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Air Date: October 19, 2021 | Length: 47:21
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It was Canada's worst fear in March 2020 — COVID-19 reached the great white north. With increasing case counts and hospital burden throughout the country and in Ontario, government officials were looking to lean on healthcare economists to predict the impact of the pandemic. Dr. Beate Sander's research highlights the importance of epidemiological modelling and how it guided public policy in Ontario. With the ever-changing data from around the world, her team highlighted the importance of certain measures to stop the spread. She discusses how the pandemic affects certain populations disproportionally. Plus, she expresses the need for better public data infrastructures, reporting, tracking and analytics to be well prepared in the future.
Follow Dr. Sander on Twitter: @BeateSander
Beate Sander, RN MBA MEcDev PhD, holds a Canada Research Chair in Economics of Infectious Diseases; is Scientist and Director, Population Health Economics Research (PHER) at the Toronto General Hospital Research Institute; Director, Health Modeling & Health Economics at the Toronto Health Economics and Technology Assessment collaborative (THETA); and holds appointments as Associate Professor at the Institute of Health Policy, Management and Evaluation (IHPME), University of Toronto; Adjunct Scientist at Public Health Ontario; and Adjunct Scientist at the Institute for Clinical Evaluative Sciences.
Dr. Sander's areas of expertise include health economics, decision analysis and simulation, infectious disease epidemiology, and population health decision-making. Beate's research focuses on economic evaluation, ranging from methods development to applied research on infectious diseases. She is leading large multidisciplinary international teams evaluating Zika, West Nile virus (WNv) and more recently SARS-COV-2 mitigation strategies using data-driven simulation models and estimating the burden of infectious diseases, such as COVD-19, using linked population-based data. She has spearheaded the linkage of laboratory and reportable disease data with administrative data, enabling novel approaches to study the burden of infectious diseases.