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Prediction of the COVID-19 transmission: a case study of Pakistan

The world has suffered a lot from COVID-19 and is still on the verge of a new outbreak. The infected regions of coronavirus have been classified into four categories: SIRD model, (1) suspected, (2) infected, (3) recovered, and (4) deaths, where the COVID-19 transmission is evaluated using a stochast...

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Autores principales: Sabir, Qurat Ul An, Shafqat, Ambreen, Aslam, Muhammad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244643/
https://www.ncbi.nlm.nih.gov/pubmed/37203211
http://dx.doi.org/10.1017/S0950268823000730
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author Sabir, Qurat Ul An
Shafqat, Ambreen
Aslam, Muhammad
author_facet Sabir, Qurat Ul An
Shafqat, Ambreen
Aslam, Muhammad
author_sort Sabir, Qurat Ul An
collection PubMed
description The world has suffered a lot from COVID-19 and is still on the verge of a new outbreak. The infected regions of coronavirus have been classified into four categories: SIRD model, (1) suspected, (2) infected, (3) recovered, and (4) deaths, where the COVID-19 transmission is evaluated using a stochastic model. A study in Pakistan modeled COVID-19 data using stochastic models like PRM and NBR. The findings were evaluated based on these models, as the country faces its third wave of the virus. Our study predicts COVID-19 casualties in Pakistan using a count data model. We’ve used a Poisson process, SIRD-type framework, and a stochastic model to find the solution. We took data from NCOC (National Command and Operation Center) website to choose the best prediction model based on all provinces of Pakistan, On the values of log L and AIC criteria. The best model among PRM and NBR is NBR because when over-dispersion happens; NBR is the best model for modelling the total suspected, infected, and recovered COVID-19 occurrences in Pakistan as it has the maximum log L and smallest AIC of the other count regression model. It was also observed that the active and critical cases positively and significantly affect COVID-19-related deaths in Pakistan using the NBR model.
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spelling pubmed-102446432023-06-08 Prediction of the COVID-19 transmission: a case study of Pakistan Sabir, Qurat Ul An Shafqat, Ambreen Aslam, Muhammad Epidemiol Infect Original Paper The world has suffered a lot from COVID-19 and is still on the verge of a new outbreak. The infected regions of coronavirus have been classified into four categories: SIRD model, (1) suspected, (2) infected, (3) recovered, and (4) deaths, where the COVID-19 transmission is evaluated using a stochastic model. A study in Pakistan modeled COVID-19 data using stochastic models like PRM and NBR. The findings were evaluated based on these models, as the country faces its third wave of the virus. Our study predicts COVID-19 casualties in Pakistan using a count data model. We’ve used a Poisson process, SIRD-type framework, and a stochastic model to find the solution. We took data from NCOC (National Command and Operation Center) website to choose the best prediction model based on all provinces of Pakistan, On the values of log L and AIC criteria. The best model among PRM and NBR is NBR because when over-dispersion happens; NBR is the best model for modelling the total suspected, infected, and recovered COVID-19 occurrences in Pakistan as it has the maximum log L and smallest AIC of the other count regression model. It was also observed that the active and critical cases positively and significantly affect COVID-19-related deaths in Pakistan using the NBR model. Cambridge University Press 2023-05-19 /pmc/articles/PMC10244643/ /pubmed/37203211 http://dx.doi.org/10.1017/S0950268823000730 Text en © The Author(s) 2023 https://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, provided the original article is properly cited.
spellingShingle Original Paper
Sabir, Qurat Ul An
Shafqat, Ambreen
Aslam, Muhammad
Prediction of the COVID-19 transmission: a case study of Pakistan
title Prediction of the COVID-19 transmission: a case study of Pakistan
title_full Prediction of the COVID-19 transmission: a case study of Pakistan
title_fullStr Prediction of the COVID-19 transmission: a case study of Pakistan
title_full_unstemmed Prediction of the COVID-19 transmission: a case study of Pakistan
title_short Prediction of the COVID-19 transmission: a case study of Pakistan
title_sort prediction of the covid-19 transmission: a case study of pakistan
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244643/
https://www.ncbi.nlm.nih.gov/pubmed/37203211
http://dx.doi.org/10.1017/S0950268823000730
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