Lockdown: a non-pharmaceutical policy to prevent the spread of COVID-19.
Mathematical modeling and computation
Abstract
In this paper, we derive and analyze an extended SIRS-model which
includes lockdown policies at the early stages of the pandemic. The
latter play a salient role for flattening the curve of infectious
diseases such as COVID-19, and is introduced as a model compartment. An
error function is reported, which serves as a bridge between the
outcomes of the model and available databases; we estimate the values of
the model parameters by minimizing the error function. The intervention
function, obtained from the equivalent system of the proposed model, and
effective reproduction function are also derived to understand the
underline scenario of the coronavirus outbreak. We then estimate the
epidemiological variables such as susceptible, recovered, lockdown etc.
for Canada and three of its provinces, Ontario, Qu\’ebec
and British Columbia, significantly affected by the coronavirus. Some
improvements, such as spatial dependence or “at risk’‘ vs “healthy”
population, will finally be proposed in order to increase the accuracy
of the modeling.