Section. We have included a paragraph, lines 93-102, to the introduction outlining infodemiology and its use in predicting disease and better informing the general public about health-related outcomes. 4. The analysis (data collection) was conducted in September 2019, considering data up to December 2018. It is now 2021, and there are two more years’ data available. I believe it would add to the value of this manuscript if the analysis was updated. We appreciate and understand the reviewers concern for having recent data for publication. However, the authors’ intention of this work is to show that value of including environmentally related features when nowcasting with Google Search terms, which does not require all recent data. This manuscript highlights the importance of considering environmental factors when creating prediction models for vector borne diseases. To this end, the models have also been posted on Eric Kontowicz’s Github (https://github.com/ekontowicz/Lyme-disease-Elastic-Net-regression-Nowcasting) for further use by other researchers and additional updates. Lastly, given the time it takes to have rigorous peer review, particularly during this COVID-19 pandemic these findings will lag all surveillance data available. Attachments Attachment Submitted filename: PLOSOne_response to ReviewerComments final.docx https://doi.org/10.1371/journal.pone.0251165.r004
2 Feb 2022 Decision Letter - Sam R. Telford III, Editor Inclusion of environmentally themed search terms improves Elastic Net regression nowcasts of regional Lyme disease rates PONE-D-21-11338R2 Dear Christy: I am 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 for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, 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, Sam R. Telford III Academic Editor PLOS ONE Additional Editor Comments (optional): Christy, sorry this has taken so long. Paradoxically with COVID and people being at home, it is no easier finding qualified reviewers and getting reviews back than when they were at work. Reviewers' comments: https://doi.org/10.1371/journal.pone.0251165.r005
Formally Accepted
1 Mar 2022 Acceptance Letter - Sam R. Telford III, Editor PONE-D-21-11338R2 Inclusion of environmentally themed search terms improves Elastic Net regression nowcasts of regional Lyme disease rates Dear Dr. Petersen: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. 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 plosone@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. Sam R. Telford III Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0251165.r006

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