Grant: Doctoral Award - Frederick Banting and Charles Best Canada Graduate Scholarships

Avian influenza (AI) is a viral disease that can cause serious human and animal health consequences. The recent outbreaks of H7N9 and H5N1 AI strains, along with the possibility for AI to change into new strains with improved human-to-human transmission, leads to concerns that AI could cause the next global pandemic. Certain AI viruses are considered to be higher risk for causing disease, particularly H5 and H7 strains. The surveillance for AI is crucial to the prevention of its devastating impacts. AI normally circulates in wild waterfowl hosts who are the targets for AI surveillance; however, these hosts typically carry the virus without showing signs of disease. Additionally, our current AI surveillance techniques in wild waterfowl is focused on testing individual birds, which is labour intensive and makes it difficult to obtain a representative sample of the whole wild host population. This is problematic as we may not be detecting many AI strains circulating in the wild hosts. A solution to this problem is to test environmental samples. As wild birds excrete the virus in their feces and many individual birds defecate in wetlands, taking samples of wetland mud allows for the detection of AI viruses deposited by many birds within the population. This project will be the first study to evaluate the use of wetland sediment for the ongoing surveillance of AI, and will evaluate the effectiveness the environmental method against the gold-standard. The two-year study will have monthly surveillance on 3 wetlands, where the diversity, rate of positivity, and timing of AI viruses in sediment is compared to those circulating in live waterfowl birds (the gold-standard method). Data will also be collected on related wetland ecological variables such as water temperature and waterfowl abundance. This project will provide human and animal health officials with a more efficient and accurate signal of seasonal AI risk and help to prevent future surveillance failures.