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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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 2661-8907 2662-995X 2661-8907 |
DOI: | 10.1007/s42979-024-03317-y |