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...

Full description

Saved in:
Bibliographic Details
Published in:Epidemiology and infection 2023-05, Vol.151, p.e89-e89, Article e89
Main Authors: Sabir, Qurat Ul An, Shafqat, Ambreen, Aslam, Muhammad
Format: Article
Language:English
Subjects:
Binomial distribution
Case reports
Casualties
Coronaviruses
COVID-19
COVID-19 - epidemiology
Datasets
Disease Outbreaks
Disease transmission
Epidemics
Fatalities
Humans
Infections
Middle East respiratory syndrome
Mortality
Original Paper
Pakistan - epidemiology
Pandemics
Prediction models
Regression analysis
Regression models
SARS-CoV-2
Statistical analysis
Statistical methods
Stochastic models
Stochastic processes
Stochasticity
Viral diseases
Viruses
Websites
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0950-2688
1469-4409
DOI:10.1017/S0950268823000730