Affiliated Series
AGENT Based Modelling for Public Health (ABMfPH) Speaker Series
GOALS:
- To develop and apply novel mathematical tools to better understand disease dynamics and improve Canadian public health outcomes.
- Inform public health policy and practice issues in a timely manner
- Train highly qualified persons with a focus on capacity building.
- Build refined models that are reliable because they’ve been tested in simulated settings.
- Develop an expert panel review process.
- Establish a longstanding, collaborative network that can mobilize rapidly and effectively in the face of future pandemics or other emergency response preparedness.
- Respond in real-time to support decision makers addressing epidemics or other disasters and emergency situations in general.
MfPH MEMBERS
Julien Arino (University of Manitoba)
Ali Asgary (York University)
Jacques Bélair (University of Montreal, CRM)
Adalsteinn Brown (University of Toronto)
Jason Brown (Dalhousie University)
Arthur Charpentier (Université du Québec à Montréal)
James Colliander (University of British Columbia, PIMS)
Dongmei Chen (Queen’s University)
Morgan Craig (University of Montreal)
Shengyuan (Michael) Chen (York University)
Charmaine Dean (University of Waterloo)
Jonathan Dushoff (McMaster University)
Ida Ferrara (York University)
David Fisman (University of Toronto)
Ed Furman (York University)
Amy Greer (University of Guelph)
Hélène Guérin (Université du Québec à Montréal)
Jane Heffernan (York University)
Joan Hu (Simon Fraser University)
Amy Hurford (Memorial University of Newfoundland)
Jeanette Jansen (Dalhousie University)
Theodore Kolokolnikov (Dalhousie University)
Jude D. Kong (York University)
Manisha Kulkarni (University of Ottawa)
Patrick Leighton (University of Montreal)
Michael Li (University of Alberta)
Juxin Liu (University of Saskatchewan)
Felicia Magpantay (Queen’s University)
Doug Manuel (Ottawa Hospital Research Instititute)
Sharmistha Mishra (University of Toronto)
Swetaprovo Chaudhuri (University of Toronto)
Manuel Morales (University of Montreal, CRM)
Junling Ma (University of Victoria)
Sajjad Mohammad (National Research Council of Canada)
Seyed Moghadas (York University)
Bouchra Nasri (University of Montreal)
Nick Ogden (Public Health Agency of Canada)
James Ooi (National Research Council of Canada)
Nathaniel Osgood (University of Saskatchewan)
Peter Park (York University)
Lin Wang (University of New Brunswick)
Luc Vinet (University of Montreal, CRM)
Javier Sanchez (University of Prince Edward Island)
Sanjeev Seahra (University of New Brunswick, AARMS)
Luis Seco (University of Toronto)
Chris Soteros (University of Saskatchewan)
Ashleigh Tuite (University of Toronto)
Edward Thommes (Sanofi Pasteur, University of Guelph)
James Watmough (University of New Brunswick)
Cheryl Waldner (University of Saskatchewan)
Michael Wolfson (University of Ottawa)
Mamadou Yauck (Université du Québec à Montréal)
Xiaoqiang Zhao (Memorial University of Newfoundland)
Xingfu Zou (Western University)
Hao Wang (University of Alberta)
Monica Cojocaru (University of Guelph)
Venkata Duvvuri (University of Toronto)
Woldegebriel Assefa Woldegerima (York University)
Suzanna Shoush (University of Toronto)
Ed Furman (York University)
MfPH NEXT GENERATION MEMBERS
Mariah Ahmad (York University)
Hudson Blue (York University)
Korryn Bodner (University of Toronto)
Gabrielle Brankston (University of Guelph)
Jummy David (York University)
Felix Foutel-Roudier (Université du Québec à Montréal (UQÀM))
Martin Grunnill (York University)
Doglin Han (University of Alberta)
Francis Hu (University of Montreal)
Sana Jahedi (McMaster University)
Patrick Leighton (University of Montreal)
Ao Li (York University)
Xiaoyan Li (University of Saskatchewan)
Ankai Liu (Queen’s University)
Wade McDonald (University of Saskatchewan)
Zahra Mohammadi (University of Guelph)
Mohsen Mousavi (York University)
Dinh Toan Nguyen (Gustave Eiffel University)
Chelsea Nyarko (University of Waterloo)
Ken Peng (University of Waterloo)
Tanya Philippsen (University of Victoria)
Weston Roda (University of Alberta)
Idriss Sekkak (University of Montreal)
Yogita Sharma (University of Victoria)
Manting Wang (University of Victoria)
Richard Zhao (Queen’s University)
Korryn Bodner (University of Toronto)
Leila Amiri (York University)
Shelly Dixit (York University)
Bushra Majeed (York University)
Zach McCarthy (York University)
Tanjima Akhter (University of Alberta)
Xuyuan Wang (University of Alberta)
Russell Milne (University of Alberta)
Brandon Bellows (University of Saskatchewan)
Mohammadali Tofighi (York University)
Arnab Mukherjee (University of Toronto)
Sasha van Katwyk (University of Ottawa)
Oskar Laverny (York University)
Nushrat Nazia (University of Waterloo)
Isam Al-Darabsah (University of Manitoba)
Sungju Moon (McMaster University)
Qiuyi Su (York University)
Zeinab Jamali (University of Saskatchewan)
Yujie Pei (University of Saskatchewan)
Somoyeh Sepahrom (University of Saskatchewan)
Dinh Toan Nguyen (Université du Québec à Montréal)
COVID-19 Task Force Investigators
NEWS
22 December 2021 'Even without Omicron, NB cases on steep upward trend'
30 November 2021 'Arrivée du variant Omicron : faut-il privilégier le masque médical?'
15 October 2021 'COVID-19 modelling: the complex science of simple lines'
9 October 2021 'COVID-19 hospitalizations could double within a month, new N.B. projections show'
INTERNATIONAL MEMBERS
Henri Berestycki, École des hautes études en sciences sociales, France
Chris Budd, University of Bath, United Kingdom
Eduardo Massadm, Fundação Getulio Vargas, Rio de Janeiro Brazil.
Alan Hastings, University of California, Davis, United States
Hiroshi Nishiura, Kyoto University, Japan
Jianguo Xu, China CDC and Institute of Public Health of Nankai University, China
STEERING COMMITTEE
Kumar Murty, Chair, Director Fields Institute
Jianhong Wu, Co-PI, LIAM Director, York University
Adalsteinn Brown, Dean, Dalla Lana School of Publich Health, University of Toronto
Jame Colliander, Director, PIMS
Octav Cornea, Director, CRM
Deirdre Haskell, Deputy Director, Fields Institute
Sanjeev Seahra, Director, AARMS
Carolyn Tuohy, University of Toronto
Luc Vinet, Director, CRM
SCIENTIFIC ADVISORY COMMITTEE
Jianhong Wu, Chair, LIAM, York University
Kumar Murty, Fields Institute, Universty of Toronto
Ali Asgary, York University
Julien Arino, University of Manitoba
Jacques Belair, University of Montreal
Michael Chen, York University
Charmaine Dean, University of Waterloo
Jude Dzevela Kong, York University
Jane Marie Heffernan, York University
Tom Hurd, McMaster University
Michael Li, University of Alberta
Junling Ma, University of Victoria
Seyed M Moghadas, York University
Nathaniel Osgood, University of Saskatchawan
James Watmough, University of New Brunswick
RESEARCH MANAGEMENT COMMITTEE
Deirdre Haskell, Chair, Deputy Director, Fields Institute
Marni Mishna, Deputy Director, PIMS
Morales Manuel, Deputy Director, CRM
Franklin Mendivil, Executive Committee, AARMS
France Gagnon, Dean of Research, Dalla Lana School of Public Health, University of Toronto
INAUGURAL PROJECTS
Project 1. Contact Mixing and Optimal Decision Making
Leads: Jianhong Wu (York University, Toronto), Kumar Murty (Fields Institute, Toronto) and Shengyuan Michael Chen (York University, Toronto)
Team Members: Amy Greer, Fred Brauer, Dongmei Chen, Jane Heffernan, Jude Kong, Doug Manuel, Ashleigh Tuite, Michael Wolfson
The project aims to develop a comprehensive modelling approach that integrates key heterogeneities by age, setting, immunization status, geographical locations and a generalized intervention package accounting for evolving pharmaceutical treatment and vaccination, non-pharmaceutical interventions, diagnostic testing, contact tracing, and case isolation. This approach will also be utilized for a broad spectrum of risk assessment, preparedness planning, reopening measures and optimization, scenario analysis and intervention evaluation.
Project 2. Integrative Modelling
Leads: Kumar Murty (Fields Institute, Toronto) and Jianhong Wu (York University, Toronto)
Team Members: Arthur Charpentier, Ida Ferrera, Ed Furman, Joan Hu, Jude Kong, Sharmistha Mishra, Manuel Morales, Bouchra Nasri, Luis Seco, Michael Wolfson, Xingfu Zou
This project aims to develop an integrative framework that explores the impact of public health interventions across a broad spectrum of societal and economic issues, through ‘stitching together’ the various individual models to determine the total effect of the virus on society.
Project 3. Risk Evaluation and Early Detection of Emerging Infectious Disease Outbreaks in Canada
Leads: Junling Ma (University of Victoria, Victoria) and Jude Kong (York University, Toronto)
Members: Arthur Charpentier, Thomas Hurd, Juxin Liu, Manuel Morales, Bouchra Nasri, Ashleigh Tuite, Jianhong Wu
This project will integrate multiple types of data such as environmental, epidemiological, news reports, and search data, and develop novel mathematical, statistical, and big data techniques to a) evaluate the risk of case importation into major Canadian cities though international travel; b) detect and give early warnings to domestic spread for cities with imported cases; and c) evaluate the risk of case spread from these to other regions in Canada through domestic travel.
Project 4. Robust Agent-Based and Network Infectious Disease Models.
Leads: Thomas Hurd (McMaster University, Hamilton) and Ali Asgary (York University, Toronto)
Team Members: Jason Brown, Arthur Charpentier, Helene Guerin, Jane Heffernan, Jeanette Jansen, Nathaniel Osgood, Sanjeev Seahra, Chris Soteros, James Watmough, Michael Wolfson
The “Robust IDM” project will build on the foundations of IDM by developing agent-based and network models. The goal is to develop, expand and refine the agent-based modeling framework, leading to families of models that depart from rigid assumptions like a well-mixed population as adopted in ODE models. To develop for a large scale initiative like MfPH, our agent-based models will follow templates that can share common features such as the underlying social network and transmission settings, and are extendible in many dimensions, as finer scale epidemiological data and new knowledge comes available. In addition to taking advantage of the intrinsic conceptual advantages of transparency, flexibility and scalability, we also develop agent-based methods to address the curse of dimensionality, by combining agent-based methods with a parallel development of network and ODE analytics which make certain kinds of assumptions that lead to dramatic shortcuts in computation time. A well-defined class of network models that can “simulate the agent-based simulations quickly and more accurately than ODE models will also be developed.
Project 5. Mobility Network and Patch Models.
Leads: Julien Arino (University of Manitoba, Winnipeg), Amy Hurford (Memorial University, Newfoundland)
Team Members: Peter Park, Javier Sanchez, Sanjeev Seahra, Lin Wang, Xiaoqiang Zhao, Xingfu Zou
The spatio-temporal spread of infectious diseases involves a succession of transport and importation events, so to better model global spread, we will develop models of both processes, in isolation and together. To do that, we will first constitute a geospatial database on movement, drawing in from a wide variety of public and private sources to obtain a global view of human mobility. We will then consider importation and patch models for infectious disease spread using this transportation data. We will in particular incorporate the multiple modalities that make up mobility, as well as consider the effect of various methods to slow spread.
Project 6. Infection Control during Mass Gathering Events
Leads: Jianhong Wu (York University, Toronto), Edward Thommes (Sanofi)
Team Members: Julien Arino, Ali Asgary, Lydia Bourouiba, Dongmei Chen, Thomas Hurd, Jude Kong, Felicia Magpantay, Ashleigh Tuite, Xiaoqiang Zhao and Sanofi mass gathering infection modeling team
Mass 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. This project aims to develop model platforms, simulations and analyses, using Hajj and Olympics as case studies, for the need of immunization to ensure mass gathering events held with minimal COVID-19 infection risk. This project involve collaboration with Sanofi Pasteur for its expertise in Health Economics, Regional Disease Epidemiology.
Project 7. Antimicrobial Resistance
Leads: Seyed Moghadas (York University) and Jianhong Wu (York University)
Team members: Nathaniel Osgood, Cheryl Waldner
Infectious diseases may evolve to escape the preventative or therapeutic measures such as vaccines and antimicrobials. Reduced efficacy of vaccines and potentially increased severity of infections caused by these variants may contribute to the demand for patient management and further use of antimicrobial agents. Recent data indicate a significant use of antimicrobial agents for COVID-19 patients, even in the absence of secondary infections, sparking concerns over exacerbation of antimicrobial resistance (AMR). However, cancellations of elective and non-critical surgeries, and the implementation of non-pharmaceutical interventions that has led to the near disappearance of various seasonal infections (e.g., influenza), have collectively reduced the use of antimicrobial agents. The effect of these tradeoffs on the rate of antimicrobial use in different population settings remains unclear. We aim to quantify this effect by considering the role of new variants in the vaccine era of COVID-19 and the potential for altered rates of AMR post-pandemic. By the inclusion of an evolutionary framework into population models of AMR, we will aim to take advantage of linking genetic and epidemiological data, and investigate the effect of various exogenous factors on the secular trend.
Project 8. Contact Tracing
Lead: Jianhong Wu (York University)
Team Members: Helene Guerin, Jeanette Jansen, Kumar Murty, Juxin Liu, Felicia Magpantay, Manuel Morales, Ashleigh Tuite, Mamadou Yauck
Contact tracing has been used as one of the major non-pharmaceutical interventions to counteract the spread of SARS-CoV-2. Efficacy of contact tracing relies not only on the tracing protocol and infrastructure, but also on a concurrent program of diagnosis of symptomatic individuals, in order to detect as many infection chains as possible. This 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.
Project 9. Joint Estimation of Parameters in Outbreak Models
Leads: Charmaine Dean (University of Waterloo, Waterloo) and Nathaniel Osgood University of Saskatchewan, Saskatoon)
Team members: Dongmei Chen, Joan Hu, Jeanette Jansen, Theodore Kolokolnikov, Juxin Liu, Felicia Magpantay, Bouchra Nasri, Chris Soteros
This project aims to address various issues relevant to joint estimation of parameters in epidemic models. We will 1). Compile, contrast and develop data fitting techniques to address common issue of incomplete and imperfect covariate information when fitting many types of mechanistic models to data; 2). Use a joint model framework to analyze the underlying correlation between key time series processes (such as daily number of cases, hospitalizations and deaths) and compare waves in a way that can give insight into how deaths and hospitalizations are changing in light of variants and vaccinations; 3). Develop change-point models to measure the effectiveness of public health interventions that changes over time according to intervention timelines; 4). Investigate the potential for using deep learning and ensemble classifier methods for classification of capacity utilization exceedance, when using Particle Markov Chain Monte Carlo methods to support joint estimation not only of model states over time, but also of parameter values.
Project 10. Dynamic Bifurcation and Scenario Analyses
Leads: Jacques Bélair (University of Montreal, Montreal) and Michael Li (University of Alberta, Edmonton)
Team Members: Julien Arino, Felicia Magpantay, Jianhong Wu, Xiaoqiang Zhao and Xingfu Zou
This 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). We will also identify and mitigate non identifiability to direct surveillance or model design to avoid the situation that a bifurcation parameter of importance for scenario analyses cannot be reliably estimated using current surveillances and models. Efficient software codes for model fitting with data that ensure convergence in the presence of non identifiability will also be developed.
Project 11. Immune response, immune memory and cross-immunity
Leads: Jane Heffernan (York University), James Watmough (University of New Brunswick) and Jianhong Wu (York University)
Team Members: Jacque Bélair, Morgan Craig, Jonathan Dushoff, Thomas Hurd, Jude Kong, Sajjad Mohammad, James Ooi, and Lin Wang.
This 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. Such pre-existing immunity has a large influence on the potential for EID spread. Previous infection by one of the common coronaviruses is expected to reduce susceptibility to SARS-CoV-2, and previous infection by SARS-CoV-2 is known to influence a person's response to vaccination and their susceptibility to emerging variants.
Project 12. Pathogen Contamination and Spread Control during Food-Processing
Lead: Hao Wang (University of Alberta) and Jianhong Wu (York University)
Pathogens causing infectious diseases can originate from food products and/or wastewater, and pathogen cross-contamination and spread within the food-processing facilities and during the food-processing and transportation can potentially lead to a disease outbreak and costly product recalls. We will develop and analyze novel deterministic and stochastic simulation models to investigate necessary conditions under which an infectious disease has emerged from food or wastewater to humans and investigate its initial and transient dynamics to inform policy makers in public health to make necessary interventions. We will also develop machine learning techniques to train these models on data of food-borne disease to predict critical transition patterns and detect early warning signals around transition boundaries for suggesting early intervention strategies of food safety and disease control.
Project 13. Phylodynamic Modelling of Infectious Diseases
Lead: Venkata R. Duvvuri (Public Health Ontario)
Team Members: Samir Patel (Public Health Ontario), Jianhong Wu (York University)
The COVID-19 pandemic highlighted a myriad of opportunities and challenges in practicing public health genomics. The use of pathogen genomic data coupled with phylodynamic approaches in understanding infectious disease outbreaks has received greater attention. In 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. These phylodynamic approaches utilize time-stamped pathogen genomic sequences; and associated meta-data. Overall, the project's goal is to translate pathogen surveillance into effective public health responses and interventions.
EOC Modeling. Simulations and Exercises
Lead: Ali Asgary (York University, Toronto)
Team members: David Fisman, Amy Greer, Nathaniel Osgood, Ashleigh Tuite, Jianhong Wu
MfPH 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. The Network will organize EOC-level expert panel reviews (EPR) for some thematic research projects in general, and COVID-19 modeling in particular. These EPRs will be similar to the decision making process at a typical public health EOC Center (EOC). Network members not participating in the project and experts outside the MfPH network will be brought together with decision makers and relevant end-users to test if thematic project outcomes can be incorporated into public health decision making processes. The first year will focus on: 1) examining how the EOC at different public health agencies were activated and operated during the pandemic; 2) how decisions were made, publicized and so on; 3) developing sample standard exercise scenarios based on the current situation for future training and applications.
PUBLICATIONS
Journal articles
Vilches, Thomas N., Pratha Sah, Seyed M. Moghadas, Affan Shoukat, Meagan C. Fitzpatrick, Peter J. Hotez, Eric C. Schneider, and Alison P. Galvani. 2022. COVID-19 hospitalizations and deaths averted under an accelerated vaccination program in northeastern and southern regions of the USA. The Lancet Regional Health-Americas 6 : 100147.
[Preprint] Wells, Chad R., Abhishek Pandey, Meagan C. Fitzpatrick, William S. Crystal, Burton H. Singer, Seyed M. Moghadas, Alison P. Galvani, and Jeffrey P. Townsend. Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: A modelling study.: