Applying SEIR model without vaccination for COVID-19 in case of the United States, Russia, the United Kingdom, Brazil, France, and India

Abstract

Abstract Objectives: Compartmental models are helpful tools to simulate and predict the spread of infectious diseases. In this work we use the SEIR model to discuss the spreading of COVID-19 pandemic for countries with the most confirmed cases up to the end of 2020, i.e. the United States, Russia, the United Kingdom, France, Brazil, and India. The simulation considers the susceptible, exposed, infective, and the recovered cases of the disease. Method: We employ the order Runge–Kutta method to solve the SIER model equations-for modelling and forecasting the spread of the new coronavirus disease. The parameters used in this work are based on the confirmed cases from the real data available for the countries reporting most cases up to December 29, 2020. Results: We extracted the coefficients of the exposed, infected, recovered and mortality rate of the SEIR model by fitting the collected real data of the new coronavirus disease up to December 29, 2020 in the countries with the most cases. We predict the dates of the peak of the infection and the basic reproduction number for the countries studied here. We foresee COVID-19 peaks in January-February 2021 in Brazil and the United Kingdom, and in February-March 2021 in France, Russia, and India, and in March-April 2021 in the United States. Also, we find that the average value of the SARS-CoV-2 basic reproduction number is 2.1460. Conclusion: We find that the predicted peak infection of COVID-19 will happen in the first half of 2021 in the six considered countries. The basic SARS-CoV-19 reproduction number values range within 1.0158–3.6642 without vaccination.