Dynamical analysis, optimal control and spatial pattern in an influenza model with adaptive immunity in two stratified population
Consistently, influenza has become a major cause of illness and mortality worldwide and it has posed a serious threat to global public health particularly among the immuno-compromised people all around the world. The development of medication to control influenza has become a major challenge now. Th...
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Published in: | AIMS mathematics Vol. 7; no. 4; pp. 4898 - 4935 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
AIMS Press
01-01-2022
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Subjects: | |
Online Access: | Get full text |
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Summary: | Consistently, influenza has become a major cause of illness and mortality worldwide and it has posed a serious threat to global public health particularly among the immuno-compromised people all around the world. The development of medication to control influenza has become a major challenge now. This work proposes and analyzes a structured model based on two geographical areas, in order to study the spread of influenza. The overall underlying population is separated into two sub populations: urban and rural. This geographical distinction is required as the immunity levels are significantly higher in rural areas as compared to urban areas. Hence, this paper is a novel attempt to proposes a linear and non-linear mathematical model with adaptive immunity and compare the host immune response to disease. For both the models, disease-free equilibrium points are obtained which are locally as well as globally stable if the reproduction number is less than 1 ( R 01 < 1 & R 02 < 1) and the endemic point is stable if the reproduction number is greater then 1 ( R 01 > 1 & R 02 > 1). Next, we have incorporated two treatments in the model that constitute the effectiveness of antidots and vaccination in restraining viral creation and slow down the production of new infections and analyzed an optimal control problem. Further, we have also proposed a spatial model involving diffusion and obtained the local stability for both the models. By the use of local stability, we have derived the Turing instability condition. Finally, all the theoretical results are verified with numerical simulation using MATLAB. |
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ISSN: | 2473-6988 2473-6988 |
DOI: | 10.3934/math.2022273 |