Analysis and Prediction of COVID-19 Outbreak by a Numerical Modelling

Abstract

Pandemic COVID-19 is a contagious disease affecting more than 200 countries, territories, and regions. Recently, Iraq is one of the countries that have immensely suffered from this outbreak. The Kurdistan Region of Iraq (KRI) is also prone to the disease. Until now, more than 23,000 confirmed cases have been recorded in the region. Since the onset of the COVID-19 in Wuhan, based on epidemiological modelling, researchers have used various models to predict the future of the epidemic and the time of peak, yielding diverse numbers in different countries. This study aims to estimate the basic reproductive number [R₀] for COVID-19 in KRI, using the standard SIR (Susceptible-Infected-Removed) epidemic model. A system of nonlinear differential equations was formulated and solved numerically by the 4^th order Runge-Kutta method. The reproductive numbers R₀ was estimated by the method of fitting the curves between the actual daily data and numerical solution by applying the least square method. For the analysis, data were taken for the duration of 165 days, from 1^st of March to 12^th August 2020, in a population of 5.2 million. It is concluded that the R₀ value was fluctuating during the outbreak, with an average of 1.33, predicting that infection cases will reach their maximum value of around 540,000 on the 5^th of November 2020. Then, the spread of the disease will die out since the number of susceptible people will decrease to about 3.2 million. While the number of removed individuals will reach approximately to 1.5 million.