Advanced Methods Webinar - COVID-19 Canada Open Data and Visualization with R Shiny
The COVID-19 Canada Open Data Working Group was founded in March 2020 in response to the need for accurate, up-to-date and accessible data on the COVID-19 pandemic in Canada. Unlike many datasets that provide only aggregate case counts, the working group dataset collects individual-level case data, which are particularly valuable during outbreaks but are seldom made available in real time. This dataset feeds into an interactive dashboard (powered by R Shiny), which enables users to visualize the data and follow the outbreak as it unfolds.
The working group’s open access, individual-level database includes information on COVID-19 cases (confirmed and presumptive positive) as well as mortality. Specifically, we collect demographic characteristics, geographic location, report date, travel history, and exposure source, where available. Time series datasets of recoveries and testing are also recorded. All data are collected from publicly available sources, including government health authorities as well as news media.
The working group’s dataset and dashboard have become a reliable pan-Canadian source for COVID-19 information. Additionally, this database has the potential for future linkages with diverse datasets, such as policy interventions, socio-behavioural changes, environmental factors, and other population-level factors. The open access aspect of this work encourages transparency and data sharing, which are crucial for supporting evidence-based control strategies and directing public health response efforts in Canada for the COVID-19 pandemic.
The webinar will provide an overview of the key features associated with the COVID-19 Canada Open Data Working Group databases and feature a demonstration of the tools available on the R Shiny dashboard. Presenters will also identify research opportunities associated with population-level analyses and the use of R Shiny to explore and visualize health outcomes.
View recorded presentation below.
Isha Berry is a PhD Candidate in Epidemiology at the Dalla Lana School of Public Health and a Fellow in the Emerging Leaders in Biosecurity Initiative at the Johns Hopkins Centre for Health Security. She is a founder of the COVID-19 Canada Open Data Working Group, which leads digital surveillance of COVID-19 cases in Canada to curate a publicly available line list and public-facing data dashboard. Isha has expertise in infectious disease epidemiology, geo-spatial methods, and mathematical modelling. Her primary area of research is understanding the socio-behavioral drivers of global emerging infectious diseases. She has experience conducting infectious disease research in low-, middle-, and high-income settings. She holds an MSc in Epidemiology from the London School of Hygiene and Tropical Medicine and a BSc in Environmental Science from McGill University.
Jean-Paul R. Soucy is a PhD student in Epidemiology in the Dalla Lana School of Public Health at the University of Toronto. He is a founder of the COVID-19 Canada Open Data Working Group. Jean-Paul's thesis research focuses on infectious disease epidemiology under the supervision of Dr. David Fisman and Dr. Kevin Brown. He is supported by a Vanier Canada Graduate Scholarship. He has previously studied antibiotic resistance and vector-borne diseases. Jean-Paul holds an MSc in Epidemiology from McGill University and an HBSc in Biology with a minor in Mathematics from the University of Ottawa.