Author:
Barik Mamta, ,Swarup Chetan,Singh Teekam,Habbi Sonali,Chauhan Sudipa, ,
Abstract
<abstract><p>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 (<italic>R</italic><sub>01</sub> < 1 & <italic>R</italic><sub>02</sub> < 1) and the endemic point is stable if the reproduction number is greater then 1 (<italic>R</italic><sub>01</sub> > 1 & <italic>R</italic><sub>02</sub> > 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.</p></abstract>
Publisher
American Institute of Mathematical Sciences (AIMS)
Reference44 articles.
1. British Columbia, BC's Pandemic Influenza Response Plan–Introduction and Background, 2012. Available from: https://www2.gov.bc.ca/assets/gov/health/about-bc-s-health-care-system/office-of-the-provincial-health-officer/reports-publications/bc-pandemic-influenza-immunization-response-plan.pdf.
2. Y. Chen, K. Leng, Y. Lu, L. Wen, Y. Qi, W. Gao, et al., Epidemiological features and time-series analysis of influenza incidence in urban and rural areas of Shenyang, China, 2010–2018, Epidemiol. Infect., 148 (2020), E29. http://dx.doi.org/10.1017/S0950268820000151
3. T. S. Böbel, S. B. Hackl, D. Langgartner, M. N. Jarczok, N. Rohleder, C. G. A. Rook, et al., Less immune activation following social stress in rural vs. urban participants raised with regular or no animal contact, respectively, PNAS, 115 (2018), 5259–5264. http://dx.doi.org/10.1073/pnas.1719866115
4. N. K. Goswami, B. Shanmukha, A mathematical model of influenza: stability and treatment, Proceedings of the International Conference on Mathematical Modeling and Simulation (ICMMS 16), 2016.
5. K. Cheng, P. Leung, What happened in china during the 1918 influenza pandemic?, Int. J. Infect. Dis., 11 (2007), 360–364. http://dx.doi.org/10.1016/j.ijid.2006.07.009
Cited by
7 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献