A Review Study on Outbreak Prediction of Covid19 By using Machine Learning

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