Epidemiology

This thesis explores the shot-term relationship between exposure to ambient air pollution and human health through metrics such as mortality and hospitalization in Canada. We begin by detailing the organization and interpolation of air pollution data from its partially quality-controlled source form. Analyses of seasonal, regional and temporal trends of all major components of PM2.5, was performed, showing a seasonal variation across most regions and validating the dataset.

A one-pollutant statistical Generalized Additive Model was applied to the data, estimating the health risk associated with exposure to thirteen different components of PM2.5. The selected components were based on those that compromised the majority of the mass and included: sulphate, nitrate, zinc, silicon, iron, nickel, vanadium, potassium, organic carbon, organic matter, elemental carbon, total carbon. Trends based on annual estimates of the association for PM2.5, and its constituents,were compared, showing that carbonaceous compounds, sulphate and nitrate had similar estimates of association. Many estimates, as is common in population ecologic epidemiology, had association estimates statistically indistinguishable from zero, but with clear features of interest, including evident differences between cold and warm season associations in Canada's temperate climate.

A method to model two correlated pollutants (in this case, PM2.5 and O3) was developed using thin plate splines. In this approach, the location of the response surface (after accounting for the temperature, a smooth function of time and day of week) that corresponds to the average pollutant concentration and the average plus one unit was used as the estimate of the joint contribution of pollutants due to a unit increase. The estimates from the thin plate spline (TPS) approach were compared to the single pollutant models, with large increases and decreases in PM2.5 and O3 being captured in the TPS estimates. However, this approach indicated significantly larger error in the estimates than would be expected, indicating a possible future area for refinement.

Author Keywords: Air pollution, Environmental Epidemiology, Generalized Additive Models, Human Health, Multivariate Models, Thin Plate Splines

Medication used to treat human illness is one of the greatest developments in human history. In Canada, prescription drugs have been developed and made available to treat a wide variety of illnesses, from infections to heart disease and so on. Records of prescription drug fulfillment at coarse Canadian geographic scales were obtained from Health Canada in order to track the use of these drugs by the Canadian population.

The obtained prescription drug fulfillment records were in a variety of inconsistent formats, including a large selection of years for which only paper tabular records were available (hard copies). In this work, we organize, digitize, proof and synthesize the full available data set of prescription drug records, from paper to final database. Extensive quality control was performed on the data before use. This data was then analyzed for temporal and spatial changes in prescription drug use across Canada from 1990-2013.

In addition, one of major research areas in environmental epidemiological studies is the study of population health risk associated with exposure to ambient air pollution. Prescription drugs can moderate public health risk, by reducing the drug user's physiological symptoms and preventing acute health effects (e.g., strokes, heart attacks, etc.). The cleaned prescription drug data was considered in the context of a common model to examine its influence on the association between air pollution exposure and various health outcomes. Since, prescription drug data were available only at the provincial level, a Bayesian hierarchical model was employed to include the prescription drugs as a covariate at regional level, which were then combined to estimate the association at national level. Although further investigations are required, the study results suggest that the prescription drugs influenced the air pollution related public health risk.

Author Keywords: Data, Error checking, Population health, Prescriptions

Understanding the maintenance and spread of invasive diseases is critical in evaluating threats to biodiversity and how to best minimize their impact, which can by done by monitoring disease occurrences across time and space. I sought to apply existing and upcoming molecular tools to assess fluctuations in both presence and strain variation of frog virus 3 (FV3), a species of Ranavirus, across Canadian waterbodies. I explored the temporal patterns and spatial distribution of ranavirus presence across multiple months and seasons using environmental DNA techniques. Results indicate that ranavirus was present in approximately 72.5% of waterbodies sampled on a fine geographical scale (<10km between sites, 7,150 km2), with higher detection rates in later summer months than earlier. I then explored the sequence variability at the major capsid protein gene (MCP) and putative virulence gene (vIF-2α) of FV3 samples from Ontario, Alberta, and the Northwest Territories, with the premise of understanding pathogen movement across the landscape. However, a lack of genetic diversity was found across regions, likely due to a lack of informative variation at the chosen genetic markers or lack of mutation. Instead, I found a novel FV3-like ranavirus and evidence for a recombinant between FV3 and a ranavirus of another lineage. This thesis provides a deeper understanding into the spatio-temporal distribution of FV3, with an idea of how widespread and threatening ranaviruses are to amphibian diversity.

Keywords: ranavirus, frog virus 3, amphibians, environmental DNA, phylogenetics, wildlife disease, disease surveillance, major capsid protein, vIF-2α

Author Keywords: amphibians, environmental DNA, frog virus 3, phylogenetics, ranavirus, wildlife disease