On the Effect of Ignoring Within-Unit Infectious Disease Dynamics When Modelling Spatial Transmission

Individual-level models (ILMs) are a class of models that can be used to analyze infectious epidemic data to assist in the understanding of the spatio-temporal dynamics of infectious diseases in discrete time (Deardon et al., 2010). ILMs are generally fitted to epidemic data through Markov chain Monte Carlo (MCMC) methods in a Bayesian statistical framework. Here, we test the effect of ignoring within-unit (e.g., city) infectious disease dynamics when we model spatial transmission. We do this by generating our epidemic data sets from a true model which considers within unit dynamics. It is often hard to get individual-level data in reality. Also, the R package EpiILM used in this thesis for model fitting does not allow for within unit dynamics. For these reasons, we cannot easily fit our generating model to data. We fitted two ILM models (one model with a covariate representing city size, and the other model without covariates), in which within unit dynamics are not explicitly accounted for. We have found from our analysis that the model with the covariate may be a slightly better model to describe the spatio-temporal dynamics of the epidemic. However, although the model with the covariate is better in describing the epidemic process, the dynamics are still not perfectly captured by this model. Our results show the dangers inherent in ignoring within unit dynamics when modelling spatial disease transmission.

Name thesis:degree_name

Master of Science (MSc)

Discipline thesis:degree_discipline

Mathematics & Statistics

Grantor dc:publisher.institution

Science

Year dc:date.issued

2019

Author dc:creator

• Ferdous, Tahsin

Advisor dc:contributor.advisor

• Deardon, Rob

Committee members dc:contributor.committeemember

• Shen, Hua
• Ngamkham, Thuntida

Statement dc:rights

• University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.

Language dc:language.iso

eng

DOI

http://dx.doi.org/10.11575/PRISM/37084

OAI identifier oai:identifier

oai:ucalgary.scholaris.ca:1880/111019