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This work presents a new polymorphic, reusable, and comprehensive mathematical model for COVID-19 epidemic transition cycle dynamics. This model has the following characteristics: (1) The core SEIR model includes asymptomatic and symptomatic infections; (2) the symptomatic infection is a multi-variant; (3) the recovery stage provides a partial feed to the symptomatic infection; and (4) the symptomatic and asymptomatic stages have additional feed streams from the protected stage. The proposed formalisation template is a canonical way to achieve different models for the underlying health control environment. This template approach endows the model with polymorphic and reusable capability across different scenarios. To verify the model's reliability and validity, this work utilised two sets of initial conditions: date range and COVID-19 data for Canada and Saudi Arabia. [ABSTRACT FROM AUTHOR]

The 2019 coronavirus disease (COVID-19) cases that are being confirmed in Canada provide an opportunity to expand the epidemic model for the simulation of disease infection spread: Susceptible- Exposed-Infectious-Recovered (SEIR). This paper develops a SEIRCRT |ˈsəːkrɪt | model that integrates the Institute for Disease Modeling's SEIR model and Critical Race Theory (CRT) to answer the question: What is in a SEIRCRT model? SEIRCRT provides a basic modeling structure from a CRT lens to simulate, predict and forecast COVID-19 cases, comorbidities affecting African Canadians, and deaths through predictive modeling. Knowledge of SEIRCRT is critical to characterize the severity of COVID-19 in this early stage. To this end, the purpose of this paper is to describe SEIRCRT's model and summarize its key characteristics. SEIRCRT as a public health framework provides insight into the conclusions drawn about race and COVID-19, and expands our thinking about what health disparities mean for African Canadian communities. [ABSTRACT FROM AUTHOR]

As part of the development of a quantitative microbial risk assessment (QMRA) model of third-generation cephalosporins (3GC)-resistant Salmonella Heidelberg, a compartmental (SEIR) model for S. Heidelberg transmission within a typical Canadian commercial broiler chicken flock was developed. The model was constructed to estimate the within-flock prevalence and the bacterial concentration in the barn environment at pre-harvest, and to assess the effect of selected control measures. The baseline scenario predicted an average within-flock prevalence of 23.5 % (95 % tolerance interval: 15.7–31.4) and an average bacterial concentration of 3.579 (0–4.294) log CFU/g of feces in the barn environment at pre-harvest (on the day the flock is sent to slaughter). Because vertical introduction of S. Heidelberg into the barn was already uncommon in the baseline scenario, vaccination of broiler parent flocks appeared to have a negligible effect, while vaccination of broiler chicken flocks substantially reduced the bacterial concentration at pre-harvest. Cleaning and disinfection between batches markedly reduced the within-flock prevalence at pre-harvest, but the effect on bacterial concentration was limited outside of the beginning of the production period. Extending downtime between batches by 7 days had little effect on within-flock prevalence or bacterial concentration of S. Heidelberg when compared to the baseline scenario. This study provides a basis to describe S. Heidelberg dynamics within a broiler chicken flock and to predict the within-flock prevalence and bacterial concentration at pre-harvest, and includes a description of the limitations and data gaps. The results of these analyses and associated uncertainties are critical information for populating QMRA models of the downstream impacts on public health from on-farm and other food-chain practices. Specifically, the study findings will be integrated into a broader farm-to-fork QMRA model to support the risk-based control of S. Heidelberg resistant to 3GC in broiler chicken in Canada. [ABSTRACT FROM AUTHOR]