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Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India

The Severe Acute Respiratory Syndrome Coronavirus 2 (SAR-CoV-2) is the strain of coronavirus that causes coronavirus disease (COVID-19), the respiratory illness that resulted in COVID-19 pandemic in early December 2019. Due to lack of knowledge of the epidemiological cycle and absence of any type of...

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Autores principales: Shringi, Sakshi, Sharma, Harish, Rathie, Pushpa Narayan, Bansal, Jagdish Chand, Nagar, Atulya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120454/
https://www.ncbi.nlm.nih.gov/pubmed/34007123
http://dx.doi.org/10.1016/j.chaos.2021.111039
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author Shringi, Sakshi
Sharma, Harish
Rathie, Pushpa Narayan
Bansal, Jagdish Chand
Nagar, Atulya
author_facet Shringi, Sakshi
Sharma, Harish
Rathie, Pushpa Narayan
Bansal, Jagdish Chand
Nagar, Atulya
author_sort Shringi, Sakshi
collection PubMed
description The Severe Acute Respiratory Syndrome Coronavirus 2 (SAR-CoV-2) is the strain of coronavirus that causes coronavirus disease (COVID-19), the respiratory illness that resulted in COVID-19 pandemic in early December 2019. Due to lack of knowledge of the epidemiological cycle and absence of any type of vaccine or medications, the Government issued various non-pharmacological measures to end the COVID-19 pandemic. Several researchers applied the Susceptible-Infected-Recovered-Deceased (SIRD) compartmental epidemiology process model to identifying the effect of different governments intervention methods enforced to mollify the spread of COVID-19 epidemic. In this paper, we aim to provide a modified SIRD model for COVID-19 spread prediction. We have analyzed the data of the Northern and Southern states of India from January 30, 2020, to October 24, 2020 using the proposed SIRD model and existing SIRD model. We have made the predictions with reasonable assumptions based on real data, considering that the precise course of an epidemic is highly dependent on how and when quarantine, isolation, and precautionary measures were imposed. The proposed method gives better approximation values of new cases, R0 (Reproductive Number), daily deaths, daily infectious, transmission rate, and recovered individuals.Through the analysis of the reported results, the proposed SIRD model can be an effective method for investigating the effect of government interventions on COVID-19 associated transmission and mortality rate at the time of epidemic.
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spelling pubmed-81204542021-05-14 Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India Shringi, Sakshi Sharma, Harish Rathie, Pushpa Narayan Bansal, Jagdish Chand Nagar, Atulya Chaos Solitons Fractals Article The Severe Acute Respiratory Syndrome Coronavirus 2 (SAR-CoV-2) is the strain of coronavirus that causes coronavirus disease (COVID-19), the respiratory illness that resulted in COVID-19 pandemic in early December 2019. Due to lack of knowledge of the epidemiological cycle and absence of any type of vaccine or medications, the Government issued various non-pharmacological measures to end the COVID-19 pandemic. Several researchers applied the Susceptible-Infected-Recovered-Deceased (SIRD) compartmental epidemiology process model to identifying the effect of different governments intervention methods enforced to mollify the spread of COVID-19 epidemic. In this paper, we aim to provide a modified SIRD model for COVID-19 spread prediction. We have analyzed the data of the Northern and Southern states of India from January 30, 2020, to October 24, 2020 using the proposed SIRD model and existing SIRD model. We have made the predictions with reasonable assumptions based on real data, considering that the precise course of an epidemic is highly dependent on how and when quarantine, isolation, and precautionary measures were imposed. The proposed method gives better approximation values of new cases, R0 (Reproductive Number), daily deaths, daily infectious, transmission rate, and recovered individuals.Through the analysis of the reported results, the proposed SIRD model can be an effective method for investigating the effect of government interventions on COVID-19 associated transmission and mortality rate at the time of epidemic. Elsevier Ltd. 2021-07 2021-05-14 /pmc/articles/PMC8120454/ /pubmed/34007123 http://dx.doi.org/10.1016/j.chaos.2021.111039 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Shringi, Sakshi
Sharma, Harish
Rathie, Pushpa Narayan
Bansal, Jagdish Chand
Nagar, Atulya
Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India
title Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India
title_full Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India
title_fullStr Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India
title_full_unstemmed Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India
title_short Modified SIRD Model for COVID-19 Spread Prediction for Northern and Southern States of India
title_sort modified sird model for covid-19 spread prediction for northern and southern states of india
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120454/
https://www.ncbi.nlm.nih.gov/pubmed/34007123
http://dx.doi.org/10.1016/j.chaos.2021.111039
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