This thesis describes the West Nile virus (WNV) epidemic in horses by exploring all aspects: sub-clinical infection, development of clinical disease and case fatality. All of the collected data were then compiled to create predictive risk maps of WNV infection for the province of Saskatchewan. <p>During the 2003 season, 133 clinical cases were documented with laboratory testing. Week of onset of clinical signs, gender, and coat color were significant predictors of whether the horse died or was euthanized due to severity of clinical signs. Studies of the serological response to vaccination and natural infection were examined to interpret the lab results from over 1100 samples taken from approximately 875 horses in 2003. A serologic study involving 212 horses on 20 farms determined the prevalence of sub-clinical infection (55.7% (95%CI, 44.9% to 65.8%)) and identified risk factors for infection. The study found risk of infection was highest in the Grasslands ecoregions compared to the Boreal Transition ecoregion. A case control study looked at risk factors for development of clinical disease. The study followed 23 case farms and control farms with a total of 300 horses sampled. This was the first field study to show that vaccination was efficacious in preventing the development of clinical signs. <p>The inclusion of horse surveillance data in the Saskatchewan Health WNV Integrated Surveillance Initiative was useful; however, it was discontinued due to time constraints, logistics, and declining monetary resources. <p>Since West Nile Virus is a mosquito-borne disease it is highly influenced by environmental changes, spatially and temporally. Discriminant analyses were used to partition Saskatchewan rural municipalities (RM) into categories of risk of infection with WNV based on acquired horse data and different environmental and meteorological data derived from both satellites or climate stations. The result was the creation of yearly predictive risk maps defining low to high risk of infection with WNV for each RM. <p>The 2003 epidemic provided a novel opportunity to study an important zoonotic disease emerging in a new environment. The information gathered will further the knowledge base upon which decisions for prevention of infection and clinical disease are made.

This thesis describes the West Nile virus (WNV) epidemic in horses by exploring all aspects: sub-clinical infection, development of clinical disease and case fatality. All of the collected data were then compiled to create predictive risk maps of WNV infection for the province of Saskatchewan. During the 2003 season, 133 clinical cases were documented with laboratory testing. Week of onset of clinical signs, gender, and coat color were significant predictors of whether the horse died or was euthanized due to severity of clinical signs. Studies of the serological response to vaccination and natural infection were examined to interpret the lab results from over 1100 samples taken from approximately 875 horses in 2003. A serologic study involving 212 horses on 20 farms determined the prevalence of sub-clinical infection (55.7% (95%CI, 44.9% to 65.8%)) and identifed risk factors for infection. The study found risk of infection was highest in the Grasslands ecoregions compared to the Boreal Transition ecoregion. A case control study looked at risk factors for development of clinical disease. The study followed 23 case farms and control farms with a total of 300 horses sampled. This was the first field study to show that vaccination was efficacious in preventing the development of clinical signs. The inclusion of horse surveillance data in the Saskatchewan Health WNV Integrated Surveillance Initiative was useful; however, it was discontinued due to time constraints, logistics, and declining monetary resources. Since West Nile Virus is a mosquito-borne disease it is highly influenced by environmental changes, spatially and temporally. Discriminant analyses were used to partition Saskatchewan rural municipalities (RM) into categories of risk of infection with WNV based on acquired horse data and different environmental and meteorological data derived from both satellites or climate stations. The result was the creation of yearly predictive risk maps defining low to high risk of infection with WNV for each RM. The 2003 epidemic provided a novel opportunity to study an important zoonotic disease emerging in a new environment. The information gathered will further the knowledge base upon which decisions for prevention of infection and clinical disease are made.

This thesis describes the West Nile virus (WNV) epidemic in horses by exploring all aspects: sub-clinical infection, development of clinical disease and case fatality. All of the collected data were then compiled to create predictive risk maps of WNV infection for the province of Saskatchewan. <p>During the 2003 season, 133 clinical cases were documented with laboratory testing. Week of onset of clinical signs, gender, and coat color were significant predictors of whether the horse died or was euthanized due to severity of clinical signs. Studies of the serological response to vaccination and natural infection were examined to interpret the lab results from over 1100 samples taken from approximately 875 horses in 2003. A serologic study involving 212 horses on 20 farms determined the prevalence of sub-clinical infection (55.7% (95%CI, 44.9% to 65.8%)) and identified risk factors for infection. The study found risk of infection was highest in the Grasslands ecoregions compared to the Boreal Transition ecoregion. A case control study looked at risk factors for development of clinical disease. The study followed 23 case farms and control farms with a total of 300 horses sampled. This was the first field study to show that vaccination was efficacious in preventing the development of clinical signs. <p>The inclusion of horse surveillance data in the Saskatchewan Health WNV Integrated Surveillance Initiative was useful; however, it was discontinued due to time constraints, logistics, and declining monetary resources. <p>Since West Nile Virus is a mosquito-borne disease it is highly influenced by environmental changes, spatially and temporally. Discriminant analyses were used to partition Saskatchewan rural municipalities (RM) into categories of risk of infection with WNV based on acquired horse data and different environmental and meteorological data derived from both satellites or climate stations. The result was the creation of yearly predictive risk maps defining low to high risk of infection with WNV for each RM. <p>The 2003 epidemic provided a novel opportunity to study an important zoonotic disease emerging in a new environment. The information gathered will further the knowledge base upon which decisions for prevention of infection and clinical disease are made.

Federal, state and local governments are increasingly focused on the effects of development on water quality and quantity. With waterbodies being especially sensitive to certain pollutants, such as sediment and nutrients, regulations have been put in place to control the amount of pollutant that gets discharged. Sediment is a cause for concern as it originates during both rural and urban activities, and often carries other pollutants (metals, nutrients, etc.) with it. Existing erosion models focus primarily on estimating erosion from agricultural watersheds. Methods are needed to predict areas with high erosive potential (EP) in urban watersheds. Highlighting highly erosive areas in urbanized watersheds allows for the prioritization of maintenance and installation of Stormwater Control Measures (SCMs), and monitoring of sediment by municipal planners and engineers. This study utilizes commonly available geospatial layers in conjunction with a computational procedure to compute relative EP risk throughout a target urban watershed. A case study of the developed methodology was performed on a watershed in Blacksburg, VA, to generate EP risk maps. Results of the study indicate areas of erosive potential within the target watershed and provide a methodology for creating erosion potential risk maps for use by municipal planners and engineers / Master of Science

Thermal pollution of waterbodies occurring from heated stormwater runoff in urban catchments is a growing concern among municipalities in the United States. The U.S. Environmental Protection Agency (EPA) maintains regulatory criteria for temperature of waters of the U.S. as many species of aquatic life depend on an environment that maintains water temperatures below a certain threshold. Thermal pollution from urban stormwater runoff threatens the livelihoods of cold-water fish species, like trout, among other species of wildlife. In order to reduce thermal pollution loading to its streams, a municipality or regulatory authority must first identify the sources of thermal pollution in its waterbodies. This study predicts areas within an urban watershed in the Town of Blacksburg, VA that may be sources of thermal pollution in stormwater runoff by investigating indicators of thermal pollution potential (TPP) through and analysis of land cover types and runoff flow patterns in a geographic information system (GIS) environment. Results of the study provide a theoretical foundation for TPP risk mapping with recommendations for authorities interested in pursuing TPP risk mapping as a tool to guide and focus efforts toward reduction of thermal pollution and land planning. / Master of Science

Doctor of Philosophy / Department of Plant Pathology / Karen A. Garrett / Late blight of potato, caused by Phytophthora infestans, is a pernicious disease of potatoes worldwide. This disease causes yield losses as a result of foliar and tuber damage. Many models exist to predict late blight risk for control purposes with-in season but rely upon fine-scale weather data collected in hourly, or finer, increments. This is a major constraint when working with disease prediction models for areas of the world where hourly weather data is not available or is unreliable. Weather or climate summary datasets are often available as monthly summaries. These provide a partial solution to this problem with global data at large time-steps (e.g., monthly). Difficulties arise when attempting to use these forms of data in small temporal scale models. My first objective was to develop new approaches for application of disease forecast models to coarser resolution weather data sets. I created metamodels based on daily and monthly weather values which adapt an existing potato late blight model for use with these coarser forms of data using generalized additive models. The daily and monthly weather metamodels have R-squared values of 0.62 and 0.78 respectively. These new models were used to map global late blight risk under current and climate change scenarios resistant and susceptible varieties. Changes in global disease risk for locations where wild potato species are indigenous, and disease risk for countries where chronic malnutrition is a problem were evaluated. Under the climate change scenario selected for use, A1B, future global late blight severity decreases. The risk patterns do not show major changes, areas of high risk remain high relative to areas of low risk with rather slight increases or decreases relative to previous years. Areas of higher wild potato species richness experience slightly increased blight risk, while areas of lower species richness experience a slight decline in risk.

The growth of the financial risk management industry has been motivated by the increased volatility of financial markets combined with the rapid innovation of derivatives. Since the 1970s, several financial crises have occurred globally with devastating consequences for financial and non-financial institutions and for the real economy. The most recent US subprime crisis led to enormous losses for financial and non-financial institutions and to a recession in many countries including the US and UK. A common lesson from these crises is that advanced financial risk management systems are required. Financial risk management is a continuous process of identifying, modeling, forecasting and monitoring risk exposures arising from financial investments. The Value at Risk (VaR) methodology has served as one of the most important tools used in this process. This quantitative tool, which was first invented by JPMorgan in its Risk-Metrics system in 1995, has undergone a considerable revolution and development during the last 15 years. It has now become one of the most prominent tools employed by financial institutions, regulators, asset managers and nonfinancial corporations for risk measurement. My PhD research undertakes a comprehensive and practical study of market risk modeling in modern finance using the VaR methodology. Two newly developed risk models are proposed in this research, which are derived by integrating volatility modeling and the quantile regression technique. Compared to the existing risk models, these two new models place more emphasis on dynamic risk adjustment. The empirical results on both real and simulated data shows that under certain circumstances, the risk prediction generated from these models is more accurate and efficient in capturing time varying risk evolution than traditional risk measures. Academically, the aim of this research is to make some improvements and extensions of the existing market risk modeling techniques. In practice, the purpose of this research is to support risk managers developing a dynamic market risk measurement system, which will function well for different market states and asset categories. The system can be used by financial institutions and non-financial institutions for either passive risk measurement or active risk control.

The Aedes aegypti mosquito is the vector for four infectious diseases of global concern – Yellow Fever, Dengue, Chikungunya, and Zikavirus. Previous attempts to model the expansion of the vector habitat due to global climate change have rarely included characteristics related to the human populations on which this mosquito is dependent. The purpose of this research was to determine whether the inclusion of human population density improves model performance while creating risk maps that can be used to determine where humans are most likely to be exposed to the vector in the future. The resulting model demonstrated that the inclusion of human population density improves the predictive power for A. aegypti and should be considered during model development. Maps produced by the model were also suitable for identifying regions where human populations are most likely to experience increased risk. Finally, two areas at risk of expansion were highlighted as a case study in pairing risk mapping with evidence-based intervention strategies to identify sites that would benefit from mosquito-control efforts. In this case, a low-cost program of insecticide-treated covers for water storage containers would likely work well in both Minas Gerais, Brazil and Northwestern Province, Zambia to mitigate mosquito risk. This research demonstrates that human population characteristic not only improve model fit but also increase the extent to which risk maps are actionable by aiding in targeting interventions.

O objetivo do estudo é apresentar um conjunto de alternativas ao mercado de seguro florestal que sistematize o processo de valoração da floresta em apólices de seguro e que proponha os indicadores mais importantes para mapeamento de riscos. Atualmente o cálculo do Valor em Risco (VR) se baseia no custeio ou no valor comercial da floresta. Esse método de cálculo apresenta limitações, pois é comum a seguradora ter que estimar esses valores. Um novo cálculo do VR é aqui proposto e leva em consideração o valor da floresta em função do seu potencial retorno econômico. Esse novo VR considera o fato de que um sinistro interrompe a expectativa de conclusão do atual ciclo de exploração, tendo como conseqüência (i) a perda de uma receita futura que seria obtida com a madeira produzida pela floresta atual, deduzidos os custos futuros; e (ii) a antecipação da ocupação da área com uma nova atividade, que só aconteceria após o término do atual ciclo de exploração. O método proposto é ilustrado com exemplos, sugerindo três modelos base de custeio: Alta, Média ou Baixa tecnologia, aplicáveis em qualquer parte do Brasil. Para o cálculo das receitas, foram geradas oito curvas de crescimento para eucalipto, com incrementos médio anuais (IMA), aos 7 anos, de: 24, 27, 32, 35, 41, 52, 47 e 60 m3ha-1ano-1, nomeadas de BP1, BP2, MP1, MP2, MP3, AP1, AP2, AP3, respectivamente. O novo VR foi aplicado em sete casos reais, em diferentes estados brasileiros. Cada local foi associado com uma estratégia de custos conforme a tecnologia empregada (Alta Média ou Baixa) e vinculado a uma das curvas de crescimento. O preço da madeira considerou valores regionais, e a taxa de desconto utilizada foi de 12% ao ano. Para o Local 1(PR), onde se considerou baixa tecnologia, curva MP1 de produção e madeira a R$45,00m-3, o novo VR se mostrou 5% inferior ao valor da apólice; para o Local 2(GO), alta tecnologia, AP2 e madeira a R$45,00m-3, o método sugere VR 29% inferior; Local 3(MA), média tecnologia, MP3, R$45,00m-3 a estimativa foi 17% superior; Local 4(MG), média tecnologia, MP3, R$33,00m-3, o resultado foi 66% inferior; Local 5(MS), alta tecnologia, MP3, e R$42,50.m-3, a estimativa resultou 41% superior; Local 6, média tecnologia, AP1, e preço R$46,50.m-3 observou-se um resultado 30% superior; e Local 7, média tecnologia, curva MP2, e preço de R$45,00m-3, a estimativa foi 11% superior. Sugeriu-se a utilização de sistemas de informação geográfica (SIG) e da fórmula de Monte Alegre (FMA) como alternativas para mapeamento de riscos. Foram identificados na literatura mapas de riscos de geada (Estado de SP) e de seca (Brasil) e aplicada a FMA em dados de Piracicaba/SP, indicando o benefício de sua utilização. Recomenda-se que o modelo de cálculo e mapas de risco aqui apresentados sejam incorporados pelas seguradoras em suas rotinas de elaboração de apólices de seguro floresta, para que se garanta um adequado respaldo técnico / The study objective is to present a set of alternatives to the forestry insurance market, to systematize the process of forest valuation and to propose the most important indicators for risk assessment. Currently the forest risk valuation (VR) is based on cost or market value of the forest. This calculation method has limitations because it is common for the insurer to have to estimate these values. A new calculation of the VR is proposed here and takes into consideration the value of the forest in terms of its potential economic return. This new VR considers the fact that hazards interrupts the expected completion of the current exploration cycle, resulting in (i) the loss of future revenue that would be obtained with the wood produced by the current forest, less the costs that would be spent and (ii) the anticipation of the area occupation with a new activity, which would only happen after the current cycle of exploitation. The proposed method is illustrated with examples, suggesting three model based costing: High, Medium or Low technologies, applicable anywhere in Brazil. For the calculation of revenues eight growth curves for eucalyptus were generated, with mean annual increments (MAI) at age 7, 24, 27, 32, 35, 41, 52, 47 and 60 R$.m-3.ha-1, named BP1, BP2, MP1, MP2, MP3, AP1, AP2, AP3, respectively. The new VR was applied to seven real cases in different states. Each site was associated with a strategy of cost as a function of the technology employed (high medium or low) and linked to one of the growth curves. The price of wood considered regional values, and the discount rate was 12% per year. For Local 1 (PR), was consider low-tech, production curve MP1, and wood to R$ 45,00m-3, the new VR showed 5% less than the value of the policy; for the Local 2 (GO), high technology, AP2 and wood to R$ 45,00m-3, the method suggests 29% lower than the policy VR; Local 3 (MA), medium-tech, MP3, R$ 45,00m-3 estimates a 17% higher VR; Local 4 (MG), medium-tech, MP3, R$ 33,00m-3, the result was 66% lower; Local 5 (MS), high-tech, MP3, and R$ 42,50m-3, the estimate suggests 41% higher; Local 6, medium technology, AP1, and price R$ 46.50m-3 was observed a 30% higher result, and Local 7, medium technology, MP2 curve, and price of R$ 45,00m-3, the estimate was 11% higher. It was suggested the use of geographic information systems (GIS) and Monte Alegre formula (FMA) as alternatives for risk assessment. Maps of frost risks (for SP state) and drought (Brazil), were indicated. The FMA was applied on Piracicaba/SP database, indicating the benefit of its use. It is recommended that the model calculation and risk maps presented here are incorporated by insurers in their daily development of forest insurance policies to ensure adequate technical support.

O objetivo do estudo é apresentar um conjunto de alternativas ao mercado de seguro florestal que sistematize o processo de valoração da floresta em apólices de seguro e que proponha os indicadores mais importantes para mapeamento de riscos. Atualmente o cálculo do Valor em Risco (VR) se baseia no custeio ou no valor comercial da floresta. Esse método de cálculo apresenta limitações, pois é comum a seguradora ter que estimar esses valores. Um novo cálculo do VR é aqui proposto e leva em consideração o valor da floresta em função do seu potencial retorno econômico. Esse novo VR considera o fato de que um sinistro interrompe a expectativa de conclusão do atual ciclo de exploração, tendo como conseqüência (i) a perda de uma receita futura que seria obtida com a madeira produzida pela floresta atual, deduzidos os custos futuros; e (ii) a antecipação da ocupação da área com uma nova atividade, que só aconteceria após o término do atual ciclo de exploração. O método proposto é ilustrado com exemplos, sugerindo três modelos base de custeio: Alta, Média ou Baixa tecnologia, aplicáveis em qualquer parte do Brasil. Para o cálculo das receitas, foram geradas oito curvas de crescimento para eucalipto, com incrementos médio anuais (IMA), aos 7 anos, de: 24, 27, 32, 35, 41, 52, 47 e 60 m3ha-1ano-1, nomeadas de BP1, BP2, MP1, MP2, MP3, AP1, AP2, AP3, respectivamente. O novo VR foi aplicado em sete casos reais, em diferentes estados brasileiros. Cada local foi associado com uma estratégia de custos conforme a tecnologia empregada (Alta Média ou Baixa) e vinculado a uma das curvas de crescimento. O preço da madeira considerou valores regionais, e a taxa de desconto utilizada foi de 12% ao ano. Para o Local 1(PR), onde se considerou baixa tecnologia, curva MP1 de produção e madeira a R$45,00m-3, o novo VR se mostrou 5% inferior ao valor da apólice; para o Local 2(GO), alta tecnologia, AP2 e madeira a R$45,00m-3, o método sugere VR 29% inferior; Local 3(MA), média tecnologia, MP3, R$45,00m-3 a estimativa foi 17% superior; Local 4(MG), média tecnologia, MP3, R$33,00m-3, o resultado foi 66% inferior; Local 5(MS), alta tecnologia, MP3, e R$42,50.m-3, a estimativa resultou 41% superior; Local 6, média tecnologia, AP1, e preço R$46,50.m-3 observou-se um resultado 30% superior; e Local 7, média tecnologia, curva MP2, e preço de R$45,00m-3, a estimativa foi 11% superior. Sugeriu-se a utilização de sistemas de informação geográfica (SIG) e da fórmula de Monte Alegre (FMA) como alternativas para mapeamento de riscos. Foram identificados na literatura mapas de riscos de geada (Estado de SP) e de seca (Brasil) e aplicada a FMA em dados de Piracicaba/SP, indicando o benefício de sua utilização. Recomenda-se que o modelo de cálculo e mapas de risco aqui apresentados sejam incorporados pelas seguradoras em suas rotinas de elaboração de apólices de seguro floresta, para que se garanta um adequado respaldo técnico / The study objective is to present a set of alternatives to the forestry insurance market, to systematize the process of forest valuation and to propose the most important indicators for risk assessment. Currently the forest risk valuation (VR) is based on cost or market value of the forest. This calculation method has limitations because it is common for the insurer to have to estimate these values. A new calculation of the VR is proposed here and takes into consideration the value of the forest in terms of its potential economic return. This new VR considers the fact that hazards interrupts the expected completion of the current exploration cycle, resulting in (i) the loss of future revenue that would be obtained with the wood produced by the current forest, less the costs that would be spent and (ii) the anticipation of the area occupation with a new activity, which would only happen after the current cycle of exploitation. The proposed method is illustrated with examples, suggesting three model based costing: High, Medium or Low technologies, applicable anywhere in Brazil. For the calculation of revenues eight growth curves for eucalyptus were generated, with mean annual increments (MAI) at age 7, 24, 27, 32, 35, 41, 52, 47 and 60 R$.m-3.ha-1, named BP1, BP2, MP1, MP2, MP3, AP1, AP2, AP3, respectively. The new VR was applied to seven real cases in different states. Each site was associated with a strategy of cost as a function of the technology employed (high medium or low) and linked to one of the growth curves. The price of wood considered regional values, and the discount rate was 12% per year. For Local 1 (PR), was consider low-tech, production curve MP1, and wood to R$ 45,00m-3, the new VR showed 5% less than the value of the policy; for the Local 2 (GO), high technology, AP2 and wood to R$ 45,00m-3, the method suggests 29% lower than the policy VR; Local 3 (MA), medium-tech, MP3, R$ 45,00m-3 estimates a 17% higher VR; Local 4 (MG), medium-tech, MP3, R$ 33,00m-3, the result was 66% lower; Local 5 (MS), high-tech, MP3, and R$ 42,50m-3, the estimate suggests 41% higher; Local 6, medium technology, AP1, and price R$ 46.50m-3 was observed a 30% higher result, and Local 7, medium technology, MP2 curve, and price of R$ 45,00m-3, the estimate was 11% higher. It was suggested the use of geographic information systems (GIS) and Monte Alegre formula (FMA) as alternatives for risk assessment. Maps of frost risks (for SP state) and drought (Brazil), were indicated. The FMA was applied on Piracicaba/SP database, indicating the benefit of its use. It is recommended that the model calculation and risk maps presented here are incorporated by insurers in their daily development of forest insurance policies to ensure adequate technical support.