Abhilash C
ABSTRACT
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.
- Debarati Das, Bhaskarjyoti Das, and Kavi Mahesh. 2016. A computational analysis of Mahabharata. In Proceedings of the 13th International Conference on Natural Language Processing. 219–228.Google Scholar
- Felipe Grando, Lisandro Z Granville, and Luis C Lamb. 2018. Machine learning in network centrality measures: Tutorial and outlook. ACM Computing Surveys (CSUR) 51, 5 (2018), 1–32.Google ScholarDigital Library
- COVID Graph. 2020. Visual graph explorer. https://github.com/covidgraph/visual-graph-explorerGoogle Scholar
- Lavanya Venkatagiri Hegde, Nerella Sreelakshmi, and Kavi Mahesh. 2016. Visual analytics of terrorism data. In 2016 IEEE International Conference on Cloud Computing in Emerging Markets (CCEM). IEEE, 90–94.Google ScholarCross Ref
- Luis G Moyano, Ana Paula Appel, Vagner F de Santana, Marcia Ito, and Thiago D dos Santos. 2016. GraPhys: Understanding health care insurance data through graph analytics.. In Proceedings of the 25th International Conference Companion on World Wide Web. 227–230.Google ScholarDigital Library
- Neo4j. 2020. Neo4j Graph database tool. https://neo4j.com/docs/graph-algorithms/3.5/Google Scholar
- NeoDB. 2020. Graph Algorithms - Combat-TB-NeoDB.https://combattb.org/combat-tb-neodb/graph-algorithms/Google Scholar
- Towards Data Sciecne. 2020. Data Science. https://towardsdatascience.com/which-python-data-science-package-should-i-use-when-e98c701364cGoogle Scholar
- ISI Bangalore Shiv Athreya. 2020. India COVID-19. https://www.isibang.ac.in/~athreya/incovid19/data.htmlGoogle Scholar
- Erjia Yan and Ying Ding. 2009. Applying centrality measures to impact analysis: A coauthorship network analysis. Journal of the American Society for Information Science and Technology 60, 10 (2009), 2107–2118.Google ScholarDigital Library
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