Vaccissure with Predictive Capacity of COVID-19

Abstract

COVID-19 infections can spread silently, due to the simultaneous presence of significant numbers of both critical and asymptomatic to mild cases. While, for the former reliable data are available (in the form of number of hospitalization and/or beds in intensive care units), this is not the case of the latter. Hence, analytical tools designed to generate reliable forecast and future scenarios, should be implemented to help decision-makers to plan ahead. With this application we will be able to check whether an area will be a hotspot or not by predicting the TPR rate and it also provide a way to check if a person is at risk or not at risk of having covid after getting fully vaccinated. We collected the individual details by sending out the Google form. The details are then categorized as fully vaccinated, dose 1 vaccinated, not vaccinated. This is again classified on the prediction-based category also. We use Random Forest algorithm for the predictions process. The technology we use is Machine learning.