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A Numerical and Analytical Study of a Stochastic Epidemic SIR Model in the Light of White Noise
by
Khan, Hasib
, Hussain, Shah
, Madi, Elissa Nadia
, Abdo, Mohammed S.
in
Epidemics
/ Epidemiology
/ Hypotheses
/ Illnesses
/ Infectious diseases
/ Investigations
/ Mathematical models
/ Noise intensity
/ Noise levels
/ Parameter estimation
/ Partial differential equations
/ Stochastic models
/ White noise
2022
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A Numerical and Analytical Study of a Stochastic Epidemic SIR Model in the Light of White Noise
by
Khan, Hasib
, Hussain, Shah
, Madi, Elissa Nadia
, Abdo, Mohammed S.
in
Epidemics
/ Epidemiology
/ Hypotheses
/ Illnesses
/ Infectious diseases
/ Investigations
/ Mathematical models
/ Noise intensity
/ Noise levels
/ Parameter estimation
/ Partial differential equations
/ Stochastic models
/ White noise
2022
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Do you wish to request the book?
A Numerical and Analytical Study of a Stochastic Epidemic SIR Model in the Light of White Noise
by
Khan, Hasib
, Hussain, Shah
, Madi, Elissa Nadia
, Abdo, Mohammed S.
in
Epidemics
/ Epidemiology
/ Hypotheses
/ Illnesses
/ Infectious diseases
/ Investigations
/ Mathematical models
/ Noise intensity
/ Noise levels
/ Parameter estimation
/ Partial differential equations
/ Stochastic models
/ White noise
2022
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A Numerical and Analytical Study of a Stochastic Epidemic SIR Model in the Light of White Noise
Journal Article
A Numerical and Analytical Study of a Stochastic Epidemic SIR Model in the Light of White Noise
2022
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Overview
This study examines a novel SIR epidemic model that takes into account the impact of environmental white noise. According to the study, white noise has a significant impact on the disease. First, we establish the solution’s existence and uniqueness. Following that, we explain that the stochastic basic production R0 is a threshold that determines the extinction or persistence of the disease. When noise levels are high, we acquire R0<1, which causes the sickness to disappear. A sufficient condition for the existence of a stationary distribution is archived when the noise intensity is high, which suggests the infection is prevalent when R0>1. Finally, numerical simulations are used to explain the key findings.
Publisher
Hindawi,John Wiley & Sons, Inc,Wiley
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