Scholarly Works, Population Health Sciences

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Research articles, presentations, and other scholarship

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An analysis of behavioral characteristics and enrollment year variability in 47,444 dogs entering the Dog Aging Project from 2020 to 2023
Li, Yuhuan; Sexton, Courtney L.; DAP Consortium; Fitzpatrick, Annette; Ruple, Audrey (Public Library of Science, 2025-09-10)
Understanding dog behavior, especially in the context of the human social environment, is critical to maintaining positive human-dog interactions and relationships. Furthermore, behavior can be an important indicator of health and welfare in companion dogs. Behavioral change can signal transitions in life stages, alert caretakers to potential illnesses or injuries, and is an important factor in understanding and measuring stress. In order to take advantage of behavioral change as a biomarker, however, we must first have a behavioral baseline to assess. Thus, using owner-reported data from dogs enrolled in the Dog Aging Project (DAP) from 2020-2023, our aim was to establish baseline behavioral measures for 47,444 dogs, with the goal of using these measures in future research investigating behavioral change in dogs and short- and long-term health outcomes. Given that the data collection period spanned the 2019 coronavirus disease (COVID-19) lockdown period and its immediate aftermath, a secondary aim of this study was to evaluate whether year of project entry impacted average reported behavior scores in dogs and to investigate additional variables that may influence observed differences. In our analyses of cohort baseline and year-over-year changes among four composite behavior domains - Fear, Attention/Excitability, Aggression, and Trainability - we find that time (year of enrollment) had the highest influence on Trainability, wherein dogs enrolled in all three years after 2020 (2021-2023) had lower average reported scores than dogs enrolled in 2020. Several other variables, including breed, life stage, sex, spay/neuter status, size, primary residence, and primary activities, have positive and negative statistical associations with mean behavioral scores in all four domains.
Trends and disparities in motor vehicle collision injuries in Washington, D.C.
Calder, Ryan S. D.; Summa, Claire; Clark, Rachel (2025-09)
Nonfatal traffic injuries are ~40 times more frequent than traffic fatalities in the United States, but little is known about racial or ethnic disparities in injury-only collisions because commonly used databases report racial/ethnic data only for fatalities. Crash data from police departments (e.g., Vision Zero) are subject to error and bias arising from changing patterns of police intervention and increased use of alternative or automated traffic enforcement. Here, we leverage Trauma Registry data to quantify racial/ethnic, temporal, and spatial patterns of trauma injuries from motor vehicle collisions among adults in Washington, D.C. and compare results to the commonly used Vision Zero database. We report results by year (2019–2023), road user type (motorists, pedestrians, cyclists, and other vulnerable road users), and ZIP code tabulation area (ZCTA) to identify primary contributors to total injury rates and racial/ethnic disparities. Between 2019 and 2023, the overall incidence rate (IR) rose from 69 to 132 per 100,000 persons per year and increased among all road user types and races/ethnicities. Compared to white people, the incidence rate ratio (IRR) was ≥4.3 among Black/African American people and ≥2.9 among Hispanic/Latino people. The IRR between Black/African American vs. white motorists is ≥9.9. Disparities were observed across 21 of 26 ZCTAs, revealing that disparities cannot be explained by solely by higher minority populations in ZCTAs with more hazardous infrastructure. The commonly used Vision Zero dashboard suggests a downward trend in injury only crashes, but our analysis suggests that this trend is the result of a bias from reduced police intervention.
Comparison of Gait Characteristics for Horses Without Shoes, with Steel Shoes, and with Aluminum Shoes
Gottleib, Katherine; Trager-Burns, Lauren; Santonastaso, Amy; Bogers, Sophie; Werre, Stephen; Burns, Travis; Byron, Christopher (MDPI, 2025-08-13)
Differences in horseshoe materials may have effects on gait that could change perceived esthetic qualities. Objective information regarding effects of shoeing on gait characteristics of horses is scant. The aim of this study was to determine differences in gait characteristics for horses under various experimental shoeing conditions (barefoot, aluminum shoes, steel shoes) on two surfaces (asphalt and soft footing) using body- and hoof-mounted sensors. We hypothesized that shoeing would affect hoof arc height during early (arc height a) and late (arc height b) swing phases but would not affect other gait variables. Twelve healthy, adult, client-owned horses were evaluated at a trot on asphalt and soft footing under the three experimental shoeing conditions. No significant (p < 0.05) effects of shoeing were detected for gait symmetry (Q score), mediolateral hoof deviation, stride length, or midstance, breakover, swing, and landing stride phase times. Hoof arc height a was significantly (p < 0.001) lower for aluminum versus steel shoes for right and left forelimbs on asphalt and soft footing. Hoof arc height b was significantly higher for aluminum versus steel shoes on soft footing for left (p < 0.001) and right (p = 0.02) forelimbs. Findings indicate that shoe weights affect early and late swing phase hoof heights differently. Further investigation is warranted to determine whether measured hoof arc height changes affect subjective esthetics of gait.
Testing for heavy metals in drinking water collected from Dog Aging Project participants
Sexton, Courtney L.; O'Brien, Janice; Lytle, Justin; Rodgers, Sam; Keyser, Amber; Kauffman, Mandy; Dunbar, Matthew D.; Dog Aging Project Consortium; Edwards, Marc A.; Krometis, Leigh-Anne H.; Ruple, Audrey (PLOS, 2025-08-06)
Heavy metals are commonly found in groundwater and can affect the quality of drinking water. In this pilot study, we analyzed the quality of drinking water for dogs participating in the Dog Aging Project (DAP) who lived in homes not served by a municipal water supply. In order to capture both diverse and localized environmental factors that may affect drinking water, 200 owners of DAP dogs located in one of 10 selected states were invited to participate. We tested for the presence of 28 metals in dogs’ drinking water, including eight (8) heavy metals that have maximum contaminant levels (MCLs) designated by the Environmental Protection Agency (EPA) and five (5) heavy metals that have EPA health guidance levels. The eight metals with MCLs are known to cause chronic health issues in humans after long-term ingestion. Our aim in this pilot was to determine whether such elements could be detected by at-home sampling of dogs’ drinking water, and, using regression models, to examine associations between water source variables, metal values, and developed disease. We found detectable levels of all metals tested. There were 126 instances when an analyte (arsenic, lead, copper, sodium, strontium, nickel, or vanadium) was above the EPA MCL or health guidance level. We further identified potential association between the presence of titanium and chromium, and occurrence of a known health condition in dogs. This prompts further investigation with a larger, stratified sample analyzing dogs’ drinking water composition and long-term health and wellness outcomes in dogs living in diverse geographies. These results may impact veterinary care decisions and husbandry, and underscore the validity and importance of utilizing dogs as sentinels of human health outcomes in the context of drinking water contamination.
Biosecurity and Vaccines for Emerging Aquatic Animal RNA Viruses
Ahmadivand, Sohrab; Savage, Carla Phillips; Palic, Dušan (MDPI, 2025-05-28)
Emerging RNA viruses pose a critical threat to aquatic animals, leading to significant ecological and economic consequences. Their high mutation rates and genetic adaptability drive rapid evolution, cross-species transmission, and expanding host ranges, complicating disease management. In aquaculture, RNA viruses are responsible for major outbreaks in fish, while DNA viruses predominate in crustaceans. Marine mammals are increasingly affected by morbilliviruses and highly pathogenic avian influenza (HPAI) H5N1, which has caused widespread mortality events in pinniped and cetacean populations, raising concerns about zoonotic spillover. The absence of effective antiviral treatments and the complexity of vaccine development highlight the urgent need for enhanced biosecurity measures. Furthermore, novel vaccine approaches, such as self-assembling protein nanocage platforms, offer promising solutions for RNA virus mitigation. This review provides a comprehensive analysis of the emergence and significance of RNA viruses in aquatic animals over the last two decades, with a particular focus on biosecurity and vaccine development.
Guinea Pigs Are Not a Suitable Model to Study Neurological Impacts of Ancestral SARS-CoV-2 Intranasal Infection
Joyce, Jonathan D.; Moore, Greyson A.; Thompson, Christopher K.; Bertke, Andrea S. (MDPI, 2025-05-15)
Neurological symptoms involving the central nervous system (CNS) and peripheral nervous system (PNS) are common complications of acute COVID-19 as well as post-COVID conditions. Most research into these neurological sequalae focuses on the CNS, disregarding the PNS. Guinea pigs were previously shown to be useful models of disease during the SARS-CoV-1 epidemic. However, their suitability for studying SARS-CoV-2 has not been experimentally demonstrated. To assess the suitability of guinea pigs as models for SARS-CoV-2 infection and the impact of SARS-CoV-2 infection on the PNS, and to determine routes of CNS invasion through the PNS, we intranasally infected wild-type Dunkin-Hartley guinea pigs with ancestral SARS-CoV-2 USA-WA1/2020. We assessed PNS sensory neurons (trigeminal ganglia, dorsal root ganglia), autonomic neurons (superior cervical ganglia), brain regions (olfactory bulb, brainstem, cerebellum, cortex, hippocampus), lungs, and blood for viral RNA (RT-qPCR), protein (immunostaining), and infectious virus (plaque assay) at three- and six-days post infection. We show that guinea pigs, which have previously been used as a model of SARS-CoV-1 pulmonary disease, are not susceptible to intranasal infection with ancestral SARS-CoV-2, and are not useful models in assessing neurological impacts of infection with SARS-CoV-2 isolates from the early pandemic.
Unregulated drinking water contaminants and adverse birth outcomes in Virginia
Young, Holly A.; Kolivras, Korine N.; Krometis, Leigh-Anne H.; Marcillo, Cristina E.; Gohlke, Julia M. (PLOS, 2024-05-01)
Through the Unregulated Contaminant Monitoring Rule (UCMR), the Environmental Protection Agency monitors selected unregulated drinking water contaminants of potential concern. While contaminants listed in the UCMR are monitored, they do not have associated health-based standards, so no action is required following detection. Given evolving understanding of incidence and the lack of numeric standards, previous examinations of health implications of drinking water generally only assess impacts of regulated contaminants. Little research has examined associations between unregulated contaminants and fetal health. This study individually assesses whether drinking water contaminants monitored under UCMR 2 and, with a separate analysis, UCMR 3, which occurred during the monitoring years 2008–2010 and 2013–2015 respectively, are associated with fetal health outcomes, including low birth weight (LBW), term-low birth weight (tLBW), and preterm birth (PTB) in Virginia. Singleton births (n = 435,449) that occurred in Virginia during UCMR 2 and UCMR 3 were assigned to corresponding estimated water service areas (n = 435,449). Contaminant occurrence data were acquired from the National Contaminant Occurrence Database, with exposure defined at the estimated service area level to limit exposure misclassification. Logistic regression models for each birth outcome assessed potential associations with unregulated drinking water contaminants. Within UCMR 2, N-Nitrosodimethylamine was positively associated with PTB (OR = 1.08; 95% CI: 1.02, 1.14, P = 0.01). Molybdenum (OR = 0.92; 95% CI: 0.87, 0.97, P = 0.0) and vanadium (OR = 0.96; 95% CI: 0.92, 1.00, P = 0.04), monitored under UCMR 3, were negatively associated with LBW. Molybdenum was also negatively associated (OR = 0.90; 95% CI: 0.82, 0.99, P = 0.03) with tLBW, though chlorodifluoromethane (HCFC-22) was positively associated (OR 1.18; 95% CI: 1.01, 1.37, P = 0.03) with tLBW. These findings indicate that unregulated drinking water contaminants may pose risks to fetal health and demonstrate the potential to link existing health data with monitoring data when considering drinking water regulatory determinations at the national scale.
A framework for developing a real-time lake phytoplankton forecasting system to support water quality management in the face of global change
Carey, Cayelan C.; Calder, Ryan S. D.; Figueiredo, Renato J.; Gramacy, Robert B.; Lofton, Mary E.; Schreiber, Madeline E.; Thomas, R. Quinn (Springer, 2024-09-20)
Phytoplankton blooms create harmful toxins, scums, and taste and odor compounds and thus pose a major risk to drinking water safety. Climate and land use change are increasing the frequency and severity of blooms, motivating the development of new approaches for preemptive, rather than reactive, water management. While several real-time phytoplankton forecasts have been developed to date, none are both automated and quantify uncertainty in their predictions, which is critical for manager use. In response to this need, we outline a framework for developing the first automated, real-time lake phytoplankton forecasting system that quantifies uncertainty, thereby enabling managers to adapt operations and mitigate blooms. Implementation of this system calls for new, integrated ecosystem and statistical models; automated cyberinfrastructure; effective decision support tools; and training for forecasters and decision makers. We provide a research agenda for the creation of this system, as well as recommendations for developing real-time phytoplankton forecasts to support management.
Reviewing the recruitment and qualitative methods in deliberative valuation experiments
Jackson, Chloe; Mavrommati, Georgia; Howarth, Richard; Gazar, Amir; Calder, Ryan S. D. (2024-12-11)
Evaluation of a Participatory Action Planning Project to Address Opioid Misuse: Breaking Down Barriers Through Partnership Processes
Rafie, Carlin; Zimmerman, Emily; Reed, Dawn; Hargrove, Angelina (UTS ePress, 2024-12-19)
Community based participatory research and participatory action research are increasingly being used to engage communities in addressing social and health disparities. There is a need to develop broadly applicable evaluation methods that can be used across participatory project environments to identify the processes critical for addressing complex public health issues, as well as the productiveness of community research partnerships. We present a case study of a community participatory project conducted over three years and our evaluation approach. We used the Community Based Participatory Research Conceptual Model as the framework for the evaluation surveys (n=9) and interviews (n=7) with project participants, querying perspectives on the four model domains: community context, partnership processes, intervention and research and outcomes. In addition, we conducted a Ripple Effects Mapping (REM) exercise with ten community members to determine the broader impacts of the project on the community. This mixed-methods approach permitted us to confirm findings from quantitative surveys with qualitative findings from interviews and the REM. Key processes identified as facilitators to a productive partnership and positive outcomes include a context of trust, effective implementation of processes that establish equitable partner relationships and partnership synergy, a clearly defined focus for the partnership and a structured participatory research method that helped break down silos and mobilise the community for action. Our project evaluation approach, combining the CBPR model and REM, guided measurement of common metrics that are key to effective community engagement as well as exploration of unanticipated outcomes.
Analyzing multiple-source water usage patterns and affordability in rural central Appalachia
Dudzinski, Emerald; Ellis, Kimberly P.; Krometis, Leigh-Anne H.; Albi, Kate; Cohen, Alasdair (2024-07-18)
Nearly 500,000 American households lack complete plumbing, and more than 21 million Americans are reliant on public drinking water systems with at least one annual health-based drinking water violation. Rural, low-income, and minority communities are significantly more likely to be burdened with unavailable or unsafe in-home drinking water. Lack of access and distrust of the perceived quality of municipally supplied water are leading an increasing number of Americans to rely instead on less regulated, more expensive, and potentially environmentally detrimental water sources, such as roadside springs and bottled water. Previous research studies have stressed the importance of considering the economic burden of all water related expenditures including financial and non-financial water related costs; however, past examinations of water costs have primarily focused on municipal water supplies. We propose an economic model to consider the full economic burden associated with multiple-source water use by incorporating both direct costs (e.g., utility bills, well maintenance, bottled water purchase, payments for water hauling/delivery) and indirect water-related expenditures (e.g., transportation costs to gather water, productivity lost due to time spent collecting). Using data gathered from household surveys along with the economic model, this study estimates the economic burden from two case studies in rural Central Appalachia with persistent water quality concerns: (1) McDowell County, WV (n=15) and (2) Letcher and Harlan Counties, KY (n=9). All surveyed households (n=24) rely on multiple-source water to meet their needs, frequently citing their perception of unsafe in-home tap water. Bottled water was the most common choice for drinking water in both settings (92%, n=24), though roadside spring use was also prevalent in McDowell County, WV (53%, n=15). The results show that multiple-water source use is associated with a large economic burden. Households reliant primarily on bottled water as their drinking water source spent 12.3% (McDowell County, WV) and 5.6% (Letcher and Harlan Counties, KY) of their respective county’s median household income (MHI) on water related expenditures. Households reliant primarily on roadside springs as their drinking water source spent 11.8% (McDowell County, WV) of MHI on water related expenditures. Hence, the vast majority of participating households (92%, n=24) spend above the US water affordability threshold of 2% MHI. The application of this economic model highlights major water affordability concerns in water insecure Appalachian communities and provides a foundation for future studies and enhancements.
Identifying Barriers and Bridging Gaps Between Researchers and Decision Makers in Water Quality Modeling
Chowdhury, Mahabub; Carey, Cayelan C.; Figueiredo, Renato; Gramacy, Robert; Hoffman, Kathryn; Lofton, Mary; Patil, Parul; Schreiber, Madeline E.; Thomas, R. Quinn; Calder, Ryan S. D. (2024-12-12)
Modeling forest dynamics to characterize delivery of ecosystem services on military installations across the United States
Matthews, Emily; Abowd, Laurel; Borsuk, Mark E.; Krapu, Christopher; Mangin, Tracey; Mason, Sara; Olander, Lydia P.; Plantinga, Andrew; Warnell, Katie; Calder, Ryan S. D. (2024-12-13)
Causal inference to scope environmental impact assessment of renewable energy projects and test competing mental models of decarbonization
Gazar, Amir M.; Borsuk, Mark E.; Calder, Ryan S. D. (IOP Publishing, 2024-11-25)
Environmental impact assessment (EIA), life cycle analysis (LCA), and cost benefit analysis (CBA) embed crucial but subjective judgments over the extent of system boundaries and the range of impacts to consider as causally connected to an intervention, decision, or technology of interest. EIA is increasingly the site of legal, political, and social challenges to renewable energy projects proposed by utilities, developers, and governments, which, cumulatively, are slowing decarbonization. Environmental advocates in the United States have claimed that new electrical interties with Canada increase development of Canadian hydroelectric resources, leading to environmental and health impacts associated with new reservoirs. Assertions of such second-order impacts of two recently proposed 9.5 TWh yr−1 transborder transmission projects played a role in their cancellation. We recast these debates as conflicting mental models of decarbonization, in which values, beliefs, and interests lead different parties to hypothesize causal connections between interrelated processes (in this case, generation, transmission, and associated impacts). We demonstrate via Bayesian network modeling that development of Canadian hydroelectric resources is stimulated by price signals and domestic demand rather than increased export capacity per se. However, hydropower exports are increasingly arranged via long-term power purchase agreements that may promote new generation in a way that is not easily modeled with publicly available data. We demonstrate the utility of causal inference for structured analysis of sociotechnical systems featuring phenomena that are not easily modeled mechanistically. In the setting of decarbonization, such analysis can fill a gap in available energy systems models that focus on long-term optimum portfolios and do not generally represent questions of incremental causality of interest to stakeholders at the local level. More broadly, these tools can increase the evidentiary support required for consequentialist (as opposed to attributional) LCA and CBA, for example, in calculating indirect emissions of renewable energy projects.
Forecasting the impact of climate change on pathogen exposures from concentrated animal feeding operations
Chowdhury, Mahabub; Borsuk, Mark E.; Robinson, Celine S.; Krapu, Christopher; Calder, Ryan S. D. (2024-12-10)
Treatment of cattle with ivermectin and its effect on dung degradation and larval abundance in a tropical savanna setting
Ruhinda, Miriam; Xia, Kang; Rist, Cassidy; Shija, Gerald; Lyimo, Issa N.; Meza, Felician; Brewster, Carlyle; Chaccour, Carlos; Rabinovich, N. Regina; Schuerch, Roger (Elsevier, 2024-12-12)
When ingested as part of a blood meal, the antiparasitic drug ivermectin kills mosquitoes, making it a candidate for mass drug administration (MDA) in humans and livestock to reduce malaria transmission. When administered to livestock, most ivermectin is excreted unmetabolized in the dung within 5 days post administration. Presence of ivermectin, has been shown to adversely affect dung colonizers and dung degradation in temperate settings; however, those findings may not apply to, tropical environment, where ivermectin MDA against malaria would occur. Here we report results of a randomized field experiment conducted with dung from ivermectin-treated and control cattle to determine the effect of ivermectin on dung degradation in tropical Tanzania. For intact pats, we measured termite colonization, larval numbers and pat wet and dry weights. Pat organic matter was interpolated from a subsample of the pat (10 g wet weight). Additionally, we counted larvae growing in the treated and untreated pats in a semi-field setting. We found that termites colonized ivermectin pats more readily than controls. Despite this, wet weight decreased significantly slower in the ivermectin-treated pats in the first two weeks. As water was lost, sub-sample dry weight increased, and organic matter decreased similarly over time for the treatment and control. Interpolated for whole pats, total organic matter was higher, and larval counts were lower in the ivermectin-treated pats after the first month. Our results demonstrate an effect of ivermectin and its metabolites on dung degradation and fauna in a tropical savanna setting. Because slow dung degradation and low insect abundance negatively impact pastureland, these non-target, environmental effects must be further investigated within the context of real-world implementation of ivermectin MDA in cattle and weighed against the potential benefits for malaria control.
Resolving competing trends in vulnerability and coastal hazard frequency: implications for mortality forecasts
Calder, Ryan S. D.; Timilsina, Saurav; Gohlke, Julia M.; Swarup, Samarth; Zaitchik, Benjamin (2024-12-12)
Local land-use decisions drive losses in river biological integrity to 2099: Using machine learning to disentangle interacting drivers of ecological change in policy forecasts
Bourne, Kimberly; Calder, Ryan S. D.; Zuidema, Shantar; Chen, Celia; Borsuk, Mark (Wiley, 2025-01-07)
Climate and land‐use/land‐cover (LULC) change each threaten the health of rivers. Rising temperatures, changes in rainfall and runoff, and other perturbations, will all impact rivers' physical, biological, and chemical characteristics over the next century. While scientists and policymakers have increasing access to climate and LULC forecasts, the implications of each for outcomes of interest have been difficult to quantify. This is partially because climate and LULC perturb ecological outcomes via incompletely understood site‐specific, interacting, and nonlinear mechanisms that are not well suited to analysis using classical statistical methods. This creates uncertainties over the benefits of local‐level interventions such as green infrastructure investments and urban densification, and limits how forecasts can be used to inform decision‐making. Here, we demonstrate how machine learning can be used to quantify the relative contributions of LULC and climate drivers to impacts on riverine health as measured by taxonomic richness of the macroinvertebrate orders Ephemeroptera, Plecoptera, and Trichoptera (EPT). We develop a cross‐validated Random Forest (RF) model to link EPT taxa richness to meteorological, water quality, hydrologic, and LULC variables in watersheds in New Hampshire and Vermont, USA. Prospective climate and LULC scenarios are used to generate predictions of these variables and of EPT taxa richness trends through the year 2099. The model structure is mechanistically interpretable and performs well on test data (R2 ~ 0.4). Impacts on EPT taxa richness are driven by local LULC policy such as increased suburbanization. Future trends are likely to be exacerbated by climate change, although warming conditions suggest possible increases in springtime EPT taxa richness. Overall, this analysis highlights (1) the impact of local LULC decisions on riverine health in the context of a changing climate, and (2) the role machine learning methods can play in developing models that disentangle interacting physical mechanisms to advance decision support.
Theileria orientalis Ikeda infection does not negatively impact growth performance or breeding soundness exam results in young beef bulls at bull test stations
Guynn, Sierra R.; Greiner, Scott P.; Currin, John F.; Todd, S. Michelle; Assenga, Alphonce; Hungerford, Laura L.; Lahmers, Kevin K. (Frontiers, 2024-07-18)
Introduction: Theileria orientalis Ikeda genotype is an emerging cattle disease in the US. Since 2017, when T. orientalis Ikeda was discovered in beef cattle in two counties in Virginia, cattle infections have risen to include ~67% of Virginia counties and 14 states. Consistent with New Zealand studies, many infected herds in Virginia were >90% positive upon initial testing without overt evidence of infection. Central bull tests present a unique opportunity to study the effects of T. orientalis Ikeda infections, as bulls from multiple source herds are consolidated. The objective of this study was to determine if infection with T. orientalis Ikeda affected the average daily gain (ADG), adjusted yearling weight (AYW) and breeding soundness of bulls at two test stations in Virginia over a period of years. Materials and methods: The bulls were fed and housed similarly to compare their growth performance and breeding soundness. For T. orientalis Ikeda testing, DNA was extracted from whole blood for quantitative polymerase chain reaction. Results: The number of bulls infected with T. orientalis Ikeda at initial delivery to the stations increased significantly over the years studied. Multivariable linear regression models, using Angus bulls from Virginia test stations, indicated no significant effect on ADG or AYW in bulls that became test positive during the test or were positive for the duration, compared to Angus bulls that were negative for the duration. At LOC A, the odds of passing a breeding soundness exam (BSE) were not significantly different for bulls that turned positive during the test or were positive for the duration, compared to bulls that were negative for the duration of the test. At LOC B, bulls that became positive during the test were 2.4 times more likely (95% CI: 1.165–4.995, p = 0.016) to pass their BSE compared to bulls that remained negative throughout the test. Discussion: We do not suppose that an obscured infection of T. orientalis Ikeda is protective for bulls to pass a BSE. However, this study demonstrates an obscured infection of T. orientalis Ikeda does not negatively affect weight gain or achievement of a satisfactory BSE rating at the central bull test stations in Virginia.
Canadian hydroelectricity imports to the U.S.; Modeling of hourly carbon emissions reduction in New England
Mortazavigazar, Amir; Calder, Ryan S. D.; Howarth, Rich B.; Jackson, Chloe A.; Mavrommati, Georgia (2024-04-05)
United States’ hydroelectricity imports from Canada have increased by > 1 TWh per year between 2007 and 2021. This occurs as policymakers in the U.S. try to ramp up the deployment of new carbon free electricity generation and transmission infrastructure. Furthermore, recent modeling in the northeast U.S. demonstrates that Canadian hydroelectricity will play a significant role in New England’s least-cost decarbonization scenario. Additionally, decarbonization targets are well- defined in all states within the New England region, making it a priority. Consequently, it is anticipated that more hydroelectricity will flow from Canada into New England, resulting in the expansion of transborder electricity interconnections. To characterize the costs and benefits of such projects as compared to alternatives, a high-resolution simulation (i.e., hourly) of the electric grid is needed. In this study, we utilize the U.S. Environmental Protection Agency's dataset on hourly electricity generation and carbon emissions. Using pre-established decarbonization scenarios, we can calculate the precise reduction in greenhouse gas and air pollutant emissions for each scenario. Our preliminary results demonstrate that the scenario projection for 2026–2027 by New England ISO, which involves a combination of Canadian hydroelectric imports (2100 MW summer, 826 MW winter), new wind (308 MW summer and 682 MW), and solar (92 MW summer, 28 MW winter) generation commitments, can effectively offset carbon emissions in New England. These results further support the current decarbonization policy, which relies on a diversified mix of carbon free electricity sources.

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