AN AGENT-BASED MODEL TO STUDY THE SPREAD AND CONTROL OF INFLUENZA

Abstract

The world keeps on confronting flare-ups of illness because of normal causes and also the risk of biological warfare. Numerical modeling gives a road by which to foresee and eventually avert broad episodes. A wide assortment of modeling tools has been utilized as a part of the investigation into the illnesses dispersed, involving Partial Differential Equations, Ordinary Differential Equations, and Difference Equations. Agent-based (AB) simulation is a useful tool for building highly granular disease spread models incorporating the epidemiological features of the virus as well as the demographic and social behavioral attributes of tens of millions of affected people. Such disease spread models provide excellent basis on which various mitigation strategies can be tested, before they are adopted and implemented by the policymakers. Mathematical modeling has provided an economical means to comprehend the transmission dynamics of diseases as well as the ability to choose the most effective and economical interventions aimed at preventing and treating disease. An agent - based modeling is used to study the spread and control parameters of flu in this thesis. The NetLogo tool is utilized for the simulation purpose. The setup methods of such a model are completely discussed. This simulation helps clients for comprehending new illness spread progression in connection with the adjustments in control measure, travel, and versatility and furthermore see the way R_0, i.e. reproduction number, speaks as far as possible for an epidemic and comprehend the connection to integrals and subordinates, and provide opportunities to extend or change the model to include some properties of a disease. This model is used to study the effectiveness of isolation, immunization and quarantine as methods of epidemic control. It is determined that the most effective means of controlling an epidemic is to quarantine individuals. Thus, this work reduces the number of infected individuals and recovery rate due to control parameters. In addition to the control methods, travelling and social networking among individuals for spreading the influenza has been observed.