| Summary: | Despite many successes in the control of human infectious diseases they continue to pose a considerable risk to human health. The global distributions of pathogens are driven by ecological factors and the magnitude and extent of transmission are influenced by the dynamics of human behaviour. Viruses such as chikungnunya virus, Zika virus, dengue virus, and Ebola virus have recently expanded geographically. However, prior to their expansion there was little quantitative evidence available to identify locations that may be susceptible to transmission and to evaluate the likelihood of virus introduction to such locations. In this thesis statistical modelling techniques were applied with the aim of understanding infectious disease ecology, determining the main drivers of disease occurrence, and predicting the magnitude and regional spread of an outbreak in real-time. My results provide estimates of the populations now living in areas with possible transmission of chikungunya virus, show that the seasonal dynamics of Zika infection coupled with data on international travel, can better predict the arrival of the virus into new locations. Analyses of regional outbreaks of viruses including Ebola virus in West Africa and Yellow fever virus in Angola and the Democratic Republic Congo, show that patterns of human mobility strongly predict the real-time spread of disease. Further, I demonstrate that the impact of human movement varies considerably depending on the time of the outbreak (expanding versus declining phase) and the country of interest. The results and conclusions of these studies are discussed in the context of improving our understanding of infectious disease dynamics and of informing public health policies, interventions, and control efforts.
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