A Review Study on Outbreak Prediction of Covid-19 By using Machine Learning
Kamal Narayan Kamlesh

Kamal Narayan Kamlesh, Research Scholar, Department of CS & IT, Magadh University, Bodh Gaya (Bihar), India. 

Manuscript received on 12 April 2024 | Revised Manuscript received on 13 June 2024 | Manuscript Accepted on 15 June 2024 | Manuscript published on 30 June 2024 | PP: 1-11 | Volume-11 Issue-6, June 2024 | Retrieval Number: 100.1/ijies.E41240612523 | DOI: 10.35940/ijies.E4124.11060624

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In December 2019, Wuhan City, China, discovered a new infectious disease, COVID-19. Over 70 million people have been infected and one million people have died as a result of COVID-19. Defeating such a deadly, infectious disease requires accurate models that predict COVID-19 outbreaks. Using prediction models, governments can plan budgets and facilities for fighting diseases, and take control measures to make better decisions and take control measures. For example, they can determine how many medicines and medical equipment to manufacture or import, as well as how many medical personnel are needed to fight the disease. The COVID-19 outbreak has subsequently been predicted in several countries and continents using regression and classification models. A recent study that incorporated statistical and machine learning techniques was reviewed to predict COVID-19 outbreaks in the future. Ground truth datasets are used, their characteristics are investigated, models are developed, predictor variables are identified, statistical and machine learning methods are applied, performance metrics are calculated, and finally comparisons are made. By applying machine learning methods, the survey results indicate that we can make predictions about whether a patient will become infected with COVID-19, how outbreak trends will develop, and which age groups will be affected the most.

Keywords: Machine Learning, Classification, Regression, COVID-19, ARIMA
Scope of the Article: Classification