Susceptibility Analysis of Novel Corona Virus Using Hadoop Distributed File System

Samanta, Pravin Kumar; Mukherjee, Soumyadev; Rout, Nirmal Kumar

The Novel Corona Virus, COVID-19 is a major setback to the progress of the nation. The year 2020 has witnessed a disappointing beginning with this deadly virus having taken away many innocent lives. The COVID-19, which happens because of the virus Corona, showcases symptoms which are mild and at times doesn’t even reflect any. However, a small section falls severely ill, and some eventually perish. This proposed research work is implemented to identify who is having the highest risk of serious illness and who are more susceptible to this disease. In this proposed research, a huge amount of semi structured healthcare data is stored and processed which are collected from healthcare dataset. Hence, in the proposed work ‘Hadoop’ is utilized for processing the data gathered. The input data is processed using MapReduce and finally the result is loaded into the Hadoop Distributed File System (HDFS). After details analysis and justification with the help of ‘Hadoop’ proposed work has predicted many possible susceptible cases which can help to reduce the number of fatalities and also save human lives.