Mathematical Modelling of the Spread of COVID-19 Cases in Sri Lanka

Abstract

Sri Lanka confronted a substantial challenge in responding to the spread of the novel strain of coronavirus (SARS-CoV-2), which was declared as a pandemic by the World Health Organization. The government introduced multiple measures to contain the transmission of the virus within the country. This research provided information on COVID-19 and estimated the spread of the virus in Sri Lanka based on confirmed data from the national epidemiological reports for the period from October 01, 2020 to April 10, 2021. Stochastic modelling approaches were used to model the spread of the virus and its significance was also checked. The logistic growth model, where the number of infected cases are stochastic and the Susceptible-Infected-Recovered (SIR) model where the number of individuals who get disease, the number of deaths due to Coronavirus, and the number of recovered are stochastic, were employed under certain assumptions to identify the behavior of the spread of virus in a theoretical approach, during the second wave. The SIR model with a hyperparameter was used to improve the model fitting to actual data. Further, different infection and recovery rates were obtained using different time-variant scenarios. Results showed that the estimated cumulative cases were equal to 96845 within a certain period. It was also shown that both infection and recovery rates changed with time and followed different patterns. Due to changes in the COVID – 19 variants, the infected individuals also demonstrated different behaviors with increasing infection rate.