Uncovering the Hidden Patterns of the COVID-19 Global Pandemic: An in-Depth Data Analytics Approach
COVID-19 is a highly infectious respiratory illness caused by the novel coronavirus. It was first identified in Wuhan, China in December 2019 and has since spread globally, infecting and killing a vast number of people, leading to a worldwide pandemic. The pandemic has left the world in disarray. We...
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| Veröffentlicht in: | SN computer science 2024-10, Vol.5 (8), p.981, Article 981 |
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| creator | Sarobin, M. Vergin Raja Rathore, Jinen Mishra, Rajat Moolya, Vinay Vittal Seth, Yash |
| description | COVID-19 is a highly infectious respiratory illness caused by the novel coronavirus. It was first identified in Wuhan, China in December 2019 and has since spread globally, infecting and killing a vast number of people, leading to a worldwide pandemic. The pandemic has left the world in disarray. We wished to apply data analytics and regression models to understand and study the data – OwiD (Our World in Data) real time covid dataset - to analyse and draw trends and factors that led to the widespread of the virus. Doing so, allows us to identify key factors and trends that played a vital role in the rapid spread of the virus. We can thus determine the underlying hidden patterns of key factors. This will help provide a better understanding and determine the potential reasons COVID-19 took the world by storm with its fast-paced spread. |
| doi_str_mv | 10.1007/s42979-024-03317-y |
| format | Article |
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| subjects | Computer Imaging Computer Science Computer Systems Organization and Communication Networks Coronaviruses Data analysis Data Structures and Information Theory Epidemics Immunization Information Systems and Communication Service Original Research Pandemics Pattern Recognition and Graphics Regression models Software Engineering/Programming and Operating Systems Trends Viral diseases Vision |
| title | Uncovering the Hidden Patterns of the COVID-19 Global Pandemic: An in-Depth Data Analytics Approach |
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