In this work, we employ a data-fitted compartmental model to visualize the progression and
behavioral response to COVID-19 that match provincial case data in Ontario, Canada from …

The multilayer one-class classification (OCC) frameworks have gained great traction in
research on anomaly and outlier detection. However, most multilayer OCC algorithms suffer …

Since the beginning of the COVID-19 spreading, the number of studies on the epidemic
models increased dramatically. It is important for policy makers to know how the disease will …

Using an SEIR-type compartmental model and provincial case data from Ontario, Canada,
we build upon previous work to depict COVID-19 case progression from February 14 to …

COVID-19 has resulted in the mathematical modelling community producing a wide range of
analyses, forecasting and scenario modelling efforts. In our work, we propose a novel …

In the infection prevention and control of epidemics, isolation has always been an important
means for mankind to curb the spread of the epidemic. Isolation targets not only confirmed …

Since Covid-19 pandemic outbreak in 2019, forecasting of the future behavior of the
pandemic became crucial issue for decisions making. This forecasting is achieved by …

Анотація Актуальність теми. Актуальність теми" Інтерактивний додаток для
прогнозування COVID-19 на основі даних про вакцинацію" полягає в тому, що вона …

Since the beginning of the COVID-19 spreading, the number of studies on the epidemic
models increased dramatically. It is important for policymakers to know how the disease will …

In this work, we provide a “rear-view mirror” analysis for approaches to two different
diseases that were relevant to Ontario in 2020. Using probabilistic dynamic programming …