Erin E. Rees

Chief of the Public Health Geomatics Unit, Research Biologist

I am geographer and ecologist by training. I lead and support projects focused on public health risk assessment of infectious diseases by applying theory and methods from spatial epidemiology, GIS, remote sensing and geospatial analytics.

Public Health Agency of Canada

3190 Sicotte, Saint Hyacinthe

Current research and/or projects

COVID-19 response and ongoing pandemic preparedness:

integration of information from open-access social and news media to detect emerging public health threats and support situational awareness of known threats
importation risk of infectious diseases through air and land travel
impact of non-pharmaceutical interventions to reduce infectious disease transmission

Zoonotic diseases and risk mapping:

ecological niche modelling to map risks of tick and mosquito borne diseases
rabies disease ecology and assessing effectiveness of surveillance and control strategies

Spatiotemporal epidemiology of vulnerable populations:

identifying ‘hotspots’ of acute toxicity deaths (ATD) in Canada
sociodemographic factors associated with ATDs in ‘hotspots’
weather factors increasing risk of ATDs and implications for climate warming

Research and/or project statements

The Public Health Geomatics Unit, National Laboratory Microbiology Branch of the Public Health Agency of Canada, specialises in using earth observation (EO) and other spatial data for public health risk assessment drawing on the fields of health geography, spatial epidemiology, GIS, remote sensing and disease ecology. Many study systems are zoonotic infectious diseases from tick and mosquito vectors. Research projects inherently apply the One Health approach: environment (climatic and environmental sensitivities of the vectors and hosts), animal (spatiotemporal distributions of hosts and vectors of infectious pathogens), and human (identifying populations and behaviours at risk). Key project outcomes are risk maps to help inform health professionals and the general public of risk areas for now and into future with climate warming and land use changes.

Dr. Rees’ research focuses on identifying spatiotemporal factors affecting the occurrence and spread of infectious diseases using geospatial, statistical and agent-based modelling approaches. Research projects integrate georeferenced data from a variety of sources such as medical records and social demographics, social and news media, animal surveillance data, disease control/treatment strategies, environmental determinates of health (e.g. landscape/habitat/ climatic factors) and host genetic population structure. Previous study systems included raccoon rabies, chronic wasting disease, aquatic epidemiology of salmon farming systems, and bivalves as sentinels to antimicrobial resistance in coastal waters. Current research capitalises on past experiences at the animal-environment interface to apply a One Health approach to public health risk assessment of zoonotic diseases (e.g. rabies, Lyme disease, ZIKA, COVID-19). Research outcomes help improve early warning of emerging public health threats and situational awareness of known threats. Another key research outcome is to improve disease prevention, control and surveillance activities by assessing the effectiveness of different strategies under plausible scenarios of population and infection dynamics.

Professional activities / interests

Member of Geo Health Community of Practice and the Infectious Diseases small work group
Member of GREZOSP (Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique)
Member of international working group on raccoon rabies disease ecology
Supervising graduate students, Federal Student Work Experience Program, students, postdoctoral researchers

Education and awards

Education

2003-2007 Ph.D. in Spatial epidemiology of wildlife diseases, Trent University: Approaches to modelling raccoon rabies
2001-2002 M.Sc. in Geographic Information Science, University of Edinburgh: GIS, environmental change, and the late quaternary distribution of the Eurasian/African wildcat (Felis silverstris)
1996-2000 B.Sc. Honours in Geography and Biology, Queen’s University

Awards

2008 Governor General’s Academic Gold Medal Award for PhD: awarded to graduate students with the highest academic distinction at Canadian universities
2002 Best Dissertation, M.Sc. in Geographical Information Science, University of Edinburgh award
2002 Best Overall Performance, M.Sc. in Geographical Information Science, University of Edinburgh award

International experience and/or work

Key publications

Milwid RM, Gabriele-Rivet V, Ogden NH, Turgeon P, Fazil A, London D, de Montigny S, and EE Rees. A methodology for estimating SARS-CoV-2 importation risk by air travel into Canada between July and November 2021. BMC Public Health 24, 1088 (2024). https://doi.org/10.1186/s12889-024-18563-1

Hammond-Collins K, Tremblay M, Milord F, Baron G, Bouchard C, Kotchi S-O, Lambert L, Leighton P, Ogden NH, Rees EE. 2022. An ecological approach to predict areas with established populations of Ixodes scapularis in Quebec, Canada. Ticks and Tick-borne Diseases. 13(6): 102040. https://doi.org/10.1016/j.ttbdis.2022.102040.

Rees EE, Avery BP, Carabin H, Carson CA, Champredon D, Dougherty B, Nasri BR, Ogden NH. Effectiveness of non-pharmaceutical interventions to reduce SARS-CoV-2 transmission in Canada and their association with COVID-19 hospitalisation rates. Can Commun Dis Rep. 2022;48(10):438–48. https://doi.org/10.14745/ccdr.v48i10a04

Gilbert JP., Niu J., de Montigny S., Ng V., Rees E. (2022) Machine Learning Identification of Self-reported COVID-19 Symptoms from Tweets in Canada. In: Shaban-Nejad A., Michalowski M., Bianco S. (eds) AI for Disease Surveillance and Pandemic Intelligence. W3PHAI 2021. Studies in Computational Intelligence, vol 1013. Springer, Cham. https://doi.org/10.1007/978-3-030-93080-6_9.

Niu J, Rees E, Ng V, Penn G. 2021. Statistically Evaluating Social Media Sentiment Trends towards COVID-19 Non-Pharmaceutical Interventions with Event Studies. Proceedings of the Sixth Social Media Mining for Health (#SMM4H) Workshop and Shared Task. Association for Computational Linguistics. 10.18653/v1/2021.smm4h-1.1

Gilbert JP, Ng V, Niu J and Rees EE. 2020. A call for an ethical framework when using social media data for AI applications in public health research. Canadian Communicable Disease Report. 46(6): 169-173.

McClure K, Gilbert A, Chipman R, Rees E, and K Pepin. 2020. Variation in host home range size decreases rabies vaccination effectiveness by increasing the spatial spread of rabies virus. Journal of Animal Ecology. 89(6):1375-1386.

Newton E, Pond B, Tinline R, Middel K, Bélanger D and Rees EE. 2019. Differential impacts of vaccination on wildlife disease spread during epizootic and enzootic phases. Journal of Applied Ecology (56)3: 526-536. DOI:10.1111/1365-2664.13339

Rees EE, Petukhova T, Pelcat Y, and Ogden N. 2018. Environmental and social determinants of population vulnerability to Zika virus emergence at the local scale. Parasites & Vectors. 11:290.

Rees EE, Pond BA, Tinline RR, and Bélanger D. 2013. Modelling the effect of landscape heterogeneity on the efficacy of vaccination for wildlife infectious disease control. Journal of Applied Ecology. 50(4):881-891.

Rees EE, Pond BA, Cullingham CI, Tinline RR, Ball D, Kyle CJ, and White BN. 2009. Landscape modelling spatial bottlenecks: implications to raccoon rabies disease spread. Biology Letters, 5:387-390.

Rees EE, Pond BA, Cullingham CI, Tinline RR, Ball D, Kyle CJ, and White BN. 2008. Assessing a landscape barrier using genetic simulation modelling: implications for raccoon rabies management. Preventive Veterinary Medicine, 86: 107-123.

Rees EE, Pond BA, Phillips JR, and Murray DL. 2008. Raccoon Ecology Database: a resource for population dynamics modeling and meta-analysis. Ecological Informatics, 3(1): 87-96.