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Stochastic models on the transmission of novel COVID-19
New diseases have always been part of humanity’s world, and some of them had created severe threat to human kind and challenge to the researchers and medical practitioners. The deadly novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome- coronavirus -2) said to be COVID-19, the name given...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer India
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419671/ http://dx.doi.org/10.1007/s13198-021-01312-7 |
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author | Mishra, Bimal Kumar |
author_facet | Mishra, Bimal Kumar |
author_sort | Mishra, Bimal Kumar |
collection | PubMed |
description | New diseases have always been part of humanity’s world, and some of them had created severe threat to human kind and challenge to the researchers and medical practitioners. The deadly novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome- coronavirus -2) said to be COVID-19, the name given by WHO on February 11, 2020, is presently the most disastrous infectious disease. In the present paper our basic objective is to assess the risk of spreading the disease in human population and is measured in terms of probability. The proposed stochastic models help us to understand the probability of infection to n number of customers when these customers have spent time t in any system, say, shopping mall or public transportation or restaurant. Stochastic models are developed with arrival rate of the customers towards the system to be considered as a Poisson distribution and service time following an exponential distribution. A special case of cardiac centre is considered in this paper, where the risk of COVID-19 is highly contagion, with limited number of beds and doctors. |
format | Online Article Text |
id | pubmed-8419671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer India |
record_format | MEDLINE/PubMed |
spelling | pubmed-84196712021-09-07 Stochastic models on the transmission of novel COVID-19 Mishra, Bimal Kumar Int J Syst Assur Eng Manag Original Article New diseases have always been part of humanity’s world, and some of them had created severe threat to human kind and challenge to the researchers and medical practitioners. The deadly novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome- coronavirus -2) said to be COVID-19, the name given by WHO on February 11, 2020, is presently the most disastrous infectious disease. In the present paper our basic objective is to assess the risk of spreading the disease in human population and is measured in terms of probability. The proposed stochastic models help us to understand the probability of infection to n number of customers when these customers have spent time t in any system, say, shopping mall or public transportation or restaurant. Stochastic models are developed with arrival rate of the customers towards the system to be considered as a Poisson distribution and service time following an exponential distribution. A special case of cardiac centre is considered in this paper, where the risk of COVID-19 is highly contagion, with limited number of beds and doctors. Springer India 2021-09-06 2022 /pmc/articles/PMC8419671/ http://dx.doi.org/10.1007/s13198-021-01312-7 Text en © The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden 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 | Original Article Mishra, Bimal Kumar Stochastic models on the transmission of novel COVID-19 |
title | Stochastic models on the transmission of novel COVID-19 |
title_full | Stochastic models on the transmission of novel COVID-19 |
title_fullStr | Stochastic models on the transmission of novel COVID-19 |
title_full_unstemmed | Stochastic models on the transmission of novel COVID-19 |
title_short | Stochastic models on the transmission of novel COVID-19 |
title_sort | stochastic models on the transmission of novel covid-19 |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8419671/ http://dx.doi.org/10.1007/s13198-021-01312-7 |
work_keys_str_mv | AT mishrabimalkumar stochasticmodelsonthetransmissionofnovelcovid19 |