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SIR Prediction Of The Epidemics Trend Of COVID-19 In South Africa And Compared With Hubei,China

Posted on:2022-09-03Degree:MasterType:Thesis
Institution:UniversityCandidate:Shimelis Abera ZewdieZDFull Text:PDF
GTID:2494306314952009Subject:Microbiology
Abstract/Summary:PDF Full Text Request
After the new strain of coronavirus is identified in late December 2019 in Hubei province,China,the disease has spread Worldwide quickly,reaching a pandemic proportion at the beginning of March 2020,from the first reports on Coronavirus disease-2019(COVID-19).The spread of COVID-19 in Africa was different when we compare it with the other countries on the same continents.To estimate the spread of COVID19 in South Africa and compared to Hubei in China,I have used a susceptible and infectious recovered model.My expectations here are based on the data and the trends observed previously for the spread of the pandemic novel coronavirus disease.I used the public dataset novel coronavirus disease from Johns Hopkins University in this study.Shifts in the dynamics of the population and changes in the corona virus disease infection can require further predictions of the spread of the disease.I am keen to predict the coronavirus in South Africa epidemic peak outbreak and Hubei using the SIR model.in this research.No known safe treatment has been conducted to this date(March 2020);therefore,a person’s immunity system plays a crucial role in restoring the infection.In general,the highest mortality rate is probably due to COVID-19 among older people.The persons in the incubation stage can infect sensitive individuals with the COVID-19 epidemic.The construction of the responsible predictive mathematical model considers all these points.I can estimate the spread of novel coronavirus disease(COVID-19)in South Africa and Hubei using the model investigated.The peak epidemic in these countries is considered and some numerical simulations are used to assess the estimated time of infection spread.
Keywords/Search Tags:COVID-19, coronavirus, South Africa, prediction, epidemics trend
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