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All Journal JAMBURA JOURNAL OF PROBABILITY AND STATISTICS
Habeeb A Afolabi
Osun State University, Osogbo
Computer Science & IT Decision Sciences, Operations Research & Management Environmental Science Social Sciences

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STOCHASTIC MODEL ANALYSIS OF THE IMPACT OF MEDIA CAMPAIGN ON TRANSMISSION OF COVID – 19 EPIDEMIC. Kehinde Adekunle Bashiru; Taiwo Adetola Ojurongbe; Mutiu L Olaosebikan; Nureni O Adeboye; Habeeb A Afolabi; Ife Olukotun
Jambura Journal of Probability and Statistics Vol 3, No 2 (2022): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34312/jjps.v3i2.15878

Abstract

The COVID - 19 pandemic is currently causing authorities and public health officials more concern. The goal of the project is to convert a deterministic model for COVID-19 transmissions to a stochastic model, and then analyze the results to see how media-driven awareness campaigns have an impact on the disease's spread. The dynamic COVID-19 model was converted to a stochastic model, which was then examined. The model includes the following categories: Susceptible (S), Exposed (E), Infected class (I),  Isolated class ( ), Aware class  and Recovered class (R), as well as the Cumulative density of awareness programs by media denoted by   . With the help of MATLAB, the converted model is then numerically solved using the Eula Maruyama approach, allowing the existence and uniqueness of the model to be examined. The implementation of awareness programs has been found to have a significant positive impact on the spread of COVID-19. As the rate of implementation of these programs rises, the population that is exposed to the virus and those who are infected with it declines, and it has been hypothesized that this will eventually cause COVID-19 to become extinct. According to the report, putting awareness campaigns into place can help stop the COVID-19 epidemic from spreading.
Co-Authors Ife Olukotun Kehinde Adekunle Bashiru Mutiu L Olaosebikan Nureni O Adeboye Taiwo Adetola Ojurongbe