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2023 | OriginalPaper | Chapter

Pandemic Effect of COVID-19: Identification, Present Scenario, and Preventive Measures Using Machine Learning Model

Authors : A. Nazar Ali, Jai Ganesh, A. T. Sankara Subramanian, L. Nagarajan, G. R. Subhashree

Published in: System Design for Epidemics Using Machine Learning and Deep Learning

Publisher: Springer International Publishing

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Abstract

Mutation in viruses is known to be an unavoidable phenomenon. But at times, it may become a life-threatening pandemic just like in the case of the 2019 novel coronavirus, formally named as SARS-CoV-2, which consumed around 36,405 lives out of 750,890 infections as per the data available with the World Health Organization as of the end of March 2020. Found to be from the family of earlier known outbreaks (SARS and MERS) of the twenty-first century, it has now become a public health emergency of international concern (PHEIC). Countries around the world have spent millions of dollars to get a positive sign of finding vaccines, but still it remains an unsolved mystery. Even though there is implementation of strict lockdown measures from several affected countries around the globe, the trend line of COVID-19 epidemic is still increasing exponentially. Being in this scenario, this paper deals about the outbreak of 2019-nCoV and its structure, growing stages, global statistics, transmission modes, and most possible precautionary methods and also its emphasis on creating public awareness by answering few key clarifications about novel beta coronavirus disease. The machine learning method used in this study was taught using records from COVID-positive tests. Results from a week were included in the testing set (individuals who were confirmed to have COVID-19). This proposed model predicted the COVID-19 lab findings with high accuracy by only using eight numeric data, age 60, knowing contact with an infected individual, and the existence of five early clinical signs.

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Metadata
Title
Pandemic Effect of COVID-19: Identification, Present Scenario, and Preventive Measures Using Machine Learning Model
Authors
A. Nazar Ali
Jai Ganesh
A. T. Sankara Subramanian
L. Nagarajan
G. R. Subhashree
Copyright Year
2023
DOI
https://doi.org/10.1007/978-3-031-19752-9_1