COVID-19 Occurance Prediction

Abstract

Unfortunately, Covid-19 has become the new normal of human existence. As a result of the pandemic lives have been lost and health of millions has been impacted. Trying to predict the prevalence of the virus in and around the regions where it is prevalent will help people in those areas or neighborhoods be cautious. This could also help the governments of each country, to be more aware of the virus widespread areas, and in turn protect lives of people. In this paper, we will be predicting the occurrence of Covid-19 by using geo spatial data, as well as data containing affected cases counts, death cases counts, and recovery cases counts of every country. Through data mining techniques, the data is preprocessed for errors or missing data and then classification and clustering analysis are used for prediction of the disease. Our hope is that these results will aide health workers in predicting the future case rate of covid-19, and the intensity of the disease in each country.