Cargando…
Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread
COVID-19 disease has come up as a life-threatening outbreak at end of 2019. It has impacted almost all countries in the world. The major source of COVID-19 is a novel beta coronavirus. COVID-19 had a great impact on world throughout the year 2020. Now, the situation is becoming normal due to the inv...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8220443/ https://www.ncbi.nlm.nih.gov/pubmed/34178570 http://dx.doi.org/10.1007/s13369-021-05827-w |
_version_ | 1783711148754862080 |
---|---|
author | Chandra, Saroj Kumar Bajpai, Manish Kumar |
author_facet | Chandra, Saroj Kumar Bajpai, Manish Kumar |
author_sort | Chandra, Saroj Kumar |
collection | PubMed |
description | COVID-19 disease has come up as a life-threatening outbreak at end of 2019. It has impacted almost all countries in the world. The major source of COVID-19 is a novel beta coronavirus. COVID-19 had a great impact on world throughout the year 2020. Now, the situation is becoming normal due to the invention of the vaccine. All major countries started large vaccination drives. Mathematical models are used to study the impact of different measures used to decrease pandemics. Mathematical models such as susceptible–infected–removed model and susceptible–exposed–infected–removed are used to predict the spread of diseases. But these models are not suitable to predict COVID-19 spread due to various preventive measures (social distancing and quarantine) applied to reduce spread. Hence, in the present manuscript, a novel fractional mathematical model with a social distancing parameter has been proposed to provide early COVID-19 spread estimation. Fractional calculus provides flexibility in choosing arbitrary order of derivative which controls data sensitivity. The model has been validated with real data set. It has been observed that the proposed model is highly accurate in spread estimation. |
format | Online Article Text |
id | pubmed-8220443 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-82204432021-06-23 Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread Chandra, Saroj Kumar Bajpai, Manish Kumar Arab J Sci Eng Research Article-Biological Sciences COVID-19 disease has come up as a life-threatening outbreak at end of 2019. It has impacted almost all countries in the world. The major source of COVID-19 is a novel beta coronavirus. COVID-19 had a great impact on world throughout the year 2020. Now, the situation is becoming normal due to the invention of the vaccine. All major countries started large vaccination drives. Mathematical models are used to study the impact of different measures used to decrease pandemics. Mathematical models such as susceptible–infected–removed model and susceptible–exposed–infected–removed are used to predict the spread of diseases. But these models are not suitable to predict COVID-19 spread due to various preventive measures (social distancing and quarantine) applied to reduce spread. Hence, in the present manuscript, a novel fractional mathematical model with a social distancing parameter has been proposed to provide early COVID-19 spread estimation. Fractional calculus provides flexibility in choosing arbitrary order of derivative which controls data sensitivity. The model has been validated with real data set. It has been observed that the proposed model is highly accurate in spread estimation. Springer Berlin Heidelberg 2021-06-23 2022 /pmc/articles/PMC8220443/ /pubmed/34178570 http://dx.doi.org/10.1007/s13369-021-05827-w Text en © King Fahd University of Petroleum & Minerals 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 Article-Biological Sciences Chandra, Saroj Kumar Bajpai, Manish Kumar Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread |
title | Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread |
title_full | Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread |
title_fullStr | Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread |
title_full_unstemmed | Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread |
title_short | Fractional Model with Social Distancing Parameter for Early Estimation of COVID-19 Spread |
title_sort | fractional model with social distancing parameter for early estimation of covid-19 spread |
topic | Research Article-Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8220443/ https://www.ncbi.nlm.nih.gov/pubmed/34178570 http://dx.doi.org/10.1007/s13369-021-05827-w |
work_keys_str_mv | AT chandrasarojkumar fractionalmodelwithsocialdistancingparameterforearlyestimationofcovid19spread AT bajpaimanishkumar fractionalmodelwithsocialdistancingparameterforearlyestimationofcovid19spread |