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Real-time measurement of the uncertain epidemiological appearances of COVID-19 infections.

Authors :
Gupta, Meenu
Jain, Rachna
Taneja, Soham
Chaudhary, Gopal
Khari, Manju
Verdú, Elena
Source :
Applied Soft Computing; Mar2021, Vol. 101, pN.PAG-N.PAG, 1p
Publication Year :
2021

Abstract

Virus diseases are a continued threat to human health in both community and healthcare settings. The current virus disease COVID-19 outbreak raises an unparalleled public health issue for the world at large. Wuhan is the city in China from where this virus came first and, after some time the whole world was affected by this severe disease. It is a challenge for every country's people and higher authorities to fight with this battle due to the insufficient number of resources. On-going assessment of the epidemiological features and future impacts of the COVID-19 disease is required to stay up-to-date of any changes to its spread dynamics and foresee needed resources and consequences in different aspects as social or economic ones. This paper proposes a prediction model of confirmed and death cases of COVID-19. The model is based on a deep learning algorithm with two long short-term memory (LSTM) layers. We consider the available infection cases of COVID-19 in India from January 22, 2020, till October 9, 2020, and parameterize the model. The proposed model is an inference to obtain predicted coronavirus cases and deaths for the next 30 days, taking the data of the previous 260 days of duration of the pandemic. The proposed deep learning model has been compared with other popular prediction methods (Support Vector Machine, Decision Tree and Random Forest) showing a lower normalized RMSE. This work also compares COVID-19 with other previous diseases (SARS, MERS, h1n1, Ebola, and 2019-nCoV). Based on the mortality rate and virus spread, this study concludes that the novel coronavirus (COVID-19) is more dangerous than other diseases. • A predictive model of confirmed and death cases of COVID-19 is proposed. • The predictive model is a deep learning model based on LSTM networks. • COVID-19 cases and deaths for the next 30 days are predicted. • The spread and mortality rates of five different virus diseases are compared. • It is concluded that COVID-19 is more dangerous than SARS, MERS, h1n1, and Ebola. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15684946
Volume :
101
Database :
Supplemental Index
Journal :
Applied Soft Computing
Publication Type :
Academic Journal
Accession number :
148867147
Full Text :
https://doi.org/10.1016/j.asoc.2020.107039