Modelling the Significant Effect of Public Health Interventions on Covid-19 Transmission

A major Coronavirus outbreak, which was first identified in Wuhan, China in December 2019, has rapidly spread all over the world. On 11 March 2020, the World Health Organization (WHO) has declared the novel Coronavirus Disease 2019 (Covid-19) outbreak a global pandemic. The increase in the number of reported infections and deaths due to Coronavirus outbreak inspired many countries to implement intervention measures. In this work, we use Susceptible-Exposed-Infected-Recovered (SEIR) model to predict the outbreak of the disease. SEIR model was chosen compared to SIR model because exposed individuals whom are asymptomatic or having mild symptoms contribute to the increase of number of infections. We also work on modelling the transmission dynamics of Covid-19 in the presence of three intervention measures. The proposed model describes the evolution of the disease in the population when preventive measures, active case-finding and hospitalization interventions are implemented as strategies to control and eradicate the disease. Variation in the effectiveness of combined interventions for infectious individuals are observed and analyzed by simulating the Covid-19 model with interventions. Our simulation results shows that more rigorous and stringent public health interventions would reduce the risk of Covid-19 spreading. It is of great importance and practical significance to ensure early prevention, early detection and early treatment to combat Covid-19.