Effects of the Reproduction Number in a Seiird Model Describing the Time Evolution of COVID-19 at Count Ry Level
WSEAS Transactions on Computers
We consider a compartmental model of SEIIRDtype which describes the time evolution of the COVID-19 epidemy at the level of a country. For the reproduction number R(t), the crucial parameter which influences the number of new cases, we consider an explicit form as a combination of trigonometric, exponential and gaussian functions. The coefficients of the individual parts can be adapted in order that the profile of R(t) matches different scenarios. Their common structure illustrates the real
... rates the real behaviour observed in most countries. Initially we can observe large values of R(t) which enforce the first wave of the epidemy, followed by a rapid reduction below 1 due to a first lockdown which can have different intensities. The second phase consists of a relaxation of the restrictions having as a consequence an increase of the reproduction number within a range over 1. The numerical simulations show that in this case, after a period of some months with a low level of daily cases, the occurrence of a second wave is unavoidable, being inherent to the nature of the model. The intensity of the second wave depends on how much and how long the reproduction number R(t) has been over the threshold value of 1, but also on the intensity of the first lockdown. All simulations show that the behaviour of the model is very sensitive with respect to the reproduction number. Small changes in its values may have a significant impact on the long-term evolution of the epidemy at the country-level.