STOCHASTIC ANALYSIS OF A DETERMINISTIC AND SEASONALLY-FORCED SEI MODEL FOR IMPROVED DISEASE SPREAD SIMULATION

Author:

SOHAIL AYESHA1,LI ZHI WU23,IFTIKHAR MEHWISH1,MOHAMED MABRUKA4,BÉG O. ANWAR5

Affiliation:

1. Department of Mathematics, Comsats Institute of Information Technology, Lahore 54000, Pakistan

2. Institute of Systems Engineering, Macau University of Science and Technology, Taipa, Macau

3. Department of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia

4. School of Mathematics and Statistics, Hicks Building, University of Sheffeld, Sheffeld S3 7RH, UK

5. Fluid Mechanics, Bio-Propulsion and Nanosystems, Aeronautical and Mechanical Engineering Department, University of Salford, Newton Building, UG17, Manchester, M54WT, UK

Abstract

The geographic distribution of different viruses has developed widely, giving rise to an escalating number of cases during the past two decades. The deterministic Susceptible, Exposed, Infectious (SEI) models can demonstrate the spatio-temporal dynamics of the diseases and have been used extensively in modern mathematical and mechano-biological simulations. This article presents a functional technique to model the stochastic effects and seasonal forcing in a reliable manner by satisfying the Lipschitz criteria. We have emphasized that the graphical portrayal can prove to be a powerful tool to demonstrate the stability analysis of the deterministic as well as the stochastic modeling. Emphasis is made on the dynamical effects of the force of infection. Such analysis based on the parametric sweep can prove to be helpful in predicting the disease spread in urban as well as rural areas and should be of interest to mathematical biosciences researchers.

Publisher

World Scientific Pub Co Pte Lt

Subject

Biomedical Engineering

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