This thesis aims to investigate the use of numerous epidemiological tools to improve our understanding of porcine reproductive and respiratory syndrome (PRRS) transmission, control and surveillance at the herd and regional levels. These tools include spatial analysis, molecular epidemiology, network analysis, and infectious disease modelling. The main source of data for the thesis chapters was the Ontario PRRS area regional control and elimination projects. There are a few important conclusions from this thesis. First, spatial dependence in the patterns of PRRS positivity were not detected for three regions in Ontario, even though defined spatial clusters could be found. Secondly, an investigation of the occurrence of PRRS revealed that the importance of area spread and truck network connections were dependent on the virus genotype. Thirdly, description of networks showed that the Ontario swine industry is highly connected through multiple service providers, which can represent a challenge for outbreak investigations and disease surveillance and control. Lastly, the development of two types of mathematical models (hybrid and agent-based) allowed for the evaluation of herd- and regional-level control and surveillance strategies for PRRS. One of the take home messages from the herd-level model was that major PRRS outbreaks could occur in breeding herds long after the initial virus introduction, even in cases where the herd is naïve. Furthermore, neither vaccination of gilts with a modified-live PRRS virus vaccine nor their exposure through live-virus inoculation guaranteed that the introduced virus would not circulate in the piglet population in cases of novel viral introductions. The regional-level model suggested that contemporary approaches to implement risk-based surveillance based on site demographic characteristics (e.g. production type) do not appear to necessarily improve surveillance system sensitivity; which suggest novel strategies need to be explored to assure rapid detection of emerging PRRS virus strains. Conclusions from this thesis support the use of databases obtained from industry-initiated regional control projects to inform models and characterize risk, and development of epidemiological tools should continue in the future for the benefit of the swine industry as a whole.