The relationship of E. coli and total coliform culture to the quantitative molecular detection of various fecal indicators, sources, and pathogens in private drinking water wells

Water remains a predominant vector for human enteric pathogens not just for developing countries but also developed nations, where numerous infectious disease outbreaks, linked to the contamination of drinking water have been documented. Private drinking water wells are a source of drinking water that is largely unstudied even though a significant percentage of the population in Ontario relies on wells as their primary water source. As there exists little to no systematic surveillance for enteric infections or outbreaks related to well water sources, these individuals may be at higher risk of waterborne infectious diseases. The relationships between various fecal indicators in the water of private drinking water wells, including E. coli, Total Coliforms (TC) and Bacteroides, and enteric pathogens, including Campylobacter jejuni, Salmonella spp., and Shiga toxin producing E. coli, were studied. Convenience private well water samples collected from various regions of interest during the summer of 2014 underwent membrane filtration and culture to determine quantities of E. coli and TC colony forming units. 289 E. coli positive and 230 TC-only waters were successfully analyzed by individual qPCR assays for the aforementioned enteric pathogens. Microbial source tracking methods targeted to specific Bacteroides were used to determine the source of fecal contamination as either human or bovine. The source of fecal contamination varied by geographic region and is thought to be due to such things as differences in septic tank density and underlying geology, among others. Fecal indicators, E. coli and Bacteroides, were significantly correlated. E. coli as measured by qPCR was more strongly correlated to both total and human-specific Bacteroides genetic markers than culturable E. coli. Lastly, 1.9% of samples showed molecular evidence of contamination with enteric pathogens. Although low, this finding is significant given the limited volume of water available for testing, and suggests a potential health risk to consumers. Knowing the extent of contamination, as well as the biologic source, can better inform risk assessment and the development of potential intervention strategies for private well water in specific regions of Ontario.

An impulsive differential equation model for Marek's disease

Many dynamical processes are subject to abrupt changes in state. Often these perturbations can be periodic and of short duration relative to the evolving process. These types of phenomena are described well by what are referred to as impulsive differential equations, systems of differential equations coupled with discrete mappings in state space. In this thesis we employ impulsive differential equations to model disease transmission within an industrial livestock barn. In particular we focus on the poultry industry and a viral disease of poultry called Marek's disease. This system lends itself well to impulsive differential equations. Entire cohorts of poultry are introduced and removed from a barn concurrently. Additionally, Marek's disease is transmitted indirectly and the viral particles can survive outside the host for weeks. Therefore, depopulating, cleaning, and restocking of the barn are integral factors in modelling disease transmission and can be completely captured by the impulsive component of the model. Our model allows us to investigate how modern broiler farm practices can make disease elimination difficult or impossible to achieve. It also enables us to investigate factors that may contribute to virulence evolution. Our model suggests that by decrease the cohort duration or by decreasing the flock density, Marek's disease can be eliminated from a barn with no increase in cleaning effort. Unfortunately our model also suggests that these practices will lead to disease evolution towards greater virulence. Additionally, our model suggests that if intensive cleaning between cohorts does not rid the barn of disease, it may drive evolution and cause the disease to become more virulent.