PESY-D-26-00009

A protocol for biodiversity-informed wildlife disease surveillance

PLOS Ecosystems

Dear Dr. Catchen,

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Carolyn J. Lundquist, PhD

Section Editor

PLOS Ecosystems

Henrique M. Pereira

Editor-in-Chief

PLOS Ecosystems

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Additional Editor Comments (if provided):

We have received two external reviews of your manuscript, both of which highlight the novelty and usefulness of the proposed protocol. Both provide detailed feedback, noting one provides feedback primarily within an annotated copy of the manuscript of suggested revisions to enhance the quality of the manuscript. We welcome a revision of your manuscript that addresses these comments.

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Reviewers' Comments:

Reviewer's Responses to Questions

Comments to the Author

1. Does this manuscript meet PLOS Ecosystems’s publication criteria?>

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

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

Reviewer #1: Yes

Reviewer #2: Yes

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Reviewer #1:   I have all of my comments on the attached PDF. But to summarize the strengths of the manuscript:

• I appreciate the idea of identifying sampling priorities while explicitly incorporating

spatial uncertainty. Overall, I see this as a promising step forward in environmental

risk mapping.

• While species weighting always involves assumptions and caveats, I applaud the

authors for trying to bring more nuance to weighing decisions (eg serology vs PCR).

In many modeling frameworks, weighting decisions are left to the modeler’s

discretion and can feel somewhat ad hoc. The ePort to provide a more structured

approach is commendable.

• I found the distinction between sampling location and type of data sampled to be

particularly insightful

• The conceptual distinction between hazard and risk is also useful and clearly

framed

I was able to clone the repository and run part of the code. Without troubleshooting or

actively fixing errors, I was able to run the India case study but not the South Korea case

study. I initially suspected the issue might relate to OSM object, but it appears to be

unrelated. However, I am primarily an R user, so this could reflect my own skillset rather

than an issue with the repository itself. If may be helpful for the authors to ask another

primarily R user to test the workflow on a different machine.

Reviewer #2:   Developing surveillance systems for wildlife pathogens continues to be a tricky problem in the field of One Health due to the presence of many unknowns and the unavoidable constraints in sampling. One cannot sample all species all at once, so there must be some prioritization system. The authors of this manuscript have proposed a method for designing wildlife pathogen surveillance systems that stakeholders could use to better target some of the uncertainties about hosts or pathogen prevalence in a given area. The protocol appears to be ideal for use in an evolving information environment, where new host or prevalence can be added to the underlying model to create the next iteration of sampling prioritization. The manuscript followed a somewhat unusual format for a research article, but it worked well for how the content was presented, as an introduction to the concepts and the model, then a demonstration using two case studies. The boxes provided some additional useful information about how to interpret species distribution models and the recommended sampling locations outputted from the model. Overall, I think this protocol could be an excellent addition to the field. The manuscript text was clear and the figures illustrated some of the key outputs and concepts discussed in the text, such that users could refer back to this manuscript to help with interpretation of their own output. I did not have any major concerns about the model, though I did think there were many places where some additional explanation about how choices are made about species weights and other model variables would be valuable for potential users.

One other general comment: would it be useful to have a glossary of terms somewhere in the manuscript or supplement? There are some esoteric terms that get used throughout the paper and are defined in the text, but a centralized location for these terms could help readers with comprehension. Key terms may include: risk, hazard, spillover, biosurveillance, discovery sampling, prevalence sampling, Biodiversity Observation Network, biodiversity dose.

L19-20: Expand on this statement a little to provide more justification. As it stands now, this seems like a fairly empty proclamation. However, the first paragraph of Section 2 does a fantastic job with distinguishing hazard from risk and justifying why biosurveillance is a key part of estimating hazard. Pulling in some of that nuance here would make a stronger case.

L32: Hyphen not needed in Arenaviridae. Also make sure to italicize virus family names. Lastly, and this may be pedantic, but “small mammals” or “rodents and shrews” would be better than rodents here and throughout the paper. Suncus murinus and Crocidura lasiura are shrews (Eulipotyphla), not rodents. And I think broadly the hantaviruses can infect both taxa, so you should be as inclusive as possible, even if arenaviruses are more specific to rodents.

L34-35: This is more of a general comment, but it was not immediately clear how this protocol would get used in the public health space. Who are the intended users of this protocols and how would the information about sampling and testing be distributed to stakeholders? Do you think this is a purely academic exercise, or is it intended that governments and agencies would be leading these efforts? It may be worth some additional discussion at the end of the paper to make the strong case to specific end users.

L124-127: Why is this considered part of risk? As laid out in the sections above, this seems more in line with hazard rather than risk, because risk is largely driven by anthropogenic activities, no? Changes in the host side of things seem like they would have more influence on hazard than risk.

L184-185: Unclear which of the methods is the one with higher false-negatives. One would initially guess that PCR has the higher false-negative rate because of the frequently short window of pathogen shedding, such that it may be difficult to find a host actively shedding, even if they are ultimately a competent host. Whereas with serology, one runs the risk of including many noncompetent hosts that have simply been exposed but the pathogen does not replicate in or transmit from this host. So those would be false-positives in the eyes of many ecologists. This question seems like it would also have a fairly large influence on the model uncertainty. Is this something that needs to be included in sensitivity analyses? And is there a way of incorporating uncertainty in host weights into the calculation of biodiversity dose, beyond just random noise, but a more specific way of quantifying differences in uncertainty among host species?

L199: What about prevalence uncertainty? If a small sample at a location showed high prevalence, it does not mean it is always that high and is likely biased. This location would have high prevalence uncertainty (10/1000 has less uncertainty than 1/100). Is there any way to include prevalence uncertainty into this model, e.g., weighting inversely by sample size? If it is already included in the model, a short section explaining how it is done would be helpful.

L213: Could the authors provide more guidance about how all these uncertainties about host competence and prevalence get boiled down into w_{i}? Is there an equation that could be built to estimate w_{i}, or are the values based solely on investigator judgement?

L281-283: Could you also apply this to investigate the sensitivity of maps to changes in weights that do indeed reflect biological differences in host relevance, such as when one doesn’t know whether all species are equally competent hosts? Would there need to be something larger than small “nudges” to the weights?

L300-L303: Maybe indicate that the South Korea case study is about hosts of Hantaviridae. It’s not currently stated explicitly here.

L308-309: If there is no prevalence or sampling data in some locations, how can one be sure about which hosts are contributing to pathogen maintenance? Are there potentially unknown host species that need to be accounted for? And how would one go about assigning weights to these species?

L335-338: I understand what is trying to be done here with this case study, but it sort of falls short of being a great example of how one might approach this type of low information sampling. This seems from a glance to be just an assortment of relatively common species in India. The authors might have to provide a disclaimer that the species chosen by Rodrigues may be different than what would have been chosen by an alternative method that uses all available biodiversity information and phylogenetic proximity to known hosts.

L338: What were the chosen weights? Which species ended up with the highest weight in the images shown in Figure 2?

L348-349: What is the process for deciding the tilting value alpha? What sort of behavior in the model is “ideal” and how would a user decide?

L359: What is the justification for including Imjin virus here? Is there any evidence that this virus can or does infect humans? Or is this operating from a pure hazard viewpoint that any hantavirus in a host can potentially cause human infections? And what do we know about the role of these species in transmission? Are they the only hosts, or just the dominant hosts? How many additional species contribute to hantavirus transmission in South Korea that are not included in this case study?

L363-366: If the authors were performing this case study as a real analysis or sample planning exercise, what sort of sensitivity analyses would the authors suggest running to incorporate additional known hosts and other potential hosts with unknown status?

L384: Similar comment as above, how was the tilting value alpha chosen for this case study?

L481-483: The way I thought about this was in terms of additive probabilities. Because the presence of species are not mutually exclusive, their additive probabilities would be P(A or B) = P(A) + P(B) – P(A and B). However, since P(A and B) requires a joint SDM to estimate, it does not get subtracted off in the probability estimate and therefore we get an overestimate of sympatry between two species. And obviously this gets compounded when you stack an even larger number of potential sympatric species.

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Reviewer #1: No

Reviewer #2: No

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Reproducibility:

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A protocol for biodiversity-informed wildlife disease surveillance

PESY-D-26-00009R1

Dear Dr Catchen,

We are pleased to inform you that your manuscript 'A protocol for biodiversity-informed wildlife disease surveillance' has been provisionally accepted for publication in PLOS Ecosystems.

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.

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

Best regards,

Carolyn J. Lundquist, PhD

Section Editor

PLOS Ecosystems

Henrique M. Pereira

Editor-in-Chief

PLOS Ecosystems

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Thank you for submitting the revised version of the manuscript which was reviewed by one of the original reviewers, who agreed that the feedback had been adequately addressed. The reviewer noted a few minor typos that the editorial staff can determine if a further round of revisions is required or if these can be addressed in the final copy editing stage.

Reviewer Comments (if any, and for reference):

Reviewer's Responses to Questions

Comments to the Author

Reviewer #2: (No Response)

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publication criteria?>

Reviewer #2: Yes

**********

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

Reviewer #2: Yes

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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

Reviewer #2: Yes

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

Reviewer #2: Yes

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Reviewer #2: The authors have adequately addressed all comments raised in the previous round of review. I have only a few minor comments.

1. Correct spelling and grammar: “prevantative” (L24) to “preventative”, “disperate” (L92) to “disparate”, “substatially” (L94) to “substantially”, “about about” (L224) to “about”, “phyologenies” (L237) to “phylogenies”, “that” (L288) to “than”, “Hantaviridea” (L443) to “Hantaviridae”.

2. Correct sentence: “…an essential to confidence this protocol…” (L242), appears that several words are missing. Maybe correct to “…an essential step to build confidence that this protocol…”?

3. Reference all Supplemental Material: It doesn’t look like Supplemental Fig. 1 or Supplemental Table 3 are mentioned by name anywhere in the text. The authors should insert references to these items into the main text where appropriate. It might be useful to mention the Glossary early on in the text once some of the selected terms have been introduced.

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Reviewer #2: No

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