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An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model
OBJECTIVE: The coronavirus disease (COVID-19) pandemic was initiated in Wuhan Province of mainland China in December 2019 and has spread over the world. This study analyzes the effects of COVID-19 based on likely positive cases and fatality in India during and after the lockdown period from March 24...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985632/ https://www.ncbi.nlm.nih.gov/pubmed/33203489 http://dx.doi.org/10.1017/dmp.2020.444 |
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author | Tulshyan, Vatsal Sharma, Dolly Mittal, Mamta |
author_facet | Tulshyan, Vatsal Sharma, Dolly Mittal, Mamta |
author_sort | Tulshyan, Vatsal |
collection | PubMed |
description | OBJECTIVE: The coronavirus disease (COVID-19) pandemic was initiated in Wuhan Province of mainland China in December 2019 and has spread over the world. This study analyzes the effects of COVID-19 based on likely positive cases and fatality in India during and after the lockdown period from March 24, 2020, to May 24, 2020. METHODS: Python has been used as the main programming language for data analysis and forecasting using the Prophet model, a time series analysis model. The data set has been preprocessed by grouping together the days for total numbers of cases and deaths on few selected dates and removing missing values present in some states. RESULTS: The Prophet model performs better in terms of precision on the real data. Prediction depicts that, during the lockdown, the total cases were rising but in a controlled manner with an accuracy of 87%. After the relaxation of lockdown rules, the predictions have shown an obstreperous situation with an accuracy of 60%. CONCLUSION: The resilience could have been better if the lockdown with strict norms was continued without much relaxation. The situation after lockdown has been found to be uncertain as observed by the experimental study conducted in this work. |
format | Online Article Text |
id | pubmed-7985632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-79856322021-03-25 An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model Tulshyan, Vatsal Sharma, Dolly Mittal, Mamta Disaster Med Public Health Prep Original Research OBJECTIVE: The coronavirus disease (COVID-19) pandemic was initiated in Wuhan Province of mainland China in December 2019 and has spread over the world. This study analyzes the effects of COVID-19 based on likely positive cases and fatality in India during and after the lockdown period from March 24, 2020, to May 24, 2020. METHODS: Python has been used as the main programming language for data analysis and forecasting using the Prophet model, a time series analysis model. The data set has been preprocessed by grouping together the days for total numbers of cases and deaths on few selected dates and removing missing values present in some states. RESULTS: The Prophet model performs better in terms of precision on the real data. Prediction depicts that, during the lockdown, the total cases were rising but in a controlled manner with an accuracy of 87%. After the relaxation of lockdown rules, the predictions have shown an obstreperous situation with an accuracy of 60%. CONCLUSION: The resilience could have been better if the lockdown with strict norms was continued without much relaxation. The situation after lockdown has been found to be uncertain as observed by the experimental study conducted in this work. Cambridge University Press 2020-11-18 /pmc/articles/PMC7985632/ /pubmed/33203489 http://dx.doi.org/10.1017/dmp.2020.444 Text en © Society for Disaster Medicine and Public Health, Inc. 2020 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Tulshyan, Vatsal Sharma, Dolly Mittal, Mamta An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model |
title | An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model |
title_full | An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model |
title_fullStr | An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model |
title_full_unstemmed | An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model |
title_short | An Eye on the Future of COVID-19: Prediction of Likely Positive Cases and Fatality in India over a 30-Day Horizon Using the Prophet Model |
title_sort | eye on the future of covid-19: prediction of likely positive cases and fatality in india over a 30-day horizon using the prophet model |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7985632/ https://www.ncbi.nlm.nih.gov/pubmed/33203489 http://dx.doi.org/10.1017/dmp.2020.444 |
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