The lack of sufficient knowledge on the mechanisms of between-farm spread of livestock diseases hampers the development of much needed effective and fast control strategies. Some of the mechanisms responsible for pathogen spread can be deduced from epidemic tracing reports and literature while others can only be hypothesized from findings of studies on daily farm practices throughout the production round. For outbreaks without known/traced transmission routes, the concept of ‘neighbourhood’ infection is often adopted. This concept was founded based on the distance-dependence of the transmission risk with geographical proximity to an infectious farm being the key determinant of risk. Mathematical modelling plays an important role in obtaining quantitative insights into the contributions of the different mechanisms to disease spread. This can be by ranking the contributions of the individual transmission routes and/or obtaining a generic distance-dependent transmission risk. The models can guide the design of control strategies by providing a means to assess the efficacy of intervention strategies. In this thesis, modelling was used to assess the contributions of the wind-borne route and the other (traced) between-farm contacts to the transmission of highly pathogenic avian influenza during an epidemic in the Netherlands in 2003. It was found that these two routes together could only explain approximately 31% of the infections/cases. Visits by epidemic control teams were the least risky indicating the effectiveness of their biosecurity protocols in preventing transmission. New data on day-to-day farm practices and farmer opinion was collected in an attempt to generate hypotheses on transmission pathways and mechanisms that were yet to be appreciated. Indeed relevant unappreciated practices were found. They include irregularities in compliance to biosecurity as well as a broad category of neighbourhood-related risks. A new modelling approach to study neighbourhood transmission was developed guided by indirect transmission experiments. It involves the approximation of the pathogen dispersal process by a diffusive transport mechanism. Applying this diffusion model to the outbreak data of 2003, it was found that assuming delayed transmission, as opposed to instantaneous transmission, is an important phenomenon to be considered when modelling disease spread between locations. This modelling approach has the added advantage of availing an opportunity to assess the performance of intervention strategies without detailed mechanism-specific information.
