Paper Info
Title
Real-Time Measurement Of The Uncertain Epidemiological Appearances Of Covid-19 Infections
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 upto-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. (C) 2020 Elsevier B.V. All rights reserved.
Year
DOI
Venue
2021
10.1016/j.asoc.2020.107039
APPLIED SOFT COMPUTING
Keywords
DocType
Volume
COVID-19, Epidemiology, Outbreak, Deep learning, LSTM
Journal
101
ISSN
Citations 
PageRank 
1568-4946
0
0.34
References 
Authors
7
6
Name
Order
Citations
PageRank
Meenu Gupta1132.03
Rachna Jain200.34
Soham Taneja300.68
Gopal Chaudhary400.68
Manju Khari501.35
Elena Verdú69611.85