ItemArticle

An Enhanced SEIR Model for Prediction of COVID-19 with Vaccination Effect

Title
An Enhanced SEIR Model for Prediction of COVID-19 with Vaccination Effect
Creator
Poonia R.C.; Saudagar A.K.J.; Altameem A.; Alkhathami M.; Khan M.B.; Hasanat M.H.A.
Description
Currently, the spread of COVID-19 is running at a constant pace. The current situation is not so alarming, but every pandemic has a history of three waves. Two waves have been seen, and now expecting the third wave. Compartmental models are one of the methods that predict the severity of a pandemic. An enhanced SEIR model is expected to predict the new cases of COVID-19. The proposed model has an additional compartment of vaccination. This proposed model is the SEIRV model that predicts the severity of COVID-19 when the population is vaccinated. The proposed model is simulated with three conditions. The first condition is when social distancing is not incorporated, while the second condition is when social distancing is included. The third one condition is when social distancing is combined when the population is vaccinated. The result shows an epidemic growth rate of about 0.06 per day, and the number of infected people doubles every 10.7 days. Still, with imparting social distancing, the proposed model obtained the value of R0 is 1.3. Vaccination of infants and kids will be considered as future work. 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Source
Life, Vol-12, No. 5
Date
2022-01-01
Publisher
MDPI
Subject
COVID-19; SEIR model; SEIRV; social distancing; vaccination
Coverage
Poonia R.C., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Saudagar A.K.J., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Altameem A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Alkhathami M., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Khan M.B., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Hasanat M.H.A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
Rights
All Open Access; Gold Open Access; Green Open Access
Relation
ISSN: 20751729
Format
Online
Language
English
Type
Article

Collection

Articles

Citation

Poonia R.C.; Saudagar A.K.J.; Altameem A.; Alkhathami M.; Khan M.B.; Hasanat M.H.A., “An Enhanced SEIR Model for Prediction of COVID-19 with Vaccination Effect,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 23, 2025, https://archives.christuniversity.in/items/show/15153.

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