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.

Implementation of Routine In Situ Simulation in Residency Curriculum Targeting Competency in Technical and Decision-Making Skills.

OBJECTIVE: To describe the development and implementation of a comprehensive in situ simulation-based curriculum for anesthesia residents. DESIGN: This is a prospective study. SETTING: This study was conducted at a university hospital. PARTICIPANTS: This single-center prospective study included all 53 anesthesia residents enrolled in the anesthesia residency program. INTERVENTIONS: Introduction of a routine, high-fidelity, in situ simulation program that incorporates short sessions to train residents in the necessary skill sets and decision-making processes required in the operating room. MEASUREMENTS AND MAIN RESULTS: Our team conducted 182 individual 15-minute simulation sessions over 3 months during regular working hours. All 53 residents in our program actively participated in the simulations. Most residents engaged in at least 3 sessions, with an average participation rate of 3.4 per resident (range, 1-6 sessions). Residents completed an online anonymous survey, with a response rate of 71.7% (38 of 53 residents) over the 3-month period. The survey aimed to assess their overall impression and perceived contribution of this project to their training. CONCLUSIONS: Our proposed teaching method can bridge the gap in resident training and enhance their critical reasoning to manage diverse clinical situations they may not experience during their residency.

Rapid prototyping for quantifying belief weights of competing hypotheses about emergent diseases.

Emerging diseases can have devastating consequences for wildlife and require a rapid response. A critical first step towards developing appropriate management is identifying the etiology of the disease, which can be difficult to determine, particularly early in emergence. Gathering and synthesizing existing information about potential disease causes, by leveraging expert knowledge or relevant existing studies, provides a principled approach to quickly inform decision-making and management efforts. Additionally, updating the current state of knowledge as more information becomes available over time can reduce scientific uncertainty and lead to substantial improvement in the decision-making process and the application of management actions that incorporate and adapt to newly acquired scientific understanding. Here we present a rapid prototyping method for quantifying belief weights for competing hypotheses about the etiology of disease using a combination of formal expert elicitation and Bayesian hierarchical modeling. We illustrate the application of this approach for investigating the etiology of stony coral tissue loss disease (SCTLD) and discuss the opportunities and challenges of this approach for addressing emergent diseases. Lastly, we detail how our work may apply to other pressing management or conservation problems that require quick responses. We found the rapid prototyping methods to be an efficient and rapid means to narrow down the number of potential hypotheses, synthesize current understanding, and help prioritize future studies and experiments. This approach is rapid by providing a snapshot assessment of the current state of knowledge. It can also be updated periodically (e.g., annually) to assess changes in belief weights over time as scientific understanding increases. Synthesis and applications: The rapid prototyping approaches demonstrated here can be used to combine knowledge from multiple experts and/or studies to help with fast decision-making needed for urgent conservation issues including emerging diseases and other management problems that require rapid responses. These approaches can also be used to adjust belief weights over time as studies and expert knowledge accumulate and can be a helpful tool for adapting management decisions.

Assessing Skill Acquisition in Anesthesiology Interns Practicing Central Venous Catheter Placement Through Advancements in Motion Analysis.

OBJECTIVES: The study authors hypothesized that a combination of previously used (path length, translational motions, and time) and novel (rotational sum) motion metrics could be used to analyze learning curves of anesthesiology interns (postgraduate year 1) practicing central venous catheter placement in the simulation setting. They also explored the feasibility of using segmented motion recordings to inform deliberate practice. DESIGN: A prospective cohort study. SETTING: A single academic medical center. PARTICIPANTS: Anesthesiology interns (postgraduate year 1). INTERVENTIONS: Anesthesiology interns underwent a 2-day training course in which they performed 9 central venous catheter placements, while attached to motion sensors on the dorsum of their dominant hand and ultrasound probe. MEASUREMENTS AND MAIN RESULTS: Motion metrics were analyzed using generalized estimating equations for both the overall procedure and predefined segments. Five attending anesthesiologists performed 3 trials each for comparison. Overall, there was a negative trend in path length, translational motions, rotational sum, and time (p < 0.001), with the exception of translational motions of the ultrasound probe. Interns reached within 1 standard deviation of the attending anesthesiologists by trials 7-to-8 for most metrics. Segmentation identified specific components of the procedure that were either significantly improved upon or required deliberate practice. The novel metric of rotational sum exhibited a moderate-to-strong positive correlation with other metrics (p < 0.001). CONCLUSIONS: A comprehensive series of motion metrics was able to describe the learning curves of novices training to perform central venous catheter placement in the simulation setting. Furthermore, it was determined that segmentation may provide additional insight into skill acquisition and inform deliberate practice.

Simplified Algorithm for Evaluation of Perioperative Hypoxia and Hypotension (SALVATION): A Practical Echo-guided Approach Proposal.

Despite the valuable use of modern applications of perioperative ultrasound across multiple disciplines, there have been limitations to its implementation, restricting its impact on patient-based clinical outcomes. Point-of-care ultrasound evaluation of hypoxia and hypotension is an important tool to assess the underlying undifferentiated etiologies in a timely manner. However, there is a lack of consensus on the formal role of ultrasound during evaluation of perioperative hypoxia or hypotension. The previous ultrasound algorithms have adopted a complex technique that possibly ignore the pathophysiologic mechanisms underlying the conditions presenting in a similar fashion. The authors here propose a simple, sequential and focused multiorgan approach, applicable for the evaluation of perioperative hypotension and hypoxia in emergency scenarios. The authors believe this approach will enhance the care provided in the postanesthesia care unit, operating room, and intensive care unit.

Rapid Weight Gain Following Weight Cutting in Male and Female Professional Mixed Martial Artists.

Rapid weight loss or "weight cutting" is a common but potentially harmful practice used in mixed martial arts competition. Following the official weigh-in, competitors refeed and rehydrate themselves in a process known as rapid weight gain (RWG) to realize a potential competitive advantage. While data from surveys and small series have indicated the majority of mixed martial arts athletes engage in rapid weight loss, there is a lack of officially collected data from sanctioning organizations describing its prevalence. The present investigation represents a summary of the data collected between December 2015 and January 2018 by the California State Athletic Commission. In total, 512 professional mixed martial artists (455 males and 57 females) were included. Of these, 503 (98%) athletes gained body mass between weigh-in and their bouts. Total RWG between weigh-in and competition was 5.5 ± 2.5 kg, corresponding to an 8.1% ± 3.6% body mass increase. Total RWG was 5.6 ± 2.5 kg (8.1% ± 3.6%) for males and 4.5 ± 2.3 kg (8.0% ± 3.8%) for females. More than one quarter of men and one third of women gained >10% body mass between weigh-in and competition. Athletes from leading international promotions gained more absolute, but not relative, body mass than those from regional promotions. Our findings indicate RWG is nearly ubiquitous in professional , with a similar prevalence in male and female athletes. Trends based on promotion suggest a larger magnitude of RWG in presumably more experienced and/or successful mixed martial artists from leading international promotions.

Bias correction of bounded location error in binary data.

Binary regression models for spatial data are commonly used in disciplines such as epidemiology and ecology. Many spatially referenced binary data sets suffer from location error, which occurs when the recorded location of an observation differs from its true location. When location error occurs, values of the covariates associated with the true spatial locations of the observations cannot be obtained. We show how a change of support (COS) can be applied to regression models for binary data to provide coefficient estimates when the true values of the covariates are unavailable, but the unknown location of the observations are contained within nonoverlapping arbitrarily shaped polygons. The COS accommodates spatial and nonspatial covariates and preserves the convenient interpretation of methods such as logistic and probit regression. Using a simulation experiment, we compare binary regression models with a COS to naive approaches that ignore location error. We illustrate the flexibility of the COS by modeling individual-level disease risk in a population using a binary data set where the locations of the observations are unknown but contained within administrative units. Our simulation experiment and data illustration corroborate that conventional regression models for binary data that ignore location error are unreliable, but that the COS can be used to eliminate bias while preserving model choice.

"One Health" or Three? Publication Silos Among the One Health Disciplines.

The One Health initiative is a global effort fostering interdisciplinary collaborations to address challenges in human, animal, and environmental health. While One Health has received considerable press, its benefits remain unclear because its effects have not been quantitatively described. We systematically surveyed the published literature and used social network analysis to measure interdisciplinarity in One Health studies constructing dynamic pathogen transmission models. The number of publications fulfilling our search criteria increased by 14.6% per year, which is faster than growth rates for life sciences as a whole and for most biology subdisciplines. Surveyed publications clustered into three communities: one used by ecologists, one used by veterinarians, and a third diverse-authorship community used by population biologists, mathematicians, epidemiologists, and experts in human health. Overlap between these communities increased through time in terms of author number, diversity of co-author affiliations, and diversity of citations. However, communities continue to differ in the systems studied, questions asked, and methods employed. While the infectious disease research community has made significant progress toward integrating its participating disciplines, some segregation--especially along the veterinary/ecological research interface--remains.

When mechanism matters: Bayesian forecasting using models of ecological diffusion.

Ecological diffusion is a theory that can be used to understand and forecast spatio-temporal processes such as dispersal, invasion, and the spread of disease. Hierarchical Bayesian modelling provides a framework to make statistical inference and probabilistic forecasts, using mechanistic ecological models. To illustrate, we show how hierarchical Bayesian models of ecological diffusion can be implemented for large data sets that are distributed densely across space and time. The hierarchical Bayesian approach is used to understand and forecast the growth and geographic spread in the prevalence of chronic wasting disease in white-tailed deer (Odocoileus virginianus). We compare statistical inference and forecasts from our hierarchical Bayesian model to phenomenological regression-based methods that are commonly used to analyse spatial occurrence data. The mechanistic statistical model based on ecological diffusion led to important ecological insights, obviated a commonly ignored type of collinearity, and was the most accurate method for forecasting.

A Framework for Modeling Emerging Diseases to Inform Management.

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

The Implementation of a Preoperative Transthoracic Echocardiography Consult Service by Anesthesiologists.

We describe a preoperative transthoracic echocardiography consult service led by anesthesiologists. The implementation process and the patient cohort are described. Preoperative transthoracic echocardiographic examinations were mostly performed in patients undergoing intermediate- or high-risk noncardiac surgery and in patients with a higher calculated mortality risk. All transthoracic echocardiographic examinations were interpreted by anesthesiologists.

When can the cause of a population decline be determined?

Inferring the factors responsible for declines in abundance is a prerequisite to preventing the extinction of wild populations. Many of the policies and programmes intended to prevent extinctions operate on the assumption that the factors driving the decline of a population can be determined. Exogenous factors that cause declines in abundance can be statistically confounded with endogenous factors such as density dependence. To demonstrate the potential for confounding, we used an experiment where replicated populations were driven to extinction by gradually manipulating habitat quality. In many of the replicated populations, habitat quality and density dependence were confounded, which obscured causal inference. Our results show that confounding is likely to occur when the exogenous factors that are driving the decline change gradually over time. Our study has direct implications for wild populations, because many factors that could drive a population to extinction change gradually through time.

Prion Seeding Activity in Plant Tissues Detected by RT-QuIC.

Prion diseases such as scrapie, bovine spongiform encephalopathy (BSE), and chronic wasting disease (CWD) affect domesticated and wild herbivorous mammals. Animals afflicted with CWD, the transmissible spongiform encephalopathy of cervids (deer, elk, and moose), shed prions into the environment, where they may persist and remain infectious for years. These environmental prions may remain in soil, be transported in surface waters, or assimilated into plants. Environmental sampling is an emerging area of TSE research and can provide more information about prion fate and transport once shed by infected animals. In this study, we have developed the first published method for the extraction and detection of prions in plant tissue using the real-time quaking-induced conversion (RT-QuIC) assay. Incubation with a zwitterionic surfactant followed by precipitation with sodium phosphotungstate concentrates the prions within samples and allows for sensitive detection of prion seeding activity. Using this protocol, we demonstrate that prions can be detected within plant tissues and on plant surfaces using the RT-QuIC assay.

Validation of a real-time quaking-induced conversion (RT-QuIC) assay protocol to detect chronic wasting disease using rectal mucosa of naturally infected, pre-clinical white-tailed deer (Odocoileus virginianus).

Chronic wasting disease (CWD) is a fatal prion disease of cervids spreading across North America. More effective mitigation efforts may require expansion of the available toolkit to include new methods that provide earlier antemortem detection, higher throughput, and less expense than current immunohistochemistry (IHC) methods. The rectal mucosa near the rectoanal junction is a site of early accumulation of CWD prions and is safely sampled in living animals by pinch biopsy. A fluorescence-based, 96-well format, protein-aggregation assay-the real-time quaking-induced conversion (RT-QuIC) assay-is capable of ultra-sensitive detection of CWD prions. Notably, the recombinant protein substrate is crucial to the assay's performance and is now commercially available. In this blinded independent study, the preclinical diagnostic performance of a standardized RT-QuIC protocol using a commercially sourced substrate (MNPROtein) and a laboratory-produced substrate was studied using mock biopsy samples of the rectal mucosa from 284 white-tailed deer (Odocoileus virginianus). The samples were from a frozen archive of intact rectoanal junctions collected at depopulations of farmed herds positive for CWD in the United States. All deer were pre-clinical at the time of depopulation and infection status was established from the regulatory record, which evaluated the medial retropharyngeal lymph nodes (MRPLNs) and obex by CWD-IHC. A pre-analytic sample precipitation step was found to enhance the protocol's detection limit. Performance metrics were influenced by the choice of RT-QuIC diagnostic cut points (minimum number of positive wells and assay time) and by deer attributes (preclinical infection stage and prion protein genotype). The peak overall diagnostic sensitivities of the protocol were similar for both substrates (MNPROtein, 76.8%; laboratory-produced, 73.2%), though each was achieved at different cut points. Preclinical infection stage and prion protein genotype at codon 96 (G = glycine, S = serine) were primary predictors of sensitivity. The diagnostic sensitivities in late preclinical infections (CWD-IHC positive MPRLNs and obex) were similar, ranging from 96% in GG96 deer to 80% in xS96 deer (x = G or S). In early preclinical infections (CWD-IHC positive MRPLNs only), the diagnostic sensitivity was 64-71% in GG96 deer but only 25% in xS96 deer. These results demonstrate that this standardized RT-QuIC protocol for rectal biopsy samples using a commercial source of substrate produced stratified diagnostic sensitivities similar to or greater than those reported for CWD-IHC but in less than 30 hours of assay time and in a 96-well format. Notably, the RT-QuIC protocol used herein represents a standardization of protocols from several previous studies. Alignment of the sensitivities across these studies suggests the diagnostic performance of the assay is robust given quality reagents, optimized diagnostic criteria, and experienced staff.

Metagenomic sequencing sheds light on microbes putatively associated with pneumonia-related fatalities of white-tailed deer (Odocoileus virginianus).

With emerging infectious disease outbreaks in human, domestic and wild animal populations on the rise, improvements in pathogen characterization and surveillance are paramount for the protection of human and animal health, as well as the conservation of ecologically and economically important wildlife. Genomics offers a range of suitable tools to meet these goals, with metagenomic sequencing facilitating the characterization of whole microbial communities associated with emerging and endemic disease outbreaks. Here, we use metagenomic sequencing in a case-control study to identify microbes in lung tissue associated with newly observed pneumonia-related fatalities in 34 white-tailed deer (Odocoileus virginianus) in Wisconsin, USA. We identified 20 bacterial species that occurred in more than a single individual. Of these, only Clostridium novyi was found to substantially differ (in number of detections) between case and control sample groups; however, this difference was not statistically significant. We also detected several bacterial species associated with pneumonia and/or other diseases in ruminants (Mycoplasma ovipneumoniae, Trueperella pyogenes, Pasteurella multocida, Anaplasma phagocytophilum, Fusobacterium necrophorum); however, these species did not substantially differ between case and control sample groups. On average, we detected a larger number of bacterial species in case samples than controls, supporting the potential role of polymicrobial infections in this system. Importantly, we did not detect DNA of viruses or fungi, suggesting that they are not significantly associated with pneumonia in this system. Together, these results highlight the utility of metagenomic sequencing for identifying disease-associated microbes. This preliminary list of microbes will help inform future research on pneumonia-associated fatalities of white-tailed deer.

Chronic Wasting Disease: State of the Science.

Chronic wasting disease (CWD) is a prion disease affecting cervid species, both free-ranging and captive populations. As the geographic range continues to expand and disease prevalence continues to increase, CWD will have an impact on cervid populations, local economies, and ecosystem health. Mitigation of this "wicked" disease will require input from many different stakeholders including hunters, landowners, research biologists, wildlife managers, and others, working together. The NC1209 (North American interdisciplinary chronic wasting disease research consortium) is composed of scientists from different disciplines involved with investigating and managing CWD. Leveraging this broad breadth of expertise, the Consortium has created a state-of-the-science review of five key aspects of CWD, including current diagnostic capabilities for detecting prions, requirements for validating these diagnostics, the role of environmental transmission in CWD dynamics, and potential zoonotic risks associated with CWD. The goal of this review is to increase stakeholders', managers', and decision-makers' understanding of this disease informed by current scientific knowledge.

Resident Engagement With a Web- and App-based Journal Club Curriculum Utilizing Email and Text Notifications.

Background: High learner engagement is important for the success of asynchronous and online learning for graduate medical education. Medical trainees have recently reported using medical mobile apps. App-based interactions may provide more participation than email-based interactions. We sought to investigate (1) if there were higher levels of engagement with an online curriculum using notifications sent via email as compared with via text, and (2) if there were higher levels of engagement with the mobile app or website format. Methods: We implemented an online Journal Club curriculum with weekly topics for anesthesiology residents (postgraduate years 2-4) from July 2020 to June 2021. Weekly notifications were sent to residents via email for weeks 1-10, text for weeks 11-20, then email for weeks 21-49. Based on activity logs, we compared (1) the weekly numbers of interactions when email notifications were sent with the weekly numbers of interactions when text notifications were sent, and (2) the weekly numbers of interactions via the app with the weekly numbers of interactions via the website. Results: Thirty-eight of the 54 anesthesiology residents in our department at the time of the study (70.4%) interacted with the online Journal Club at least once throughout the study. The weekly numbers of interactions with email notifications (median [interquartile range (IQR)]: 13 [7-28]) were significantly higher than with text notifications (median [IQR]: 6 [4-8]) (P = .023). The weekly numbers of interactions via the website (median [IQR]: 9 [4-24]) were significantly higher than via the app (median [IQR]: 0 [0-1]) (P < .001). Conclusions: Although mobile technology may increase engagement and participation for some educational resources, learners may prefer accessing others through more conventional methods.

Bayesian forecasting of disease spread with little or no local data.

Rapid and targeted management actions are a prerequisite to efficiently mitigate disease outbreaks. Targeted actions, however, require accurate spatial information on disease occurrence and spread. Frequently, targeted management actions are guided by non-statistical approaches that define the affected area by a pre-determined distance surrounding a small number of disease detections. As an alternative, we present a long-recognized but underutilized Bayesian technique that uses limited local data and informative priors to make statistically valid predictions and forecasts about disease occurrence and spread. As a case study, we use limited local data that were available after the detection of chronic wasting disease in Michigan, U.S. along with information rich priors obtained from a previous study in a neighboring state. Using these limited local data and informative priors, we generate statistically valid predictions of disease occurrence and spread for the Michigan study area. This Bayesian technique is conceptually and computationally simple, relies on little to no local data, and is competitive with non-statistical distance-based metrics in all performance evaluations. Bayesian modeling has added benefits because it allows practitioners to generate immediate forecasts of future disease conditions and provides a principled framework to incorporate new data as they accumulate. We contend that the Bayesian technique offers broad-scale benefits and opportunities to make statistical inference across a diversity of data-deficient systems, not limited to disease.