The cost of delay in disease response

• Main Author: Tan, Ming Xuan
• Other Authors: XIAO Gaoxi
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Electrical and electronic engineering
• Online Access: https://hdl.handle.net/10356/149384
• Institution: Nanyang Technological University

This report details the process of simulating an Infectious Disease Model (SIR) on a random graph network. The SIR parameters used is arbitrary and does not reflect any real life infectious disease such as Covid-19. The software used to construct the simulation platform for this project is Python. It is high- level and general-purpose programming language that has many unique packages that assist in developing specific software programs. One of the main packages use in this project is EoN (Epidemics on Networks), it is a package for the simulation of epidemics on networks and solving ODE models of disease spread. (Ting, 20 December 2019) Another package used is NetworkX, it is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. (Aric A. Hagberg, 2008) Apart from simulating different network models and implementing infectious disease models into them, this report also further explores the impacts of implementing preventive methods within the simulated models in restricting the spread of infectious disease and evaluating how the time of implementation plays in preventing disease spread.