Determining important parameters in COVID-19 transmission through the sensitivity analysis of an SIR model

COVID-19 is a novel coronavirus caused by the SARS-CoV-2 virus that affects humans worldwide. Mathematical models are widely used to understand and predict epidemic outbreaks. In this study, the susceptible-infected-recovered (SIR) model of COVID-19 transmission is formulated to identify significant parameters in controlling the number of infected cases. The constructed SIR model is modified to include quarantine compartment and vaccination parameter. The local sensitivity analysis is used to determine significant parameters in COVID-19 transmission. Since the initial disease transmission is highly related to the basic reproduction number, R0, the sensitivity indices of the R0 to every parameter are calculated. The results show that the most sensitive parameter that contributes to the reduction of COVID-19 infected cases is the quarantine rate, followed by the natural mortality rate. The finding revealed that quarantine measure is more effective in controlling the spread of COVID-19 than vaccination. These suggest that the health authorities should keep implementing the quarantine measure for infected cases despite already being vaccinated.