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COVID-19 Time Series Prediction and Lockdown Effectiveness
6th International Conference on Computational Intelligence in Data Mining, ICCIDM 2021 ; 281:211-223, 2022.
Article in English | Scopus | ID: covidwho-1872353
ABSTRACT
The origin of the COVID-19 pandemic lies at the wet market of Wuhan, China, which reportedly incepted from a person's consumption of a wild animal that was already infected with the disease. Since then, the virus has spread worldwide like wildfire and poses a major threat to the entirety of the human species itself. Coronavirus causes respiratory tract infections that can range from mild to lethal. This paper discusses the use of data analysis and machine learning to draw from the implications of the growth patterns of previous pandemics in general and projects that specifically predict future scenarios of COVID-19. It also compares and measures some of the present pandemic’s short- and long-span predictions with the equivalent real-world data observed during and after the said span. It also attempts to analyze how effective the lockdown has been across various countries and what India specifically must do to prevent a catastrophic outcome. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Prognostic study Language: English Journal: 6th International Conference on Computational Intelligence in Data Mining, ICCIDM 2021 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Experimental Studies / Prognostic study Language: English Journal: 6th International Conference on Computational Intelligence in Data Mining, ICCIDM 2021 Year: 2022 Document Type: Article