Geology topics

Fernando Arce

Publications and source records attributed to Fernando Arce.

3 recordsLinked to original sources

USGS2024

One Health collaboration is more effective than single-sector actions at mitigating SARS-CoV-2 in deer

One Health aims to achieve optimal health outcomes for people, animals, plants, and shared environments. We describe a multisector effort to understand and mitigate SARS-CoV-2 transmission risk to humans via the spread among and between captive and wild white-tailed deer. We first framed a One Health problem with three governance sectors that manage captive deer, wild deer populations, and public health. The problem framing included identifying fundamental objectives, causal chains for transmission, and management actions. We then developed a dynamic model that linked deer herds and simulated SARS-CoV-2. Next, we evaluated management alternatives for their ability to reduce SARS-CoV-2 spread in white-tailed deer. We found that single-sector alternatives reduced transmission, but that the best-performing alternative required collaborative actions among wildlife management, agricultural management, and public health agencies. Here, we show quantitative support that One Health actions outperform single-sector responses, but may depend on coordination to track changes in this evolving system.

Nature Communications↗

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↗

USGS2024

Reframing wildlife disease management problems with decision analysis

Contemporary wildlife disease management is complex because managers need to respond to a wide range of stakeholders, multiple uncertainties, and difficult trade-offs that characterize the interconnected challenges of today. Despite general acknowledgment of these complexities, managing wildlife disease tends to be framed as a scientific problem, in which the major challenge is lack of knowledge. The complex and multifactorial process of decision-making is collapsed into a scientific endeavor to reduce uncertainty. As a result, contemporary decision-making may be oversimplified, rely on simple heuristics, and fail to account for the broader legal, social, and economic context in which the decisions are made. Concurrently, scientific research on wildlife disease may be distant from this decision context, resulting in information that may not be directly relevant to the pertinent management questions. We propose reframing wildlife disease management challenges as decision problems and addressing them with decision analytical tools to divide the complex problems into more cognitively manageable elements. In particular, structured decision-making has the potential to improve the quality, rigor, and transparency of decisions about wildlife disease in a variety of systems. Examples of management of severe acute respiratory syndrome coronavirus 2, white-nose syndrome, avian influenza, and chytridiomycosis illustrate the most common impediments to decision-making, including competing objectives, risks, prediction uncertainty, and limited resources.

Conservation Biology↗