The Surveillance lab within the Clinical and Health Informatics Research Group at McGill University brings together a vibrant multidisciplinary team of over 20 investigators, public health practitioners, clinicians, research staff, students and software developers, all dedicated to conducting research and development of computational methods and software that has immediate impact on improving population health through the science and practice of biosurveillance. The Surveillance Lab is funded by several sources including the Canadian Foundation for Innovation, the Canadian Institutes of Health Research, a Canada Research Chair, the Bill and Melinda Gates Foundation, the National Sciences and Engineering Research Council, the Centers for Disease Control and Prevention and many other sources. On many projects, we work closely with public health practitioners in Quebec and from around the world. The computerized solutions we have developed are used by public health agencies in Quebec, Canada, and internationally.
Lab Lead
David L. Buckeridge
Professor
David Buckeridge is a Professor of Epidemiology and Biostatistics at McGill University in Montreal where he holds a Canada Research Chair in Health Informatics and Data Science. He is also a Medical Consultant to the Institut national d’excellence en santé et en services social. Dr Buckeridge has consulted on surveillance to organizations such as the Public Health Agency of Canada, the US Institute of Medicine, the US and Chinese Centers for Disease Control, the European Centers for Disease Control, and the World Health Organization. He holds a M.D. from Queen’s University, a M.Sc. in Epidemiology from the University of Toronto, a Ph.D. in Biomedical informatics from Stanford University and is a Fellow of the Royal College of Physicians and Surgeons of Canada with specialty training in Public Health and Preventive Medicine.
Yu Luo
Yu Luo is a Post Doc in Biostatistics at McGill University, working with David Buckeridge and David Stephens. He did his master’s and part of his undergraduate studies at University of Waterloo in Math and Statistics. His PhD work was mainly focused on the development of methodology related to spatial-temporal data, multi-stage models and non-parameter Bayesian statistics. He is currently working on a project for predicting ADHD prevalence based on the Canadian pharmacy sales data.
Yu Luo est post doc en biostatistique à l’Université McGill University, où il travaille avec David Buckeridge et David Stephens. Il a obtenu son diplôme de maîtrise et effectué une partie de son baccalauréat à l’Université de Waterloo en mathématiques et statistiques. Sa recherche doctorale est centrée sur l’élaboration de méthodologie liée aux données spatiales et temporelles, aux modèles à degrés multiples et aux statistiques bayésiennes non paramétriques. Il travaille actuellement sur un projet visant à prévoir la prévalence du TDAH d’après les données de ventes pharmaceutiques canadiennes.
Xuefei Shi
Xuefei obtained her Bachelor’s degree in Biomedical engineering(in direction of biomedical informatics) from Southern Medical University and her Master’s degree in Computer Science from Concordia University. She’s been working as a developer of PopHR since fall 2016. Her main duties include maintaining, designing and developing new features of the application.
Xuefei a obtenu son baccalauréat en génie biomédical (en direction de l’informatique biomédicale) de la Southern Medical University et sa maîtrise en informatique de l’Université Concordia. Elle travaille comme développeuse de PopHR depuis l’automne 2016. Ses tâches principales incluent la maintenance, la conception et le développement de nouvelles fonctionnalités de l’application.
Alexis Hamel
Alexis studied at the University de Montreal in Computer Science and Information Management, he joined the team in 2013, working on the PopHR project.
Diplomé de l’Université de Montréal en informatique et gestion de l’information, il joint l’équipe en 2013 et travail depuis sur le projet PopHR.
Anya Okhmatovskaia
Anya’s research interests lie in applied artificial intelligence, knowledge modeling and stochastic agent-based simulation. She has been involved in several projects designing ontology-driven software systems and simulation models.
She has a Bachelor’s and a PhD degree in Psychology from Moscow University, and a Master’s in Computer Science from the University of Southern California. Before joining the Surveillance Lab in 2006 Anya was working at the USC Institute for Creative Technologies, in the field of affective computing and human computer interaction.
Les domaines de recherche d’Anya se centrent sur l’intelligence artificielle appliquée, la modélisation des connaissances et la simulation stochastique à base d’agents. Elle est impliquée dans plusieurs projets de conception de logiciels et de modèles de simulation axés sur l’ontologie.
Elle possède un diplôme de Baccalauréat et un Doctorat en psychologie de l’Université de Moscou ainsi qu’une Maîtrise en science informatique de la University of Southern California. Avant de rejoindre le laboratoire de surveillance en 2006, Anya travaillait au USC Institute for Creative Technologies, dans le domaine de l’informatique affective et de l’interaction humain-ordinateur.
Maxime Lavigne
By the time he graduated from Software Engineering, he had acquired the skills and theoretical knowledge that allowed him to excel in clinical informatics. In addition to system design, semantic web, and theoretical computing, Maxime brings to his projects a passion for medicine and innovation. He is now pursuing a PhD in Epidemiology in addition to being a member of the PopHR and SDIDS projects. By combining his background in software engineering and medical informatics research, he helps bridge the gap between research and implementation.
Lorsqu’il a obtenu son diplôme de génie logiciel, il avait déjà acquis les compétences et les connaissances théoriques nécessaires à lui permettre d’exceller en informatique clinique. En plus de la conception de systèmes, de la toile sémantique et de la théorie informatique, Maxime apporte à ses projets une passion pour la médecine et l’innovation. Simultanément, il effectue un doctorant en épidemiologie est membre de PopHR et participe à des projets d’intégration de données évolutives destinées à la surveillance des maladies. En combinant ses antécédents en génie logiciel et en informatique médicale, il aide à faire les liens entre recherche et implantation.
Aman Verma
Aman received a Bachelor’s degree in Computer Science from Queen’s University, a Master’s degree in Health Informatics from Dalhousie University and a doctoral degree in Epidemiology from McGill. Since joining the Surveillance Lab he has been involved in projects simulating anthrax inhalation outbreaks, monitoring infectious disease through e-prescribing software, and detecting tuberculosis outbreaks through space-time surveillance. He is currently interested in modeling hospital readmissions in Montreal hospitals.
Aman a obtenu un baccalauréat en informatique de l’Université Queen’s, une maîtrise en informatique de la santé de l’Université Dalhousie et un doctorat en épidémiologie de l’Université McGill. Depuis qu’il a rejoint le laboratoire de surveillance, il a participé à des projets simulant des épidémies d’inhalation de charbon, surveillant les maladies infectieuses au moyen d’un logiciel de prescription électronique et détectant les épidémies de tuberculose grâce à une surveillance spatio-temporelle. Il s’intéresse actuellement à la modélisation des réadmissions dans les hôpitaux montréalais.
Hiroshi Mamiya
Hiroshi completed his BSc in the University of Winnipeg and MSc and PhD in Epidemiology under the supervision of Dr. Buckeridge. He is a post-doctoral fellow supported by the Institut de valorisation des données (https://ivado.ca/en/spotlight-on-our-academic-community/) under the supervision of Dr. Erica EM. Moodie (https://www.ericamoodie.com/) and Dr. Alexandra M. Schmidt (http://alex-schmidt.research.mcgill.ca/). His main research interest is identifying the distribution and socio-environmental, political, and economic determinants of health-related behaviors, with a focus on public health nutrition. His past and current work includes small area estimation of diets, estimating dynamic effect of food marketing activities on food purchasing patterns, dynamic segmentation of grocery shoppers, and analysis of market innovations related to healthy food promotions. His research is characterized by the application of linked and spatio-temporally indexed health and non-health data to generate granular statistics relevant to policy/program formulation and evaluation for small subpopulations and neighborhoods.
Hiroshi a complété son baccalauréat en sciences à l’Université de Winnipeg et sa maîtrise et son doctorat en épidémiologie sous la supervision du Dr. Buckeridge. Il est stagiaire postdoctoral soutenu par l’Institut de valorisation des données (https://ivado.ca/zoom-sur-notre-communaute-academique/) sous la direction du Dr. Erica EM. Moodie (https://www.ericamoodie.com/) et Dre Alexandra M. Schmidt (http://alex-schmidt.research.mcgill.ca/). Son principal intérêt de recherche est l’identification de la distribution et des déterminants socio-environnementaux, politiques et économiques des comportements liés à la santé, en mettant l’accent sur la nutrition en santé publique. Ses travaux passés et actuels comprennent l’estimation sur de petits domaines des régimes alimentaires, l’estimation de l’effet dynamique des activités de marketing alimentaire sur les modèles d’achat d’aliments, la segmentation dynamique des acheteurs d’épicerie et l’analyse des innovations du marché liées aux promotions d’aliments sains. Ses recherches se caractérisent par l’application de données liées et indexées spatio-temporellement sur la santé et les autres domaines pour générer des statistiques granulaires pertinentes pour la formulation et l’évaluation de politiques / programmes pour les petites sous-populations et les quartiers.
Erin Yiran Liu
Erin is currently a PhD Epidemiology student at McGill University. Previously, she worked as a Methodologist at the Ottawa Hospital Research Institute and as a Senior Analyst at Cancer Care Ontario. Her research interests are in using computational methods for analyzing population health data and integrating these methods in the PopHR platform to inform decision-making.
Erin est actuellement doctorante en épidémiologie à l’Université McGill. Auparavant, elle a travaillé comme méthodologiste à l’Institut de recherche de l’Hôpital d’Ottawa et comme analyste principale à Action Cancer Ontario. Ses recherches portent sur l’utilisation de méthodes informatiques pour analyser les données sur la santé de la population et l’intégration de ces méthodes dans la plateforme PopHR afin d’éclairer la prise de décision.
Daniela Anker
Daniela Anker is an exchange student at the Surveillance Lab and works on developing a frailty index based on claims data from Quebec. She received an MSc in biomedical sciences at the University of Bern in Switzerland and she is a PhD student in Epidemiology at the University of Bern. Her research interests are in frailty and the relationship between frailty and blood pressure in older adults.
Daniela Anker est un étudiante en échange au Surveillance Lab et travaille sur l’élaboration d’un indice de fragilité basé sur des données d’assurance maladie du Québec. Elle est titulaire d’un master en sciences biomédicales de l’Université de Berne en Suisse et elle fait un PhD en épidémiologie à l’Université de Berne. Ses intérêts de recherche portent sur la fragilité et la relation entre la fragilité et la pression artérielle chez les personnes âgées.
Publication majeure
Below you will find some of the main publications of the surveillance laboratory. For a more complete list, please visit Dr. Buckeridge’s Google Scholar page.
Current Projects
PopHR
The Population Health Record (PopHR) is an informatics platform that uses existing epidemiological and public health knowledge to integrate multiple clinical and administrative data sources to provide a coherent view of the health of populations. Users of the PopHR can develop detailed portraits of the health status and healthcare utilization patterns for a population, monitor various health indicators to detect temporal and spatial variations in disease activity, and evaluate the effectiveness of interventions on population health. The platform provides representative information in near-real time with high geographical resolution, thereby assisting public health professionals, clinicians and the public in diagnostic and therapeutic decision-making. At the same time, the PopHR provides a platform for advancing research in public health informatics and disease surveillance.
To view the Canada-wide version of the software please click here. Please note that it is optimized for use in the Chrome Browser. Additional information on the POPHR can also be found in our Gitbook.
Funded By: Public Health Agency of Canada
*The views expressed herein do not necessarily represent the views of the Public Health Agency of Canada.
E-Health Interventions in Public Health
We all use information to make decisions. In our daily life, we have seen remarkable gains in the ease with which we can access information. Unfortunately, similar advances in information access have not occurred in public health practice, where it is often difficult to access necessary information. There is a huge potential benefit to society if we can develop and evaluate software to help people make better decisions about preventing chronic diseases, detecting infectious disease outbreaks, and planning the delivery of public health services. This research program will develop and evaluate innovative strategies that use modern computing to improve decisions about important public health problems.
Funded By: Canadian Institutes for Health Research
In Collaboration with: Sante Montreal, INSPQ, NCCPH, Stanford University, McGill University
Surveillance of Vaccination Opinions and Beliefs in Online Media
The goal of this project is to develop methods for public health surveillance of opinions and beliefs about vaccination expressed in online media. In particular, we intend to automate the detection and classification of comments about the safety and effectiveness of vaccines. To develop these methods we are using a large sample of media reports from HealthMap’s Vaccine Intelligence Surveillance System. The automated methods will be evaluated against manual classification of the same reports. As we develop and evaluate our methods, we are also performing descriptive analyses to understand how the frequency of media reports containing comments about vaccines changes over time and space. This work will provide evidence to guide the use of online media surveillance and monitor vaccine opinions and beliefs.
Funded By: CIRN
In Collaboration with: Concordia University and Harvard University
Past Projects
Opioid Overdose
The use of illegal drugs imposes a devastating cost on Canadians, both in terms of lives lost and dollars spent. The rate of prescribing opioids, in particular, has increased close to one hundred-fold since 2000 and more Canadians are now dying of accidental overdoses from POs than from street drugs such as heroin and cocaine. Prevention efforts are needed urgently, but detecting individuals likely to experience a PO overdose is currently difficult. The goal of this project is to identify personal characteristics and patterns of healthcare use associated with unintentional death from PO overdose. We will use health data from multiple sources, including the Coroner’s Office, hospital records and drug prescribing databases, to identify characteristics of PO abusers who are likely to die from an accidental overdose. This information should allow public health policy-makers to optimize treatment services and harm reduction efforts.
Funded By: Canadian Institutes for Health Research
Scalable Data Integration for Disease Surveillance (SDIDS)
Data for global disease surveillance are fragmented across diseases, countries, funders, and a wide range of clinical settings. This fragmentation of data makes it challenging to assess population health, target disease control activities, and evaluate the effect of interventions. We are developing the SDIDS software platform to integrate surveillance data and make them available to support global health decision making. A proof-of-concept version of the system has been to integrate malaria surveillance data for Uganda. SDIDS makes extensive use of ontologies, including an ontology of data sources and an ontology of global health. Raw data sources are mapped to these ontologies and then automatically translated into a common format, where the integrated data can then be accessed by software to calculate and visualize a variety of indicators. We are now in the process of scaling-up SDIDS to include data for the main causes of under-five mortality in Africa.
Funded by: Bill and Melinda Gates Foundation
In Collaboration with the Uganda Malaria Surveillance Project and the National Malaria Control Programme, University of Washington, Stanford University, Harvard University.
GI Project
Reviews of the public health response to historical outbreaks of GI illness call consistently for improvements to the public health surveillance. There is not sufficient evidence, however, to determine the effectiveness of specific changes to the existing surveillance infrastructure. The goal of the project is to evaluate empirically how enhancements to public health surveillance systems will impact the effectiveness of these systems in detecting waterborne enteric disease outbreaks.
Former Members
Guido Powell
Mengru Yuan
Luc de Montigny
Kate Zinszer
Arash Shaban-Nejad
Deepa Jahagirdar
Jean-Paul Soucy
Marc-Andre Blanchette
Yun-Hsuan Wu (Wendy)
Kathryn Morrison
Kody Crowell