Expansion of the Lyme Disease Vector Ixodes scapularis in Canada inferred from CMIP5 Climate Projections.


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June, 01, 2017


The emergence of Lyme disease has become a notable public health concern across Canada.  Lyme disease is caused by the bacterium Borrelia burgdorferi and is transmitted by Ixodid ticks. In western Canada and central/eastern Canada the main vectors are Ixodes pacificus and Ixodes scapularis (also known as deer ticks), respectively. In the early 1990's, Long Point on the Ontario shore of Lake Erie was identified as Canada's first endemic area for Lyme disease. Since that time, both the number of endemic regions and the annual number of diagnosed human cases of Lyme disease has steadily increased.

Studies suggest that climate suitability, predominantly temperature, is a key determinant of the survival of deer tick populations. As a result of climate change, additional areas in Canada may become climatically suitable for tick establishment. Furthermore, areas in Canada that are already experiencing reproducing deer tick populations may experience an increase in tick abundance. This information suggests that climate change may lead to both new and increased risk of Lyme disease across Canada.

An interdisciplinary group of researchers with backgrounds ranging from nursing and biology to climate sciences and entomology has conducted a study, based at St. Francis Xavier University, which may help to inform and stimulate adaptation planning associated with the increasing incidence of Lyme disease. M.Sc. students Michelle McPherson, Almudena García-García and Francisco José Cuesta-Valero (all students of StFX’s NSERC CREATE Training program in Climate Sciences) in collaboration with Drs. Hugo Beltrami (St. Francis Xavier University, Canada Research Chair in Climate Dynamics), Patti Hansen-Ketchum, Donna MacDougall (both professors at StFX’s School of Nursing) and Nicholas Hume Ogden (National Microbiology Laboratory, Public Health Agency of Canada) worked collaboratively to estimate the future potential impacts of climate change on the presence, abundance and propagation of the Lyme disease carrying tick, using the most up-to-date climate models.


The authors present the results of their study in a recent paper published in the prestigious journal, Environmental Health Perspectives, which is published with support from the National Institute of Environmental Health Sciences, the National Institutes of Health and the U.S. Department of Health and Human Services. Here authors provide comprehensive estimates of the current distribution and future emergence of the deer tick by using an ensemble of the most up-to-date General Circulation Models (GCMs) and emission scenarios (called Representative Concentration Pathways or RCPs). Each RCP relates to the magnitude of climate change associated with a specific greenhouse gas emission trajectory resulting from varying technological, demographic, economic, policy, emission and land-use futures. Using a range of emission scenarios and climate models simulations allowed for deer tick propagation estimates to be representative of a broad range of future climate outcomes. This study also assessed both when and where tick propagation becomes significant. Additionally, this study allowed for an assessment of how mitigation efforts may impact future Lyme disease emergence and propagation in Canada.

Over time all four RCP scenarios project statistically significant magnitudes of tick population propagation for all of Nova Scotia, areas of New Brunswick, Quebec and Ontario south of 47 °N and Manitoba south of 52 °N. Estimates show that expansions of the ticks' range in Canada are statistically significant even under the lowest emission scenario (RCP2.6), thus, Lyme disease risk may continue to emerge in Canada even if the Paris Agreements' goal is achieved. Researchers also showed that mitigation associated with the three lower emission scenarios may result in public health benefits which would not be realized if we continue with the currently implemented mitigation policies, which would likely lead to warming within the ranges projected by the highest emission scenario. However, mitigation may not have a marked impact on Lyme disease risks for those who will be inhabiting or undergoing outdoor activities in southern regions of Canada that are predicted to be climatically suitable for I. scapularis populations in the early decades of this century, and where we are now experiencing the emergence of the tick and Lyme disease.


Preparing regions for increased and/or new Lyme disease risks may need to become a public health priority. Public health efforts will need to include increasing awareness about Lyme disease and its prevention amongst the public, enhancing the knowledge and capacity of medical practitioners to diagnose and treat Lyme disease, enhancing surveillance to identify where Lyme disease risk is emerging, and developing information for public health practitioners on surveillance, prevention and control. Vulnerability of Canadian populations to Lyme disease will continue to evolve over the coming century, and it is likely that the success of public health's response to Lyme disease will depend on sustained adaptation efforts.


The team’s research was funded by The Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant, NSERC-CREATE award Training Program in Climate Sciences based at StFX, the Canada Research Chairs program, the Nova Scotia Research and Innovation Graduate Scholarship as well as the Climate & Atmospheric Sciences Institute (CASI) at St. Francis Xavier University.



The work can be freely accessed at:

McPherson, M. Y., A. García-García, F. J. Cuesta-Valero, H. Beltrami, P. Hansen-Ketchum, D. MacDougall, and N. Ogden (2017) Expansion of the Lyme Disease Vector Ixodes Scapularis in Canada inferred from CMIP5 Climate Projections. Environ Health Perspect; DOI:10.1289/EHP57.


Get PDF here:

https://ehp.niehs.nih.gov/wp-content/uploads/2017/05/EHP57.alt_.pdf

 

Figure Caption: Multi-model mean R0 values for I.scapularis (maps a-c) and the climate model

variability (95% confidence interval) (maps d-f) for the period 1971 to 2000 using the

Historical simulation and for the periods 2011 to 2040 and 2041 to 2070 using RCP4.5

simulations. R0 > 1 values were mapped for areas east of the Rocky Mountains and for

elevations below 500m. Black stippling in maps b and c shows the spatial distribution

of statistically significant changes in R0 between each future time period, 2011-2040

and 2041-2070, and the historical time period, 1971-2000. Statistical significance was

calculated using the Kolmogorov-Smirnov test.