Can wildlife surveillance contribute to public health preparedness for climate change? A Canadian perspective
Craig Stephen () and
Colleen Duncan
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Craig Stephen: Canadian Wildlife Health Cooperative
Colleen Duncan: College of Veterinary Medicine and Biomedical Sciences, Colorado State University
Climatic Change, 2017, vol. 141, issue 2, No 9, 259-271
Abstract:
Abstract Early warning systems for climate change adaptation, preparedness and response will need to take into consideration the range of factors that can drive risk and vulnerability. There are no data from which to nominate the most effective, efficient and reliable wildlife health signals for public health planning, but there is growing opinion that wildlife health could signal public health vulnerability related to climate change. The objective of this commentary is to explore the potential for wildlife to contribute to climate change early warning for public health protection in Canada. Wildlife impact many determinants of human health through both direct and indirect mechanisms; several of which are strongly interconnected. There is a long history of wildlife serving as bio-sentinels for environmental pollutants and pathogens. Wildlife health could support public health threat detection, risk assessment and risk communication by detecting and tracking infectious and non-infectious hazards, being bio-sentinels of effects of new or changed hazards, providing biologically understandable information to motivate changes in personal risk behaviours and providing insights into new and unanticipated threats. Public health risk communication and strategic planning priorities for climate change could benefit from a wildlife health intelligence system that collects data on incidents of disease and hazard discovery as well as information on social and environmental conditions that affect risk perception and likelihoods of human exposure or harms.
Keywords: Early Warning; West Nile Virus; Lyme Disease; Climate Change Adaptation; Domoic Acid (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s10584-016-1892-x
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