Portrait of David Buckeridge

David Buckeridge

Associate Academic Member
Full Professor, McGill University, Department of Epidemiology, Biostatistics and Occupational Health


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

PhD - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University
Master's Research - McGill University


Machine Learning Informed Diagnosis for Congenital Heart Disease in Large Claims Data Source
Ariane Marelli
Chao Li
Aihua Liu
Hanh Nguyen
Harry Moroz
James M. Brophy
Liming Guo
BAND: Biomedical Alert News Dataset
Zihao Fu
Meiru Zhang
Zaiqiao Meng
Yannan Shen
Anya Okhmatovskaia
Nigel Collier
CODA: an open-source platform for federated analysis and machine learning on distributed healthcare data
Louis Mullie
Jonathan Afilalo
Patrick Archambault
Rima Bouchakri
Kip Brown
Yiorgos Alexandros Cavayas
Alexis F Turgeon
Denis Martineau
François Lamontagne
Martine Lebrasseur
Renald Lemieux
Jeffrey Li
Michaël Sauthier
Pascal St-Onge
An Tang
William Witteman
Michaël Chassé
Extrapolatable Transformer Pre-training for Ultra Long Time-Series Forecasting
Ziyang Song
Qincheng Lu
Hao Xu
Estimating the population effectiveness of interventions against COVID-19 in France: a modelling study
Iris Ganser
Jane M. Heffernan
M. Prague
Rodolphe Thiébaut
Background Non-pharmaceutical interventions (NPIs) and vaccines have been widely used to manage the COVID-19 pandemic. However, uncertainty … (see more)persists regarding the effectiveness of these interventions due to data quality issues, methodological challenges, and differing contextual factors. Accurate estimation of their effects is crucial for future epidemic preparedness. Methods To address this, we developed a population-based mechanistic model that includes the impact of NPIs and vaccines on SARS-CoV-2 transmission and hospitalization rates. Our statistical approach estimated all parameters in one step, accurately propagating uncertainty. We fitted the model to comprehensive epidemiological data in France from March 2020 to October 2021. With the same model, we simulated scenarios of vaccine rollout. Results The first lockdown was the most effective, reducing transmission by 84% (95% confidence interval (CI) 83-85). Subsequent lockdowns had diminished effectiveness (reduction of 74% (69-77) and 11% (9-18), respectively). A 6pm curfew was more effective than one at 8 pm (68% (66-69) vs. 48% (45-49) reduction), while school closures reduced transmission by 15% (12-18). In a scenario without vaccines before November 2021, we predicted 159,000 or 194% (95% prediction interval (PI) 74-424) more deaths and 1,488,000 or 340% (136-689) more hospitalizations. If a vaccine had been available after 100 days, over 71,000 deaths (16,507-204,249) and 384,000 (88,579-1,020,386) hospitalizations could have been averted. Conclusion Our results highlight the substantial impact of NPIs, including lockdowns and curfews, in controlling the COVID-19 pandemic. We also demonstrate the value of the 100 days objective of the CEPI initiative for vaccine availability.
Impact of a vaccine passport on first-dose SARS-CoV-2 vaccine coverage by age and area-level social determinants of health in the Canadian provinces of Quebec and Ontario: an interrupted time series analysis
Jorge Luis Flores Anato
Huiting Ma
M. Hamilton
Yiqing Xia
Sam Harper
Marc Brisson
Michael P. Hillmer
Kamil A. Malikov
Aidin Kerem
Reed Beall
Caroline E Wagner
Étienne Racine
S. Baral
Ève Dubé
Sharmistha Mishra
Mathieu Maheu‐giroux
The evolution of SARS-CoV-2 seroprevalence in Canada: a time-series study, 2020–2023
Tanya J. Murphy
Hanna Swail
Jaspreet Jain
Maureen Anderson
Philip Awadalla
Lesley Behl
P. Brown
C. Charlton
Karen Colwill
S. Drews
A. Gingras
Deena Hinshaw
P. Jha
J. Kanji
Victoria A. Kirsh
Amanda L.s. Lang
Marc-andré Langlois
Stephen Lee
Antoine Lewin
Sheila F O’Brien … (see 10 more)
Chantale Pambrun
Kimberly Skead
David A. Stephens
Derek Riley Stein
G. Tipples
Paul G. Van Caeseele
Timothy Grant Evans
Olivia Oxlade
Bruce D. Mazer
Background: During the first year of the COVID-19 pandemic, the proportion of reported cases of COVID-19 among Canadians was under 6%. Altho… (see more)ugh high vaccine coverage was achieved in Canada by fall 2021, the Omicron variant caused unprecedented numbers of infections, overwhelming testing capacity and making it difficult to quantify the trajectory of population immunity. Methods: Using a time-series approach and data from more than 900 000 samples collected by 7 research studies collaborating with the COVID-19 Immunity Task Force (CITF), we estimated trends in SARS-CoV-2 seroprevalence owing to infection and vaccination for the Canadian population over 3 intervals: prevaccination (March to November 2020), vaccine roll-out (December 2020 to November 2021), and the arrival of the Omicron variant (December 2021 to March 2023). We also estimated seroprevalence by geographical region and age. Results: By November 2021, 9.0% (95% credible interval [CrI] 7.3%–11%) of people in Canada had humoral immunity to SARS-CoV-2 from an infection. Seroprevalence increased rapidly after the arrival of the Omicron variant — by Mar. 15, 2023, 76% (95% CrI 74%–79%) of the population had detectable antibodies from infections. The rapid rise in infection-induced antibodies occurred across Canada and was most pronounced in younger age groups and in the Western provinces: Manitoba, Saskatchewan, Alberta and British Columbia. Interpretation: Data up to March 2023 indicate that most people in Canada had acquired antibodies against SARS-CoV-2 through natural infection and vaccination. However, given variations in population seropositivity by age and geography, the potential for waning antibody levels, and new variants that may escape immunity, public health policy and clinical decisions should be tailored to local patterns of population immunity.
Protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against the omicron variant and severe disease: a systematic review and meta-regression
Niklas Bobrovitz
Harriet Ware
Xiaomeng Ma
Zihan Li
Reza Hosseini
Christian Cao
Anabel Selemon
Mairead Whelan
Zahra Premji
Hanane Issa
Brianna Cheng
Laith J Abu Raddad
Maria D Van Kerkhove
Vanessa Piechotta
Melissa M Higdon
Annelies Wilder-Smith
Isabel Bergeri
Daniel R Feikin
Rahul K. Arora … (see 2 more)
Minal K Patel
Lorenzo Subissi
A Bayesian Non-Stationary Heteroskedastic Time Series Model for Multivariate Critical Care Data
Zayd Omar
David A. Stephens
Alexandra M. Schmidt
Proactive Contact Tracing
Prateek Gupta
Martin Weiss
Nasim Rahaman
Hannah Alsdurf
Nanor Minoyan
Soren Harnois-Leblanc
Joanna Merckx
andrew williams
Victor Schmidt
Pierre-Luc St-Charles
Akshay Patel
Yang Zhang
Bernhard Schölkopf
A three-state coupled Markov switching model for COVID-19 outbreaks across Quebec based on hospital admissions (preprint)
Dirk Douwes-Schultz
Alexandra M. Schmidt
Yannan Shen
Canada's Provincial Covid-19 Pandemic Modelling Efforts: A Review of Mathematical Models and Their Impacts on the Responses
Yiqing Xia
Jorge Luis Flores Anato
Caroline Colijin
Naveed Janjua
Michael Otterstatter
Mike Irvine
Tyler Williamson
Marie B. Varughese
Michael Li
Nathaniel Osgood
David J. D. Earn
Beate Sander
Lauren E. Cipriano
Kumar Murty
Fanyu Xiu
Arnaud Godin
Amy Hurford
Sharmistha Mishra
Mathieu Maheu-Giroux