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Background: Drivers of COVID-19 severity are multifactorial and include multidimensional and potentially interacting factors encompassing viral determinants and host-related factors (i.e., demographics, pre-existing conditions and/or genetics), thus complicating the prediction of clinical outcomes for different severe acute respiratory syndrome coronavirus (SARS-CoV-2) variants. Although millions of SARS-CoV-2 genomes have been publicly shared in global databases, linkages with detailed clinical data are scarce. Therefore, we aimed to establish a COVID-19 patient dataset with linked clinical and viral genomic data to then examine associations between SARS-CoV-2 genomic signatures and clinical disease phenotypes. Methods: A cohort of adult patients with laboratory confirmed SARS-CoV-2 from 11 participating healthcare institutions in the Greater Toronto Area (GTA) were recruited from March 2020 to April 2022. Supervised machine learning (ML) models were developed to predict hospitalization using SARS-CoV-2 lineage-specific genomic signatures, patient demographics, symptoms, and pre-existing comorbidities. The relative importance of these features was then evaluated. Results: Complete clinical data and viral whole genome level information were obtained from 617 patients, 50.4% of whom were hospitalized. Notably, inpatients were older with a mean age of 66.67 years (SD ± 17.64 years), whereas outpatients had a mean age of 44.89 years (SD ± 16.00 years). SHapley Additive exPlanations (SHAP) analyses revealed that underlying vascular disease, underlying pulmonary disease, and fever were the most significant clinical features associated with hospitalization. In models built on the amino acid sequences of functional regions including spike, nucleocapsid, ORF3a, and ORF8 proteins, variants preceding the emergence of variants of concern (VOCs) or pre-VOC variants, were associated with hospitalization. Conclusions: Viral genomic features have limited utility in predicting hospitalization across SARS-CoV-2 diversity. Combining clinical and viral genomic datasets provides perspective on patient specific and virus-related factors that impact COVID-19 disease severity. Overall, clinical features had greater discriminatory power than viral genomic features in predicting hospitalization. [ABSTRACT FROM AUTHOR]

Alveolar echinococcosis (AE) is a chronic infection caused by the larval stage of the Echinococcus multilocularis tapeworm and commonly manifests within the liver. In humans and dogs, AE is typically [...]

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 pandemic, is capable of infecting a variety of wildlife species. Wildlife living in close contact with humans are at an increased risk of SARSCoV- 2 exposure and, if infected, have the potential to become a reservoir for the pathogen, making control and management more difficult. The objective of this study is to conduct SARSCoV- 2 surveillance in urban wildlife from Ontario and Québec, increasing our knowledge of the epidemiology of the virus and our chances of detecting spillover from humans into wildlife. Methods: Using a One Health approach, we leveraged activities of existing research, surveillance and rehabilitation programs among multiple agencies to collect samples from 776 animals from 17 different wildlife species between June 2020 and May 2021. Samples from all animals were tested for the presence of SARS-CoV-2 viral ribonucleic acid, and a subset of samples from 219 animals across three species (raccoons, Procyon lotor; striped skunks, Mephitis mephitis; and mink, Neovison vison) were also tested for the presence of neutralizing antibodies. Results: No evidence of SARS-CoV-2 viral ribonucleic acid or neutralizing antibodies was detected in any of the tested samples. Conclusion: Although we were unable to identify positive SARS-CoV-2 cases in wildlife, continued research and surveillance activities are critical to better understand the rapidly changing landscape of susceptible animal species. Collaboration between academic, public and animal health sectors should include experts from relevant fields to build coordinated surveillance and response capacity. [ABSTRACT FROM AUTHOR]

Background: We determined the burden of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in air and on surfaces in rooms of patients hospitalized with coronavirus disease 2019 (COVID-19) and investigated patient characteristics associated with SARS-CoV-2 environmental contamination.Methods: Nasopharyngeal swabs, surface, and air samples were collected from the rooms of 78 inpatients with COVID-19 at 6 acute care hospitals in Toronto from March to May 2020. Samples were tested for SARS-CoV-2 ribonucleic acid (RNA), cultured to determine potential infectivity, and whole viral genomes were sequenced. Association between patient factors and detection of SARS-CoV-2 RNA in surface samples were investigated.Results: Severe acute respiratory syndrome coronavirus 2 RNA was detected from surfaces (125 of 474 samples; 42 of 78 patients) and air (3 of 146 samples; 3 of 45 patients); 17% (6 of 36) of surface samples from 3 patients yielded viable virus. Viral sequences from nasopharyngeal and surface samples clustered by patient. Multivariable analysis indicated hypoxia at admission, polymerase chain reaction-positive nasopharyngeal swab (cycle threshold of ≤30) on or after surface sampling date, higher Charlson comorbidity score, and shorter time from onset of illness to sampling date were significantly associated with detection of SARS-CoV-2 RNA in surface samples.Conclusions: The infrequent recovery of infectious SARS-CoV-2 virus from the environment suggests that the risk to healthcare workers from air and near-patient surfaces in acute care hospital wards is likely limited. [ABSTRACT FROM AUTHOR]

Prior to 2012, Echinococcus multilocularis was not known to occur in any host in Ontario, Canada. However, since that year, five cases of alveolar echinococcosis have been diagnosed in dogs that resided at the western end of Lake Ontario. In addition, E. multilocularis has been shown to be a common infection in wild canids (i.e. coyotes and foxes) across southern Ontario with a high‐risk infection cluster in the area surrounding the western shores of Lake Ontario and northern shores of Lake Erie. In regions endemic for E. multilocularis, dog ownership is considered a risk factor for human alveolar echinococcosis. A study was therefore carried out to determine the prevalence of E. multilocularis intestinal infections in dogs within the high‐risk infection cluster. From May to November 2018, faecal samples were collected from 477 dogs aged ≥6 months that visited 12 off‐leash dog parks in the Halton, Hamilton and Niagara public health units. Faecal samples were analysed via a magnetic capture probe DNA extraction and real‐time PCR method for E. multilocularis DNA. Overall, 0% (97.5% CI: 0%–0.80%) of samples tested positive. This result informs preventive recommendations for E. multilocularis infections in dogs in this region. [ABSTRACT FROM AUTHOR]