Highlights
Introduction
Epidemiology is the study of the spread of disease within a population. Epidemiologists often use a computer model to predict and mitigate the spread of disease. For example, it might be desirable to know the most effective strategy for selective vaccination when vaccine availability is limited. For this assignment, you will model the spread of a disease and the effect of selective interventions (e.g. vaccination, or isolation). You will also investigate the consequences of different type of social networks. If the topic causes you any anxiety that may affect your ability to complete the assignment, please contact your unit coordinator as soon as possible. Assignment Specification The model Every individual will be modelled as a vertex in small world network using an undirected graph. Frequent contacts of each individual will be modelled as edges connecting to other vertices. Each individual will be in one of three groups: susceptible, infected, or recovered (this is known as the SIR model). Susceptible individuals will have a chance of moving to the infected group if one or more of their neighbours are in the infected group. Infected individuals will have a chance of moving to the recovered group. Recovered individuals cannot infect anyone or become reinfected. We will also use the “recovered” group to model immunised individuals. The spread of the infection will be modelled over a number of time-steps. At each timestep:
• For each infected individual
o For each susceptible neighbour there will be a probability, inf_rate, that the neighbour will become infected
o There will also be a probability, rec_rate, that the individual will recover
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