The measles epidemic model assessment under real statistics: an application of stochastic optimal control theory

Liu, Yijie; Ikram, Rukhsar; Khan, Amir; Din, Anwarud

doi:10.1080/10255842.2022.2050222

Cited by 10 publications

(2 citation statements)

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“…White noise plays a vital role in explaining the dynamics of physical and biological problems. The impact of external environmental factors such as white noise on the dynamics of measles epidemics is significant [15]. Due to the non-homogeneity and nonlinearity of population interactions and other complexities, epidemic prediction cannot be depicted using traditional modeling approaches.…”

Section: Introductionmentioning

confidence: 99%

“…It has been demonstrated that stochastic models are more realistic compared to deterministic models. Several researchers have recently focused on perturbations that can capture the true dynamics of the epidemic based on stochastic modelling [13,15,16]. The Lévy white noise is important at various velocities for the spacing of threshold parameters.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Lévy Noise with Infinite Activity on the Dynamics of Measles Epidemics

Song

Liu

2023

Fractal Fract

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This research article investigates the application of Lévy noise to understand the dynamic aspects of measles epidemic modeling and seeks to explain the impact of vaccines on the spread of the disease. After model formulation, the study utilises uniqueness and existence techniques to derive a positive solution to the underlying stochastic model. The Lyapunov function is used to investigate the stability results associated with the proposed stochastic model. The model’s dynamic characteristics are analyzed in the vicinity of the infection-free and endemic states of the associated ODEs model. The stochastic threshold Rs that ensures disease’s extinction whenever Rs<1 is calculated. We utilized data from Pakistan in 2019 to estimate the parameters of the model and conducted simulations to forecast the future behavior of the disease. The results were compared to actual data using standard curve fitting tools.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%