Discrete Epidemic Models: Neural Network Approach

In this paper we consider a discrete epidemic SIR/COVID model.Since models can be used for early warning and to forecast the behavior of an epidemic and develop intervention strategies it is critical to be able to effectively predict transmission and recovery rates.Based on available daily infection and death data from South Carolina for the period December 1, 2020, to June 1, 2021 we develop a discrete model and analyze evolution of the model using optimization, artificial neural network, machine learning and Grey model inferring the daily, transmission, and reproduction rates, and recovery for each day of the period.The models and results are consistent with the observations.The models developed using data help us understand the recovery and transmission rates, hence the evolution of the epidemic.The infection and recovery increasing in South Carolina do not show improvement in the period covered.The number of dead people tends to increase although by small amount.Forecasting data for a short time in the future can be used to judge the possible evolution of the epidemic and intervention.Models were developed based on the available data.For the period December to June there were no available data on recovered populations and we have to determine them as well as transmission and recovery rates based on data of infected populations and dead population using artificial neural networks and optimization methodologies where transmission, recovery, relapsation immunity and death rates from infection are considered as decision variables.From the data from CDC we see that the number of infected population is increasing.We have also data for the number of dead population due to the virus.Our models are consistent with the data we have available for the infected and dead population.However, there were no data for recovered population in South Carolina for the entire period December 1 to June 1.We have to use our model to come up with recovered population number.One thing we observe is that the number of infected population was increasing.One of the control measures that are believed to be reliable methods of curbing the spread of the virus is quarantine.We include a model that includes quarantine in our work.In our quarantine we see that if 100,000 susceptible people in the whole state were quarantined there would have been a considerable decrease in the number of infected population.