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Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2

AIM: Coronavirus Disease (COVID‐19) is spreading typically to the human population all over the world and the report suggests that scientists have been trying to map the pattern of the early transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) since it has been reported as an...

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Autores principales: Batabyal, Saikat, Batabyal, Arthita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8177899/
https://www.ncbi.nlm.nih.gov/pubmed/34136660
http://dx.doi.org/10.1002/hsr2.305
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author Batabyal, Saikat
Batabyal, Arthita
author_facet Batabyal, Saikat
Batabyal, Arthita
author_sort Batabyal, Saikat
collection PubMed
description AIM: Coronavirus Disease (COVID‐19) is spreading typically to the human population all over the world and the report suggests that scientists have been trying to map the pattern of the early transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) since it has been reported as an epidemic. Our main aim is to show if the rise‐in‐cases proceeds in a gradual and staggered manner instead of soaring quickly then we can suppress the burden of the health system. In this new case study, we are attempting to show how to control the outbreak of the infectious disease COVID‐19 via mathematical modeling. We have examined that the method of flattening the curve of the coronavirus, which increases the recovery rate of the infected individuals and also helps to decrease the number of deaths. In this pandemic situation, the countries like Russia, India, the United States of America (USA), South Africa, and the United Kingdom (UK) are leading in front where the virus is spreading in an unprecedented way. From our point of view, we establish that if these countries are following the method of flattening the curve like China and South Korea then these countries can also overcome this pandemic situation. METHOD: We propose a Susceptible, Infected, and Recovered (SIR) mathematical model of infectious disease with onset data of COVID‐19 in Wuhan and international cases, which has been propagated in Wuhan City to calculate the transmission rate of the infectious virus COVID‐19 until now. To understand the whole dynamics of the transmission rate of coronavirus, we portray time series diagrams such as growth rate diagram, flattening the pandemic curve diagram, infected and recovered rate diagram, prediction of the transmission of the disease from the available dataset in Wuhan, and internationally exported cases from Wuhan. RESULTS: We have observed that the basic reproduction number in Wuhan declined from 2.2 (95% Confidence Interval [CI] 1.15‐4.77) to 1.05 (0.41‐2.39) and the mean incubation period was 5.2 days (95% [CI], 4.1‐7.0). Interestingly the mean value lies between 2 and 2.5 for COVID‐19. The doubling time of COVID‐19 was registered 7.4 days (95% CI, 5.3‐19) in the early stages and now the value decreases to −4.9 days. Similarly, we have observed the doubling time of the epidemic in South Korea decreased to −9.6 days. Currently, the doubling time of the epidemic in Russia, India, and the USA are 19.4 days, 16.4 days, and 41 days, respectively. We have investigated the growth rate of COVID‐19 and plotted the curve flattening diagram against time. CONCLUSION: Via flattening the curve method, China and South Korea control the transmission of the fatal disease COVID‐19 in the human population. Our results show that these two countries initially sustained pandemics in a large portion of the human population in the form of virus outbreaks that basically prevented the virus from spreading further and created ways to prevent community transmission. The majority portion of the people are perfectly fine, who are quarantined strictly and never get sick, but the portion of people who have developed symptoms is quickly isolated further.
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spelling pubmed-81778992021-06-15 Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2 Batabyal, Saikat Batabyal, Arthita Health Sci Rep Research Articles AIM: Coronavirus Disease (COVID‐19) is spreading typically to the human population all over the world and the report suggests that scientists have been trying to map the pattern of the early transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) since it has been reported as an epidemic. Our main aim is to show if the rise‐in‐cases proceeds in a gradual and staggered manner instead of soaring quickly then we can suppress the burden of the health system. In this new case study, we are attempting to show how to control the outbreak of the infectious disease COVID‐19 via mathematical modeling. We have examined that the method of flattening the curve of the coronavirus, which increases the recovery rate of the infected individuals and also helps to decrease the number of deaths. In this pandemic situation, the countries like Russia, India, the United States of America (USA), South Africa, and the United Kingdom (UK) are leading in front where the virus is spreading in an unprecedented way. From our point of view, we establish that if these countries are following the method of flattening the curve like China and South Korea then these countries can also overcome this pandemic situation. METHOD: We propose a Susceptible, Infected, and Recovered (SIR) mathematical model of infectious disease with onset data of COVID‐19 in Wuhan and international cases, which has been propagated in Wuhan City to calculate the transmission rate of the infectious virus COVID‐19 until now. To understand the whole dynamics of the transmission rate of coronavirus, we portray time series diagrams such as growth rate diagram, flattening the pandemic curve diagram, infected and recovered rate diagram, prediction of the transmission of the disease from the available dataset in Wuhan, and internationally exported cases from Wuhan. RESULTS: We have observed that the basic reproduction number in Wuhan declined from 2.2 (95% Confidence Interval [CI] 1.15‐4.77) to 1.05 (0.41‐2.39) and the mean incubation period was 5.2 days (95% [CI], 4.1‐7.0). Interestingly the mean value lies between 2 and 2.5 for COVID‐19. The doubling time of COVID‐19 was registered 7.4 days (95% CI, 5.3‐19) in the early stages and now the value decreases to −4.9 days. Similarly, we have observed the doubling time of the epidemic in South Korea decreased to −9.6 days. Currently, the doubling time of the epidemic in Russia, India, and the USA are 19.4 days, 16.4 days, and 41 days, respectively. We have investigated the growth rate of COVID‐19 and plotted the curve flattening diagram against time. CONCLUSION: Via flattening the curve method, China and South Korea control the transmission of the fatal disease COVID‐19 in the human population. Our results show that these two countries initially sustained pandemics in a large portion of the human population in the form of virus outbreaks that basically prevented the virus from spreading further and created ways to prevent community transmission. The majority portion of the people are perfectly fine, who are quarantined strictly and never get sick, but the portion of people who have developed symptoms is quickly isolated further. John Wiley and Sons Inc. 2021-06-04 /pmc/articles/PMC8177899/ /pubmed/34136660 http://dx.doi.org/10.1002/hsr2.305 Text en © 2021 The Authors. Health Science Reports published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Batabyal, Saikat
Batabyal, Arthita
Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2
title Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2
title_full Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2
title_fullStr Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2
title_full_unstemmed Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2
title_short Public healthcare system capacity during COVID‐19: A computational case study of SARS‐CoV‐2
title_sort public healthcare system capacity during covid‐19: a computational case study of sars‐cov‐2
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8177899/
https://www.ncbi.nlm.nih.gov/pubmed/34136660
http://dx.doi.org/10.1002/hsr2.305
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