Paper detail

A New Dynamic Model to Predict the Effects of Governmental Decisions on the Progress of the CoViD-19 Epidemic

We have established a novel mathematical model that considers various aspects of the spreading of the virus, including, the transmission based on being in the latent period, environment to human transmission, governmental decisions, and control measures. To accomplish this, a compartmental model with eight batches (sub-population groups) has been proposed and the simulation of the set of differential equations has been conducted to show the effects of the various involved parameters. Also, to achieve more accurate results and closer to reality, the coefficients of a system of differential equations containing transmission rates, death rates, recovery rates and etc. have been proposed by some new step-functions viewpoint. Results: First of all, the efficiency of the proposed model has been shown for Iran and Italy, which completely denoted the flexibility of our model for predicting the epidemic progress and its moment behavior. The model has shown that the reopening plans and governmental measures directly affect the number of active cases of the disease. Also, it has specified that even releasing a small portion of the population (about 2-3 percent) can lead to a severe increase in active patients and consequently multiple waves in the disease progress. The effects of the healthcare capacities of the country have been obtained (quantitatively), which clearly specify the importance of this context. Control strategies including strict implementation of mitigation (reducing the transmission rates) and re-quarantine of some portion of population have been investigated and their efficiency has been shown.