A Study of the COVID-19 Impacts on the Canadian Population

Abstract

With the recent outbreak of COVID-19, the reach and scale of COVID-19 cases is top of mind for everyone and many research groups are actively monitoring and exploring the potential spread. A positive consequence of past epidemics and pandemics is that there are sound epidemiological compartmental modelling approaches that can effectively model disease spread. With minor changes to the underlying dynamical system of equations, many different strategies and situations can be explored. In particular, one such strategy of social distancing is top of mind for many Canadians as our political leaders, local businesses, and fellow Canadians promote and adopt this approach with the hopes that it will effectively 'flatten the curve' and reduce or prevent further spread. In this paper, the baseline model is introduced with its close counterpart, the model. Social distancing is modelled through the isolation of a subset of the susceptible population and comparative studies are performed considering a range in the proportion of individuals isolated. Robust and accurate numerical approximation techniques are used to simulate the pessimistic base case for which no preventative measures are taken and for various social distancing regimes. The results of social distancing are consolidated into two groups-those that flatten the curve and those that completely halt the disease spread. Mathematical formulations show that the turning point between these two regimes is when the effective reproductive rate, denoted , is equal to 1. Conclusions are made regarding the impacts and extent of the spread in relation to the severity of social distancing measures.

Smart Monitoring System For Physical Distancing

“…A recent research, numerical simulations of social distancing are done and consolidated into two groups -those that flatten the curve and those that completely halt the disease spread [6]. These findings reflect the importance of such an approach in battling COVID-19 spread.…”

Assessing the Impact of Alternative Responses to COVID-19: Stopping the Spread in Newfoundland and Labrador, Canada

“…The formulations of these models are a set of ordinary differential equations that evolve the dynamics between various population states, to be outlined briefly in the following. The two most common methods are known as SIR and SEIR [31].…”

“…In [31], SIR and SEIR models used for modeling infectious diseases were implemented, and coefficients to model social distancing were proposed. The impacts of social distancing were studied and explored through numerical simulations, and mathematical formulations show that the turning point between these two groups is when the effective reproductive rate is equal to 1.…”

Risk Assessment and Prediction of COVID-19 Based on Epidemiological Data From Spatiotemporal Geography

“…Since infectious disease theory is not involved here, only short-term predictive analysis can be performed (Polo et al, 2020). Dynamic models can be divided into several basic types, such as susceptible-infected (SI), susceptible-infected-susceptible (SIS), susceptible-infectedrecovered (SIR), and susceptible-exposed-infected-recovered (SEIR) models, based on the characteristics of pathogens, infectious agents, post infection immunity, the source of infection, the route of transmission, and susceptible populations (Yawney and Gadsden, 2020). Moreover, as dynamic models take into account the factors influencing disease transmission and related social factors, they can effectively reveal the trends of the epidemic and change course of the disease (Li et al, 2020).…”