Graph Analytics Applied to COVID19 Karnataka State Dataset

Abhilash, C.; Mahesh, K.

The coronavirus pandemic, or COVID19, has emerged as a pandemic. Handling this pandemic situation is a fundamental challenge to the concerned authorities. However, not all states of India have had the same position or spread counts. The significant impact was from Lockdown 1.0, which controlled the growth of the exponential curve. Here we have considered the Karnataka state data referring to the Ministry of Health and Family welfare department, GoK. This paper presents a case study on the state pandemic "coronavirus"named "COVID19"growth curves for 30 Karnataka state districts with deep insights using graph-based analytical techniques. The study also explores the reasons for the spread and deaths, considering the KaTrace dataset. In graph-based analytics, certain concepts that may be explored on their own and in combination with other attributes yield interestingness in the dataset. Interesting insights are derived considering key attributes and relationships like age, gender, duration with reason, and the district of origin. The COVI19 has resulted in the closing of border segments and made everyone stay-at-home for a certain amount of time as a preventive measures to control the spread. We have discussed the usability of centrality measures in patient's spread analysis, a useful indicator for impact analysis, and to implement preventive measures. © 2021 ACM.