A Novel Approach for Tracking the Spread of COVID-19 Disease and Discovering the Symptom Patterns of COVID-19 Patients Using Association Rule Mining

Coronavirus disease also known as COVID-19 is an infectious disease which is caused by the SARS-CoV-2 virus. People who get infected by the virus will experience respiratory diseases and might recover easily, but few will become seriously ill and require medical attention. Top researchers from across the world are working on cures for it. A lot of research is being conducted on the spread of the disease and cures for it. Only developing cure for this virus would not be enough. With the current technology, advanced data mining techniques can be used to track and trace the virus which is quicker and faster solution which will change the course of the pandemic. The rate at which people are getting affected, tracking becomes vital. It is necessary to alert a person when they are near the infected person. With the help of GPS and Bluetooth technologies, the users are alerted. Data mining also known as knowledge discovery of data, is the process of analyzing huge chunks of data in different ways and converting it into useful information. This process plays a significant role in various fields with vast data. Healthcare industries generate and store large amounts of data like name of the patient, disease, diagnosis method, resources, this is where data mining techniques can be applied. So the data which can be obtained from COVID datasets can be used by healthcare industries to improve the tracking and spreading of COVID-19. We propose a method to identity patterns using the factors in the dataset which can be used to predict if a person having similar symptoms is affected by the virus or not. Clustering, association rule mining, classification and other various data science concepts are used to analyze the spread of COVID in India.