The University of Southampton
University of Southampton Institutional Repository

Simulating the “freshers’ flu”: an individual-level simulation approach utilising social networking and epidemiological models with a spatial component

Simulating the “freshers’ flu”: an individual-level simulation approach utilising social networking and epidemiological models with a spatial component
Simulating the “freshers’ flu”: an individual-level simulation approach utilising social networking and epidemiological models with a spatial component
Despite a range of epidemiological models existing, the majority of these are cohort-level instead of individual-level models. Individual level models allow for contact tracing, where one can see who each individual interacts with. With the increasing popularity of social media amongst students, most noticeably the rise of Facebook, we have chosen to integrate an evolving social networking model with a conventional Susceptible-Infectious-Recovered (SIR) epidemiological model in order to simulate how infection is spread by contact with a growing network of friends within a population. We considered the case of “Freshers’ Flu”, a form of seasonal influenza, in a closed population simulation of new students at university. This is a comparatively well-defined infection with known consistent values for the rate of infection and recovery, and is primarily spread by airborne transmission. Using the principles of discrete event simulation, and collecting data on lectures, social events and population demographics we created unique series of events per individual, combined with a personality type defined by their individual average daily friendship growth. We ran several scenarios which examined the default case of an infection spreading, the recommended university strategy of closing campus during an epidemic and the effects of vaccinating specific subsets of the population such as individuals on a particular degree course or those living in specific halls of residences. The model produced results which were consistent with a typical SIR model of an influenza outbreak, although smaller and over a longer time period. The social network and the formation of friends over time within the model were shown to have an impact on incidence, the number of new cases of infection per day. Prior to lectures commencing, the greatest influence on infection were the contacts made in halls of residences, with a background contribution from communal and social events. Post lectures, there was a consistent spike in incidence after the formation of friendships based upon studying the same degree.
Davie, Paul
99039d5f-cb6e-4c57-b975-131d85559569
Davie, Paul
99039d5f-cb6e-4c57-b975-131d85559569
Brailsford, Sally
634585ff-c828-46ca-b33d-7ac017dda04f

(2015) Simulating the “freshers’ flu”: an individual-level simulation approach utilising social networking and epidemiological models with a spatial component. University of Southampton, Southampton Business School, Masters Thesis, 295pp.

Record type: Thesis (Masters)

Abstract

Despite a range of epidemiological models existing, the majority of these are cohort-level instead of individual-level models. Individual level models allow for contact tracing, where one can see who each individual interacts with. With the increasing popularity of social media amongst students, most noticeably the rise of Facebook, we have chosen to integrate an evolving social networking model with a conventional Susceptible-Infectious-Recovered (SIR) epidemiological model in order to simulate how infection is spread by contact with a growing network of friends within a population. We considered the case of “Freshers’ Flu”, a form of seasonal influenza, in a closed population simulation of new students at university. This is a comparatively well-defined infection with known consistent values for the rate of infection and recovery, and is primarily spread by airborne transmission. Using the principles of discrete event simulation, and collecting data on lectures, social events and population demographics we created unique series of events per individual, combined with a personality type defined by their individual average daily friendship growth. We ran several scenarios which examined the default case of an infection spreading, the recommended university strategy of closing campus during an epidemic and the effects of vaccinating specific subsets of the population such as individuals on a particular degree course or those living in specific halls of residences. The model produced results which were consistent with a typical SIR model of an influenza outbreak, although smaller and over a longer time period. The social network and the formation of friends over time within the model were shown to have an impact on incidence, the number of new cases of infection per day. Prior to lectures commencing, the greatest influence on infection were the contacts made in halls of residences, with a background contribution from communal and social events. Post lectures, there was a consistent spike in incidence after the formation of friendships based upon studying the same degree.

PDF
Final MPhil thesis - Davie, Paul.pdf - Author's Original
Download (2MB)

More information

Published date: March 2015
Organisations: University of Southampton, Southampton Business School

Identifiers

Local EPrints ID: 388391
URI: http://eprints.soton.ac.uk/id/eprint/388391
PURE UUID: decc59ec-3ea5-42df-8681-8c37f2b0802d
ORCID for Sally Brailsford: ORCID iD orcid.org/0000-0002-6665-8230

Catalogue record

Date deposited: 15 Mar 2016 12:59
Last modified: 01 Dec 2018 01:36

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×