2022 CCDM Incubation Day
2022 CCDM INCUBATION DAY
With:
Postdoctoral Fellows and Graduate Students @ CCDM
Department of Mathematics and Statistics, York University
May 16-17
May 16: 11 a.m. – 5:30 p.m. EDT (Toronto)
May 17: 11 a.m. – 5:30 p.m. EDT (Toronto)
In-person: Room 003, Accolade East Building Accolade East Bldg
Virtual: Meeting ID: 940 0237 6148 https://yorku.zoom.us/j/94002376148
Plenary speaker: Nathaniel Osgood
Panel discussion: Micheal Li, Iain Moyles, Vicky Ng, Hsu Kiang (James) Ooi, and Ashleigh Tuite
All talks of Postdoctoral Fellows and Graduate Students will be 20 minutes. Snack and refreshment breaks will be provided.
Incubation Day is a day when the Centre for Disease Modelling (CCDM) brings together its graduate students and postdocs to showcase and share their research work and promote communications between members of CCDM network.
Advisors: Drs Amy Hurford, Bouchra Nasri, Jude Dzevela Kong, Lin Wang and Huaiping Zhu
Volunteers for Organization:(Alphabetic order)
Planning, Elaheh Abdollahi, Joseph Baafi, David Dick, Sana Jahedi, Geneva Liwag, Zahra Mohammadi, Congjie (Nancy) Shi, Yi Tan, Jingjing Xu, and Pei Yuan
Content Creation, George Adu-Boahen, Sana Jahedi, Tyler Meadows and Liu Yang
Communication, Francis Anokye, Ogbuokiri Blessing, Zahra Movahhedinia, Claudia Robayo,Vadim Tyuryaev, and Jingjing Xu
Everyone is welcome to join us
More details at: 2022 CCDM INCUBATION DAY | Canadian Center for Disease Modeling (CCDM) (yorku.ca)
Event Agenda
2022 CCDM INCUBATION DAY – DAY 1
May 16 11 a.m. – 5:30 p.m. EDT (Toronto)
In-person: Room 003, Accolade East Building
Virtual: Meeting ID: 940 0237 6148 https://yorku.zoom.us/j/94002376148
| 11 – 11:15 a.m. | Opening Remarks |
|---|---|
| 11:15 a.m. – noon | Plenary speaker: Nathaniel Osgood |
| noon – 1 p.m. | Lunch Break |
| 1 – 2:20 p.m. | Session 1 |
| 1 – 1:20 p.m. | David Dick: Distribution of Immunity to SARS-CoV-2 within Canadian Provinces |
| 1:20 – 1:40 p.m. | Yi Tan: A Stochastic Differential Equation Model for Mitigation and Control of COVID-19 with Vaccination |
| 1:40-2 p.m. | Vadim Tyuryaev: Statistical and Machine Learning GPU Computing with R |
| 2:00 pm-2:20 pm | Arma Khan: Modelling a Combined CFD-Mathematical SI Model Based on Spatial Heterogeneity of Airborne Transmission in Indoor Environments |
| 2:20 – 2:30 p.m. | Break |
| 2:30 – 4:10 p.m. | Session 2 |
| 2:30 – 2:50 p.m. | Jingjing Xu: Modelling the Spreading Speed of Chronic Wasting Disease Across Deer Groups with Overlapping Home Ranges |
| 2:50 – 3:10 p.m. | Liu Yang: The Effect of the Illegal Poultry Trade Caused by H7N9 Avian Flu Scare on the Transmission of the Disease |
| 3:10 – 3:30 p.m. | Pei Yuan: Projections of the Transmission of the Omicron Variant under the Targeted Testing-reporting Strategy |
| 3:30 – 3:50 p.m. | Sanaz Gholizadeh: Interaction of Epidemic with People’s Behavior and Attitude toward Protection Measures on Multiplex Network |
| 3:50 – 4 p.m. | Break |
| 4 – 5:20 p.m. | Session 3 |
| 4 – 4:20 p.m. | Qing Han: Estimation of Epidemiological Parameters and Ascertainment Rate from Early Transmission of COVID-19 across Africa |
| 4 – 4:40 p.m. | Jeta Molla: Adaptive and Optimized COVID-19 Vaccination Strategies across Geographical Regions and Age Groups |
| 4:40 – 5 p.m. | Sonia Gazeau: Generating Virtual Patient Populations to Compare Immune Responses between Immunosuppressed and Cancer Patients with COVID-19 |
| 5 – 5:20 p.m. | Elena Aruffo: Mathematical Modelling of Vaccination Rollout and NPIs Lifting on COVID-19 Transmission with VOC: A Case Study in Toronto, Canada |
2022 CCDM INCUBATION DAY – DAY 2
May 17 11 a.m. – 5:30 p.m. EDT (Toronto)
In-person: Room 003, Accolade East Building
Virtual: Meeting ID: 940 0237 6148 https://yorku.zoom.us/j/94002376148
| 11 – 11:10 a.m. | Panel speaker introduction, moderator: Iain Moyles |
| 11:10 a.m. – 12:30 p.m. | Panel discussion:Micheal Li, Vicky Ng, Hsu Kiang (James) Ooi, and Ashleigh Tuite |
| 12:30 – 1:20 p.m. | Lunch Break |
| 1:20 – 2:20 p.m. | Session 4 |
| 1:20 – 1:40 p.m. | Abu Raihan Ibna Ali: Numerical Modeling of Cough Aerosol Transmission in Public Transportation |
| 1:40 – 2 p.m. | Kishon Webb: Molecular Dynamics Simulations of a Single Coronavirus (SARS- COV-2) Structure Suspended in a Mist of Air and Water Droplets |
| 2 – 2:20 p.m. | Sam Luik: Implications of Reduced Costs for Stressor Mheffertesting in Honeybee Colonies |
| 2:20 – 2:30 p.m. | Break |
| 2:30 – 3:50 p.m. | Session 5 |
| 2:30 – 2:50 p.m. | Simon Leoz: Optimizing TMZ- and SMI-based Combined Treatments for Glioblastoma |
| 2:50 – 3:10 p.m. | Tyler Meadows: Incorporating Wastewater Surveillance Data into Epidemiological Models |
| 3:10 – 3:30 p.m. | Suzan Farhang Sardroodi: A Machine Learning Approach to Differentiate Between COVID-19 and Influenza Infection Using Synthetic Data |
| 3:30 – 3:50 p.m. | Adrien Saucier: Weighting and Representativity in Estimations of SARS-CoV-2 Antibodies Seroprevalence in School Children in Montréal, Québec |
| 3:50 – 4 p.m. | Break |
| 4 – 5:20 p.m. | Session 6 |
| 4 – 4:20 p.m. | Zahra Movahedi Nia: Tracing Unemployment Rate of South Africa during the COVID-19 Pandemic Using Twitter Data |
| 4:20 – 4:40 p.m. | Wisdom S. Avusuglo: The Role of Behavioral Compliance with Non-pharmaceutical and Pharmaceutical Interventions in the Fight against COVID-19 |
| 4:40 – 5 p.m. | Blessing Ogbuokiri: Determining the Impact of Omicron Variant in Vaccine Uptake in South Africa Using Twitter Data |
| 5 – 5:20 p.m. | Srikanth Boligarla, Raja Mahadevan: Assessing Twitter’s Potential to Predict Lyme Disease Incidence Rates in the US |
| 5:20 – 5:30 p.m. | Closing Remarks |
Plenary speaker Nathaniel Osgood
Nathaniel Osgood serves as Professor in the Department of Computer Science at the University of Saskatchewan, and Director of the Computational Epidemiology and Public Health Informatics Laboratory. His research focuses on combining tools from Systems Science, Data Science, Computational Science and Mathematics to inform decision making in health & health care. Dr. Osgood serves as Chief Research Advisor for the Saskatchewan Centre for Patient Oriented Research and has contributed to or co-led over a dozen initiatives involving people with lived experience with dynamic modeling, machine learning and/or big data collection efforts. Dr. Osgood served as the technical director of COVID-19 modeling for the Province of Saskatchewan from March 2020-April 2021. Through cross-leveraging combinations of dynamic modeling, Artificial Intelligence/Machine Learning, and diverse data sources, has CEPHIL delivered COVID-19 situational analyses and short-term forecasts daily for Saskatchewan, multiple times a week for all provinces across Canada for PHAC and once a week to First Nations Reserves across Canada via FNIHB. In addition to dozens of published applications of agent-based, compartmental modeling and in diverse health & health care areas and guiding analytics that have shaped important policy and investment decisions at the Saskatchewan at the Ministry of Health, Dr. Osgood has contributed techniques hybridizing multiple simulation approaches with machine learning tools and which leverage such hybrid models with data from multiple high-velocity data sources, innovations to improve dynamic modeling quality and efficiency, introduced novel modeling languages, and worked enhance dynamic modeling formulation using approaches from category theory. Among his many data science contributions, Dr. Osgood is the co-creator of diverse epidemiological surveillance and data collection systems, most prominently the Google Android-, iPhone- and web-based Ethica Data platform applied in hundreds of health studies around the world, including for multiple COVID-19 related studies. Prior to joining the U of S faculty, he graduated from MIT with a PhD in Computer Science, served as a Senior Lecturer and Research Associate at MIT and served in a variety of academic, consulting and industry positions.
Panelist speakers
(Alphabetic order)
Michael Li
Dr. Michael Li is a Professor of Mathematics at the University of Alberta. He received his PhD from the University of Alberta, and his postdoctoral training at Georgia Institute of Technology. His research interests are mathematical investigation and modeling of population dynamics of disease transmission, and in vivo dynamics of viral infections and immune responses.
His research group collaborates with Alberta Ministry of Health on modeling HIV, TB, Influenza and COVID-19, and with China CDC on estimation of HIV incidence using mathematical modeling. He also collaborates with virologists and immunologists at the Li Ka-Shing Institute of Virology at the UofA on modeling viral dynamics. His many trainees have successful careers in the academia, industry and government agencies.
Iain Moyles
Dr. Iain Moyles is an Assistant Professor in the department of Mathematics and Statistics at York University. He obtained his PhD in biological pattern formation at the University of British Columbia in 2015 and completed a postdoc in soil nutrient modelling at the University of Limerick and in 2018 was named a Charlemont Scholar by the Royal Irish Academy. His research interests are in mathematical modelling, analysis, and computation. Particularly, he employs methods of model reduction which can greatly improve computational speed and efficiency as well as elucidate underlying model mechanisms. He works in a broad field of application including ecology, batteries, and disease modelling.
Dr. Moyles is a member of the Canadian Centre for Disease Modelling and an associate director of the One Health Modelling Network for Emerging Infections (OMNI). He is also a leader of the OMNI subtheme on intervention and control of emerging infections where he is overseeing a project on mathematical modelling of human response behaviour, opinion dynamics, and social influence during pandemics.
Vicky Ng
Dr. Victoria Ng is an epidemiologist and mathematical modeller at the Public Health Agency of Canada, her expertise includes quantitative risk assessment, disease prioritization, infectious disease epidemiology and statistical/mathematical modelling of infectious diseases. She holds a PhD in epidemiology from the Australian National University; her doctorate explored predicting outbreaks of Ross River virus disease in Australia. Victoria completed her Postdoc at the Department of Population Medicine, University of Guelph and was the Epidemiologist Lead at Public Health Ontario before she joined the Public Health Agency of Canada in 2014.
Her current projects include modelling the importation and transmission of exotic mosquito-borne diseases in Canada under current and projected climate change, developing quantitative tools to prioritize diseases of public health importance and incorporating artificial intelligence and machine learning techniques into public health research and practice. For much of 2020, Victoria’s focus has been on responding to the COVID-19 pandemic including developing an agent-based model to explore the effectiveness of non-pharmaceutical interventions for community COVID-19 transmission in Canada and using social media data to forecast COVID-19 incidence in Canada and to explore sentiments and adherence to COVID-19 public health measures.
Hsu Kiang (James) Ooi
James Ooi’s research interest is in mathematical modelling and simulations of dynamical systems and the application of quantum computing technology in drug discovery. He obtained his Master of Science in Electrical Engineering (MSEE) and Ph.D. in Biomedical Engineering from the University of Texas at Dallas, followed by postdoctoral training at the University of Ottawa. He then joined IBM Canada and worked on high-performance computing applications using accelerators such as GPU, FPGA and QPU. He joined NRC in October 2019 and has been the Site Lead of the newly formed NRC‑Fields Institute Collaboration Centre.
At the NRC‑Fields Institute Collaboration Centre, James is pursuing interdisciplinary research projects applying techniques from mathematical modelling, machine learning and quantum computing for disease modelling, and material & drug discoveries. James is the project lead for the quantum-enhanced design for materials and drug discovery project and the SARS-CoV-2 vaccination and immunity modelling project.
Ashleigh Tuite
Ashleigh Tuite is an infectious disease epidemiologist, mathematical modeler, and assistant professor at University of Toronto’s Dalla Lana School of Public Health. She also is manager of health economics and modeling at the National Advisory Committee on Immunization Secretariat.
Dr. Tuite’s research program focuses on the use of mathematical modeling and other quantitative methods to improve decision-making related to communicable diseases, including vaccine-preventable diseases. She is particularly interested in the use of mathematical models to synthesize and communicate complex information and uncertainty.
