Mathematical Modelling for COVID-19 Dynamics with Vaccination Class

We develop a six-compartment differential equation model for the transmission of COVID-19 by dividing the human population into susceptible; vaccinated; exposed; infectious; confirmed; and recovered. We use the basic reproduction number R0 to determine when the disease will die out and when it will...

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Main Authors: Lagura, Maria Czarina T, David, Roden Jason, De Lara-Tuprio, Elvira P
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出版: Archīum Ateneo 2022
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在線閱讀:https://archium.ateneo.edu/mathematics-faculty-pubs/229
https://doi.org/10.1007/978-3-031-04028-3_23
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機構: Ateneo De Manila University
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spelling ph-ateneo-arc.mathematics-faculty-pubs-12302023-07-12T03:05:24Z Mathematical Modelling for COVID-19 Dynamics with Vaccination Class Lagura, Maria Czarina T David, Roden Jason De Lara-Tuprio, Elvira P We develop a six-compartment differential equation model for the transmission of COVID-19 by dividing the human population into susceptible; vaccinated; exposed; infectious; confirmed; and recovered. We use the basic reproduction number R0 to determine when the disease will die out and when it will stay in the community. This is done by showing that when R0 < 1; then the disease-free equilibrium solution is globally asymptotically stable; and when R0 > 1; the endemic equilibrium is globally asymptotically stable. Finally; we use numerical solutions to confirm the results of our stability analysis. 2022-01-01T08:00:00Z text https://archium.ateneo.edu/mathematics-faculty-pubs/229 https://doi.org/10.1007/978-3-031-04028-3_23 Mathematics Faculty Publications Archīum Ateneo Covid-19 Compartmental model Vaccination Stability analysis Basic reproduction number Next generation matrix Applied Mathematics Epidemiology Medicine and Health Sciences Physical Sciences and Mathematics Public Health
institution Ateneo De Manila University
building Ateneo De Manila University Library
continent Asia
country Philippines
Philippines
content_provider Ateneo De Manila University Library
collection archium.Ateneo Institutional Repository
topic Covid-19
Compartmental model
Vaccination
Stability analysis
Basic reproduction number
Next generation matrix
Applied Mathematics
Epidemiology
Medicine and Health Sciences
Physical Sciences and Mathematics
Public Health
spellingShingle Covid-19
Compartmental model
Vaccination
Stability analysis
Basic reproduction number
Next generation matrix
Applied Mathematics
Epidemiology
Medicine and Health Sciences
Physical Sciences and Mathematics
Public Health
Lagura, Maria Czarina T
David, Roden Jason
De Lara-Tuprio, Elvira P
Mathematical Modelling for COVID-19 Dynamics with Vaccination Class
description We develop a six-compartment differential equation model for the transmission of COVID-19 by dividing the human population into susceptible; vaccinated; exposed; infectious; confirmed; and recovered. We use the basic reproduction number R0 to determine when the disease will die out and when it will stay in the community. This is done by showing that when R0 < 1; then the disease-free equilibrium solution is globally asymptotically stable; and when R0 > 1; the endemic equilibrium is globally asymptotically stable. Finally; we use numerical solutions to confirm the results of our stability analysis.
format text
author Lagura, Maria Czarina T
David, Roden Jason
De Lara-Tuprio, Elvira P
author_facet Lagura, Maria Czarina T
David, Roden Jason
De Lara-Tuprio, Elvira P
author_sort Lagura, Maria Czarina T
title Mathematical Modelling for COVID-19 Dynamics with Vaccination Class
title_short Mathematical Modelling for COVID-19 Dynamics with Vaccination Class
title_full Mathematical Modelling for COVID-19 Dynamics with Vaccination Class
title_fullStr Mathematical Modelling for COVID-19 Dynamics with Vaccination Class
title_full_unstemmed Mathematical Modelling for COVID-19 Dynamics with Vaccination Class
title_sort mathematical modelling for covid-19 dynamics with vaccination class
publisher Archīum Ateneo
publishDate 2022
url https://archium.ateneo.edu/mathematics-faculty-pubs/229
https://doi.org/10.1007/978-3-031-04028-3_23
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