PCSY-D-24-00018

Informing pandemic intervention strategies through coupled contact tracing and network node prioritization

PLOS Complex Systems

Dear Dr. Blair,

Thank you for submitting your manuscript to PLOS Complex Systems. After careful consideration, we feel that it has merit but does not fully meet PLOS Complex Systems'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.

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We look forward to receiving your revised manuscript.

Kind regards,

Chloe Clifford Astbury

Academic Editor

PLOS Complex Systems

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Complex Systems’s publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #1: Partly

Reviewer #2: Yes

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

Reviewer #1: No

Reviewer #2: I don't know

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3. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. 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

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4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS Complex Systems 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: The writing is good, and the addressed topic is relevant. However, there are various other issues.

- The figures are not included in the submitted file, only their captions.

- The contributions are weak. Aside from tracing strategies, only existing models/methods were employed. The novelty/relevance of the work is not clear to me.

- The simulations considered only small networks (up to 500 nodes). Larger networks are required to better understand this approach.

- There is no statistical evaluation (and the networks are small). Therefore, the reported measurements are questionable.

Reviewer #2: Overall, I found this article to be exhilarating - clear, compelling, and charming. Despite the numerous techniques utilized within the article, it remains easy to read. Below are some questions and suggestions that you may find useful. I didn't have access to the figures in the article, so I can't evaluate a portion of the work.

Summary of the article:

This article introduces a novel tracing strategy in the battle against COVID-19. The authors suggest testing a hypothesis: the individuals with the most influence are the ones most likely to spread COVID-19. To explore this idea, the authors employ simulation models that replicate a diffusion network. Utilizing the PRIoritizatioN and Complex Elucidation (PRINCE) algorithm, they analyze an influence score that assesses the diffusion potential of the nodes.

Global comment:

1/ First comment concerns the utilization of network analysis method

Line 134 “Mathematically, we define an undirected network, G 2 Rn_n, as a symmetric binary adjacency matrix g(i; j) = g(j; i) = 1 if nodes i and j are connected, and g(i; j) = g(j; i) = 0 otherwise.”

I'm not entirely convinced that employing unidirectional edges is the optimal solution for analyzing the spread of influence or information. Why not utilize directional edges in the model? Is it not feasible to model this type of data with the chosen methodology? If so, it would be intriguing to specify this limitation in the method section.

Moreover, as pointed out by the authors in the discussion section of the article, the simulation model does not the integration of information regarding relational characteristics (e.g., intensity, type, and duration of relationships). Line 352: "Metadata such as duration and intensity of contacts contribute to inferring contagion dynamics [30]." Are there any models that would enable the integration of such information? If so, why were these methods not employed?

2/ Most influential agents are the most contagious

Line 130 “However, in this work, we focus on a measure of influence that reflects a node's ability to propagate information through the network. In the disease networks, we assume the information reflects disease. Influence scores for each node are computed using the PRIoritizatioN and Complex Elucidation (PRINCE) algorithm.” Why is the use of the PRINCE model deemed more appropriate than other connectivity measures in calculating influence?

Couldn't influence be captured by other indicators? For instance, the role of brokers, such as those identified by Burt's structural holes theory, could play a significant role in disseminating information and thus impacting disease spread. Have you explored other indicators to measure the influence of individuals? If so, how do the results compare? Could the most influential agents be those with the highest betweenness centrality or eigenvector centrality?

Line 147 “In this work, a node is considered influential if its influence score falls in the top 25%”

How is the justification for the top 25% threshold for identifying influential players established? Why not consider the top 10% instead?

3/ Justifying the strategy

The strategy outlined in the article is well elucidated. Nevertheless, including a diagram depicting the developed strategy would enhance comprehension, particularly for readers unfamiliar with these approaches, aiding in navigating the various stages of the procedure.

Moreover, justifying the chosen strategy by specifying why this approach was favored over others would add depth to the discussion. Clarifying the rationale behind the selection process would offer readers insight into the considerations that influenced the methodology.

4/ Testing the model

Have you explored alternative models? Could comparable results be achieved using different models?

Is it feasible to test the hypotheses posited in the article with empirical data?

Smaller comments:

- Line 128: “A node's connectivity can be characterized using measures such as its degree [14], centrality [15, 16] and clustering coefficients [17].” Is it possible to give a more precise definition of the indicators cited in this section? What is the difference centrality and degree? Isn't degree centrality an integral part of centrality measures? What does clustering coefficients measure mean?

- I'm not very familiar with this type of model, but it would be interesting to explain why the diagonal does not correspond to 0 in the adjacency matrix.

- In your introduction, you rightly point out the economic and socio-economic effects of confinement. Two comments: what differences do you see between the two? Can you give a few examples or a reference to highlight the economic and/or socio-economic effects?

- Line 115: “In this setting, the nodes in the network represent individuals, and the edges depict social association. In this work, it is assumed that the associations are undirected.” Can you explain what you mean by social association?

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Reviewer #1: No

Reviewer #2: No

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PCSY-D-24-00018R1

Informing pandemic intervention strategies through coupled contact tracing and network node prioritization

PLOS Complex Systems

Dear Dr. Blair,

Thank you for submitting your manuscript to PLOS Complex Systems. After careful consideration, we feel that it has merit but does not fully meet PLOS Complex Systems'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 within 60 days Feb 18 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 complexsystems@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pcsy/ 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 editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. This file does not need to include responses to any formatting updates and technical items listed in the 'Journal Requirements' section below.

* 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, competing interests statement, or data availability statement, please make these updates within the submission form at the time of resubmission. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

We look forward to receiving your revised manuscript.

Kind regards,

Claus Kadelka

Academic Editor

PLOS Complex Systems

Hocine Cherifi

Editor-in-Chief

PLOS Complex Systems

Additional Editor Comments (if provided):

I apologize for the slow review process: After failing to secure the two reviewers of the original manuscript, we struggled to get the second review. The new reviewer (#3) raises many important suggestions, which will strengthen the manuscript. 

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)

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2. Does this manuscript meet PLOS Complex Systems's publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #2: Yes

Reviewer #3: Partly

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

Reviewer #2: I don't know

Reviewer #3: N/A

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4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. 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: No

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

PLOS Complex Systems 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: No comments

Reviewer #3: The authors here explore how prioritizing influential nodes in contact tracing strategies helps disease control while reducing network disruption. For this purpose, they leverage the PRINCE algorithm and compare the performance of five different interventions, differing the reach of the contact tracing strategies for a reported case (primary or secondary neighborhood) and the pool of individuals to be traced (entire neighborhood or the subset of influential nodes within each of them). The comparison is made considering three different networks: two synthetic, Erdös-Renyi and Barábasi-Albert and an empirical one.

Overall, I find the manuscript confusing and difficult to read given the way the information is presented and discussed. The main figure of the manuscript, figure 2, contains too many panels, making extracting any conclusion from the figure very hard for the reader. Moreover, the exhaustive comparison among all the strategies and networks blur the most important findings of the manuscript, related in my opinion to the comparison between selective secondary strategies and primary strategies. Namely, yet isolating less individuals, selective secondary contact strategies reduce the infections occurring in the population compared to primary contact strategies. This effect is more pronounced as the network becomes heterogeneous. This constitutes an interesting result showing the benefits of sharply interrupting potential transmission chains for disease control.

In what follows, I will make some suggestions to the authors to improve the structure and enhance the readability of the manuscript.

- In my opinion, the authors should represent the results of the different strategies in a single panel for a given epidemiological indicator. This allows the reader to have a more direct comparison of the performance of the different strategies. Therefore, I suggest using the color code to include different strategies in a single panel and use columns to represent the different epidemiological indicators. In this sense, I would avoid including the information of isolations as they always constitute 80% of the infections given the model parameters.

- The authors could also think in reducing the number of strategies represented in the main text. Primary, selective primary strategies and pseudo-secondary tracing seem relevant and coherent. In contrast, secondary contact strategies are hardly achievable, given the large pool of individuals to be traced simultaneously. I have opposite feelings for selective secondary tracing, as the most interesting results are obtained exploring this strategy. Nonetheless, isolating the most influential secondary contacts of the primary contacts without isolating all these primary contacts seems unrealistic. I would suggest the authors exploring another more plausible strategy, consisting in isolating the secondary influential contacts of only those primary contacts that were influential. Such strategy would correspond to restricting tracing and isolating efforts to influential agents in the network. If the authors decide to stick to their original proposal, they should reflect on the practical limitations on such strategy despite its theoretical interest.

- Given the arbitrary choice for influential nodes in the network, I would recommend including a figure comparing the benefits of selective policies varying the threshold used to define influential users. Such analysis would complement the results shown in the manuscript and offer a more nuanced picture on the advantages/limitations of selective contact strategies, as further reducing the pool of prioritized individuals might eventually hamper epidemic control.

- I have found another similar work exploring the impact of prioritization strategies of the effectiveness of contact tracing policies which should be cited in the manuscript [A. Bassolas et al. Phys Rev Research 4, 023092 (2022)].

- The explanation of the epidemic dynamics is not very clear. In particular, the probability of infection per contact is not properly described in the text. Does it correspond with the scaling factor to the infection probability mentioned in Table S1? Likewise, the duration of the outbreaks indicated in the text contrasts with that included in Table S1.

- The assignment of influence scores to nodes is not quite clear either. What is the $\alpha$ value the authors are considering? Did you use the steady state of the recursive equation to set the influence score of each node? If I understood correctly the algorithm, such steady solution should correspond to the PageRank centrality score widely used in network science. There is also a typo in the definition of $G\^{prime}$ as it should read $D^{-1/2} G D^{-1/2}$.

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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.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: Yes: Léo Delpy

Reviewer #3: No

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Informing pandemic intervention strategies through coupled contact tracing and network node prioritization

PCSY-D-24-00018R2

Dear Dr. Blair,

We are pleased to inform you that your manuscript 'Informing pandemic intervention strategies through coupled contact tracing and network node prioritization' has been provisionally accepted for publication in PLOS Complex Systems.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow-up email from a member of our team. 

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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 complexsystems@plos.org.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Complex Systems.

Best regards,

Claus Kadelka

Academic Editor

PLOS Complex Systems

Hocine Cherifi

Editor-in-Chief

PLOS Complex Systems

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While I generally agree with Reviewer 3's comments about Figure 2, I can also empathize with your reasoning why you want to keep the figure the way it is.

Please ensure that you fix Table 3: the caption mentions confidence intervals but it seems standard deviations of the mean are provided instead, and that your manuscript abides with the PLOS Data Policy:

Upload all code required to reproduce your findings in the currently empty GitHub repository https://github.com/adithyanarayanan/Network-Outbreak-Simulations, and ideally create a permanent DOI (using e.g. Zenodo) that you link to in the Data Availability Statement.

Reviewer Comments (if any, and for reference):

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 #3: (No Response)

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2. Does this manuscript meet PLOS Complex Systems's publication criteria? Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe methodologically and ethically rigorous research with conclusions that are appropriately drawn based on the data presented.

Reviewer #3: Partly

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

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception. 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 #3: No

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

PLOS Complex Systems 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 #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 #3: The authors have addressed satisfactorily most of my concerns and the readability and clarity of explanations in the revised version of the manuscript have been substantially improved. I still think that the paper would benefit from a better visualization of the results shown in Figure 2. I understand the point made by the authors but, if the main point of the manuscript is proposing novel strategies, the suitability of these strategies would be better illustrated with a direct comparison between strategies in the same panel. Regarding the PRINCE algorithm, I agree with the authors that there is no random movement in the expression. However, the influence score of each node is updated by a factor $(1-alpha)Y$, with $Y$ being an uniform distribution according to the authors choice. This resembles the rationale behind the computation of the PageRank centrality and I think it is worth mentioning this fact in the main text.

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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.

Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public.

For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #3: No

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