11th International Virtual Seminar on COVID-19 Part II
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Accepted Abstracts

An SEIRD Epidemic Model for Predicting the Spread of COVID-19 over a Period of One Year: A Case of the United States

Arhin Joseph Roger*
University of Electronic Science and Technology of China, China

Citation: Roger AJ (2020) An SEIRD Epidemic Model for Predicting the Spread of COVID-19 over a Period of One Year: A Case of the United States. SciTech Central COVID-19.

Received: November 24, 2020         Accepted: November 26, 2020         Published: November 26, 2020

Abstract

COVID-19 is currently a perilous disease that has an incubation period between 4 and 6 days. The United States Disease Control and Prevention Centers posited that in certain cases, coronaviruses are zoonotic, which means that they have been responsible for moving from animals to humans. The outbreak of the new coronavirus (COVID-19) disease has had an enormous impact globally. The World Health Organization (WHO) has put in place various safety measures that will help alleviate the spread of the epidemic. This paper presents an SEIRD epidemic model with government policy to predict the spread of COVID-19. Through mathematical analysis, the essence of the model is investigated. The basic reproductive number of the envisaged model is computed and decides whether or not the disease is present in the population. Disease-free and symptomatic equilibria are studied for their existence and stability via the Lyapunov function. It is established from our numerical simulations that the introduction of government policy helps to alleviate the spread of the disease, where the basic reproductive number takes part in sustaining their stability. In the prediction of infected and death cases that were very similar to real life data, it was established that the model was effective.