SimCOVID: An Open-Source Simulink-Based Program for Simulating the COVID-19 Epidemic

Ismael Khorshed Abdulrahman

The proposed method to estimate the variable parameters is to divide the curve (either the daily-infection-rate curve or the cumulative-infectious curve) into at least two parts around some observed critical points. The objective is to cover and better fit the concave-up and -down portions of the curve. In this study and for more reliable results, the cumulative reported cases graph is split into three periods at two critical points: (1) period-1 from time zero until 1, where stands for starting time, (2) period-2 from 1 to 2 and (3) period-3 from 2 until the rest of simulation time. The critical time points ( 1 and 2) were chosen empirically based on some observation notes about the given curve. It is also possible to let these values variables to be found by the program. The total period of time was chosen to be from the day when the first case of the disease was reported until the curve starts to flatten. Three step-blocks were used for the parameters ( , ). These quantities are unknown variables; we want to determine their values and the overall shape forms so that the output of our simulation and the collected data are equals. The parameter estimation tool in Simulink was employed to optimize the system and predict the infection and recovery rates. A reasonable set of initial values were selected for the parameters (positive values between 0-2 for the recovery gains and negative similar values for the exponential powers used for the infection function). Figure 3 shows a part of this simulation with the number of iterations, values of the parameters at each iteration, and the comparison between the collected and simulated data. We can observe a quite matching between the two curves after 100 iterations. It should be noted that the selection of initial values given to the optimization algorithm plays a significant role in the speed to reach the desired accuracy. Therefore, it is recommended to set reasonable values for these quantities to accelerate the simulation. An important indicator of a pandemic is the ratio between the infection and recovery rates, or namely, the reproduction ratio. author/funder, who has granted medRxiv a license to display the preprint in perpetuity.