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đ
Covid-19
Interest
1
#704045
Tags: Covid, SARS-CoV-2
CONTEXT
(Help)
-
EIDMâ »
EIDMâ
EIDMââThe Emerging Infectious Diseases Modelling Initiative (EIDM) â by the Public Health Agency of Canada and NSERC â aims to establish multi-disciplinary network(s) of specialists across the country in modelling infectious diseases to be applied to public needs associated with emerging infectious diseases and pandemics such as COVID-19. [1]âF1CEB7
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Research interests »
Research interests
Research interestsââ9FDEF6
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Covid-19
Covid-19ââ9FDEF6
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Alex Petiquan »
Alex Petiquan
Alex PetiquanâAlex Petiquan is Anishinaabe from Wabauskang First Nation and graduated from the Northern Ontario School of Medicine in Thunder Bay, ON. He now works as a Senior Analyst in the Federal sector which has spanned Indigenous Public Health, epidemiology, data sharing agreements, regional Indigenous community engagements and participating in joint departmental public health response for emerging issues and COVID-19.âFFFACD
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Amy Hurford »
Amy Hurford
Amy HurfordâAmy Hurford is an Associate Professor jointly appointed in the Department of Biology and the Department of Mathematics and Statistics at Memorial University of Newfoundland and Labrador. âFFFACD
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Arne Ruckert »
Arne Ruckert
Arne RuckertâArne Ruckert is a Managing Director (Research) at the Globalization and Health Equity Research Unit, and Research Coordinator of the Global One Health Network, at the University of Ottawa. He is also the Associate Director of the OMNI-REUNIS Infectious Disease Modeling Network, at York University.âFFFACD
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Christopher Cotton »
Christopher Cotton
Christopher CottonâChristopher Cotton is a Professor of Economics at Queenâs University where he holds the Jarislowsky-Deutsch Chair in Economic & Financial Policy.âFFFACD
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Christopher McCabe »
Christopher McCabe
Christopher McCabeâDr. Christopher McCabe is the CEO and Executive Director of the Institute of Health Economics (IHE).âFFFACD
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David Earn »
David Earn
David EarnâProfessor of Mathematics and Faculty of Science Research Chair in Mathematical Epidemiology at McMaster University.âFFFACD
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Erica Moodie »
Erica Moodie
Erica MoodieâErica Moodie obtained her PhD in Biostatistics in 2006 from the University of Washington, before joining McGill University where she is now a William Dawson Scholar and an Associate Professor of Biostatistics. Her main research interests are in causal inference and longitudinal data with a focus on adaptive treatment strategies. She is an Elected Member of the International Statistical Institute, and an Associate Editor of Biometrics and the Journal of the American Statistical Association. âFFFACD
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Erin Kirwin »
Erin Kirwin
Erin KirwinâErin Kirwin (she/her) is a Health Economist at the Institute of Health Economics (IHE) in Alberta, Canada. She holds a Bachelor of Arts (Honours) in Economics and International Development Studies from McGill University and a Master of Arts in Economics from the University of Alberta. Prior to joining the IHE, Erin was the Manager of Advanced Analytics at Alberta Health. Erin is a PhD candidate at the University of Manchester.âFFFACD
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Fred Brauer - In Memoriam »
Fred Brauer - In Memoriam
Fred Brauer - In MemoriamâFred Brauer, professor emeritus, died on 17 October 2021 in Vancouver, BC. âFFFACD
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Frédéric Tremblay »
Frédéric Tremblay
FrĂ©dĂ©ric TremblayâFrĂ©dĂ©ric recently completed his PhD in Economics at Queenâs University where he researched savings groups as a financial inclusion intervention in international development. In the last year, he also worked on the modelling of the economic impact of COVID-19 and the associated lockdown policies, analysis which has shaped provincial and federal policy. FrĂ©dĂ©ric also has extensive experience in tax policy modelling and tax expenditures estimation.âFFFACD
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Harini Kapali »
Harini Kapali
Harini KapaliâHarini Kapali is a Master of Arts (MA) Candidate in the Department of Economics at the University of Victoria. Her research interests are in the areas of health, labour, and environmental economics. Particularly, she is interested in using applied Microeconometric tools and techniques to help evaluate programs and inform policy decisions.âFFFACD
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Huw Lloyd-Ellis »
Huw Lloyd-Ellis
Huw Lloyd-EllisâHuw Lloyd-Ellis has over 25 years of experience conducting academic research in a broad range of areas, including economic development, growth and inequality, economic fluctuations, fiscal policy and housing. His research has been published in leading academic journals, including the American Economic Review, the Review of Economic Studies and the International Economic Review.âFFFACD
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Jean-Paul Soucy »
Jean-Paul Soucy
Jean-Paul SoucyâPhD candidate in epidemiology in the Dalla Lana School of Public Health at the University of Toronto. Co-founder and lead developer of the COVID-19 Canada Open Data Working Group (@ccodwg)âFFFACD
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Jo-Anne Relf-Eckstein »
Jo-Anne Relf-Eckstein
Jo-Anne Relf-EcksteinâJo-Anne was born and raised on a mixed dairy farm in southeastern Saskatchewan, completed a degree in Agriculture and worked in research after leaving the family farm. In 2020, she defended her thesis in COVID-times style graduating with a masterâs degree in Public Policy (MPP) from the Johnson-Shoyama Graduate School of Public Policy, University of Saskatchewan.âFFFACD
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John Edmunds »
John Edmunds
John EdmundsâDr. John Edmunds, OBE FMedSci is a British epidemiologist, and a professor in the Faculty of Epidemiology and Population Health at the London School of Hygiene & Tropical Medicine.âFFFACD
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Julien Arino »
Julien Arino
Julien ArinoâProfessor and Faculty of Science Research Chair in Fundamental Science with the Department of Mathematics at the University of Manitoba.âFFFACD
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Justin Remais »
Justin Remais
Justin RemaisâProf. Justin Remaisâ research advances methods for estimating the health risks that result from a wide range of environmental changes, such as those associated with rapid urbanization, industrialization, changes in water resources, and a changing and more variable climate.âFFFACD
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Larry Svenson - In Memoriam »
Larry Svenson - In Memoriam
Larry Svenson - In MemoriamâDr. Larry Svenson, who passed away unexpectedly on Friday, March 25, 2022, was an Associate Professor, Special Continuing in the Division of Preventive Medicine, Department of Medicine, University of Alberta.âFFFACD
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Lindsay Tedds »
Lindsay Tedds
Lindsay TeddsâDr. Lindsay Tedds is an Associate Professor in the Department of Economics, fully seconded to the School of Public Policy, at the University of Calgary. Her primary research fields are in tax policy, public economics, and public policy design and implementation. Her transciplinary approach to research harnesses the strengths of economics, law, public administration, and intersectionality in the study of public policy problems.âFFFACD
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Lisa Kanary »
Lisa Kanary
Lisa KanaryâInstructor, Business Administration in the School of Business and Leadership at Yukon University.âFFFACD
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Lorian Hardcastle »
Lorian Hardcastle
Lorian HardcastleâAssociate Professor in the Faculty of Law at the University of Calgary.âFFFACD
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Marc Brisson »
Marc Brisson
Marc BrissonâDr. Marc Brisson is full professor at Laval University where he leads the Research Group in Mathematical Modeling and Health Economics of Infectious Diseases.âFFFACD
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Marina Freire-Gormaly »
Marina Freire-Gormaly
Marina Freire-GormalyâDr. Marina Freire-Gormaly is an Assistant Professor in Mechanical Engineering Department at the Lassonde School of Engineering at York University. âFFFACD
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Matt Keeling »
Matt Keeling
Matt KeelingâMy research focuses on the three Eâs: Epidemiology, Evolution and Ecology. I am particularly interested in how spatial structure, heterogeneities and stochasticity affect the emergent population-level dynamics; as such my work uses a wide range of modelling tools and concepts.âFFFACD
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Michael WZ Li »
Michael WZ Li
Michael WZ LiâMichael Li is Senior Scientist in the Public Health Risk Science Division (PHRS) of the Public Health Agency of Canada (PHAC) and a Research Associate at the South African Centre for Epidemiological Modelling and Analysis (SACEMA).âFFFACD
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Michael Y Li »
Michael Y Li
Michael Y LiâProfessor of Mathematics in the Department of Mathematical and Statistical Sciences at the University of Alberta, and Director of the Information Research Lab (IRL).âFFFACD
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Morgan Craig »
Morgan Craig
Morgan CraigâMorgan Craig is a Researcher at the Sainte-Justine University Hospital Research Centre and an Assistant Professor in the Department of Mathematics and Statistics at the University of MontrĂ©al. âFFFACD
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Nabil Afodjo »
Nabil Afodjo
Nabil AfodjoâDr. Nabil Afodjo is a One Society Network Post-Doctoral Fellow in the Department of Economics at Queenâs University. He holds a PhD and an MA in Economics from Carleton University, and an MSc in Mathematics from the University of Ottawa. Dr. Afodjo is an Applied Microeconomist whose main research interests are in education, health, and public economics.âFFFACD
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Samira Mubareka »
Samira Mubareka
Samira MubarekaâSamira Mubareka is currently a virologist, medical microbiologist and infectious disease physician at Sunnybrook Health Sciences Centre in Toronto, Ontario, Canada and in the Department of Laboratory Medicine and Pathobiology at the University of Toronto.âFFFACD
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Sanjeev Seahra »
Sanjeev Seahra
Sanjeev SeahraâChair of the Department of Mathematics and Statistics at the University of New Brunswick (Fredericton) and the Director of AARMS (the Atlantic Association for Research in the Mathematical Sciences).âFFFACD
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Seyed Moghadas »
Seyed Moghadas
Seyed MoghadasâSeyed Moghadas is an infectious disease modeller whose research includes mathematical and computational modelling in epidemiology and immunology. In particular, he is interested in the theoretical and computational aspects of mathematical models describing the underlying dynamics of infectious diseases, with a particular emphasis on establishing strong links between micro (individual) and macro (population) levels.âFFFACD
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Shelby Sturrock »
Shelby Sturrock
Shelby SturrockâPhD Candidate in Epidemiology at the University of Toronto Dalla Lana School of Public Health.âFFFACD
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Thomas Hurd - In Memoriam »
Thomas Hurd - In Memoriam
Thomas Hurd - In MemoriamâTom Hurd, professor in the Department of Mathematics and Statistics at McMaster University and world leading researcher in financial mathematics, died on April 28, 2022, at St Peterâs Hospital, Hamilton ON, five weeks after being diagnosed with brain cancer. [1]âFFFACD
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Thomas Poder »
Thomas Poder
Thomas PoderâProfessor in the School of Public Health, Department of Health Management, Evaluation and Policy at the University of Montreal.âFFFACD
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British Columbia COVID-19 Group »
British Columbia COVID-19 Group
British Columbia COVID-19 GroupâThe BC COVID-19 Modelling Group works on rapid response modelling of the COVID-19 pandemic, with a special focus on British Columbia and Canada.âFFFACD
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COVID-19 Canada Open Data Working Group »
COVID-19 Canada Open Data Working Group
COVID-19 Canada Open Data Working GroupâThe COVID-19 Canada Open Data Working Group is made up of a dedicated team of volunteers with expertise in epidemiology, public health, and data science.âFFFACD
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2021/09/07 Feaven Sahle, Kamil Malikov & Peter Hamilton »
2021/09/07 Feaven Sahle, Kamil Malikov & Peter Hamilton
2021/09/07 Feaven Sahle, Kamil Malikov & Peter HamiltonâThe use of a hurricane model in public health: method, use and presentation.âFFFACD
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2021/09/21 Julien Arino »
2021/09/21 Julien Arino
2021/09/21 Julien ArinoâSome observations about the spatial and temporal spread of COVID-19.âFFFACD
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2021/10/05 Nathaniel Osgood & Cheryl Waldner »
2021/10/05 Nathaniel Osgood & Cheryl Waldner
2021/10/05 Nathaniel Osgood & Cheryl WaldnerâAntimicrobial resistance from farm to fork: first steps in a multi-scale modelling approach.âFFFACD
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2021/10/19 Nathaniel Osgood »
2021/10/19 Nathaniel Osgood
2021/10/19 Nathaniel OsgoodâService Delivery from Models: Production-grade real-time COVID-19 epidemiology and acute care demand monitoring and nowcasting via Particle-Filter & Particle MCMC-leveraged Transmission ModelsâFFFACD
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2021/11/16 Gabrielle Brankston »
2021/11/16 Gabrielle Brankston
2021/11/16 Gabrielle BrankstonâQuantifying Social Contact Patterns in Response to COVID-19 Public Health Measures in Canada.âFFFACD
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2021/11/23 Jane Heffernan »
2021/11/23 Jane Heffernan
2021/11/23 Jane HeffernanâModelling Immunity.âFFFACD
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2021/12/07 Sharmistha Mishra »
2021/12/07 Sharmistha Mishra
2021/12/07 Sharmistha MishraâSpecial EDI Session 1 - Modellers, first do no harm: terminology, assumptions, and the interpretation of epidemic models in the context of communities most affected.âFFFACD
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2021/12/14 Nathaniel Osgood »
2021/12/14 Nathaniel Osgood
2021/12/14 Nathaniel OsgoodâSpecial EDI Session 2 - Dynamic Modelling & Health Inequities: Peril & Promise, Principles & PracticesâFFFACD
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22/01/11 Amy Hurford »
22/01/11 Amy Hurford
22/01/11 Amy HurfordâModelling COVID-19 importations and travel restrictions in smaller jurisdictionsâFFFACD
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2022/01/18 Ali Asgary & Nathaniel Osgood »
2022/01/18 Ali Asgary & Nathaniel Osgood
2022/01/18 Ali Asgary & Nathaniel OsgoodâDeveloping the Next Generation of Pandemic Training Exercises for EOCâFFFACD
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2022/01/25 WF Shadwick & Ana Cascon »
2022/01/25 WF Shadwick & Ana Cascon
2022/01/25 WF Shadwick & Ana CasconâPredicting the Course of Covid-19âFFFACD
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2022/01/26 MfPH Workshop on Endemic COVID-19: Mathematical Insights »
2022/01/26 MfPH Workshop on Endemic COVID-19: Mathematical Insights
2022/01/26 MfPH Workshop on Endemic COVID-19: Mathematical InsightsâDiscussions on modeling challenges of the following public health issues: (1) What is a âdefinitionâ of post-COVID-19 new normal or the endemic state; (2) What are the necessary public-health measures (monitoring, surveillance, contact tracing, face masks, vaccine passport etc) and pharmaceutical interventions to achieve the transition from epidemic to endemic state; (3) What are the indicators that can be used for a sustained normal or âtolerableâ endemic state?âFFFACD
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2022/02/10 â Huw Lloyd-Ellis & FrĂ©dĂ©ric Tremblay »
2022/02/10 â Huw Lloyd-Ellis & FrĂ©dĂ©ric Tremblay
2022/02/10 â Huw Lloyd-Ellis & FrĂ©dĂ©ric TremblayâOn Modelling the Economic Impacts of Policy Responses to PandemicsâFFFACD
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2022/02/24 â Vic Adamowicz, Patrick Lloyd-Smith & Tsegaye Gatiso »
2022/02/24 â Vic Adamowicz, Patrick Lloyd-Smith & Tsegaye Gatiso
2022/02/24 â Vic Adamowicz, Patrick Lloyd-Smith & Tsegaye GatisoâEconomics, the Environment, and the Covid-19 Pandemic: An Overview and Research AgendaâFFFACD
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2022/03/10 â Ellen Rafferty & Danica Wolitski »
2022/03/10 â Ellen Rafferty & Danica Wolitski
2022/03/10 â Ellen Rafferty & Danica WolitskiâEffect of the COVID-19 Pandemic on Economic Outcomes within the Health Care Sector.âFFFACD
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2022/03/24 â Kate Harback »
2022/03/24 â Kate Harback
2022/03/24 â Kate HarbackâNot a Monolith: Transportation & the PandemicâFFFACD
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22/03/28 COVID-19 Model Comparison Workshop »
22/03/28 COVID-19 Model Comparison Workshop
22/03/28 COVID-19 Model Comparison WorkshopâTo compare models, identify key unknown parameters, and determine how much they affect key outcomes.âFFFACD
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2022/04/05 Jorge Velasco-Hernandez »
2022/04/05 Jorge Velasco-Hernandez
2022/04/05 Jorge Velasco-HernandezâModeling behavioral change and COVID-19 containment in MexicoâFFFACD
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2022/04/21 â Maggie Jones »
2022/04/21 â Maggie Jones
2022/04/21 â Maggie JonesâTitle: The Interaction Between COVID-19 and Educational Outcomes: What Have We Learned 2.5 Years Into the Pandemic?âFFFACD
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2022/05/12 â Cheryl Waldner & Jo-Anne Relf-Eckstein »
2022/05/12 â Cheryl Waldner & Jo-Anne Relf-Eckstein
2022/05/12 â Cheryl Waldner & Jo-Anne Relf-EcksteinâCOVID-19 and the Canadian cattle/beef production system: Developing a Causal Loop Diagram for modelling the unstructured problem of the pandemic.âFFFACD
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2022/05/22 â François Castonguay »
2022/05/22 â François Castonguay
2022/05/22 â François CastonguayâSpatial Allocation of Scarce COVID-19 Vaccines: When Does an Allocation Rule Based on Relative Population Size Perform Well?âFFFACD
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2022/05/31 David Champredon »
2022/05/31 David Champredon
2022/05/31 David ChampredonâWastewater-Based Modelling to Support COVID-19 SurveillanceâFFFACD
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2022/06/01 COVID-19 in the UK: Data, Models, Projections and Policy »
2022/06/01 COVID-19 in the UK: Data, Models, Projections and Policy
2022/06/01 COVID-19 in the UK: Data, Models, Projections and PolicyâDr. Matt Keeling, Professor in the Mathematics Institute and the School of Life Sciences at the University of Warwick (UK), June 1, 2022.âFFFACD
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2022/06/16 â Laurel Wheeler »
2022/06/16 â Laurel Wheeler
2022/06/16 â Laurel WheelerâIndigenous-Engaged Research and Scholarship: Lessons Learned and Methodological ApproachesâFFFACD
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2022/08/17 Jude Kong »
2022/08/17 Jude Kong
2022/08/17 Jude KongâEstimation of COVID-19 ascertainment rates across Africa and drivers of transmission dynamics worldwide in the early stage.âFFFACD
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2022/09/28 Iain Moyles »
2022/09/28 Iain Moyles
2022/09/28 Iain MoylesâFrom population spread to cellular immunity: A mathematical modellers journey through COVID-19âFFFACD
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01 Imperfect testing and serosurveys »
01 Imperfect testing and serosurveys
01 Imperfect testing and serosurveysâProjects in this node of the network involve developing statistical methods for analyzing infectious disease data, both in the context of the COVID-19 pandemic and other contexts. Goals include addressing various challenging issues associated with noisy data, including heterogeneity, varying incubation times, reporting errors, imperfect test specificity and sensitivity, and missing values.âFFFACD
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02 COVID mortality forecasting »
02 COVID mortality forecasting
02 COVID mortality forecastingâAn existing forecasting model is made up of multiple waves, each of which follows the shape of a skew-normal density function, with model fitting done with Bayesian MCMC. A challenge of working with this model is the large number of latent variables which are not Gaussian. The model will be extended to make spatio-temporal forecasts, and improved algorithms for handling waves of infections must be built. Methods for handling censored, aggregated, and age-specific death counts are also required.âFFFACD
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04 Estimating COVID-19 prevalence in homeless populations »
04 Estimating COVID-19 prevalence in homeless populations
04 Estimating COVID-19 prevalence in homeless populationsâWe will develop novel statistical models for estimating the abundance of hidden populations. Specifically, we will consider challenges associated with using Electronic Health Records to obtain estimates for populations at risk such as homeless populations under the COVID-19 pandemic.âFFFACD
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05 Hidden Markov Individual-level Models of Disease Transmission »
05 Hidden Markov Individual-level Models of Disease Transmission
05 Hidden Markov Individual-level Models of Disease TransmissionâWe will develop a hidden Markov modelling framework for individual-level models of disease transmission. Such an approach allows for the incorporation of individual-level covariates, including spatial or network-based distance, as well as delayed and under-reporting of cases. Models developed will be used to gain a greater understanding of the epidemiology of diseases such as COVID-19, influenza and Ebola.âFFFACD
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06 Infection Control during Mass Gathering Events »
06 Infection Control during Mass Gathering Events
06 Infection Control during Mass Gathering EventsâMass gatherings (MG) have the potential to facilitate global spread of infectious pathogens. Individuals from disease-free areas may acquire the pathogen while at the mass gathering site, which in turn could lead to its translocation in the originally disease-free zones when individuals return home.âFFFACD
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07 Small-area estimation and serosurveys »
07 Small-area estimation and serosurveys
07 Small-area estimation and serosurveysâThis project will develop novel statistical models for infectious diseases to address some challenges in terms of prevalence rate of infection in different small areas and domains in Canada due to COVID-19 pandemic.âFFFACD
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08 Spatial-Temporal Modeling of COVID-19 Adverse Outcomes in Canada »
08 Spatial-Temporal Modeling of COVID-19 Adverse Outcomes in Canada
08 Spatial-Temporal Modeling of COVID-19 Adverse Outcomes in CanadaâThe aims of the research are to (1) identify localised risk factors for increased severe conditions for COVID-19 (2) identify localised areas in spaceâtime at significantly higher risk, and (3) quantify the impact of changes in localised restriction policies on adverse outcomes and forecast the epidemic.âFFFACD
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10 Dynamic Bifurcation and Scenario Analyses »
10 Dynamic Bifurcation and Scenario Analyses
10 Dynamic Bifurcation and Scenario AnalysesâThis project aims to deliver a MfPH Library of important model frameworks (discrete vs continuous, deterministic vs stochastic, homogeneous vs heterogeneous and structured); examine their respective strengths and limitations in association with those issues addressed in other MfPH projects; link the bifurcation phenomena to observed patterns of COVID-19 pandemic in Canada and globally; and distinguish finite-time behaviour optimisation from asymptotic behaviour (infinite time horizon).âFFFACD
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13 Phylodynamic Modelling of Infectious Diseases »
13 Phylodynamic Modelling of Infectious Diseases
13 Phylodynamic Modelling of Infectious DiseasesâIn this project, we aim to develop phylodynamic and phylogeographic models to a) characterize the early spread of the epidemic that include insights into the origin, transmission potential, transmission routes, and genetic diversity of the pathogen; b) understand pathogen spread across spatiotemporal scales within and between geographical locations, and determine the factors that have driven pathogen spread. âFFFACD
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EOC Modeling Simulations and Exercises »
EOC Modeling Simulations and Exercises
EOC Modeling Simulations and ExercisesâMfPH will utilize the Advanced Disaster, Emergency and Rapid Simulation Facility (ADERSIM) facility housed at York University to develop Emergency Operations Center (EOC) modeling, simulation and exercises.âFFFACD
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CANMODâ »
CANMODâ
CANMODââCANadian Network for MODelling infectious Disease / RĂ©seau CANadien de MODĂ©lisation des maladies infectieusesâFFFACD
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MfPH »
MfPH
MfPHâMathematics for Public Health (MfPH), led by Dr. V. Kumar Murty, Director of the Fields Institute and Professor at the University of Toronto, will aim to bridge the gap between mathematical research and real public health issues. The team will seek to produce models that are effective, practical and reliable for applications to public health issues for COVID-19 as well as boost Canadaâs future pandemic preparedness. [1]âFFFACD
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OMNI »
OMNI
OMNIâThe One Health Modelling Network for Emerging Infections (OMNI), led by Dr. Huaiping Zhu at York University, will identify gaps that can be used to prioritize more targeted surveillance or data collection and then use those data to refine models. This work will contribute to an improved understanding of the conditions that enable pathogen spread and transmission and identify actions that can most effectively manage these conditions. [1]âFFFACD
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OSN »
OSN
OSNâThe One Society Network (OSN), led by Dr. Christopher McCabe at the University of Alberta, will include developing modelling for evaluating alternative policy responses during pandemics for all sectors of the economy and aspects of society, including marginalised groups. They will also be collaborating on multi-disciplinary training programs for skills development to support public policy making in future pandemics. [1]âFFFACD
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SMMEID »
SMMEID
SMMEIDâThis project assembles the top biostatisticians in Canada working on infectious diseases, and joins them with epidemiologists developing novel methods for data collection during the COVID-19 pandemic. Our group is developing methods and tools to get an accurate picture of the nature and extent of infectious disease transmission in the population, relying on real-world data from administrative sources and surveys. [2]âFFFACD
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04 Intervention and Control »
04 Intervention and Control
04 Intervention and ControlâAs evident in the COVID-19 pandemic, a substantial challenge in managing epidemics is the duration of the application of non-pharmaceutical interventions (NPIs), especially those that disrupt ânormalâ societal organization and function such as social distancing. These measures quickly become infeasible as pandemic fatigue builds.âFFFACD
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05 Indigenous Peoples Health and Wellbeing »
05 Indigenous Peoples Health and Wellbeing
05 Indigenous Peoples Health and WellbeingâThis research theme will study key areas of concern specific to Indigenous communities not addressed in modelling approaches, including: what factors contribute to different rates and pathways for ID spread in Indigenous populations (IP); how improved non-invasive monitoring strategies and early detection can empower communities and enhance self-determination; and, how response and mitigation can be informed by these data to limit spread and contain viruses at the earliest point of detection.âFFFACD
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Advancing agent-based simulation scalability »
Advancing agent-based simulation scalability
Advancing agent-based simulation scalabilityâHigh-fidelity simulation models provide the most accurate representation of the spread of COVID and related diseases but are subject to computational limitations. Agent-based modelling, which treats each individual as a unique agent with objectives/properties/etc., is an example of such a high-fidelity model. The projectâs objective is to realize a vastly improved scalability of this type of analysis, using modern techniques in the field of deep learning and AI.âFFFACD
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Behaviour »
Behaviour
BehaviourâIn infectious disease outbreaks we often see the population reacting to outbreak severity, changing the transmission dynamics over time. For example, the COVID-19 pandemic has led to voluntary and government-mandated physical distancing across the world, which slows spread. Further, we see these behaviours relax when case counts are low and increase when high.âFFFACD
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Emerging Infectious Disease and Indigenous Peoples Health & Wellbeing »
Emerging Infectious Disease and Indigenous Peoples Health & Wellbeing
Emerging Infectious Disease and Indigenous Peoples Health & WellbeingâThe focus is on understanding how the modelling approach needs to be different. Areas include: Health and non-health based factors influencing rate and spread of disease, mobilizing knowledge to inform, engage and empower Indigenous communities in decision-making around health and Indigenous-centered approaches to early detection, response & mitigation.âFFFACD
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Heterogeneity and syndemics »
Heterogeneity and syndemics
Heterogeneity and syndemicsâEmerging infectious diseases impose disproportionate burdens according to societal fault lines marked by marginalization, socioeconomic disparities, injustices, and inequities. In some cases (e.g., COVID-19) this is marked by syndemics. We will build on and extend an existing cross-sectoral partnership including patient and family advisors to greatly enrich agent-based modeling (ABM), informed by those with lived experience. âFFFACD
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Mathematical modelling of human response behaviour during pandemics »
Mathematical modelling of human response behaviour during pandemics
Mathematical modelling of human response behaviour during pandemicsâMathematical modelling of human response behaviour, opinion dynamics, and social influence during pandemics. COVID-19 showed that understanding human response to intervention is essential in mitigating disease spread and forming policy. We are particularly interested in understanding how opinion influence affects vaccine and NPI hesitancy. This project aims to incorporate a broader understanding of intervention and control, which embodies the entire theme.âFFFACD
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Smaller jurisdictions »
Smaller jurisdictions
Smaller jurisdictionsâCANMOD will develop mathematical models that: (i) are appropriate for provincial/territorial planning in smaller jurisdictions; (ii) explain how optimal public health response may be different in regions with a high proportion in imported cases; and (iii) explore how the different epidemic dynamics experienced in AC-T are influenced by the social dynamics of small and remote communities.âFFFACD
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Testing »
Testing
TestingâEffective diagnostic testing serves at least four purposes: (i) diagnosis, (ii) surveillance, (iii) outbreak mitigation/control and (iv) screening (e.g., for access to long-term care (LTC) homes, etc.). âFFFACD
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Vaccination »
Vaccination
VaccinationâThe existence of COVID-19 vaccines highlights the importance of research on vaccination distribution strategies. CANMOD vaccination research will focus on (i) pandemic endgames, (ii) optimal deployment, (iii) behavioural dynamics and (iv) evaluation of vaccine programs.âFFFACD
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Vaccination and antimicrobials, from the individual to the population »
Vaccination and antimicrobials, from the individual to the population
Vaccination and antimicrobials, from the individual to the populationâVaccination and antimicrobials, from the individual to the population: Real-time modelling and data analysis to project therapeutic intervention.âFFFACD
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CCODWG »
CCODWG
CCODWGââFFFACD
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COVID Hospital Surge »
COVID Hospital Surge
COVID Hospital SurgeâCOVID-19 Healthcare Surge Model for Greater Toronto Area Hospitals.âFFFACD
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COVID JupyterHub »
COVID JupyterHub
COVID JupyterHubââFFFACD
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COVID Prevalence Estimate »
COVID Prevalence Estimate
COVID Prevalence EstimateâAn implementation of Bayesian inference and prediction of COVID-19 point-prevalence.âFFFACD
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COVID-19 Re - Generation Time »
COVID-19 Re - Generation Time
COVID-19 Re - Generation TimeâEstimating the effective reproduction number Re(t) for COVID19 in GTA, Canada. [1]âFFFACD
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covidseir »
covidseir
covidseirâcovidseir fits a Bayesian SEIR (Susceptible, Exposed, Infectious, Recovered) model to daily COVID-19 case data. The package focuses on estimating the fraction of the usual contact rate for individuals participating in physical distancing (social distancing). The model is coded in Stan. The model can accommodate multiple types of case data at once (e.g., reported cases, hospitalizations, ICU admissions) and accounts for delays between symptom onset and case appearance. [1]âFFFACD
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CovidSim »
CovidSim
CovidSimâCovidSim models the transmission dynamics and severity of COVID-19 infections throughout a spatially and socially structured population over time.âFFFACD
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covid-topic-modeling »
covid-topic-modeling
covid-topic-modelingâSocial media topic modeling software.âFFFACD
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Efficacy of quarantine »
Efficacy of quarantine
Efficacy of quarantineâR files linked to the paper Quarantine and the risk of COVID-19 importation [2]âFFFACD
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epi base package for SyncroSim »
epi base package for SyncroSim
epi base package for SyncroSimâA scenario-based modelling framework for generating locally relevant forecasts of COVID-19âFFFACD
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Estimating the infection fatality rate of Covid-19 »
Estimating the infection fatality rate of Covid-19
Estimating the infection fatality rate of Covid-19âEstimating the infection fatality rate of Covid-19 using demographics data and deaths records from Italys hardest hit area. [1]âFFFACD
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Localized Epidemiological Agent-Based Simulation (ABS) »
Localized Epidemiological Agent-Based Simulation (ABS)
Localized Epidemiological Agent-Based Simulation (ABS)â This ABS provides information about risk and the effects of both pharmacological and non-pharmacological interventions, as well as detailed control over the rapidly evolving epidemiological characteristics of COVID-19. [1]âFFFACD
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Ontario pandemic mobility »
Ontario pandemic mobility
Ontario pandemic mobilityâThis interactive data tool uses publicly available Google Mobility data to generate graphs displaying overall mobility changes in Ontario. Google typically updates their datasets every 3-5 days, and the new data will contain data points with a 2-3 day lag. âFFFACD
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Open Data Model »
Open Data Model
Open Data ModelâMetadata and code to support covid-19 environmental surveillance for public health. Wastewater-based surveillance for Covid-19, with support for other health risks and environmental settings. [1]âFFFACD
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Prediction Codes »
Prediction Codes
Prediction CodesâDataset of COVID-19 outbreak and potential predictive features in the USA.âFFFACD
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PyCoMod »
PyCoMod
PyCoModâPyCoMod is a Python package for building and running compartment models derived from systems of differential equations such as the Susceptible-Infectious-Recovered (SIR)model of infectious diseases.âFFFACD
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python Population Modeller »
python Population Modeller
python Population ModellerâThe pyPM.ca software was developed to study and characterize the CoViD-19 epidemic.âFFFACD
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Stochastic simulations of classroom-level COVID-19 outbreaks »
Stochastic simulations of classroom-level COVID-19 outbreaks
Stochastic simulations of classroom-level COVID-19 outbreaksâThis repository contains code associated with a preprint exploring COVID-19 outbreaks in classrooms, and how these might be managed with several different protocols: COVID-19s unfortunate events in schools: mitigating classroom clusters in the context of variable transmission. [1]âFFFACD
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FAIR Covid19 Data Project »
FAIR Covid19 Data Project
FAIR Covid19 Data ProjectâA repository to organize the FAIR COVID-19 Data for Canada project. Led by the COVID-19 Canada Open Data Working Group and supported by CANMOD.âFFFACD
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Benjamin Bolker »
Benjamin Bolker
Benjamin BolkerâIâm a professor in the departments of Mathematics & Statistics and of Biology at McMaster University, and currently Director of the School of Computational Science and Engineering and Acting Associate Chair (Graduate) for Mathematics.âFFFACD
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McMasterPandemic »
McMasterPandemic
McMasterPandemicâCompartmental epidemic models for forecasting and analysis of infectious disease pandemics: contributions from Ben Bolker, Jonathan Dushoff, David Earn, Weiguang Guan, Morgan Kain, Michael Li, Irena Papst, Steve Walker (in alphabetical order).âFFFACD
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Jonathan Dushoff »
Jonathan Dushoff
Jonathan DushoffâProfessor in the Department Of Biology at McMaster University.âFFFACD
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Caroline Colijn »
Caroline Colijn
Caroline ColijnâDr. Caroline Colijn works at the interface of mathematics, evolution, infection and public health, and leads the MAGPIE research group. She joined SFUs Mathematics Department in 2018 as a Canada 150 Research Chair in Mathematics for Infection, Evolution and Public Health. She has broad interests in applications of mathematics to questions in evolution and public health, and was a founding member of Imperial College Londons Centre for the Mathematics of Precision Healthcare.âFFFACD
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David Buckeridge »
David Buckeridge
David BuckeridgeâDavid is a Professor in the School of Population and Global Health at McGill University, where he directs the Surveillance Lab, an interdisciplinary group that develops, implements, and evaluates novel computational methods for population health surveillance. He is also the Chief Digital Health Officer at the McGill University Health Center where he directs strategy on digital transformation and analytics and he is an Associate Member with the Montreal Institute for Learning Algorithms (Mila).âFFFACD
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Sandrine Moreira »
Sandrine Moreira
Sandrine MoreiraâSandrine Moreira is the lead genomics for SARS-CoV-2 at the Laboratoire de SantĂ© Publique du QuĂ©bec (LSPQ) and is associate professor in the Department of Biochemistry and Molecular Medicine at the UniversitĂ© de Montreal. She has advanced expertise in microbial genomics that she acquired in cutting-edge research institutes, at the Institut Pasteur in Paris and in Columbia University in New York.âFFFACD
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Genomics »
Genomics
GenomicsâWhile virus genomes can describe the global context of introductions and origins of local clusters of cases, CANMOD will focus on building methods for characterizing and modelling local transmission once it is established, and for surveillance for viral determinants of increased fitness and of enhanced risk of spillover, virulence and transmission.âFFFACD
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2021/10/12 Jude Dzevela Kong & Junling Ma »
2021/10/12 Jude Dzevela Kong & Junling Ma
2021/10/12 Jude Dzevela Kong & Junling MaâFrameworks for early warning signals of emerging infectious diseases.âFFFACD
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08 Contact tracing »
08 Contact tracing
08 Contact tracingâThis project aims to develop models and analyses that incorporates the processes of diagnosis of symptomatic individuals and contact tracing to address important issues relevant to outbreak control: tracing delays; tracing resource allocation among regions with different prevalence or growth rate; adherence of individuals to isolation and to disclosure of contacts; vaccine coverage levels.âFFFACD
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11 Immune response, immune memory and cross-immunity »
11 Immune response, immune memory and cross-immunity
11 Immune response, immune memory and cross-immunityâThis project aims to develop and analyze a suite of models of an immune response to an emergent infectious pathogen incorporating immune memory generated by prior infection by related pathogens.âFFFACD
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OSN â Goals »
OSN â Goals
OSN â GoalsâThe One Society Network has three main goals.âFFFACD
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Ashleigh Tuite »
Ashleigh Tuite
Ashleigh TuiteâAshleigh Tuite is an Assistant Professor in the Epidemiology Division at the Dalla Lana School of Public Health at the University of Toronto.âFFFACD
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Carl E. James »
Carl E. James
Carl E. JamesâCarl E. James holds the Jean Augustine Chair in Education, Community & Diaspora in the Faculty of Education, York University, Toronto, where he is also the Senior Advisor in Equity and Representation in the Office of the VP Equity, People and Culture.âFFFACD
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Genomics »
Genomics
GenomicsââFFFACD
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Respiratory infections »
Respiratory infections
Respiratory infectionsââFFFACD
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Ătienne Racine »
Ătienne Racine
Ătienne RacineâĂtienne is a medical advisor at the National Institute of Public Health of Quebec (INSPQ).âFFFACD
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Evan Mitchell »
Evan Mitchell
Evan MitchellâEvan is a postdoctoral fellow in the Department of Mathematics and Statistics at McMaster University.âFFFACD
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David Champredon »
David Champredon
David ChampredonâDr. David Champredon is a senior scientist at the Public Health Agency of Canada. His work focuses on modelling the spread of infectious diseases at the population level, especially respiratory and sexually transmitted infections. During the past two years, he supported the modelling efforts to respond to the COVID-19 pandemic, particularly wastewater-based modelling.âFFFACD
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Azadeh Aghaeeyan »
Azadeh Aghaeeyan
Azadeh AghaeeyanâAzadeh is a postdoctoral researcher in the Department of Mathematics & Statistics and the Ramazi Research Group at Brock University, working on integrating human decision making and epidemiological models to reveal the human impact on epidemics, and using evolutionary game theory and SIR models.âFFFACD
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Jennafer Mee »
Jennafer Mee
Jennafer MeeâJenna Mee is a doctoral student in computer science at the University of Saskatchewan.âFFFACD
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Nick Ogden »
Nick Ogden
Nick OgdenâNicholas Ogden is a senior research scientist and Director of the Public Health Risk Sciences Division within the National Microbiology Laboratory at the Public Health Agency of Canada.âFFFACD
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Jesse Shapiro »
Jesse Shapiro
Jesse ShapiroâJesse Shapiro is an Associate Professor in the Faculty of Medicine and Health Sciences at McGill University. Jesseâs research uses genomics to understand the ecology and evolution of microbes, ranging from freshwater bacterioplankton to the human gut microbiome. His work has helped elucidate the origins of bacterial species, leading to a more unified species concept across domains of life, and has developed genome-wide association study (GWAS) methods tailored for bacteria.âFFFACD
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Sana Naderi »
Sana Naderi
Sana NaderiâSana is a PhD student in the Shapiro Lab in the McGill Genome Center and the Department of Microbiology and Immunology at McGill University.âFFFACD
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Ben Ashby »
Ben Ashby
Ben AshbyâBen is an Associate Professor in the Department of Mathematics at Simon Fraser University.âFFFACD
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Edward Thommes »
Edward Thommes
Edward Thommes âEdward W. Thommes is an Adjunct Professor of Mathematics at the University of Guelph and at York University. He is a Global Modeling Lead in the Modeling, Epidemiology and Data Science (MEDS) team of Sanofi Vaccines, an Affiliate Researcher in the Waterloo Institute for Complexity and Innovation (WICI), and a member of the Strategic Advisory Committee for the Mathematics for Public Health program at the Fields Institute.âFFFACD
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Monica Cojocaru »
Monica Cojocaru
Monica CojocaruâProfessor in the Mathematics & Statistics Department at the University of Guelph. âFFFACD
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Woldegebriel Assefa Woldegerima »
Woldegebriel Assefa Woldegerima
Woldegebriel Assefa WoldegerimaâDr. Woldegerima, knows as Assefa, is an Assistant Professor at the Department of Mathematics and Statistics at York University.âFFFACD
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Venkata Duvvuri »
Venkata Duvvuri
Venkata DuvvuriâDr. Duvvuri is an Assistant Professor and leads an interdisciplinary research program advancing genomic surveillance research, development, and practice in the Department of Laboratory Medicine & Pathobiology at the University of Toronto. He is also a Scientist in Machine Learning at Public Health Ontario.âFFFACD
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Wastewater-based surveillance (WBS) »
Wastewater-based surveillance (WBS)
Wastewater-based surveillance (WBS) ââFFFACD
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Contact tracing »
Contact tracing
Contact tracingââFFFACD
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221117 Stochasticity in adherence to nonpharmaceutical interventions »
221117 Stochasticity in adherence to nonpharmaceutical interventions
221117 Stochasticity in adherence to nonpharmaceutical interventionsâSeminar 4: The stochasticity in adherence to nonpharmaceutical interventions and booster doses and the mitigation of COVID-19. Speaker: Yi Tan, November 17, 2022.âFFFACD
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221215 Compliance with social distancing and vaccination for COVID-19 »
221215 Compliance with social distancing and vaccination for COVID-19
221215 Compliance with social distancing and vaccination for COVID-19âSeminar 5: An investigation into compliance with social distancing and vaccination for COVID-19. Speaker: Jeta Molla, December 15, 2022âFFFACD
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