Portrait of David Buckeridge

David Buckeridge

Associate Academic Member
Full Professor, McGill University, Department of Epidemiology, Biostatistics and Occupational Health
Research Topics
Medical Machine Learning
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Biography

David Buckeridge is a professor at the School of Population and Global Health at McGill University, as well as chief digital health officer for the McGill University Health Centre and executive scientific director of the Public Health Agency of Canada.

A Tier 1 Canada Research Chair in Health Informatics and Data Science, Buckeridge has projected health system demand for the Canadian province of Quebec, led data management and analytics for the Canadian Immunity Task Force, and supported the World Health Organization in monitoring global immunity to SARS-CoV-2. He has an MD from Queen's University, an MSc in epidemiology from the University of Toronto and a PhD in biomedical informatics from Stanford University. He is a Fellow of the Royal College of Physicians of Canada.

Current Students

Kalash Dave
Master's Research - McGill University
Eva Gao
PhD - McGill University
yachen li Li
Master's Research - McGill University
yachen.li@mail.mcgill.ca
Aidan Licoppe
Master's Research - McGill University
Github
Yannan Shen
Master's Research - McGill University

Publications

Guest Editorial Explainable AI: Towards Fairness, Accountability, Transparency and Trust in Healthcare
Arash Shaban-Nejad
Martin Michalowski
John S. Brownstein
David Buckeridge
2021-01-01
IEEE journal of biomedical and health informatics (published)
doi.org
Assessing the Electronic Evidence System Needs of Canadian Public Health Professionals: A Cross-Sectional Study (Preprint)
Bandna Dhaliwal
Sarah E Neil-Sztramko
Nikita Boston-Fisher
David Buckeridge
Maureen Dobbins
BACKGROUND True evidence-informed decision making in public health relies on incorporating evidence from a number of sources in addition to… (see more) traditional scientific evidence. Lack of access to these types of data, as well as ease of use and interpretability of scientific evidence contribute to limited uptake of evidence-informed decision making in practice. An electronic evidence system that includes multiple sources of evidence and potentially novel computational processing approaches or artificial intelligence holds promise as a solution to overcoming barriers to evidence-informed decision making in public health. OBJECTIVE To understand the needs and preferences for an electronic evidence system among public health professionals in Canada. METHODS An invitation to participate in an anonymous online survey was distributed via listservs of two Canadian public health organizations. Eligible participants were English or French speaking individuals currently working in public health. The survey contained both multiple choice and open-ended questions about needs and preferences relevant to an electronic evidence system. Quantitative responses were analyzed to explore differences by public health role. Inductive and deductive analysis methods were used to code and interpret the qualitative data. Ethics review was not required by the host institution. RESULTS Respondents (n = 371) were heterogeneous, spanning organizations, positions, and areas of practice within public health. Nearly all (98.0%) respondents indicated that an electronic evidence system would support their work. Respondents had high preferences for local contextual data, research and intervention evidence, and information about human and financial resources. Qualitative analyses identified a number of concerns, needs, and suggestions for development of such a system. Concerns ranged from personal use of such a system, to the ability of their organization to use such a system. Identified needs spanned the different sources of evidence including local context, research and intervention evidence, and resources and tools. Additional suggestions were identified to improve system usability. CONCLUSIONS Canadian public health professionals have positive perceptions towards an electronic evidence system that would bring together evidence from the local context, scientific research, and resources. Elements were also identified to increase the usability of an electronic evidence system.
2020-12-14
JMIR Public Health and Surveillance (published)
doi.org
Global Surveillance of COVID-19 by mining news media using a multi-source dynamic embedded topic model
Yue Li
Pratheeksha Nair
Zhi Wen
Imane Chafi
Anya Okhmatovskaia
Guido Powell
Yannan Shen
David Buckeridge
2020-11-10
Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (published)
doi.org
Effectiveness of quarantine and testing to prevent COVID-19 transmission from arriving travelers
Russell Wa
David Buckeridge
2020-11-04
medRxiv (preprint)
doi.org
Explainability and Interpretability: Keys to Deep Medicine
Arash Shaban-Nejad
Martin Michalowski
David Buckeridge
2020-11-03
Explainable AI in Healthcare and Medicine (published)
doi.org
Association between extreme precipitation, drinking water and acute gastrointestinal illness in the Great Lakes
R. Graydon
M. Mezzacapo
J. Boehme
David Buckeridge
S. Foldy
T. Edge
J. Brubacher
L. Chan
M. Dellinger
E. Faustman
J. Rose
T. Takaro
2020-10-26
ISEE Conference Abstracts (published)
doi.org
Importation of SARS-CoV-2 following the "semaine de relache" and Quebec's (Canada) COVID-19 burden - a mathematical modeling study
Arnaud Godin
Yiqing Xia
David Buckeridge
Sharmistha Mishra
Dirk Douwes-Schultz
Yannan Shen
Maxime Lavigne
Mélanie Drolet
Alexandra M. Schmidt
Marc Brisson
Mathieu Maheu-Giroux
Background: The Canadian epidemics of COVID-19 exhibit distinct early trajectories, with Quebec bearing a very high initial burden. The sema… (see more)ine de relache, or March break, took place two weeks earlier in Quebec as compared to the rest of Canada. This event may have played a role in the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to examine the role of case importation in the early transmission dynamics of SARS-CoV-2 in Quebec. Methods: Using detailed surveillance data, we developed and calibrated a deterministic SEIR-type compartmental model of SARS-CoV-2 transmission. We explored the impact of altering the number of imported cases on hospitalizations. Specifically, we investigated scenarios without case importation after March break, and as scenarios where cases were imported with the same frequency/timing as neighboring Ontario. Results: A total of 1,544 and 1,150 returning travelers were laboratory-confirmed in Quebec and Ontario, respectively (with symptoms onset before 2020-03-25). The cumulative number of hospitalizations could have been reduced by 55% (95% credible interval [95%CrI]: 51-59%) had no cases been imported after Quebec's March break. However, had Quebec experienced Ontario's number of imported cases, cumulative hospitalizations would have only been reduced by 12% (95%CrI: 8-16%). Interpretation: Our results suggest that case importation played an important role in the early spread of COVID-19 in Quebec. Yet, heavy importation of SARS-CoV-2 in early March could be insufficient to resolve interprovincial heterogeneities in cumulative hospitalizations. The importance of other factors -public health preparedness, responses, and capacity- should be investigated.
2020-10-25
International Journal of Infectious Diseases (published)
doi.org
The role of case importation in explaining differences in early SARS-CoV-2 transmission dynamics in Canada—A mathematical modeling study of surveillance data
Arnaud Godin
Yiqing Xia
David Buckeridge
Sharmistha Mishra
Dirk Douwes-Schultz
Yannan Shen
Maxime Lavigne
Mélanie Drolet
Alexandra M. Schmidt
Marc Brisson
Mathieu Maheu-Giroux
2020-10-25
International Journal of Infectious Diseases (published)
doi.org
Parametric models for combined failure time data from an incident cohort study and a prevalent cohort study with follow-up
James H. McVittie
David B. Wolfson
David A. Stephens
Vittorio Addona
David Buckeridge
2020-10-12
The International Journal of Biostatistics (published)
doi.org
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing
Prateek Gupta
Tegan Maharaj
Martin Weiss
Nasim Rahaman
Hannah Alsdurf
abhinav sharma
Nanor Minoyan
Soren Harnois-Leblanc
Victor Schmidt
Pierre-Luc St-Charles
Tristan Deleu
andrew williams
Akshay Patel
Meng Qu
Olexa Bilaniuk
gaetan caron
pierre luc carrier
satya ortiz gagne
Marc-Andre Rousseau
David Buckeridge … (see 9 more)
Joumana Ghosn
Yang Zhang
Bernhard Schölkopf
Jian Tang
Irina Rish
Chris Pal
Joanna Merckx
Eilif Benjamin Muller
Yoshua Bengio
2020-10-02
OpenReview.net/Anonymous_Preprint (unknown)
openreview.net
openreview.net
NutriQuébec: a unique web-based prospective cohort study to monitor the population’s eating and other lifestyle behaviours in the province of Québec
Annie Lapointe
Catherine Laramée
Ariane Belanger-Gravel
David Buckeridge
Sophie Desroches
Didier Garriguet
Lise Gauvin
Simone Lemieux
Céline Plante
Benoit Lamarche
2020-10-01
BMJ Open (published)
doi.org
Correction to: Why public health matters today and tomorrow: the role of applied public health research
Lindsay McLaren
Paula Braitstein
David Buckeridge
Damien Contandriopoulos
Maria I. Creatore
Guy Faulkner
David Hammond
Steven J. Hoffman
Yan Kestens
Scott Leatherdale
Jonathan McGavock
Wendy V. Norman
Candace Nykiforuk
Valéry Ridde
Janet Smylie
The article “Why public health matters today and tomorrow: the role of applied public health research,” written by Lindsay McLaren et al… (see more)., was originally published Online First without Open Access.
2020-09-02
Canadian Journal of Public Health = Revue Canadienne de Santé Publique (published)
doi.org