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Using small world models to study infection communication and control

Ganney, Paul Sefton

Authors

Paul Sefton Ganney



Contributors

Roger, computer scientist Phillips
Supervisor

Abstract

The modelling of infection transmission has taken many forms: The simple Susceptible-Infected-Removed (SIR) model yields good epidemiological results, but is not well suited to the modelling of the application of interventions. Attention has focused in recent years on graph (network) models and especially on those exhibiting the small-world properties described by Watts and Strogatz in “Nature” in 1998. This thesis examines such graph models, discovering several attributes which may yield improved results. In order to quantify the effects of these proposals, a classification system was developed together with a Goodness-of-Fit (GoF) measure. Additionally, a questionnaire was developed to reveal the operational organisational structure of the NHS Trust being examined. The resultant theoretical model was implemented in software and seeded with a graph derived from this questionnaire. This model was then examined to determine the effectiveness of these proposals, as measured via the GoF. The additional features proving beneficial were shown to be: full directionality in the graphs; modelling unknown paths via a new concept termed an “external path”; the division of the probability of infection transmission into three components; the seeding of the model with one derived from an organizational questionnaire. The resulting model was shown to yield very good results and be applicable to modelling both infection propagation and control.

Citation

Ganney, P. S. (2011). Using small world models to study infection communication and control. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4211386

Thesis Type Thesis
Deposit Date Sep 27, 2011
Publicly Available Date Feb 22, 2023
Keywords Computer science
Public URL https://hull-repository.worktribe.com/output/4211386
Additional Information Department of Computer Science, The University of Hull
Award Date Apr 1, 2011

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Copyright Statement
© 2011 Ganney, Paul Sefton. All rights reserved. No part of this publication may be reproduced without the written permission of the copyright holder.




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