Covid-19 Outbreak Modelling Using Regression Techniques

Since the onset of COVID-19 pandemic, officials and several others have been making an effort to form informed decisions and take relevant measures to curb the outbreak. Mostly authorities have used standard statistical models, and epidemiological models to determine the outbreak. Although these models have shown to have accuracy in the past, they seem to be highly ineffective during the COVID-19 pandemic, mostly because of the complexities in it's outbreak. With the lack of studies done on the outbreak, it's imperative for us to determine the attributes which could show correlation with the spread for us to improve upon our predictions. Therefore in this paper the authors have tried to find the attributes which best help in the outbreak modelling and have applied those attributes to the traditional regression models to study their effects on the predictions.