This thesis is an investigation of external biosecurity and its application to risk-based surveillance approaches in the southern Ontario swine industry. In each of two datasets, the best number of groups to describe biosecurity practices was identified, resulting in two groups with high biosecurity standards and one group with low biosecurity standards. Multinomial logistic regression models identified herd density, herd size, and herd type among significant predictors of biosecurity group membership. A map of southern Ontario that can be used as a tool in the risk-based surveillance of contagious swine diseases was developed using geographic information about swine density, and the distribution of herds belonging to the high biosecurity groups. Finally, multiple correspondence analysis examined how individual biosecurity practices form strategies on sow farms. Some practices that are generally considered high-risk were closely associated with other practices that mitigate the risk, suggesting that evaluation of the overall strategy is essential for complete assessment of biosecurity. / The Ontario Ministry of Agriculture, Food and Rural Affairs (under the Emergency Management research theme); Ontario Pork; the Ontario Pork Industry Council's Swine Health Advisory Board; the Natural Sciences and Engineering Research Council of Canada;

O cultivo de camarão branco Litopennaeus vannamei tem provado ser um sector promissor para a economia do nordeste do Brasil. Contudo, a criação de camarão branco no Brasil tem sido afetada negativamente pela ocorrência de doenças virais, ameaçando a sua expansão e sustentabilidade. Por esta razão, depreende-se a importância da elaboração de um sistema de vigilância capaz de detectar e definir a ausência de doenças virais de elevado impacto econômico. O modelo estocástico AquaVigil é aqui implementado para avaliar prospectivamente diferentes estratégias de vigilância para determinar a ausência de doença e identificar a estratégia exigindo menor esforço de amostragem e simultaneamente, fazer o melhor uso dos recursos disponíveis através da implementação de vigilância baseada em risco. O estudo apresentado exemplifica a aplicação regional do sistema proposto para o estado do Ceará, podendo ser aplicado a outros estados do Brasil. O modelo AquaVigil pode analisar qualquer sistema de vigilância baseada em risco semelhante àquele aqui considerado. A criação de camarão no nordeste do Brasil tem sido alvo de vários desafios, desde a ocorrência de doenças virais a mudanças no acesso aos mercados internacionais. Tendo em consideração as dificuldades encontradas pela aquicultura de camarão no nordeste do Brasil, facilmente se compreende a importância de caracterizar e melhor compreender este setor e assim assegurar o seu desenvolvimento sustentável. Para este fim, foram aplicados métodos de análise de correspondência multipla e clustering particional a dados recolhidos durante um levantamento nacional de fazendas de carcinicultura de forma a obter informação necessária para caracterizar tendências e identificar falhas e necessidades existentes. Esta informação será útil no momento de melhorar o manejo das fazendas e elaborar legislação a favor do desenvolvimento do setor / The farming of Pacific white shrimp Litopennaeus vannamei in northeast Brazil, has proven to be a promising sector. However, the farming of Pacific white shrimp in Brazil has been affected negatively by the occurrence of viral diseases, threatening this sector\'s expansion and sustainability. For this reason, the drafting of a surveillance system for early detection and definition of freedom from viral diseases, whose occurrence could result in high economic loses, is of the utmost importance. The stochastic model AquaVigil was implemented to prospectively evaluate different surveillance strategies to determine freedom from disease and identify the strategy with the lowest sampling efforts, making the best use of available resources through risk-based surveillance. The worked example presented was designed for regional application for the state of Ceará and can easily be applied to other Brazilian states. The AquaVigil model can analyze any risk-based surveillance system that considers a similar outline to the strategy here presented. In recent years, shrimp aquaculture has faced many challenges, ranging from the occurrence of viral diseases to changes in market access. Considering the past and present challenges faced by the shrimp farmers in Northeast Brazil it is easily understood that the comprehensive characterization of the shrimp farming is of the utmost importance when striving for sustainable development. To this aim, the exploratory data analysis methods of multiple correspondence analysis and partitional clustering were applied to the data collected through a national census to extract the greatest amount of information and profile shrimp farms, identifying gaps and needs. The results of the analysis will contribute to improve management practices and policy-making for sustainable shrimp farming in Northeast Brazil

O cultivo de camarão branco Litopennaeus vannamei tem provado ser um sector promissor para a economia do nordeste do Brasil. Contudo, a criação de camarão branco no Brasil tem sido afetada negativamente pela ocorrência de doenças virais, ameaçando a sua expansão e sustentabilidade. Por esta razão, depreende-se a importância da elaboração de um sistema de vigilância capaz de detectar e definir a ausência de doenças virais de elevado impacto econômico. O modelo estocástico AquaVigil é aqui implementado para avaliar prospectivamente diferentes estratégias de vigilância para determinar a ausência de doença e identificar a estratégia exigindo menor esforço de amostragem e simultaneamente, fazer o melhor uso dos recursos disponíveis através da implementação de vigilância baseada em risco. O estudo apresentado exemplifica a aplicação regional do sistema proposto para o estado do Ceará, podendo ser aplicado a outros estados do Brasil. O modelo AquaVigil pode analisar qualquer sistema de vigilância baseada em risco semelhante àquele aqui considerado. A criação de camarão no nordeste do Brasil tem sido alvo de vários desafios, desde a ocorrência de doenças virais a mudanças no acesso aos mercados internacionais. Tendo em consideração as dificuldades encontradas pela aquicultura de camarão no nordeste do Brasil, facilmente se compreende a importância de caracterizar e melhor compreender este setor e assim assegurar o seu desenvolvimento sustentável. Para este fim, foram aplicados métodos de análise de correspondência multipla e clustering particional a dados recolhidos durante um levantamento nacional de fazendas de carcinicultura de forma a obter informação necessária para caracterizar tendências e identificar falhas e necessidades existentes. Esta informação será útil no momento de melhorar o manejo das fazendas e elaborar legislação a favor do desenvolvimento do setor / The farming of Pacific white shrimp Litopennaeus vannamei in northeast Brazil, has proven to be a promising sector. However, the farming of Pacific white shrimp in Brazil has been affected negatively by the occurrence of viral diseases, threatening this sector\'s expansion and sustainability. For this reason, the drafting of a surveillance system for early detection and definition of freedom from viral diseases, whose occurrence could result in high economic loses, is of the utmost importance. The stochastic model AquaVigil was implemented to prospectively evaluate different surveillance strategies to determine freedom from disease and identify the strategy with the lowest sampling efforts, making the best use of available resources through risk-based surveillance. The worked example presented was designed for regional application for the state of Ceará and can easily be applied to other Brazilian states. The AquaVigil model can analyze any risk-based surveillance system that considers a similar outline to the strategy here presented. In recent years, shrimp aquaculture has faced many challenges, ranging from the occurrence of viral diseases to changes in market access. Considering the past and present challenges faced by the shrimp farmers in Northeast Brazil it is easily understood that the comprehensive characterization of the shrimp farming is of the utmost importance when striving for sustainable development. To this aim, the exploratory data analysis methods of multiple correspondence analysis and partitional clustering were applied to the data collected through a national census to extract the greatest amount of information and profile shrimp farms, identifying gaps and needs. The results of the analysis will contribute to improve management practices and policy-making for sustainable shrimp farming in Northeast Brazil

Les maladies émergentes à transmission vectorielle sont une préoccupation croissante et particulièrement lorsqu’elles affectent les chevaux, une population spécifiquement à risque vis-à-vis de la propagation de maladies. En effet, les chevaux voyagent fréquemment et, malgré l’impact sanitaire et économique des maladies équines, les règlementations sanitaires et les principes de biosécurité et de traçabilité censés assurer la sécurité des mouvements d'équidés ne sont pas toujours en place. Notre travail propose d'améliorer la surveillance des maladies à transmission vectorielle chez les chevaux en utilisant différentes méthodes pour estimer la probabilité d'émergence d'une maladie. Tout d'abord, nous avons développé un modèle quantitatif et spatio-temporel combinant différentes probabilités pour estimer les risques d'introduction de la peste équine et de l’encéphalose équine. Ces combinaisons permettent d’obtenir une image plus détaillée du risque posé par ces agents pathogènes. Nous avons ensuite évalué des systèmes de surveillance syndromique par deux approches méthodologiques: l'approche classique avec un seuil d'alarme basé sur un multiple de l'erreur standard de prédiction, et l'approche bayésienne basée sur le rapport de vraisemblance. Nous avons travaillé ici principalement sur la détection précoce du virus West Nile en utilisant les symptômes nerveux des chevaux. Les deux approches ont fourni des résultats prometteurs, mais l’approche bayésienne était particulièrement intéressante pour obtenir un résultat quantitatif et pour combiner différentes informations épidémiologiques. Pour finir, l'approche bayésienne a été utilisée pour combiner quantitativement différentes sources d'estimation du risque : surveillance syndromique multivariée, et combinaison de la surveillance syndromique avec les résultats d’analyses de risques. Ces combinaisons ont données des résultats prometteurs. Ce travail, basé sur des estimations de risque, contribue à améliorer la surveillance des maladies à transmission vectorielle chez les chevaux et facilite la prise de décision. Les principales perspectives de ce travail sont d'améliorer la collecte et le partage de données, de mettre en oeuvre une évaluation complète des performances des systèmes de surveillance multivariés, et de favoriser l'adoption de ce genre d’approche par les décideurs en utilisant une interface conviviale et en mettant en place un transfert de connaissance. / Emerging vector-borne diseases are a growing concern, especially for horse populations, which are at particular risk for disease spread. In general, horses travel widely and frequently and, despite the health and economic impacts of equine diseases, effective health regulations and biosecurity systems to ensure safe equine movements are not always in place. The present work proposes to improve the surveillance of vector-borne diseases in horses through the use of different approaches that assess the probability of occurrence of a newly introduced epidemic. First, we developed a spatiotemporal quantitative model which combined various probabilities in order to estimate the risk of introduction of African horse sickness and equine encephalosis. Such combinations of risk provided more a detailed picture of the true risk posed by these pathogens. Second, we assessed syndromic surveillance systems using two approaches: a classical approach with the alarm threshold based on the standard error of prediction, and a Bayesian approach based on a likelihood ratio. We focused particularly on the early detection of West Nile virus using reports of nervous symptoms in horses. Both approaches provided interesting results but Bayes’ rule was especially useful as it provided a quantitative output and was able to combine different epidemiological information. Finally, a Bayesian approach was also used to quantitatively combine various sources of risk estimation in a multivariate syndromic surveillance system, as well as a combination of quantitative risk assessment with syndromic surveillance (applied to West Nile virus and equine encephalosis, respectively). Combining evidence provided promising results. This work, based on risk estimations, strengthens the surveillance of VBDs in horses and can support public health decision making. It also, however, highlights the need to improve data collection and data sharing, to implement full performance assessments of complex surveillance systems, and to use effective communication and training to promote the adoption of these approaches.