Areas Of Ontario Research Articles

Using UAVs to collect filtered water samples for mineral exploration: Will it take off?

The advent of unmanned aerial vehicle (UAV) assisted surface water sampling and ongoing technological advances in sampling and data acquisition, offers many opportunities to conduct high-quality hydrogeochemical surveys with low cost, high efficiency, and reduced human interactions. Hydrogeochemical mineral exploration is one area that could greatly benefit from a UAV sampling revolution, with survey sites often located in highly remote areas with limited existing infrastructure. Currently, a lack of point source filtration and complicated physiochemical data acquisition hinder mainstream UAV deployment in the context of hydrogeochemical studies. The aim of this paper is to provide guidance on effective UAV sampling methods and physiochemical data collection for use in surface water hydrogeochemical mineral exploration. To date, case study surveys have utilized sampling systems where sampled waters are filtered after collection or analyzed for ‘total’ (unfiltered) concentrations. This paper details a methodology for point-source filtration of water samples using a UAV system to recover filter sample aliquots for the determination of ‘dissolved’ (<0.45 μm) trace element concentrations and compares UAV methods to conventional sampling strategies. This study systematically compares the quality of analytical data collected from lakes, ponds, and rivers in the Long Lake area of southern Ontario, using conventional manual sampling (from a boat or canoe) and a series of UAV-based sampling methodologies. The waters sampled within the study area are highly meteoric and show evidence of solute input from water-rock interaction with local country rocks. The results of this study show that in general, conventional sampling methodologies are statistically comparable to samples collected using UAVs. However, there is some evidence of element variation related to lake stratification, with dissolved Cu concentrations higher in samples collected at depth compared to those from the surface. Similarly, samples filtered after collection typically have lower concentrations of Fe and Mn, potentially resulting from precipitation before filtration. An enclosed sampling system offered from peristaltic pumping with in-line filtration removes the potential for contamination from the surrounding environment and from the UAV itself.

Microfacies Analysis and Depositional Model for the Black River -Trenton Carbonates (Ordovician) of Southern Ontario, Canada

This study documents the detailed microfacies depositional environment of the Ordovician Black River and Trenton limestone Groups in Lake Simcoe area of southern Ontario, resting unconformably on Precambrian basement. Local Precambrian 'highs' complicate the overall facies pattern and lithofacies patterns define local shoal, intershoal and basinal environments. Detailed microfacies and facies analysis in large quarries in the Lake Simcoe area are used to infer various carbonate environments by comparison with analogous modern and ancient ramps. Fifteen microfacies are grouped into six microfacies associations based on composition, grain size and texture. Relative energy levels, and depositional environments for these are then inferred. These environments resemble the Recent Arabian Shelf of the Persian Gulf for the Black River Group, and the Recent West Florida Shelf for the Trenton, though other Recent ramps like South Australia are also comparable. The vertical arrangement of facie\s in the Lake Simcoe area forms repetitive cycles, which can then be traced laterally into adjacent areas, complicated by the effects of sea-floor topography and possibly by synsedimentary faulting.

Exploring everyday racist symbolism in community recreation spaces: a critical race content analysis

ABSTRACT There has been a palpable shift in the public’s collective consciousness about the realities of racism in recent years. Community recreation organizations, like all other institutions, are not exempt from promoting racial inequity through taken for granted policies and practices. The purpose of this study was to explore some of the racist symbolism found within everyday artifacts at local community centres in a sub-urban area of Ontario, Canada. A Critical Race Content Analysis methodology was used to analyze bandages, promotional materials, and sunscreen. This study found that bandages in first aid supplies were exclusively for White skin tones, images in promotional materials featured mostly White people, and the sunscreen products stocked were not made for dark skinned folx. A discussion on the implications of each finding is provided followed by limitations and recommendations for research and practice.

Characterizing multifaceted environmental risks of oil and gas well leakage through soil and well methane and hydrogen sulfide emissions

Oil and gas wells (OGWs) can lead to soil and well emissions of methane (CH4), a potent greenhouse gas, and hydrogen sulfide (H2S), a highly toxic gas, both of which reduce air quality and can cause explosions when emitted into confined spaces. Developments have been occurring over OGWs, posing larger health and safety risks. However, to our knowledge, previous studies have not conjunctively analyzed well and soil emissions while considering development on or near OGWs. In this paper, we characterize 343 CH4 and H2S emission rate measurements from 67 non-producing (abandoned) and 35 producing (active) OGWs, including 205 measurements from soils surrounding 81 OGWs in Ontario and Quebec. We also provide the first emission rate estimates from an abandoned water and OGW-linked explosion and map OGWs in urban and built-up areas in Ontario and Quebec. We estimate the explosion-linked emissions to be 3,000 g CH4/hour and 7 g H2S/hour. Moreover, we find that 7,264 and 161 OGWs in Ontario and Quebec, respectively, are in urban and built-up areas, with 94% of these wells being abandoned. For the 102 wells we measured, we find OGW emission rate ranges of -16 to 47,000 mg CH4/hour and 0.001 to 3,300 mg H2S/hour, with 9% of the wells having positive detections of H2S. Although soil CH4 emissions at a 1-meter distance from the wells are most correlated with well emissions, the highest soil emission rate was observed at a 3-meter distance, indicating the potential for OGW-related emissions into buildings to occur away from the well. Overall, our multi-faceted measurement dataset provides a basis for conjunctive analysis of the broad range of environmental risks of OGWs to climate, indoor and outdoor air quality, and explosions.

Temporal Behavior of Glacially Induced Stresses and Strains at Potential Sites for Long‐Term Storage of Used Nuclear Fuel in Canada

AbstractContinental‐scale glaciations cause deformation, geopotential, rotation and stress changes of the Earth. Subsurface stress changes have implications to future activities such as carbon capture and storage, enhanced oil recovery and deep geological disposal of nuclear waste. We model glacially induced stresses, strain changes and deformation for North America, with emphasis on the two potential sites for long‐term storage of used nuclear fuel in Canada (Saugeen Ojibway Nation (SON)‐South Bruce area in southwestern Ontario and Wabigoon Lake Ojibway Nation (WLON)‐Ignace area in northwestern Ontario). We apply a revised, high‐resolution ice history of the past glacial cycle from the University of Toronto Glacial Systems Model, assumed to be representative for future glacial cycles, together with a set of seven different one‐ and three‐dimensional earth structures. We find that glacially induced stresses and strains can vary strongly throughout a glacial cycle, whereas especially the horizontal components can change from tensional to compressive in nature. Such changes can happen within a few 1,000 years, caused by drastic and rapid ice thickness increase or decrease above the potential site. Despite SON‐South Bruce being located further away from the ice sheet center than WLON‐Ignace and temporarily in the forebulge of the developing ice sheet during glaciation, stresses and strains are very similar in magnitude and range at both sites. We also see the potential that the glacially induced stresses can alter the direction of the pre‐existing maximum horizontal stress at SON‐South Bruce. These results will be incorporated in the site safety and site selection process.

A Multi-Year Study of Mycotoxin Co-Occurrence in Wheat and Corn Grown in Ontario, Canada.

Mycotoxin emergence and co-occurrence trends in Canadian grains are dynamic and evolving in response to changing weather patterns within each growing season. The mycotoxins deoxynivalenol and zearalenone are the dominant mycotoxins detected in grains grown in Eastern Canada. Two potential emerging mycotoxins of concern are sterigmatocystin, produced by Aspergillus versicolor, and diacetoxyscirpenol, a type A trichothecene produced by a number of Fusarium species. In response to a call from the 83rd Joint Expert Committee on Food Additives and Contaminants, we conducted a comprehensive survey of samples from cereal production areas in Ontario, Canada. Some 159 wheat and 160 corn samples were collected from farms over a three-year period. Samples were extracted and analyzed by LC-MS/MS for 33 mycotoxins and secondary metabolites. Ergosterol was analyzed as an estimate of the overall fungal biomass in the samples. In wheat, the ratio of DON to its glucoside, deoxynivalenol-3-glucoside (DON-3G), exhibited high variability, likely attributable to differences among cultivars. In corn, the ratio was more consistent across the samples. Sterigmatocystin was detected in some wheat that had higher concentrations of ergosterol. Diacetoxyscirpenol was not detected in either corn or wheat over the three years, demonstrating a low risk to Ontario grain. Overall, there was some change to the mycotoxin profiles over the three years for wheat and corn. Ongoing surveys are required to reassess trends and ensure the safety of the food value chain, especially for emerging mycotoxins.

An App for Navigating Patient Transportation and Acute Stroke Care in Northwestern Ontario Using Machine Learning: Retrospective Study.

A coordinated care system helps provide timely access to treatment for suspected acute stroke. In Northwestern Ontario (NWO), Canada, communities are widespread with several hospitals offering various diagnostic equipment and services. Thus, resources are limited, and health care providers must often transfer patients with stroke to different hospital locations to ensure the most appropriate care access within recommended time frames. However, health care providers frequently situated temporarily (locum) in NWO or providing care remotely from other areas of Ontario may lack sufficient information and experience in the region to access care for a patient with a time-sensitive condition. Suboptimal decision-making may lead to multiple transfers before definitive stroke care is obtained, resulting in poor outcomes and additional health care system costs. We aimed to develop a tool to inform and assist NWO health care providers in determining the best transfer options for patients with stroke to provide the most efficient care access. We aimed to develop an app using a comprehensive geomapping navigation and estimation system based on machine learning algorithms. This app uses key stroke-related timelines including the last time the patient was known to be well, patient location, treatment options, and imaging availability at different health care facilities. Using historical data (2008-2020), an accurate prediction model using machine learning methods was developed and incorporated into a mobile app. These data contained parameters regarding air (Ornge) and land medical transport (3 services), which were preprocessed and cleaned. For cases in which Ornge air services and land ambulance medical transport were both involved in a patient transport process, data were merged and time intervals of the transport journey were determined. The data were distributed for training (35%), testing (35%), and validation (30%) of the prediction model. In total, 70,623 records were collected in the data set from Ornge and land medical transport services to develop a prediction model. Various learning models were analyzed; all learning models perform better than the simple average of all points in predicting output variables. The decision tree model provided more accurate results than the other models. The decision tree model performed remarkably well, with the values from testing, validation, and the model within a close range. This model was used to develop the "NWO Navigate Stroke" system. The system provides accurate results and demonstrates that a mobile app can be a significant tool for health care providers navigating stroke care in NWO, potentially impacting patient care and outcomes. The NWO Navigate Stroke system uses a data-driven, reliable, accurate prediction model while considering all variations and is simultaneously linked to all required acute stroke management pathways and tools. It was tested using historical data, and the next step will to involve usability testing with end users.

On the prediction of rare events when sampling from large data

When modeling rare events using logistic regression, independent samples of event occurrence (ones) and nonoccurrence (zeros) are commonly taken from large datasets in order to fit models efficiently. A deterministic offset may then be included in the model to compensate for that sampling method. We propose a more complex sampling approach using stratified sampling within the sets of ones and zeros to ensure that we may sample more zeros from strata of interest. This design may avoid situations in which a random sample of zeros fails to capture the range of a key covariate. We employ sampling weights along with stratum-specific intercepts to obtain unbiased estimates of the logistic regression coefficients (including the intercept) and their standard errors. We use simulation to show that this method provides unbiased parameter estimates comparable with those of maximum likelihood. We also illustrate an application of this method to wildland fire occurrence prediction in a study area in northwestern Ontario, Canada.

Toxicology findings from drivers suspected of drug-impaired driving in Ontario (2008–2019)

Objective This study examines the results of toxicological tests performed on blood and urine samples collected from suspected drug-impaired drivers in Ontario from 2008 to 2019. The report examines the results of toxicological analysis of the samples submitted, the characteristics of those drivers from whom samples were collected, and the temporal and situational circumstances that led to police investigations and sample collection to better understand drug-impaired driving behavior and to assist in the development and implementation of countermeasure strategies and programs. Methods Blood and urine samples were sent to the Center of Forensic Sciences where they were analyzed using standardized comprehensive toxicological analysis to test for a wide variety of potentially impairing drugs. Demographic and temporal information for each case from which a sample was collected were also examined to describe the circumstances and characteristics of these driving incidents. Results During the 12-year period examined, 5,388 samples collected from suspected drug-impaired drivers were analyzed. The number of samples collected increased substantially following the implementation of the Drug Evaluation and Classification Program (DECP) in July 2008, the enactment of legislation facilitating the collection of blood samples from suspects, and the legalization of cannabis for nonmedical purposes in 2018. The number of samples submitted shows temporal correlation with the number of police officers certified as Drug Recognition Experts (DRE) in the province. Over the 12-year period of this study, cannabis was the most frequently detected substance in drivers (52.8% of cases), followed by cocaine (44.3%) and methamphetamine (24.8%). In 80% of cases, more than one substance was detected. Conclusions Examining the characteristics of suspected drug-impaired drivers, the temporal circumstances, and the drug findings throughout the large geographic area of Ontario and over the extended period of this study enhances our understanding of drug-impaired driving behavior. These characteristics can assist in the development and/or evaluation of enforcement strategies and enhanced countermeasure activities.

Sociodemographic factors associated with vaccine hesitancy in the South Asian community in Canada.

South Asians represent the largest non-white ethnic group in Canada and were disproportionately impacted by the COVID-19 pandemic. We sought to determine the factors associated with vaccine hesitancy in South Asian Canadians. We conducted a cross-sectional analysis of vaccine hesitancy using data collected at the baseline assessment of a prospective cohort study, COVID CommUNITY South Asian. Participants (18 + years) were recruited from the Greater Toronto and Hamilton Area in Ontario (ON) and the Greater Vancouver Area in British Columbia (BC) between April and November 2021. Demographic characteristics and vaccine attitudes measured by the Vaccine Attitudes Examination (VAX) scale were collected. Each item is scored on a 6-point Likert scale, and higher scores reflect greater hesitancy. A multivariable linear mixed effects model was used to identify sociodemographic factors associated with vaccine hesitancy, adjusting for multiple covariates. A total of 1496 self-identified South Asians (52% female) were analyzed (mean age = 38.5years; standard deviation (SD): 15.3). The mean VAX score was 3.2, SD: 0.8 [range: 1.0‒6.0]. Factors associated with vaccine hesitancy included: time since immigration (p = 0.04), previous COVID-19 infection (p < 0.001), marital status (p < 0.001), living in a multigenerational household (p = 0.03), age (p = 0.02), education (p < 0.001), and employment status (p = 0.001). Among South Asians living in ON and BC, time since immigration, prior COVID-19 infection, marital status, living in a multigenerational household, age, education, and employment status were associated with vaccine hesitancy. This information can be used to address vaccine hesitancy in the South Asian population in future COVID-19 waves or pandemics.

Wolverine density, survival, and population trends in the Canadian boreal forest

AbstractThere is limited information available on wolverine (Gulo gulo) population density and trends in the boreal forest of North America. We estimated wolverine density using spatial capture‐recapture methods across 2 boreal forest study areas in Red Lake, Ontario (26,568 km2) and Rainbow Lake, Alberta (19,084 km2), Canada. We also used radio‐telemetry data to estimate annual survival of adult and sub‐adult wolverines and evaluated population trends with a stage‐based matrix model. We used an array of run poles and live traps to detect wolverines. In Red Lake over 3 winter field seasons (2019–2022), we detected 56 individual wolverines (17 females, 32 males, and 7 unknown sex), and in Rainbow Lake over 2 field seasons (2014–2016), we detected 48 individuals (19 females, 18 males, and 11 of unknown sex). Average densities in Red Lake and Rainbow Lake were 3.64 and 6.74 wolverines/1,000 km2, respectively. Adults and sub‐adults occurred at equal abundance. Spring snow cover, roads, and industrial developments were not associated with spatial patterns of wolverine density. Most deaths occurred near roads; wolverines were killed in fur traps set along roads, by wolves using roads to travel, and by vehicles. The largest source of death was from incidental (n = 6 in Red Lake) or licensed fur trapping (n = 8 in Rainbow Lake) and we report 8 injuries from fur trapping sets. Red Lake survival estimates for adults (0.87) and sub‐adults (0.86) contributed to a stable population trend. Rainbow Lake survival estimates for adults (0.66) and sub‐adults (0.50) contributed to a declining population trend based on a relatively low sample of radio‐days. Red Lake and Rainbow Lake combined survival estimates for adults (0.77) and sub‐adults (0.73) also contributed to a declining population trend. Our survival and population modeling suggests that human‐caused mortality is a significant risk to these populations. Our results can be applied to wolverine status assessments and used as benchmarks for future monitoring. Wolverine population stability or growth might be achieved by reducing incidental trapping deaths or injury and hindering human access to wolverine habitats through decommissioning or limiting development of industrial roads or other anthropogenic linear features.

CO2 fluxes of vegetation in the Greenbelt of Ontario and increased net ecosystem emissions associated with its removal

The fluxes of carbon dioxide (CO2) to and from vegetation can be significant on a regional scale. It is therefore important to understand the biogenic fluxes of CO2 in order to quantify local carbon budgets. The Greenbelt of Ontario is a protected region of cropland and natural vegetation surrounding the Greater Toronto and Hamilton Area (GTHA) in Ontario, Canada. Recently, changes were proposed to the Greenbelt, including the removal of 2,995 ha (7,400 acres) of protected land to be replaced with housing. In this study, we estimate the biogenic CO2 fluxes of the entire Greenbelt as well as the areas that were proposed for removal by using a modified version of the Solar-induced fluorescence for Modeling Urban biogenic Fluxes vegetation model. We find that, on average, the entire Greenbelt has a net sequestration of 9.9 ± 6.4 TgCO2 each year, where the uncertainty represents half of the interannual variability plus error from the individual years, for the years 2018–2020. The net amount of CO2 absorbed by the Greenbelt is roughly equivalent to a fifth of the annual human-made emissions reported for the entire GTHA. The areas proposed for removal are found to have a net sequestration of 0.0061–0.031 TgCO2 annually. During construction, these lands will remain barren, and the soil will continue to emit CO2, thus changing the area from a net sink to a net source of CO2. For a 3- to 5-year construction period, this soil efflux would result in net ecosystem emissions of 0.314 ± 0.078 TgCO2, in addition to the net sequestration lost by removing the original vegetation (−0.077 ± 0.035 TgCO2). This results in a net difference in biogenic CO2 fluxes of 0.390 ± 0.083 TgCO2, which is equivalent to the average CO2 emissions of roughly 85,000 gasoline passenger vehicles over the course of a year. In addition to biogenic fluxes, there will be CO2 emissions associated with the construction of the proposed single-family housing developments as well as larger per capita emissions associated with low-density housing compared to creating higher density housing using less land.

Design and implementation of the Our Health Counts (OHC) methodology for First Nations, Inuit, and Metis (FNIM) health assessment and response in urban and related homelands.

Methods for enumeration and population-based health assessment for First Nations, Inuit, and Metis (FNIM) living in Canadian cities are underdeveloped, with resultant gaps in essential demographic, health, and health service access information. Our Health Counts (OHC) was designed to engage FNIM peoples in urban centres in "by community, for community" population health assessment and response. The OHC methodology was designed to advance Indigenous self-determination and FNIM data sovereignty in urban contexts through deliberate application of Indigenous principles and linked implementation strategies. Three interwoven principles (good relationships are foundational; research as gift exchange; and research as a vehicle for Indigenous community resurgence) provide the framework for linked implementation strategies which include actively building and maintaining relationships; meaningful Indigenous community guidance, leadership, and participation in all aspects of the project; transparent and equitable sharing of project resources and benefits; and technical innovations, including respondent-driven sampling, customized comprehensive health assessment surveys, and linkage to ICES data holdings to generate measures of health service use. OHC has succeeded across six urban areas in Ontario to advance Indigenous data sovereignty and health assessment capacity; recruit and engage large population-representative cohorts of FNIM living in urban and related homelands; customize comprehensive health surveys and data linkages; generate previously unavailable population-based FNIM demographic, health, and social information; and translate results into enhanced policy, programming, and practice. The OHC methodology has been demonstrated as effective, culturally relevant, and scalable across diverse Ontario cities.

Reducing falls among residents of retirement homes: A DNP project.

Falls among older adults (OAs) living in retirement homes (RHs) in Canada are a major public health concern due to high morbidity and mortality as well as significant healthcare expenditures. This quality improvement (QI) initiative, conducted for the author's Doctor of Nursing Practice (DNP) project, aimed to decrease fall rates and ED transfers related to falls among OAs in six RHs across the Greater Toronto Area in Ontario, Canada through a multipart intervention with two primary goals. First, the project aimed to facilitate RH NPs' implementation of a comprehensive fall risk assessment and fall prevention strategy in their practice by incorporating the Stopping Elderly Accidents, Deaths & Injuries (STEADI) toolkit into their armamentarium. Second, it sought to enhance the knowledge of the RHs' registered practical nurses (RPNs), personal support workers (PSWs), and unregulated care providers (UCPs) in assessing fall risk and incorporating fall prevention strategies in their daily practice. By improving NP, RPN, PSW, and UCP knowledge and increasing (by 20%) RPN, PSW, and UCP use of fall prevention strategies, this QI initiative successfully reduced fall rates in the RHs by 40.4%, with no falls requiring transfer to the ED, in the postintervention period. The results of this project highlight the need for an interdisciplinary approach to fall risk reduction in RHs that includes implementation of multifactorial intervention strategies as well as effective organizational policies and procedures for maximum impact.

The mental health needs of autistic youth in remote areas of Ontario, Canada: Clinicians’ perspectives.

The mental health needs of autistic youth in remote areas of Ontario, Canada: Clinicians’ perspectives.

Sample Size Optimization for Digital Soil Mapping: An Empirical Example

In the evolving field of digital soil mapping (DSM), the determination of sample size remains a pivotal challenge, particularly for large-scale regional projects. We introduced the Jensen-Shannon Divergence (DJS), a novel tool recently applied to DSM, to determine optimal sample sizes for a 2790 km2 area in Ontario, Canada. Utilizing 1791 observations, we generated maps for cation exchange capacity (CEC), clay content, pH, and soil organic carbon (SOC). We then assessed sample sets ranging from 50 to 4000 through conditioned Latin hypercube sampling (cLHS), feature space coverage sampling (FSCS), and simple random sampling (SRS) to calibrate random forest models, analyzing performance via concordance correlation coefficient and root mean square error. Findings reveal DJS as a robust estimator for optimal sample sizes—865 for cLHS, 874 for FSCS, and 869 for SRS, with property-specific optimal sizes indicating the potential for enhanced DSM accuracy. This methodology facilitates a strategic approach to sample size determination, significantly improving the precision of large-scale soil mapping. Conclusively, our research validates the utility of DJS in DSM, offering a scalable solution. This advancement holds considerable promise for improving soil management and sustainability practices, underpinning the critical role of precise soil data in agricultural productivity and environmental conservation.

Humans drive spatial variation in mortality risk for a threatened wolf population in a Canis hybrid zone

Abstract Large carnivores often exhibit high survival rates in protected areas, whereas intentional and unintentional human‐caused mortality may be greater in adjacent areas. These patterns can result in source‐sink dynamics and limit population expansion beyond protected areas. We used telemetry data from 438 canids in 141 packs collected from 2002 to 2020 to evaluate mortality risk for wolves, coyotes, and admixed canids in a 3‐species hybrid zone in and adjacent to a large protected area in Ontario, Canada. The hybrid zone is occupied by most of the remaining eastern wolves (Canis lycaon), a rare, threatened species that hybridizes with sympatric eastern coyotes (C. latrans) and Great Lakes grey wolves (C. lupus). Within Algonquin Provincial Park (APP), annual human‐caused mortality from harvest and vehicles was low (0.06, 95% CI [0.03, 0.08]), whereas annual human‐caused mortality was higher in adjacent areas (0.31, 95% CI [0.25, 0.37]). Smaller protected areas implemented to help protect eastern wolves did not significantly reduce mortality. Eastern wolves survived poorly relative to other canids and dispersing canids survived poorly relative to residents. Mortality risk was greater when canids were closer to roads. Mortality risk was also increased or reduced by the strength of individual‐level selection or avoidance of roads relative to their availability, respectively. Our results provide a comprehensive evaluation of factors influencing spatial variation in mortality risk for canids to inform eastern wolf recovery efforts. Additionally, we developed a novel modelling approach for investigating the influence of resource selection on mortality risk, which highlighted that individual‐level responses to risk can strongly influence population‐level mortality patterns. Synthesis and applications. Despite being listed as ‘threatened’ under the Ontario Endangered Species Act, eastern wolves are still legally trapped and shot outside protected areas in central Ontario. Eastern wolves and dispersing canids survive poorly outside of APP, primarily from human‐caused mortality. These results, along with the apparent inadequacy of the smaller protected areas, suggest that expanding the threatened eastern wolf population outside APP is unlikely under current management conditions. Protecting eastern wolves from human‐caused mortality is complicated as it would require a harvest ban for all canids, including coyotes.

Disproportionate Rates of COVID-19 Among Black Canadian Communities: Lessons from a Cross-Sectional Study in the First Year of the Pandemic.

Racialized communities, including Black Canadians, have disproportionately higher COVID-19 cases. We examined the extent to which SARS-CoV-2 infection has affected the Black Canadian community and the factors associated with the infection. We conducted a cross-sectional survey in an area of Ontario (northwest Toronto/Peel Region) with a high proportion of Black residents along with 2 areas that have lower proportions of Black residents (Oakville and London, Ontario). SARS-CoV-2 IgG antibodies were determined using the EUROIMMUN assay. The study was conducted between August 15, 2020, and December 15, 2020. Among 387 evaluable subjects, the majority, 273 (70.5%), were enrolled from northwest Toronto and adjoining suburban areas of Peel, Ontario. The seropositivity values for Oakville and London were comparable (3.3% (2/60; 95% CI 0.4-11.5) and 3.9% (2/51; 95% CI 0.5-13.5), respectively). Relative to these areas, the seropositivity was higher for the northwest Toronto/Peel area at 12.1% (33/273), relative risk (RR) 3.35 (1.22-9.25). Persons 19 years of age or less had the highest seropositivity (10/50; 20.0%, 95% CI 10.3-33.7%), RR 2.27 (1.23-3.59). There was a trend for an interaction effect between race and location of residence as this relates to the relative risk of seropositivity. During the early phases of the pandemic, the seropositivity within a COVID-19 high-prevalence zone was threefold greater than lower prevalence areas of Ontario. Black individuals were among those with the highest seroprevalence of SARS-CoV-2.

Development and Validation of a Treatment Algorithm for Osteoarthritis Pain Management in Patients With End-Stage Kidney Disease Undergoing Hemodialysis.

Although osteoarthritis is common in the hemodialysis population and leads to poor health outcomes, pain management is challenged by the absence of clinical guidance. A treatment algorithm was developed and validated to aid hemodialysis clinicians in managing osteoarthritis pain. The objective was to develop and validate a treatment algorithm for managing osteoarthritis pain in patients undergoing hemodialysis. A validation study was conducted based on Lynn's method for content validation. To develop and validate a treatment algorithm, interviews were conducted virtually by the primary researcher with clinicians from various institutions across the Greater Toronto and Hamilton Area in Ontario. The treatment algorithm was developed and validated for the management of osteoarthritis pain in patients on hemodialysis. Patients were not involved in the development or validation of the tool. The algorithm was measured for content and face validity. Content validity was measured by calculating the content validity index of each component (I-CVI) of the algorithm and the overall scale validity index (S-CVI). Face validity was assessed by calculating the percentage of positive responses to the face validity statements. A draft algorithm was developed based on literature searches and expert opinion and validated by interviewing nephrology and pain management clinicians. Through consecutive rounds of 1:1 interviews, content and face validity were assessed by asking participants to rate the relevance of each component of the algorithm and indicate their level of agreeability with a series of statements. Following each round, the I-CVI of the algorithm as well as the S-CVI was calculated and the percentage of positive responses to the statements was determined. The research team revised the algorithm in response to the findings. The final algorithm provides a stepwise approach to the non-pharmacologic and pharmacologic management of pain, including topical, oral, and opioid use. A total of 18 clinicians from 7 institutions across the Greater Toronto and Hamilton Area were interviewed (10 pharmacists, 5 nurse practitioners, and 3 physicians). The average S-CVI of the algorithm across all 3 rounds was 0.93. At least 78% of participants provided positive responses to the face validity statements. An algorithm was developed based on input from clinicians working in the province of Ontario, limiting the generalizability of the algorithm across provinces. In addition, the algorithm did not include the perspectives of primary care providers or patients/caregivers. An algorithm for the management of osteoarthritis pain in the hemodialysis population was developed and validated through expert review to standardize practices and encourage clinicians to use evidence-based treatments and address the psychosocial symptoms of pain. As the algorithm possesses a high degree of content and face validity, it may improve osteoarthritis pain management among patients undergoing hemodialysis. Future research will assess the implementation of the algorithm across hemodialysis settings.

Seed protein biotyping in Amaranthus species: a tool for rapid identification of weedy amaranths of concern

BackgroundThe Amaranthus genus contains at least 20 weedy and invasive species, including Amaranthus palmeri (palmer’s amaranth) and Amaranthus tuberculatus (tall waterhemp), two species of regulatory concern in North America, impacting production and yield in crops like corn, soybean and cotton. Amaranthus tuberculatus is regulated in Canada with limited establishment, while current climate models predict a range expansion of A. palmeri impacting crop growing areas in Ontario, Quebec and Manitoba. Since many Amaranthus species are similar in their morphology, especially at the seed stage, this demands the development of additional methods that can efficiently aid in the detection and identification of these species. Protein biotyping using Matrix-Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF-MS) has been traditionally used to identify microorganism species, races and pathotypes. Major protein fractions extracted from an organism, ionized and run through a biotyper using mass spectrometry, result in protein spectra that represent a fingerprint at the species or lower taxonomic rank, providing an efficient molecular diagnostics method. Here we use a modified protein biotyping protocol to extract major protein fractions from seeds of the family Brassicaceae to test our protocol, and then implemented the standardized approach in seeds from Amaranthus species. We then created a database of Amaranthus protein spectra that can be used to test blind samples for a quick identification of species of concern.ResultsWe generated a protein spectra database with 16 Amaranthus species and several accessions per species, spanning target species of regulatory concern and species which are phylogenetically related or easily confused at the seed stage due to phenotypic plasticity. Testing of two Amaranthus blind sample seed sets against this database showed accuracies of 100% and 87%, respectively.ConclusionsOur method is highly efficient in identifying Amaranthus species of regulatory concern. The mismatches between our protein biotyping approach and phenotypic identification of seeds are due to absence of the species in the database or close phylogenetic relationship between the species. While A. palmeri cannot be distinguished from A. watsonii, there is evidence these two species have the same native range and are closely related.