Geology topics

Daniel P. Walsh

Publications and source records attributed to Daniel P. Walsh.

At least 19 recordsLinked to original sources

USGS2026

Modeling localized deer removal strategies for managing chronic wasting disease

We used a published individual-based model to evaluate localized deer removal strategies for managing chronic wasting disease (CWD) in a free-ranging white-tailed deer population in central Michigan, USA. We simulated fine-scale (23.3 km 2 ) deer culling using ring, land parcel-based, and habitat quality-based removal methods. Ring culling consisted of highly concentrated culling in a focal area (e.g., CWD detection area), with effort diminishing as distance away from that location increased. Land parcel-based culling represented a scenario where land access permissions varied across space. Habitat quality-based culling represented intense culling in areas thought to be high-quality deer habitat (thereby likely containing more targets). We also assessed male-targeted strategies for ring and parcel-based methods. We used cost estimates from 2016–2021 in Michigan to calculate total annual localized deer culling expenditures for each removal method. Lastly, we investigated how local conditions, including initial deer density and study area context, affected management outcomes. Chronic wasting disease was less likely to persist in our projections, and prevalence rate was lower, for deer inhabiting a suburban study area compared to an exurban area. All culling methods reduced the probability that CWD would persist and lowered 15-year prevalence in the population compared to no culling. Ring culling near the site of detection (1.6-km instead of 2.4-km radii ring) was most effective at minimizing CWD persistence at medium and high deer densities. However, the ring size most effective at reducing 15-year CWD prevalence depended on study area context and deer densities, with the 2.4-km cull resulting in the lowest prevalence at medium and high deer densities in the suburban study area. At low deer density, parcel-based culling performed best in both study area contexts. Targeting male deer only was consistently less effective at reducing CWD persistence and prevalence and more costly than non-selective deer culling. All culling methods that did not target males had similar total costs for one year of culling in the 23.3-km 2 area, but costs varied considerably based on study area ($5,500–22,100 USD) and deer density ($14,300–25,700). Our model simulations indicated that male-focused culling strategies are less effective and more expensive than non-selective strategies, that ring-based culling is most effective at medium and high deer densities, and that CWD persistence and prevalence in exurban locales are greater compared to suburban locales, regardless of culling strategy.

Michigan↗

USGS2026

Digging into soil: Effects of soil texture on RT-QuIC performance for environmental prion surveillance.

Chronic wasting disease (CWD) is a fatal neurodegenerative disease caused by infectious prions affecting wild and captive cervids. Transmission occurs directly between hosts or indirectly through contact with prion-contaminated environments. Soils, particularly those rich in clay, are hypothesized to enhance prion stability, retention, and bioavailability. Accurate detection of prions is therefore important for understanding environmental transmission risks. Real-time quaking-induced conversion (RT-QuIC) is a sensitive assay used to detect PrP CWD in tissue, excreta, and environmental materials. However, RT-QuIC performance across soil textures has not been evaluated. This study assessed RT-QuIC sensitivity and specificity using laboratory-prepared soils spiked with CWD-positive brain homogenate or water controls under a standardized extraction method. Conditional on the extraction method used, results suggest that RT-QuIC performance depends on soil texture, and thus, an optimal time-to-threshold (TTT) cutoff required to balance sensitivity and specificity will also vary with soil texture. RT-QuIC exhibited higher sensitivity and moderate specificity in soils with low clay (<20%) and moderate to high silt content, whereas high-clay soils (>20%) with low to moderate silt content (2%–60%) reduced both sensitivity and specificity, and required shorter TTT cutoffs. These findings highlight the importance of accounting for soil texture in environmental CWD surveillance.

Environmental Science and Technology↗

USGS2026

A practical framework for GT-seq panel optimization

Genotyping-in-thousands by sequencing (GT-seq) panels are powerful tools in ecological, evolutionary and conservation genomics, yet the optimization process critical for robust and reproducible genotyping remains poorly formalized. Here, we present an iterative workflow for GT-seq panel optimization that emphasizes systematic refinement, quality control and structured decision-making to improve panel performance across diverse populations and study contexts. We illustrate this framework through the development and optimization of a GT-seq panel for white-tailed deer, a widely distributed and ecologically important North American species. From an initial set of 1200 candidate SNPs selected from a commercial microarray (OVSNP60, containing 72,728 SNPs) and prioritized for high heterozygosity, primers were designed for 646 loci. The final optimized panel contains 508 high-performing markers retained after iterative removal of overamplifying primer pairs, adjustment of primer concentrations, PCR conditions and bioinformatic filtering. The overall proportion of SNPs with more than 70% genotype rate increased from 25.5% in the first optimization round to 87.8% in the final round. Consequently, the overall genotype rate increased from 39.4% to 84%. We also identify key quality-control checkpoints and practical criteria to guide panel refinement and ensure consistent performance. By prioritizing optimization as an integral component of GT-seq panel development, this work provides a reproducible framework for generating robust, high-throughput genotyping tools in non-model species and underscores the importance of iterative refinement to maximize data quality and utility.

Molecular Ecology Resources↗

USGS2026

Roost switching and behavioural shifts following human disturbance of vampire bats in complex landscapes

In Latin America, management of vampire bats has had inconsistent effects on the spread of lethal rabies infections from bats to humans and livestock. Positive and negative effects on rabies are hypothesised to reflect changes in bat roost fidelity and behaviour following human disturbance, but high landscape complexity has precluded monitoring bat movement in the areas where rabies transmission and bat management activity are most intense. We used animal-borne GPS tags to track 93 vampire bats in a rabies hotspot in the Peruvian Andes, where limited satellite visibility led to partial observation of animal locations. Immediately after capture, handling and tag application, 43% of bats, particularly males and bats with longer forearms, disappeared from the study area, suggesting a rapid roost switching response. Among the remaining 55 bats, a Bayesian state-space model revealed high individual heterogeneity on the disturbance night but on average increased flight distances. Over the remaining 8-night study period, bats gradually remained closer to the roost. These disturbance-driven shifts provide mechanisms to explain how bat disturbance can both accelerate and decelerate rabies spatial spread. More broadly, we present a modelling framework to infer key movement metrics in landscapes where GPS data limitations challenge conventional movement models.

BioRxiv↗

USGS2026

An optimized rabies vaccine vehicle for orotopical administration to wild vampire bats

Rabies vaccination of vampire bats ( Desmodus rotundus ) has been proposed as a superior control method to culling but has yet to be implemented. Success of rabies vaccination depends on a topical vehicle that spreads through a bat colony via allogrooming while additionally preserving vaccine immunogenicity. This work describes the in vitro and in vivo optimization of a new orotopical gel for rabies vaccine delivery to vampire bats. Autonomous transferability of our carboxymethyl cellulose (CMC) gel vaccine delivery formulation was tested in a microchipped vampire bat colony in rural Jalisco, Mexico. Intra-colony gel uptake was traced using the fluorescent biomarker rhodamine B. Importantly, application of topical treatment of ∼20% of the bat colony resulted in estimated uptake by over 85% of the colony. The in vitro stability of our raccoon poxviral-vectored rabies vaccine candidate within CMC was measured at time points up to 3 months at 40 °C, 23 °C, and 4 °C. Extended storage at 4 °C and short exposure at higher temperatures of potential vampire bat environments preserved vaccine titers within CMC. Furthermore, physical properties of our CMC formulation were compared to the previously used glycerin jelly at 40 °C, 20 °C, and 0 °C using rheological tests. These tests indicate that CMC exhibits optimal properties for topical application to bats even at extreme temperatures possible during field vaccination. This study advances our rabies vaccination strategy for vampire bats by providing a topical vehicle suitable for field application that may additionally be employed for other significant bat diseases.

BioRxiv↗

USGS2025

A generalization error bound of physics-informed neural networks for ecological diffusion models

Ecological diffusion equations (EDEs) are partial differential equations (PDEs) that model spatiotemporal dynamics, often applied to wildlife diseases. Derived from ecological mechanisms, EDEs are useful for forecasting, inference, and decision-making, such as guiding surveillance strategies for wildlife diseases. Physics-informed neural networks (PINNs) offer a cutting-edge approach to approximating the solution of EDEs by constraining the loss function. PINNs have shown empirical success in forecasting and inference in wildlife disease problems. However, theoretical properties of PINNs in this context remain unexplored. In this paper, we derive a generalization error bound for PINNs applied to forward problems in EDEs, providing new crucial theoretical results for statistical analysis. Furthermore, we compare the performance of PINNs with commonly used numerical solvers, showing that PINNs achieve competitive accuracy while providing important modelling flexibility. Our results help connecting theory and application in EDE-based statistical models for ecological systems.

Stat↗

USGS2025

Development of high-throughput genomic resources to inform white-tailed deer population and disease management

White-tailed deer ( Odocoileus virginianus ) are the most abundant and widespread cervid in North America. Genetic data are used as a tool to monitor populations and make management decisions for this game species. However, the development and use of genomic tools that can generate a set of markers suitable for longitudinal genomic data collection, whether for management purposes or to study the demographic and evolutionary processes of widely distributed species, have been challenging. This is mainly due to the cost required to fully implement and interpret the data produced. Here, we generated whole genome resequencing data for 44 free-ranging deer from three regions in their central and eastern North American range and identified over 89 million single nucleotide polymorphisms (SNPs). We used a subset of these SNPs to develop two nested SNP tools, a high-density array (702,183 SNPs) and a medium-density array (72,723 SNPs) to support deer and chronic wasting disease (CWD) management and research. SNPs were selected to ensure an even distribution across scaffolds of the reference genome and include SNPs associated with CWD susceptibility. Using genotyping results for 469 deer from 15 states in the US and Mexico generated by the high-density array and 1335 deer from 18 states generated by the medium-density array, we assessed genotyping success across different populations and explored some insights into population structure. These genomic tools offer a standard set of markers that will enable researchers and managers to address important questions related to white-tailed deer and CWD management. Our SNP arrays also offer the opportunity to examine aspects of white-tailed deer ecology and evolutionary history that were previously difficult to address.

Molecular Ecology Resources↗

USGS2025

Strategic planning of prevention and surveillance for emerging diseases and invasive species

Emerging infectious diseases and biological invasions pose increasing threats to public and ecosystems health. Proactive measures—such as prevention and surveillance taken before initial detection of the pathogen or species—are essential to ensure minimal spread prior to first detection. We developed an optimization model to determine where, when, and how much effort should be allocated to prevention versus surveillance. The model accounts for imperfect detection, system dynamics, spatial heterogeneity in risk and costs and is scalable to large landscapes. We found that the most cost-effective strategy is to maintain the prevention and surveillance efforts at stable equilibrium for the majority of the time, with deviations occurring only initially to steer the system toward the equilibrium. The equilibrium effort is jointly determined by the introduction risk, management costs, and total budget. Application of this model to chronic wasting disease in New York State suggests that the optimal strategy could reduce the cumulative disease cases before initial detection by an average of 22% compared to current practice. The optimal surveillance strategy could detect the disease on average over 8 mo earlier than the current strategy.

PNAS↗

USGS2025

Animal trajectory imputation and uncertainty quantification via deep learning

Imputing missing data in animal trajectories is crucial for understanding animal movements during unobserved periods. However, the traditional methods, such as linear interpolation and the continuous-time correlated random walk model, are often inadequate to capture the complexity of animal movements. Here, we develop a deep learning approach to animal trajectory imputation by a conditional diffusion model. Unlike the traditional methods, our deep learning method uses observed data and external covariates to impute missing positions along an animal trajectory, capturing periodic patterns and the influence of covariates, which leads to more accurate imputations. In a case study of imputing deer trajectories, our method not only provides more accurate deterministic imputations than existing approaches but also achieves uncertainty quantification through probabilistic imputation.

Environmetrics↗

USGS2025

Doe diligence: A regional analysis of antlerless deer harvest regulations in the Midwestern United States of America.

Wildlife management in the United States of America (US) is primarily delegated to the individual states wherein state wildlife agencies manage wildlife populations to achieve multiple and sometimes conflicting objectives. White-tailed deer ( Odocoileus virginianus ) are an important species in the Midwestern US whose populations are primarily managed through recreational hunting. Managers aim to adjust populations by altering the harvest of antlerless (usually female) animals by changing the number of harvest permits available, hunting season lengths, or applying incentive programs like earn-a-buck, where a hunter must harvest an antlerless deer before they may harvest an antlered deer. We estimated the effect on antlerless deer harvest from changes in these regulations and changes in the number of licensed hunters across eight states in the Midwest. We used a Bayesian hierarchical model to estimate individual state and regional (i.e., across all states) effects. We found that increasing antlerless harvest permits increased antlerless harvest; however, this effect plateaued as the number of available permits increased. Providing unlimited harvest permits increased harvest, but the same increases were achieved by minimally increasing the number of limited harvest permits. Increasing the length of hunting season had a generally positive effect on antlerless harvest but the effect was non-linear and state dependent. The earn-a-buck incentive program resulted in the largest estimated increase in harvest. Finally, the number of licensed deer hunters in a state had a strong positive effect on the number of antlerless deer harvested. Our findings show that commonly applied changes in harvest regulations have a weak effect on the number of antlerless deer harvested, highlighting the challenges facing deer managers in the Midwestern US.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗

USGS2025

White‐tailed deer habitat use and implications for chronic wasting disease transmission

Animal space use, activity patterns, and habitat selection—and heterogeneity in these patterns—have important implications for where and when infectious diseases are transmitted. White-tailed deer ( Odocoileus virginianus ) are habitat generalists, with a high degree of heterogeneity in their movement ecology based on sex, age, season, and region. These heterogeneities have important implications for the transmission and management of chronic wasting disease (CWD), which is a deadly prion disease transmitted both directly and indirectly through the environment. As such, favored deer habitats may promote direct interactions between conspecifics or indirect spatial overlap and subsequent environmental transmission. However, little is known about how individual animal space use translates to actual spatial overlap between individuals, leaving uncertainty in how habitat shapes the risk of direct or environmental CWD transmission. In this study, we evaluated seasonal activity patterns, home ranges, and habitat selection for 596 white-tailed deer in southwest Wisconsin, USA, from 2017-2022. We also estimated seasonal encounter distributions—regions where a pair of deer were most likely to encounter each other—for all pairs of deer putatively in different social groups (between-group) in our study, and quantified seasonal variation in the habitat composition of these areas. We found that deer selection for crops, pasture, or grasslands was generally low, relative to forest, but was highest in the post-fawning (summer) and non-breeding (winter) seasons. We observed similar patterns for the habitat composition of encounter distributions, suggesting that crops, pasture, and grasslands may be attractive resources that facilitate between-group transmission. Site fidelity between years was generally high; combined with small female home ranges in the fawning season, this implies that females likely re-use the same small, high-quality fawning habitats from year to year. We found that attraction toward between-group individuals was low during the post-fawning season but high during the breeding (fall) and non-breeding seasons. These results suggest that space use and habitat selection could shape the risk of environmental transmission in the fawning and post-fawning seasons, social selection could favor direct transmission risk in the breeding season, and combined social and habitat selection may shape risk of both direct and environmental transmission during the non-breeding season. We provide a detailed picture of the physiological and social drivers of deer movement through the year, with implications for CWD transmission and management.

Iowa, Wisconsin↗

USGS2025

Learning complex spatial dynamics of wildlife diseases with machine learning-guided partial differential equations

Emerging wildlife pathogens often display geographic variability due to landscape heterogeneity. Modeling approaches capable of learning complex, non-linear spatial dynamics of diseases are needed to rigorously assess and mitigate the effects of pathogens on wildlife health and biodiversity. We propose a novel machine learning (ML)-guided approach that leverages prior physical knowledge of ecological systems, using partial differential equations. We present our approach, taking advantage of the universal function approximation property of neural networks for flexible representation of the underlying dynamics of the geographic spread and growth of wildlife diseases. We demonstrate the benefits of our approach by comparing its forecasting power with commonly used methods and highlighting the obtained insights on disease dynamics. Additionally, we show the theoretical guarantees for the approximation error of our model. We illustrate the implementation of our ML-guided approach using data from white-nose syndrome (WNS) outbreaks in bat populations across the US. WNS is an infectious fungal disease responsible for significant declines in bat populations. Our results on WNS are useful for disease surveillance and bat conservation efforts. Our methods can be broadly used to assess the effects of environmental and anthropogenic drivers impacting wildlife health and biodiversity.

Environmental Data Science↗

USGS2025

Characterization of the long-distance dispersal kernel of white-tailed deer and evaluating its impact on chronic wasting disease spread in Wisconsin

Chronic wasting disease (CWD) is a fatal neurodegenerative disease infecting cervids. It is highly contagious and caused by misfolded prions that propagate via templated conformational conversion of the cervid’s normal prion protein. Prevalence of CWD in free-ranging deer in North America is mostly low, but in some regions local prevalence has reached 80%. CWD prions can be transmitted via direct contact with infected individuals or indirectly through the environment. Infected individuals shed prions through feces, urine, saliva or carcasses, and prions have long environmental persistence. Long-distance dispersal of infected deer poses a significant risk for CWD spread. We propose an integrodifference equation (IDE) model to capture CWD dynamics and the consequences of long-distance dispersal behavior in white-tailed deer (WTD, Odocoileus virginianus ). A diffusion-settling model characterizes long-distance dispersal kernels, accommodating hypothetical dispersal behaviors through time-dependent settling rate functions. Three new closed-form dispersal kernels are approximated using Laplace’s method and parameterized with GPS location data collected from WTD in Wisconsin, USA. Settling rates reflecting ongoing sensitivity to stimuli which prompt deer to disperse from their natal home range give the most supported long-distance dispersal kernel. Impact of long-distance dispersal on CWD spread is quantified using the IDE model. At high population densities, long-distance dispersal can magnify CWD spread by a factor of four. At lower population densities single infected individuals cannot initiate an outbreak, but CWD may still spread due to the accumulation of environmental hazard from prions behind the wave of invasion, possibly presenting substantial management challenges.

Wisconsin↗

USGS2025

Spatiotemporal causal inference with mechanistic ecological models: Evaluating targeted culling on chronic wasting disease dynamics in cervids

Spatiotemporal causal inference methods are needed to detect the effect of interventions on indirectly measured epidemiological outcomes that go beyond studying spatiotemporal correlations. Chronic wasting disease (CWD) causes neurological degeneration and eventual death to white-tailed deer ( Odocoileus virginianus ) in Wisconsin. Targeted culling involves removing deer after traditional hunting seasons in areas with high CWD prevalence. The evaluation of the causal effects of targeted culling in the spread and growth of CWD is an important unresolved research and CWD management question that can guide surveillance efforts. Reaction–diffusion partial differential equations (PDEs) can be used to mechanistically model the underlying spatiotemporal dynamics of wildlife diseases, like CWD, allowing researchers to make inference about unobserved epidemiological quantities. These models indirectly regress spatiotemporal covariates on diffusion and growth rates parameterizing such PDEs, obtaining associational conclusions. In this work we develop an innovative method to obtain causal estimators for the effect of targeted culling interventions on CWD epidemiological processes using an inverse-probability-of-treatment-weighted technique by means of marginal structural models embedded in the PDE fitting process. Additionally we establish a novel scheme for sensitivity analysis under unmeasured confounder for testing the hypothesis of a significant causal effect in the indirectly measured epidemiological outcomes. Our methods can be broadly used to study the impact of spatiotemporal interventions and treatment exposures in the epidemiological evolution of infectious diseases that can help to inform future efforts to mitigate public health implications and wildlife disease burden.

Wisconsin↗

USGS2025

A system dynamics model to understand the integrated ecological and human dimension aspects of wildlife health and disease management

Chronic wasting disease (CWD) presents an ongoing challenge for the management of deer populations and sustaining harvest opportunities across North America. Existing disease models often fail to fully capture the complex interplay between disease dynamics, host ecology, and socio-economic factors. We developed a comprehensive system dynamics (SD) model that integrates demographic, epidemiological, ecological, and socio-economic processes within a single model to more fully characterize the complex network of causal feedbacks throughout the system. The model was calibrated using a Bayesian approach that incorporates prior knowledge to generate biologically interpretable outcomes, even with sparse data. For estimating the joint posterior distribution of model parameters, we leveraged time series of deer abundance, harvest composition, genetic profiles, CWD surveillance, and hunter demographics and behavior. Model outputs reproduced key system behaviors, including observed CWD prevalence trends, deer population dynamics, and hunter license purchasing patterns. Model predictions were most sensitive to parameters governing initial deer population size and recruitment. While model predictions generally aligned with observed data, discrepancies in early CWD detection and overestimation of the reactivation of long-inactive hunters reflect data limitations and modeling challenges. Key results suggest that indirect transmission is necessary to explain observed prevalence, that transmission is moderately density-dependent, and that observed population-level genetic shifts driven by CWD may play a role in transmission and progression. The SD modelling approach enabled estimation of difficult-to-measure parameters and identified potential leverage points for management—such as prioritizing increasing participation in antlerless harvest of existing hunters over the recruitment of new hunters. This integrated modeling approach offers a flexible foundation for adaptive wildlife disease management and emphasizes the value of unifying biological and human dimension processes to better inform effective, evidence-based policy.

BioRxiv↗

USGS2025

Fatal interactions: Pneumonia in bighorn lambs following experimental exposure to carriers of Mycoplasma ovipneumoniae

We hypothesized that bighorn sheep ewes with chronic nasal Mycoplasma ovipneumoniae carriage are the source of infection that results in fatal lamb pneumonia. We tested this hypothesis in captive bighorn ewes at two study facilities over a 5-year period, by identifying carrier ewes and then comparing lamb fates in groups that did (exposed pens) or did not (non-exposed pens) include one or more carrier ewes. Most (23 of 30) lambs born in exposed pens, but none of 11 lambs born in non-exposed pens, contracted fatal pneumonia. In addition, surviving lambs in exposed pens showed obvious signs of respiratory disease while lambs in non-exposed pens did not. In crossover experiments, individual non-carrier ewes had lambs that experienced fatal pneumonia in years when housed in exposed pens, but not in years when housed in non-exposed pens. The results of these studies clearly associate lamb pneumonia to exposure to M. ovipneumoniae carrier ewes, consistent with a necessary role for this agent in epizootic pneumonia of bighorn sheep. These data specifically highlight the role of chronic M. ovipneumoniae carriage by some bighorn ewes in the epidemiology of this population-limiting wildlife disease.

Idaho, Montana, Nevada, Oregon, South Dakota, Wash↗

USGS2024

Wildlife health capacity enhancement in Thailand through the World Organisation for Animal Health Twinning Program

There is an increasing need for robust wildlife health programs that provide surveillance and management for diseases in wildlife and wild aquatic populations to manage associated risks. This paper illustrates the value of a systematic method to enhancing wildlife health programs. The U.S. Geological Survey and Mahidol University, Faculty of Veterinary Science, Thailand National Wildlife Health Center formally twinned under the auspices of the World Organisation for Animal Health to enhance wildlife health capacity in Thailand and the Southeast Asia Region. We used a system-wide approach to holistically and interdependently enhance capacity. The project commenced with a wildlife health program needs assessment, and capacity enhancement focused on strengthening the general wildlife health surveillance network and improving wildlife health information management. Activities included partner surveys, interactive and didactic workshops, and individual personnel training. Topics included development of wildlife health information management systems, analysis of the current surveillance network, development of a Theory of Change for a strengthened surveillance network, planning workshops to create a wildlife health network, training on wildlife disease outbreak investigation and field sample collection, leading networks, and individual training on bioinformatics and laboratory techniques. Engagement of stakeholders at all levels, continuous communication throughout the project, use of both strategic planning tools and pedagogical methods, and using iterative and adaptive approaches, were key factors to the success of this project.

Frontiers in Veterinary Science↗

USGS2024

Epidemiological modeling of SARS-CoV-2 in white-tailed deer (Odocoileus virginianus) reveals conditions for introduction and widespread transmission

Emerging infectious diseases with zoonotic potential often have complex socioecological dynamics and limited ecological data, requiring integration of epidemiological modeling with surveillance. Although our understanding of SARS-CoV-2 has advanced considerably since its detection in late 2019, the factors influencing its introduction and transmission in wildlife hosts, particularly white-tailed deer ( Odocoileus virginianus ), remain poorly understood. We use a Susceptible-Infected-Recovered-Susceptible epidemiological model to investigate the spillover risk and transmission dynamics of SARS-CoV-2 in wild and captive white-tailed deer populations across various simulated scenarios. We found that captive scenarios pose a higher risk of SARS-CoV-2 introduction from humans into deer herds and subsequent transmission among deer, compared to wild herds. However, even in wild herds, the transmission risk is often substantial enough to sustain infections. Furthermore, we demonstrate that the strength of introduction from humans influences outbreak characteristics only to a certain extent. Transmission among deer was frequently sufficient for widespread outbreaks in deer populations, regardless of the initial level of introduction. We also explore the potential for fence line interactions between captive and wild deer to elevate outbreak metrics in wild herds that have the lowest risk of introduction and sustained transmission. Our results indicate that SARS-CoV-2 could be introduced and maintained in deer herds across a range of circumstances based on testing a range of introduction and transmission risks in various captive and wild scenarios. Our approach and findings will aid One Health strategies that mitigate persistent SARS-CoV-2 outbreaks in white-tailed deer populations and potential spillback to humans.

PLOS Computational Biology↗