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

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

Aidan Licoppe Aidan

Master's Research - McGill University

Master's Research - McGill University

PhD - McGill University

Master's Research - McGill University

Master's Research - McGill University

Master's Research - McGill University

Publications

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

David Buckeridge

Amy Hurford

Sharmistha Mishra

Mathieu Maheu-Giroux

2024-07-25

Canadian Journal of Public Health (published)

Canada’s approach to SARS-CoV-2 sero-surveillance: Lessons learned for routine surveillance and future pandemics

Sheila F. O’Brien

Michael Asamoah-Boaheng

Brian Grunau

Mel Krajden

David Buckeridge

David M. Goldfarb

Maureen Anderson

Marc Germain

Patrick Brown

Derek R. Stein

Kami Kandola

Graham Tipples

Philip Awadalla

Amanda Lang

Lesley Behl

Tiffany Fitzpatrick

Steven J. Drews

2024-07-09

Canadian journal of public health (published)

A Bayesian Non-Stationary Heteroskedastic Time Series Model for Multivariate Critical Care Data

Zayd Omar

David A. Stephens

Alexandra M. Schmidt

David Buckeridge

2024-07-02

Statistics in Medicine (published)

Economic evaluation of the effect of needle and syringe programs on skin, soft tissue, and vascular infections in people who inject drugs: a microsimulation modelling approach

Jihoon Lim

Mariam El-Sheikh

David Buckeridge

Dimitra Panagiotoglou

2024-06-28

Harm Reduction Journal (published)

Temporal trends in disparities in COVID-19 seropositivity among Canadian blood donors

Yuan Yu

Matthew J Knight

Diana Gibson

Sheila F O’Brien

David Buckeridge

W Alton Russell

Abstract Background In Canada’s largest COVID-19 serological study, SARS-CoV-2 antibodies in blood donors have been monitored since 2020. … (see more)No study has analysed changes in the association between anti-N seropositivity (a marker of recent infection) and geographic and sociodemographic characteristics over the pandemic. Methods Using Bayesian multi-level models with spatial effects at the census division level, we analysed changes in correlates of SARS-CoV-2 anti-N seropositivity across three periods in which different variants predominated (pre-Delta, Delta and Omicron). We analysed disparities by geographic area, individual traits (age, sex, race) and neighbourhood factors (urbanicity, material deprivation and social deprivation). Data were from 420 319 blood donations across four regions (Ontario, British Columbia [BC], the Prairies and the Atlantic region) from December 2020 to November 2022. Results Seropositivity was higher for racialized minorities, males and individuals in more materially deprived neighbourhoods in the pre-Delta and Delta waves. These subgroup differences dissipated in the Omicron wave as large swaths of the population became infected. Across all waves, seropositivity was higher in younger individuals and those with lower neighbourhood social deprivation. Rural residents had high seropositivity in the Prairies, but not other regions. Compared to generalized linear models, multi-level models with spatial effects had better fit and lower error when predicting SARS-CoV-2 anti-N seropositivity by geographic region. Conclusions Correlates of recent COVID-19 infection have evolved over the pandemic. Many disparities lessened during the Omicron wave, but public health intervention may be warranted to address persistently higher burden among young people and those with less social deprivation.

2024-06-05

International Journal of Epidemiology (published)

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

David Buckeridge

2024-02-01

JACC: Advances (published)

BAND: Biomedical Alert News Dataset

Zihao Fu

Meiru Zhang

Zaiqiao Meng

Yannan Shen

Anya Okhmatovskaia

David Buckeridge

Nigel Collier

2024-01-01

AAAI (published)

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

David Buckeridge

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

Michael Chassé

2023-12-21

J. Am. Medical Informatics Assoc. (published)

Extrapolatable Transformer Pre-training for Ultra Long Time-Series Forecasting

Ziyang Song

Qincheng Lu

Hao Xu

David Buckeridge

2023-11-29

ArXiv (preprint)

Estimating the population effectiveness of interventions against COVID-19 in France: a modelling study

Iris Ganser

David Buckeridge

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.

2023-09-14

medRxiv (preprint)

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

David Buckeridge

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

2023-09-01

CMAJ Open (published)

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 Lang

Marc-andré Langlois

Stephen Lee

Antoine Lewin

Sheila F O’Brien … (see 10 more)

Chantale Pambrun

Kimberly Skead

David A. Stephens

Derek R. Stein

G. Tipples

Paul G. Van Caeseele

Timothy Grant Evans

Olivia Oxlade

Bruce D. Mazer

David Buckeridge

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.

2023-08-13

Canadian Medical Association Journal (published)