A Prediction Model - Comparative Analysis and Effective Visualization for COVID-19 Dataset

Abstract:

Covid-19 is a dangerous infection which is caused by SAR-COV 2 (stands for severe acute respiratory syndrome coronavirus 2). The first known coronavirus case was found in Wuhan, China in 2019. On 11th March 2020 the World health organization declared covid-19 as an epidemic and from that point of time it has been mutated into various variants and thus causing a lot of health issues among the people. It has affected the people as well as the economy of the country in a negative way. Major symptoms which were recognize from the people who were affected from the covid includes cough, fatigue, constant fever, difficulty during breathing and loss of smell and taste. In this study, an overview of analysis of the variants of the coronavirus as well as impact of covid-19 in various countries has been studied in a detailed manner. In order to show the impact of Covid-19 on a clear picture, the study has been visualized with the help of various charts and figures in order to make it easy to understand. Techniques which provide effective visualization is discussed. A comparison of the prediction models with deep learning algorithms is also mentioned in this paper. This study would be helpful for covid-19 research as it gives a clear view of trends and different aspects of covid-19 as well as a detailed view on the variants which were formed.

• Periodical: Advances in Science and Technology (Volume 124)
• Pages: 525-535
• DOI: https://doi.org/10.4028/p-w6dra9
• Online since: February 2023
• Authors: S. Vishal*, M. Uma, S. Metilda Florence
• Keywords: Bi-LSTM, COVID-19, Data Visualization, Exploratory Data Analysis (EDA), GRU, LSTM, Predictive Analytics, Prophet

References

[1] S. Latif et al., Leveraging Data Science to Combat COVID-19: A Comprehensive Review,, in IEEE Transactions on Artificial Intelligence, vol. 1, no. 1, pp.85-103, Aug. 2020,.

[2] R. Chauhan, P. Goel, V. Kumar, N. Soni and N. singh, Understanding Covid-19 using data visualization,, 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), 2021, pp.555-559,.

DOI: 10.1109/icacite51222.2021.9404700

[3] C. K. Leung, Y. Chen, C. S. H. Hoi, S. Shang, Y. Wen and A. Cuzzocrea, Big Data Visualization and Visual Analytics of COVID-19 Data,, 2020 24th International Conference Information Visualisation (IV), 2020, pp.415-420,.

DOI: 10.1109/iv51561.2020.00073

[4] Y. Zhou et al., Visual Analysis and Exploration of COVID-19 Based on Multi-source Heterogeneous Data,, 2020 International Conferences on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics), 2020, pp.62-69,.

DOI: 10.1109/ithings-greencom-cpscom-smartdata-cybermatics50389.2020.00029

[5] Aurelle Tchagna Kouanou, Thomas Mih Attia, Cyrille Feudjio, Anges Fleurio Djeumo, Adèle Ngo Mouelas, Mendel Patrice Nzogang, Christian Tchito Tchapga, Daniel Tchiotsop, An Overview of Supervised Machine Learning Methods and Data Analysis for COVID-19 Detection,, Journal of Healthcare Engineering, vol. 2021, Article ID 4733167, 18 pages, 2021. https://doi.org/10.1155/202 1/4733167.

DOI: 10.1155/2021/4733167

[6] N. Darapaneni, P. Jain, R. Khattar, M. Chawla, R. Vaish and A. R. Paduri, Analysis and Prediction of COVID-19 Pandemic in India,, 2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN), 2020, pp.291-296,.

DOI: 10.1109/icacccn51052.2020.9362817

[7] A. Abdullha and S. Abujar, COVID-19: Data Analysis and the situation Prediction Using Machine Learning Based on Bangladesh perspective,, 2020 15th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP), 2020, pp.1-8,.

DOI: 10.1109/isai-nlp51646.2020.9376812

[8] S. K. Saini, V. Dhull, S. Singh and A. Sharma, Visual Exploratory Data Analysis of COVID-19 Pandemic,, 2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2020, pp.1-6,.

DOI: 10.1109/icraie51050.2020.9358331

[9] F. Clement, A. Kaur, M. Sedghi, D. Krishnaswamy and K. Punithakumar, Interactive Data Driven Visualization for COVID-19 with Trends, Analytics and Forecasting,, 2020 24th International Conference Information Visualisation (IV), 2020, pp.593-598,.

DOI: 10.1109/iv51561.2020.00101

[10] Z. Pan, D. Mehta, A. Tiwari, S. Ireddy, Z. Yang and F. Jin, An Interactive Platform to Track Global COVID-19 Epidemic,, 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2020, pp.948-951,.

DOI: 10.1109/asonam49781.2020.9381436