Data and Privacy During a Global Pandemic Conference

Friday, December 4, 2020 12:00 am - 12:00 am EST (GMT -05:00)

What needs to be done in order to curb the spread of Covid-19: Exposure notification, legal considerations, and statistical modeling

Organized by the Master of Public Service Policy & Data Lab and GEDI and sponsored by the Waterloo Cybersecurity & Privacy Institute, this virtual conference brings together experts from the social and physical sciences, computer science and engineering, statistics, and law to help frame policy recommendations for a variety of societal issues that have emerged with COVID-19. There are three broad themes: (1) downloads of the Federal Government exposure notification app have been extremely low, mitigating its usefulness. What can be done legally and from a behavioural lens in order to increase the use of exposure notification apps?; (2) the lack of disaggregated COVID-19 data across the country has impaired the ability of researchers to conduct relevant and important research. What do governments need to do to ensure better data availability and what are novel data sources that can be studied by researchers?; (3) the use of statistical models in predicting the incidence and burden of COVID-19.

Speaker

Position

Topic

Dr. Vivek Goel Special Advisor to the President and Provost at the University of Toronto and a Professor in the Institute of Health Policy, Management and Evaluation at the Dalla Lana School of Public Health Opening remarks and welcome

Colleen Flood

Professor, Faculty of Law, University of Ottawa and University Research Chair in Health Law and Policy. Director for the University of Ottawa Centre for Health Law, Policy and Ethics

What Powers Does the Federal Government Have to Require Exposure Notification Apps for COVID-19?

Michael Wolfson

Former Assistant Chief Statistician, Analysis and Development, at Statistics Canada & Adjunct Professor, School of Epidemiology and Public Health, University of Ottawa

How Data Availability from Government has Impeded COVID-19 Research & the ‘Chilling’ Effects of Privacy Concerns

Anindya Sen

Professor of Economics & Director, Master of Public Service, University of Waterloo. Member, Waterloo Artificial Intelligence Institute & Waterloo Cybersecurity & Privacy Institute.

A Cost Benefit Analysis Approach to Accommodating Privacy Concerns in Data Collection & How Canada Compares to Other Jurisdictions

Jeff Chan

Assistant Professor, Department of Economics, Wilfrid Laurier University

How Social Media and Cellphone Data Can be Used to Track Mobility During Pandemics

Igor Grossmann

Associate Professor of Psychology & Director, Wisdom and Culture Lab, University of Waterloo

Using Behavioural Psychology to Understand How Exposure Notification Apps Can Be Successful

Ashleigh Tuite

Assistant Professor of Epidemiology, Dalla Lana School of Public Health, University of Toronto

How Epidemiological Models (Even Wrong Ones) Can be Useful for Identifying Critical Data Gaps

Mark Crowley

Assistant Professor, Department of Electrical and Computer Engineering, Waterloo Artificial Intelligence Institute, University of Waterloo

Prediction and Causality: How Can Machine Learning be Used for COVID-19?

Plinio Morita

Assistant Professor, School of Public Health and Health Systems

J.W. Graham Information Technology Emerging Leader Chair in Applied Health Informatics

Director, Ubiquitous Health Technology Lab (UbiLab), University of Waterloo

How to Design Better COVID-19 Exposure Notification Apps

Ashley Rose Mehlenbacher Associate Professor specializing in rhetorical theory and science communication and PI of the Democratization through Education in Medicine, Technology, and Science Lab (Demos Lab) Communicating about Health and Safety Benefits and Privacy Risks in COVID-19 Exposure Notification Tracking Apps

Scott Leatherdale 

University Research Chair and Professor, School of Public Health and Health Systems, University of Waterloo Evaluating the Effects of COVID-19 on Schools: Evidence from COMPASS Data 



Q & A Session 1 Statistical Modeling 
  • Jeff Chan (Wilfrid Laurier University), How Social Media and Cellphone Data Can be Used to Track Mobility During Pandemics 
  • Mark Crowley (University of Waterloo), Prediction and Causality: How Can Machine Learning be Used for COVID-19?  
  • Ashleigh Tuite (University of Toronto), How Epidemiological Models (Even Wrong Ones) Can be Useful for Identifying Critical Data Gaps
Q & A moderated by Bessma Momani 
Q & A Session 2 Exposure Notification Apps 
  • Colleen Flood (University of Ottawa), What Powers Does the Federal Government Have to Require Exposure Notification Apps for COVID-19?  
  • Igor Grossmann (University of Waterloo), Using Behavioural Psychology to Understand How Exposure Notification Apps Can Be Successful  
  • Ashley Rose Mehlenbacher (University of Waterloo), Communicating about Health and Safety Benefits and Privacy Risks in COVID-19 Exposure Notification Tracking Apps  
Q & A moderated by Catherine Burns 
Q & A Session 3  Data and Privacy Concerns
  • Michael Wolfson (University of Ottawa), How Data Availability from Government has Impeded COVID-19 Research & the ‘Chilling’ Effects of Privacy Concerns  
  • Plinio Morita (University of Waterloo), How to Design Better COVID-19 Exposure Notification Apps  
  • Anindya Sen (University of Waterloo), A Cost Benefit Analysis Approach to Accommodating Privacy Concerns in Data Collection & How Canada Compares to Other Jurisdictions  
Q & A moderated by Catherine Burns

See detailed speaker bios on the Conference TicketFi Site