Biology subjects

Walsh, D. P.

Publications and source records attributed to Walsh, D. P..

6 recordsLinked to original sources

bioRxiv2025

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.

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bioRxiv2025

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 {degrees}C, 23 {degrees}C, and 4 {degrees}C. Extended storage at 4 {degrees}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 {degrees}C, 20 {degrees}C, and 0 {degrees}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.

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bioRxiv2025

Diverse behavioural responses of vampire bats to human disturbance revealed by state-space modelling of sparse GPS data.

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.

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bioRxiv2023

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.

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bioRxiv2023

Prions in carnivore feces: recovery from spiking experiments and detection in free-ranging carnivores

Chronic wasting disease (CWD) is a highly contagious, fatal neurodegenerative disease caused by infectious prions (PrPCWD) affecting wild and captive cervids. Although experimental feeding studies have demonstrated prions in feces of crows (Corvus brachyrhynchos), coyotes (Canis latrans), and cougars (Puma concolor), the role of scavengers and predators in CWD epidemiology remains poorly understood. Here we applied the real-time quaking-induced conversion (RT-QuIC) assay to detect PrPCWD in feces from cervid consumers, to advance surveillance approaches, which could be used to improve disease research and adaptive management of CWD. We assessed recovery and detection of PrPCWD by experimental spiking of PrPCWD into carnivore feces from 9 species sourced from CWD-free populations or captive facilities. We then applied this technique to detect PrPCWD from feces of predators and scavengers in free-ranging populations. Our results demonstrate that spiked PrPCWD is detectable from feces of free-ranging mammalian and avian carnivores using RT-QuIC. Results show that PrPCWD acquired in natural settings is detectable in feces from free-ranging carnivores, and that PrPCWD rates of detection in carnivore feces reflect relative prevalence estimates observed in the corresponding cervid populations. This study adapts an important diagnostic tool for CWD, allowing investigation of the epidemiology of CWD at the community-level.

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bioRxiv2020

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

O_LIMotion-activated wildlife cameras (or "camera traps") are frequently used to remotely and non-invasively observe animals. The vast number of images collected from camera trap projects have prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. C_LIO_LIWe used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the "species model," and one that determines if an image is empty or if it contains an animal, the "empty-animal model." C_LIO_LIOur species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36-91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91-94% on out-of-sample datasets from different continents. C_LIO_LIOur software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths. C_LI

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