A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic

We present new data analytics-based predictions results that can help governments to plan their future actions and also help medical services to be better prepared for the future. Our system can predict new corona cases with 99.82% accuracy using susceptible infected recovered (SIR) model. We have p...

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Autores principales: Shah, Vruddhi, Shelke, Ankita, Parab, Mamata, Shah, Jainam, Mehendale, Ninad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Research Paper
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8019340/
https://www.ncbi.nlm.nih.gov/pubmed/33841583
http://dx.doi.org/10.1007/s12065-021-00600-2
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author Shah, Vruddhi
Shelke, Ankita
Parab, Mamata
Shah, Jainam
Mehendale, Ninad
author_facet Shah, Vruddhi
Shelke, Ankita
Parab, Mamata
Shah, Jainam
Mehendale, Ninad
author_sort Shah, Vruddhi
collection PubMed
description We present new data analytics-based predictions results that can help governments to plan their future actions and also help medical services to be better prepared for the future. Our system can predict new corona cases with 99.82% accuracy using susceptible infected recovered (SIR) model. We have predicted the results of new COVID cases per day for dense and highly populated country i.e. India. We found that traditional statistical methods will not work efficiently as they do not consider the limited population in a particular country. Using the data analytics-based curve we predicted four most likely possibilities for the number of new cases in India. Hence, we expect that the results mentioned in the manuscript help people to better understand the progress of this disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12065-021-00600-2.
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spelling pubmed-80193402021-04-06 A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic Shah, Vruddhi Shelke, Ankita Parab, Mamata Shah, Jainam Mehendale, Ninad Evol Intell Research Paper We present new data analytics-based predictions results that can help governments to plan their future actions and also help medical services to be better prepared for the future. Our system can predict new corona cases with 99.82% accuracy using susceptible infected recovered (SIR) model. We have predicted the results of new COVID cases per day for dense and highly populated country i.e. India. We found that traditional statistical methods will not work efficiently as they do not consider the limited population in a particular country. Using the data analytics-based curve we predicted four most likely possibilities for the number of new cases in India. Hence, we expect that the results mentioned in the manuscript help people to better understand the progress of this disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12065-021-00600-2. Springer Berlin Heidelberg 2021-04-03 2022 /pmc/articles/PMC8019340/ /pubmed/33841583 http://dx.doi.org/10.1007/s12065-021-00600-2 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Research Paper
Shah, Vruddhi
Shelke, Ankita
Parab, Mamata
Shah, Jainam
Mehendale, Ninad
A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic
title A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic
title_full A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic
title_fullStr A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic
title_full_unstemmed A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic
title_short A statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic
title_sort statistical and deep learning-based daily infected count prediction system for the coronavirus pandemic
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8019340/
https://www.ncbi.nlm.nih.gov/pubmed/33841583
http://dx.doi.org/10.1007/s12065-021-00600-2
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