Mathematical Modelling and Propagation of Infectious Diseases in Confined Areas

A mathematical model for the propagation of infectious diseases has been discussed in this paper. The model that has been examined is basically SIR model. The governing equations have been solved to the best possible solution. The influence of critical parameters over the system has been discussed with the graphical illustrations. It is observed that as the transmission (β) increases the sensitive population and, with the duration increasing, the vulnerable population diminishes and stays constant and is time-independent. Further, it is observed that as the rate of infection increases the susceptible population tens to zero. In addition to the above as rate of recovered individual (R) increases the susceptible population (S) decreases. The phenomena is an agreement with the real life situation. In addition to the above as rate of recovered individual increases the susceptible population decreases.

Authors

Publication Details

Journal
Panamerican mathematical journal.
Published
2024-11-21
DOI
https://doi.org/10.52783/pmj.v35.i2s.2426
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
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article

Mathematical Modelling and Propagation of Infectious Diseases in Confined Areas

Srinivasarao veerla
Panamerican mathematical journal.
COVID-19 epidemiological studies
article

Mathematical Modelling and Propagation of Infectious Diseases in Confined Areas

Srinivasarao veerla
article en

Abstract

A mathematical model for the propagation of infectious diseases has been discussed in this paper. The model that has been examined is basically SIR model. The governing equations have been solved to the best possible solution. The influence of critical parameters over the system has been discussed with the graphical illustrations. It is observed that as the transmission (β) increases the sensitive population and, with the duration increasing, the vulnerable population diminishes and stays constant and is time-independent. Further, it is observed that as the rate of infection increases the susceptible population tens to zero. In addition to the above as rate of recovered individual (R) increases the susceptible population (S) decreases. The phenomena is an agreement with the real life situation. In addition to the above as rate of recovered individual increases the susceptible population decreases.

Panamerican mathematical journal.Vol. 35(2s)
Openalex Percentile: Top 73%
COVID-19 epidemiological studies
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Mathematical Modelling and Propagation of Infectious Diseases in Confined Areas — Srinivasarao veerla · Panamerican mathematical journal. (2024) | TGRS Research Map | TGRS