The seroprevalence and risk factors for exposure to Neospora caninum and Neospora hughesi in Ontario broodmares.

The seroprevalence and risk factors for exposure to Neospora caninum and Neospora hughesi in broodmares in Ontario were investigated. Sixty of the 219 (27.4%) study broodmares were seropositive for N. caninum and 65/219 (29.7%) for N. hughesi with cut-offs of ≥1:40 and ≥1:160, respectively. Thirty-one of 63 participating farms (49.2%) had at least 1 broodmare seropositive for N. caninum. Thirty-three of the 63 (52.4%) participating farms had at least 1 broodmare positive for N. hughesi. Risk factors for N. caninum included presence of farm dogs (OR = 6.70; 95% CI = 2.14-20.97; p = 0.001), and high stocking density (OR = 2.83; 95% CI = 1.27-6.30; p = 0.011). Presence of livestock, excluding cattle, was associated with reduced risk of exposure (OR = 0.17; 95% CI = 0.06-0.53; p = 0.002). The only risk factor for exposure to N. hughesi was feeding hay on the ground in the paddock (OR = 4.31; 95% CI = 1.65-11.22; p = 0.003). This study demonstrated widespread exposure to Neospora spp. in broodmares in Ontario.

Environmental and sociodemographic factors associated with zoonotic pathogen occurrence in Norway rats (Rattus norvegicus) from Windsor, Ontario.

AIMS: Rat-associated zoonotic pathogen transmission at the human-wildlife interface is a public health concern in urban environments where Norway rats (Rattus norvegicus) thrive on abundant anthropogenic resources and live in close contact with humans and other animal species. To identify potential factors influencing zoonotic pathogen occurrence in rats, we investigated associations between environmental and sociodemographic factors and Leptospira interrogans and Bartonella spp. infections in rats from Windsor, Ontario, Canada, while controlling for the potential confounding effects of animal characteristics (i.e., sexual maturity and body condition). METHODS AND RESULTS: Between November 2018 and June 2021, 252 rats were submitted by collaborating pest control professionals. Kidney and spleen samples were collected for L. interrogans and Bartonella spp. PCR and sequencing, respectively. Of the rats tested by PCR, 12.7% (32/252) were positive for L. interrogans and 16.3% (37/227) were positive for Bartonella species. Associations between infection status and environmental and sociodemographic variables of interest were assessed via mixed multivariable logistic regression models with a random intercept for social group and fixed effects to control for sexual maturity and body condition in each model. The odds of L. interrogans infection were significantly higher in rats from areas with high building density (odds ratio [OR]: 3.76; 95% CI: 1.31-10.79; p = 0.014), high human population density (OR: 3.31; 95% CI: 1.20-9.11; p = 0.021), high proportion of buildings built in 1960 or before (OR: 11.21; 95% CI: 2.06-60.89; p = 0.005), and a moderate number of reports of uncollected garbage compared to a low number of reports (OR: 4.88; 95% CI: 1.01-23.63; p = 0.049). A negative association was observed between median household income and Bartonella spp. infection in rats (OR: 0.26; 95% CI: 0.08-0.89; p = 0.031). CONCLUSIONS: Due to the complexity of the ecology of rat-associated zoonoses, consideration of environmental and sociodemographic factors is of critical importance to better understand the nuances of host-pathogen systems and inform how urban rat surveillance and intervention efforts should be distributed within cities.

Rat Hepatitis E Virus in Norway Rats, Ontario, Canada, 2018-2021.

We tested liver samples from 372 Norway rats (Rattus norvegicus) from southern Ontario, Canada, during 2018-2021 to investigate presence of hepatitis E virus infection. Overall, 21 (5.6%) rats tested positive for the virus. Sequence analysis demonstrated all infections to be rat hepatitis E virus (Rocahepevirus ratti genotype C1).

Investigating the association between socioeconomic and agricultural risk factors and the incidence of Salmonella Heidelberg and Salmonella Typhimurium in Ontario in 2015: A multi-level ecological approach.

The incidence of salmonellosis, and other enteric zoonotic diseases, has been associated with various food and environmental exposures and socioeconomic factors. Increasingly, there is interest in exploring differences among serotypes of Salmonella to better inform public health prevention efforts. Consequently, we investigated whether rates of Salmonella Heidelberg and Typhimurium in Ontario communities in 2015 were influenced by household characteristics, agricultural factors, and the presence of meat plants. Data for each reported case of S. Heidelberg and S. Typhimurium in Ontario in 2015 were collected. Expected cases of each serotype were calculated, stratified by age group and sex, according to the underlying population distribution from the Canadian census. Socioeconomic, agricultural census data, and data concerning provincial and federally inspected meat plants were combined with observed and expected case counts. The association between community-level agricultural, meat processing, and socioeconomic variables, serotype, and the rate of salmonellosis in each census subdivision (CSD) was explored using multilevel Poisson models, with random intercepts for CSD and census division (CD). Rates of S. Heidelberg and S. Typhimurium were associated with the proportion of married individuals in a CSD, and were higher in CSDs with the highest quantile of labour participation compared to those in the lowest quantile. There was an interaction effect between cattle, poultry and swine farm density in a CD and serotype, with rates of either serotype decreasing as cattle, poultry, or swine farm density in the encompassing CD increased. The rate of the decrease varied by serotype. Our findings concerning community-level household characteristics may be explained by the influence of family structure and occupation on food consumption patterns and environmental exposures. Rates of S. Heidelberg and S. Typhimurium may be lower in areas with increased animal farm density due to naturally acquired immunity from routine exposure to Salmonella via livestock.

A qualitative study of university students' perspectives of hope during the COVID-19 pandemic.

Background: Students in higher education commonly experience mental health problems. There is an ongoing need to explore potential intervention targets to focus on mental health promotion among students. Hopefulness may alleviate or be protective against various negative mental health conditions such as depression, anxiety, suicide, and trauma-related disorders. Objective: To explore postsecondary students' meanings and experiences of hope during the COVID-19 pandemic and identify factors affecting hopefulness during crises. Methods: Purposive sampling was used to recruit participants for online semi-structured interviews in a university located in Southwestern Ontario, Canada. Data were analyzed using thematic analysis. Results: In total, 12 participants were interviewed, and 4 themes were generated: (1) hope is a complex concept with an associated set of behaviors, (2) cognitive framing of hope as a means of student resilience, (3) COVID-19 as an antagonist which amplifies preexisting student concerns and issues, and (4) the social and physical environments serve as barriers and enablers to hope and well-being. Hope was perceived as a positive mental trait, external events and the environment were reported to impact hope, and those who were generally more hopeful adjusted better mentally when unexpected circumstances arose. Conclusions: Findings shed light on the interconnectedness and complex nature of hope, its sources, and enablers. Novel findings include the ways in which hope was affected during the COVID-19 pandemic. Recommendations for individual- and community-based interventions include targeting enablers to hopefulness by promoting social support systems, offering virtual extracurricular activities, and delivering alternative approaches to teaching and learning.

Comparing the diagnostic performance of ordinary, mixed, and lasso logistic regression models at identifying opioid and cannabinoid poisoning in U.S. dogs using pet demographic and clinical data reported to an animal poison control center (2005-2014).

Researchers have begun studying the impact of human opioid and cannabinoid use on dog populations. These studies have used data from an animal poison control center (APCC) and there are concerns that due to the illicit nature and social stigma concerning the use of these drugs, owners may not always be forthcoming with veterinarians or APCC staff regarding pet exposures to these toxicants. As a result, models derived from APCC data that examine the predictability of opioid and cannabinoid dog poisonings using pet demographic and health disorder information may help veterinarians or APCC staff more reliably identify these toxicants when examining or responding to a call concerning a dog poisoned by an unknown toxicant. The fitting of epidemiologically informed statistical models has been useful for identifying factors associated with various health conditions and as predictive tools. However, machine learning, including lasso regression, has many useful features as predictive tools, including the ability to incorporate large numbers of independent variables. Consequently, the objectives of our study were: 1) identify pet demographic and health disorders associated with opioid and cannabinoid dog poisonings using ordinary and mixed logistic regression models; and 2) compare the predictive performance of these models to analogous lasso logistic regression models. Data were obtained from reports of dog poisoning events collected by the American Society for the Prevention of Cruelty to Animals' (ASPCA) Animal Poisoning Control Center, from 2005-2014. We used ordinary and mixed logistic regression models as well as lasso logistic regression models with and without controlling for autocorrelation at the state level to train our models on half the dataset and test their predictive performance on the remainder. Although epidemiologically informed logistic regression models may require substantial knowledge of the disease systems being investigated, they had the same predictive abilities as lasso logistic regression models. All models had relatively high predictive parameters except for positive predictive values, due to the rare nature of calls concerning opioid and cannabinoid poisonings. Ordinary and mixed logistic regression models were also substantially more parsimonious than their lasso equivalents while still allowing for the epidemiological interpretation of model coefficients. Controlling for autocorrelation had little effect on the predictive performance of all models, but it did reduce the number of variables included in lasso models. Several disorder variables were associated with opioid and cannabinoid calls that were consistent with the acute effects of these toxicants. These models may help build diagnostic evidence concerning dog exposure to opioids and cannabinoids, saving time and resources when investigating these cases.

CANINE DISTEMPER VIRUS ECOLOGY: INSIGHTS FROM A LONGITUDINAL SEROLOGIC STUDY IN WILD RACCOONS (PROCYON LOTOR).

Increasing reports of canine distemper virus (CDV) in a variety of hosts, and changing CDV dynamics, have led to renewed interest in the ecology of CDV infections in wildlife. Longitudinal serologic studies provide insights into intrapopulation and intraindividual pathogen dynamics, but few studies in wildlife have been conducted. We used data from 235 raccoons (Procyon lotor) captured on more than one occasion between May 2011 and November 2013 to investigate CDV dynamics in Ontario, Canada. Using mixed multivariable logistic regression, we found that juvenile raccoons were more likely to be seronegative from August to November than from May to July. Using paired titers from CDV-exposed individual raccoons, we determined that the winter breeding season, when there is high intraspecific contact and an increase in susceptible juveniles, may be a period of high risk for CDV exposure. Interestingly, CDV seropositive adult raccoons had nondetectable titers ranging from 1 mo to 1 yr later. Based on our preliminary investigation using two different statistical approaches, CDV exposure was associated with a decrease in parvovirus titer. This result raises important questions about whether virus-induced immune amnesia occurs after CDV exposure, which has been described for measles virus, a closely related pathogen. Overall, our results provide significant insights into CDV dynamics. Further research is needed to investigate whether CDV-induced immune amnesia occurs in raccoons and to determine the potential impacts of a reduced population immunity that may occur secondary to CDV exposure, particularly as it relates to rabies control efforts.

Abundance and diversity of Culicoides Latreille (Diptera: Ceratopogonidae) in southern Ontario, Canada.

BACKGROUND: Culicoides Latreille (Diptera: Ceratopogonidae) is a genus of hematophagous midges feeding on various vertebrate hosts and serving as a vector for numerous pathogens important to livestock and wildlife health. North American pathogens include bluetongue (BT) and epizootic hemorrhagic disease (EHD) viruses. Little is known about Culicoides spp. distribution and abundance and species composition in Ontario, Canada, despite bordering numerous U.S. states with documented Culicoides spp. and BT and EHD virus activity. We sought to characterize Culicoides spp. distribution and abundance and to investigate whether select meteorological and ecological risk factors influenced the abundance of Culicoides biguttatus, C. stellifer, and the subgenus Avaritia trapped throughout southern Ontario. METHODS: From June to October of 2017 to 2018, CDC-type LED light suction traps were placed on twelve livestock-associated sites across southern Ontario. Culicoides spp. collected were morphologically identified to the species level when possible. Associations were examined using negative binomial regression among C. biguttatus, C. stellifer, and subgenus Avaritia abundance, and select factors: ambient temperature, rainfall, primary livestock species, latitude, and habitat type. RESULTS: In total, 33,905 Culicoides spp. midges were collected, encompassing 14 species from seven subgenera and one species group. Culicoides sonorensis was collected from three sites during both years. Within Ontario, the northern trapping locations had a pattern of seasonal peak abundance in August (2017) and July (2018), and the southern locations had abundance peaks in June for both years. Culicoides biguttatus, C. stellifer, and subgenus Avaritia were significantly more abundant if ovine was the primary livestock species at trapping sites (compared to bovine). Culicoides stellifer and subgenus Avaritia were significantly more abundant at mid- to high-temperature ranges on trap days (i.e., 17.3-20.2 and 20.3-31.0 °C compared to 9.5-17.2 °C). Additionally, subgenus Avaritia were significantly more abundant if rainfall 4 weeks prior was between 2.7 and 20.1 mm compared to 0.0 mm and if rainfall 8 weeks prior was between 0.1 and 2.1 mm compared to 0.0 mm. CONCLUSIONS: Results from our study describe Culicoides spp. distribution in southern Ontario, the potential for spread and maintenance of EHD and BT viruses, and concurrent health risks to livestock and wildlife in southern Ontario in reference to certain meteorological and ecological risk factors. We identified that Culicoides spp. are diverse in this province, and appear to be distinctly distributed spatially and temporally. The livestock species present, temperature, and rainfall appear to have an impact on the abundance of C. biguttatus, C. stellifer, and subgenus Avaritia trapped. These findings could help inform targeted surveillance, control measures, and the development of management guides for Culicoides spp. and EHD and BT viruses in southern Ontario, Canada.

Risk and protective factors associated with hopelessness among Canadian postsecondary students.

Hopelessness has been linked to several negative mental health outcomes among young adults and the prevalence of it has increased in recent years. The aim was to identify factors associated with hopelessness among Canadian postsecondary students using a socioecological model as a framework. A set of factors for investigation were identified using previously published literature and proxy questions from the American College Health Association's National College Health Assessment II (n = 48,584). A multivariable logistic regression model was fitted to examine these potential associations. Overall, modifiable factors such as belonging to a community, general health, academic performance, and life stressors were found to be associated with hopelessness. In contrast, hopelessness was also associated with some negative health outcomes: loneliness, depression, and suicide ideation. The findings provide preliminary evidence for integrating hope into well-being programming and campus-based interventions aimed at improving postsecondary student mental health. Supplementary Information: The online version contains supplementary material available at 10.1007/s11469-023-01050-w.

Classification of porcine reproductive and respiratory syndrome clinical impact in Ontario sow herds using machine learning approaches.

Since the early 1990s, porcine reproductive and respiratory syndrome (PRRS) virus outbreaks have been reported across various parts of North America, Europe, and Asia. The incursion of PRRS virus (PRRSV) in swine herds could result in various clinical manifestations, resulting in a substantial impact on the incidence of respiratory morbidity, reproductive loss, and mortality. Veterinary experts, among others, regularly analyze the PRRSV open reading frame-5 (ORF-5) for prognostic purposes to assess the risk of severe clinical outcomes. In this study, we explored if predictive modeling techniques could be used to identify the severity of typical clinical signs observed during PRRS outbreaks in sow herds. Our study aimed to evaluate four baseline machine learning (ML) algorithms: logistic regression (LR) with ridge and lasso regularization techniques, random forest (RF), k-nearest neighbor (KNN), and support vector machine (SVM), for the clinical impact classification of ORF-5 sequences and demographic data into high impact and low impact categories. First, baseline classifiers were evaluated using different input representations of ORF-5 nucleotides, amino acid sequences, and demographic data using a 10-fold cross-validation technique. Then, we designed a consensus voting ensemble approach to aggregate the different types of input representations for genetic and demographic data for classifying clinical impact. In this study, we observed that: (a) for abortion and pre-weaning mortality (PWM), different classifiers gained improvement over baseline accuracy, which showed the plausible presence of both genotypic-phenotypic and demographic-phenotypic relationships, (b) for sow mortality (SM), no baseline classifier successfully established such linkages using either genetic or demographic input data, (c) baseline classifiers showed good performance with a moderate variance of the performance metrics, due to high-class overlap and the small dataset size used for training, and (d) the use of consensus voting ensemble techniques helped to make the predictions more robust and stabilized the performance evaluation metrics, but overall accuracy did not substantially improve the diagnostic metrics over baseline classifiers.

A Cross-Sectional Study and Observational Assessment of Shoppers' COVID-19 Prevention Behaviors in Southwestern Ontario, Canada.

OBJECTIVE: The aim of this study was to observe the level of alcohol-based sanitizer, mask use, and physical distancing across indoor community settings in Guelph, ON, Canada, and to identify potential barriers to practicing these behaviors. METHODS: Shoppers were observed in June 2022 across 21 establishments. Discrete in-person observations were conducted and electronically recorded using smartphones. Multilevel logistic regression models were fitted to identify possible covariates for the 3 behavioral outcomes. RESULTS: Of 946 observed shoppers, 69% shopped alone, 72% had at least 1 hand occupied, 26% touched their face, 29% physically distanced ≥ 2 m, 6% used hand sanitizer, and 29% wore masks. Sanitizer use was more commonly observed among people who wore masks and in establishments with coronavirus disease (COVID-19) signage posted at the entrance. Mask use was more commonly observed during days without precipitation and in establishments with some or all touch-free entrances. Shoppers more commonly physically distanced ≥ 2 m when they were shopping alone. CONCLUSIONS: This supports evidence for environmental context influencing COVID-19 preventive behaviors. Intervention efforts aimed at visible signage, tailored messaging, and redesigning spaces to facilitate preventive behaviors may be effective at increasing adherence during outbreaks.

Environmental determinants of infectious and chronic disease prevention behaviours: A systematic review and thematic synthesis of qualitative research.

Regulatory health policies facilitate desired health behaviours in communities, and among them, smoke-free policies and COVID-19 restrictions have been widely implemented. Qualitative research studies have explored how these measures and other environmental influences shape preventive behaviours. The objective of this systematic review was to synthesize previously published qualitative research, generate across-study themes, and propose recommendations for behaviour change interventions. We used a comprehensive search strategy, relevance screening and confirmation, data extraction, quality assessment, thematic synthesis, and quality-of-evidence assessment. In total, 87 relevant studies were identified. Findings were grouped under six overarching themes and mapped under three categories: (i) the political environment, (ii) the sociocultural environment, and (iii) the physical environment. These findings provide insights into the environmental influences of behaviour and indicate future interventions may be more effective by considering moral norms, community norms, policy support, and group identity.

Factors associated with Giardia infection in dogs in southern Ontario, Canada.

Information concerning risk factors associated with Giardia infection in dogs in southern Ontario, Canada, is currently lacking. This study therefore aimed to identify risk factors for Giardia infection in dogs that visit off-leash dog parks in southern Ontario. From May-November 2018, fecal samples were collected from 466 dogs in 12 off-leash dog parks in the Niagara and Hamilton regions of Ontario. A survey that asked questions pertaining to travel history (i.e., area of residence, locations and regions visited in the previous 6 months), basic medical history (i.e., spay/neuter status, veterinary visits, use of deworming medication), consumption of a raw diet, and the physical (i.e., age, sex, breed) and behavioral characteristics (i.e., off-leash activities, hunting activities) of each dog sampled was administered to the respective owner. All fecal samples were examined with the Giardia plate ELISA (IDEXX Laboratories) for parasite antigen. Multivariable logistic regression analyses were conducted on the survey data to investigate putative risk factors for Giardia infection. Overall, 11.8% (95% CI: 9.2-15.1%) of samples tested positive for Giardia antigen. Results from the multivariable logistic regression analyses identified an interaction between dog age and spay/neuter status that was significantly associated with Giardia infection. The odds of infection were greater in intact as compared to neutered adult dogs (OR: 3.6, 95% CI: 1.7-7.9, p = 0.001), and in neutered juvenile dogs as compared to neutered adults (OR: 5.2, 95% CI: 2.2-12.2, p < 0.001). The results provide veterinarians with evidence-based information for identifying dogs at greatest risk of Giardia infection in southern Ontario.

Predictive analysis for pathogenicity classification of H5Nx avian influenza strains using machine learning techniques.

Over the past decades, avian influenza (AI) outbreaks have been reported across different parts of the globe, resulting in large-scale economic and livestock loss and, in some cases raising concerns about their zoonotic potential. The virulence and pathogenicity of H5Nx (e.g., H5N1, H5N2) AI strains for poultry could be inferred through various approaches, and it has been frequently performed by detecting certain pathogenicity markers in their haemagglutinin (HA) gene. The utilization of predictive modeling methods represents a possible approach to exploring this genotypic-phenotypic relationship for assisting experts in determining the pathogenicity of circulating AI viruses. Therefore, the main objective of this study was to evaluate the predictive performance of different machine learning (ML) techniques for in-silico prediction of pathogenicity of H5Nx viruses in poultry, using complete genetic sequences of the HA gene. We annotated 2137 H5Nx HA gene sequences based on the presence of the polybasic HA cleavage site (HACS) with 46.33% and 53.67% of sequences previously identified as highly pathogenic (HP) and low pathogenic (LP), respectively. We compared the performance of different ML classifiers (e.g., logistic regression (LR) with the lasso and ridge regularization, random forest (RF), K-nearest neighbor (KNN), Naïve Bayes (NB), support vector machine (SVM), and convolutional neural network (CNN)) for pathogenicity classification of raw H5Nx nucleotide and protein sequences using a 10-fold cross-validation technique. We found that different ML techniques can be successfully used for the pathogenicity classification of H5 sequences with ∼99% classification accuracy. Our results indicate that for pathogenicity classification of (1) aligned deoxyribonucleic acid (DNA) and protein sequences, with NB classifier had the lowest accuracies of 98.41% (+/-0.89) and 98.31% (+/-1.06), respectively; (2) aligned DNA and protein sequences, with LR (L1/L2), KNN, SVM (radial basis function (RBF)) and CNN classifiers had the highest accuracies of 99.20% (+/-0.54) and 99.20% (+/-0.38), respectively; (3) unaligned DNA and protein sequences, with CNN's achieved accuracies of 98.54% (+/-0.68) and 99.20% (+/-0.50), respectively. ML methods show potential for regular classification of H5Nx virus pathogenicity for poultry species, particularly when sequences containing regular markers were frequently present in the training dataset.

Investigating the distribution of calls to a North American animal poison control call center by veterinarians and the public in space, time, and space-time.

Health assessments via phone call or tele-triage have become very popular. Tele-triage in the veterinary field and North American context is available since the early 2000s. However, there is little knowledge of how caller type influences the distribution of calls. The objectives of this study were to examine the distribution of calls to the Animal Poison Control Center (APCC) by caller type in space, time, and space-time. Data regarding caller location were obtained from the APCC by American Society for the Prevention of Cruelty to Animals (ASPCA). The data were analysed using the spatial scan statistic to identify clusters of higher-than-expected proportion of veterinarian or public calls in space, time, and space-time. Statistically significant spatial clusters of increased call frequencies by veterinarians were identified in some western, midwestern, and southwestern states for each year of the study period. Furthermore, annual clusters of increased call frequencies by the general public were identified from some northeastern states. Based on yearly scans, we identified statistically significant temporal clusters of higher-than-expected public calls during Christmas/winter holidays. During space-time scans of the entire study period, we identified a statistically significant cluster of higher-than-expected proportion of veterinarian calls at the beginning of the study period in the western, central, and southeastern states followed by a significant cluster of excess public calls near the end of the study period on the northeast. Our results suggest that user patterns of the APCC vary by region and both season and calendar time.

Characterization of Escherichia coli and Other Enterobacterales Resistant to Extended-Spectrum Cephalosporins Isolated from Dairy Manure in Ontario, Canada.

Extended-spectrum cephalosporins (ESCs) resistance genes, such as blaCTX-M, blaCMY, and blaSHV, have been found regularly in bacteria from livestock. However, information on their distribution in dairy cattle in Canada and on the associated genome sequences of ESC-resistant Enterobacterales is sparse. In this study, the diversity and distribution of ESC-resistant Escherichia coli throughout manure treatments in six farms in Southern Ontario were assessed over a one-year period, and their ESC-resistance plasmids were characterized. The manure samples were enriched using selective media. The resulting isolates were screened via polymerase chain reaction for blaCTX-M, blaCMY, and blaSHV. No E. coli carrying blaSHV were detected. Escherichia coli (n = 248) carrying blaCTX-M or blaCMY underwent whole-genome sequencing using an Illumina MiSeq/NextSeq. These isolates were typed using multilocus sequence typing (MLST) and their resistance gene profiles. A subset of E. coli (n = 28) were sequenced using Oxford Nanopore Technologies. Plasmids were assembled using Unicycler and characterized via the resistance genes pattern, replicon type, plasmid MLST, phylogenetic analysis, and Mauve alignments. The recovery of ESC-resistant Enterobacterales (18 species, 8 genera) was drastically reduced in manure outputs. However, multiple treatment stages were needed to attain a significant reduction. 62 sequence types were identified, with ST10, ST46, ST58, ST155, ST190, ST398, ST685, and ST8761 being detected throughout the treatment pipeline. These STs overlapped with those found on multiple farms. The ESC-resistance determinants included CTX-M-1, -14, -15, -17, -24, -32, -55, and CMY-2. The plasmids carrying blaCTX-M were more diverse than were the plasmids carrying blaCMY. Known "epidemic plasmids" were detected for both blaCTX-M and blaCMY. IMPORTANCE The increase in antimicrobial resistance is of concern for human and animal health, especially when resistance is conferred to extended-spectrum cephalosporins, which are used to treat serious infections in both human and veterinary medicine. Bacteria carrying extended-spectrum cephalosporin resistance genes, including blaCTX-M and blaCMY, are frequently found in dairy manure. Manure treatment influences the loads and diversity of bacteria, including those carrying antimicrobial resistance genes, such as Enterobacterales and Escherichia coli. Any bacteria that survive the treatment process are subsequently applied to the environment. Enterobacterales carrying blaCTX-M or blaCMY can contaminate soil and crops consumed by humans and animals, thereby increasing the potential for antimicrobial resistance genes to integrate into the human gut microflora through horizontal gene transfer. This furthers the dissemination of resistance. Therefore, it is imperative to understand the effects manure treatments have on ESC-resistance in environmentally applied manure.

Factors associated with stress impacting academic success among post-secondary students: A systematic review.

Objective: To synthesize peer-reviewed primary research exploring factors associated with perceived stress impacting post-secondary students' academic success. Methods: A systematic review identified research conducted in North America, Europe, and Australia in the last ten years across 12 databases. Results: Of the 6,214 references screened, 14 English articles published between 2011 and 2018 were deemed relevant. Subsequent analysis characterized articles by study design, location, population, factors with a statistically significant relationship with both perceived stress and academic success, and future research directions. Findings reveal a complex relationship among overlapping factors associated with perceived stress on academic success at both the intrapersonal (eg, academic, demographic, psychological, attitudinal, and behavioral characteristics) and interpersonal levels (eg, social capital). Conclusions: Further research should measure the association of the identified factors to inform areas where resources could be targeted within post-secondary institutions to prevent stress from unduly impacting students' educational outcomes.

Can North American animal poison control center call data provide early warning of outbreaks associated with contaminated pet food? Using the 2007 melamine pet food contamination incident as a case study.

The 2007 melamine pet food contamination incident highlighted the need for enhanced reporting of toxicological exposures and development of a national quantitative disease surveillance system for companion animals. Data from poison control centers, such as the Animal Poison Control Center (APCC), may be useful for conducting real-time surveillance in this population. In this study, we explored the suitability of APCC call data for early warning of toxicological incidents in companion animal populations by using a-priori knowledge of the melamine-related nephrotoxicosis outbreak. Patient and household-level information regarding possible toxicological exposures in dogs and cats reported to the APCC from 2005 to 2007, inclusive, were extracted from the APCC's AnTox database. These data were used to examine the impact of surveillance outcome, statistical methodology, analysis level, and call source on the ability to detect the outbreak prior to the voluntary recall issued by the pet food manufacturer. Retrospective Poisson temporal scan tests were applied for each combination of outcome, method, level, and call source. The results showed that month-adjusted scans using syndromic data may have been able to help detect the outbreak up to two months prior to the voluntary recall although the success of these methods varied across call sources. We also demonstrated covariate month-adjustment can lead to vastly different results based on the surveillance outcome and call source to which it is applied. This illustrates care should be taken prior to arbitrarily selecting a surveillance outcome and statistical model for surveillance efforts and warns against ignoring the impacts of call source or key covariates when applying quantitative surveillance methods to APCC call data since these factors can lead to very different results. This study provides further evidence that APCC call data may be useful for conducting surveillance in the US companion animal population and further exploratory analyses and validation studies are warranted.

Examining the differential use of a North American animal poison control call center by veterinarians and the public for dog-related calls.

Tele-triage, a subset of telehealth services, is becoming increasingly common, they offer users the ability to receive credible health advice from licensed professionals in the comfort of their own home. In the field of veterinary medicine, tele-triage services have been employed since the early 2000s, but there has been little examination of how these services are used by callers. The objectives of this study were to explore how the use of an animal poison control center (APCC) tele-triage service varied between veterinarians and the public in terms of toxicant type, animal demographics, availability of veterinary services, as well as seasonal and secular trends. Data regarding dog poisoning events were obtained from the APCC of the American Society for the Prevention of Cruelty to Animals' (ASPCA). We fitted a mixed logistic regression model with random intercepts for county and state and identified associations between caller type and the following: animal characteristics (i.e., age, weight, breed-class), type of toxicant, season, year, and access to veterinary services (i.e., veterinarians per capita in the county of the caller). The model included interaction effects between season and both plant and pesticide toxicants. There was also an interaction between year and access to veterinary care. Further investigations are needed to understand how the novelty of a toxicant and the severity of clinical signs associated with a toxicant predict the type of caller, if pet demographics are associated with the caller based on medical issues or owner attitudes, and how access to veterinary care influences the use of this tele-triage service.

"I Can Sense When My Hands Need Washing": A Qualitative Study and Thematic Analysis of Factors Affecting Young Adults' Hand Hygiene.

Handwashing is one of the most effective and low-cost public health measures. However, it is often not practiced frequently enough or correctly by the public. Young adults in particular have poorer intentions to wash their hands, frequency of handwashing, and sanitizer use compared to other age groups. Therefore, there is a need to identify barriers and facilitators affecting hand hygiene within this group. The objective of this qualitative study was to apply the Theoretical Domains Framework to explore factors which influence hand hygiene among young adults aged 18 to 25 years old. An online questionnaire (n = 37) and thematic analysis were used to generate 3 overarching themes. The main findings indicated internal factors such as knowledge and intentions; interpersonal factors such as social norms; and environmental factors such as reminders, cues, accessibility, and cleanliness of handwashing facilities determined the level of hand hygiene practiced among young adults. The findings suggest that behavior change techniques such as social comparisons and tailored messaging to suit the needs of young adults may be more effective at increasing hand hygiene.