Pivoting data and analytic capacity to support Ontario’s COVID-19 response

Hannah Chung; Mahmoud Azimaee; Susan E Bronskill; Rosario  Cartagena; Astrid Guttmann; Minnie M Ho; Lisa Ishiguro; Jeffrey C Kwong; J Michael Paterson; Sujitha  Ratnasingham; Laura Rosella; Michael J Schull; Marian J Vermeulen; J Charles Victor

doi:10.23889/ijpds.v5i4.1682

International Journal of Population Data Science (Jan 2022)

Pivoting data and analytic capacity to support Ontario’s COVID-19 response

Hannah Chung,
Mahmoud Azimaee,
Susan E Bronskill,
Rosario Cartagena,
Astrid Guttmann,
Minnie M Ho,
Lisa Ishiguro,
Jeffrey C Kwong,
J Michael Paterson,
Sujitha Ratnasingham,
Laura Rosella,
Michael J Schull,
Marian J Vermeulen,
J Charles Victor

Affiliations

Hannah Chung: ICES, Toronto, ON
Mahmoud Azimaee: ICES, Toronto, ON; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON
Susan E Bronskill: ICES, Toronto, ON; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON; Dalla Lana School of Public Health, University of Toronto, Toronto, ON; Evaluative Clinical Sciences, Sunnybrook Research Institute, Toronto, ON; Women's College Research Institute, Toronto, ON
Rosario Cartagena: ICES, Toronto, ON; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON
Astrid Guttmann: ICES, Toronto, ON; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON; Dalla Lana School of Public Health, University of Toronto, Toronto, ON;Hospital for Sick Children, Toronto, ON; Child Health Evaluative Sciences, SickKids Research Institute, Toronto, ON; Leong Centre for Healthy Children, University of Toronto, Toronto, ON
Minnie M Ho: ICES, Toronto, ON
Lisa Ishiguro: ICES, Toronto, ON
Jeffrey C Kwong: ICES, Toronto, ON; Dalla Lana School of Public Health, University of Toronto, Toronto, ON; Public Health Ontario, ON; Centre for Vaccine Preventable Diseases, University of Toronto, Toronto, ON; Department of Family and Community Medicine, University of Toronto, Toronto, ON; University Health Network, Toronto, ON
J Michael Paterson: ICES, Toronto, ON; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON; Department of Family Medicine, McMaster University, Hamilton, ON
Sujitha Ratnasingham: ICES, Toronto, ON
Laura Rosella: ICES, Toronto, ON; Dalla Lana School of Public Health, University of Toronto, Toronto, ON; Banting and Best Diabetes Centre, Vulnerable Populations/Population Health, University of Toronto, Toronto, ON; Institute for Better Health, Trillium Health Partners, Mississauga, ON; Institute for Better Health, Trillium Health Partners, Mississauga, ON; Vector Institute for Artificial Intelligence, Toronto, ON
Michael J Schull: ICES, Toronto, ON; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON; Evaluative Clinical Sciences, Sunnybrook Research Institute, Toronto, ON; Department of Medicine, University of Toronto, Toronto, ON; Sunnybrook Health Sciences Centre, Toronto, ON
Marian J Vermeulen: ICES, Toronto, ON
J Charles Victor: ICES, Toronto, ON; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON

DOI: https://doi.org/10.23889/ijpds.v5i4.1682
Journal volume & issue: Vol. 5, no. 3

Abstract

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Introduction Health care systems have faced unprecedented challenges due to the COVID-19 pandemic. Access to timely population-based data has been vital to informing public health policy and practice. Methods We describe how ICES, an independent not-for-profit research and analytic institute in Ontario, Canada, pivoted existing research infrastructure and engaged health system stakeholders to provide near real-time population-based data and analytics to support Ontario's COVID-19 pandemic response. Results Since April 2020, ICES provided the Ontario COVID-19 Provincial Command Table and public health partners with regular and ad hoc reports on SARS-CoV-2 testing and COVID-19 vaccine coverage. These reports: 1) helped identify congregate care/shared living settings that needed testing and prevention efforts early in the pandemic; 2) provided early indications of inequities in testing and infection in marginalized neighbourhoods, including areas with higher proportions of immigrants and visible minorities; 3) identified areas with high test positivity, which helped Public Health Units target and evaluate prevention efforts; and 4) contributed to altering the province's COVID-19 vaccine roll-out strategy to target high-risk neighbourhoods and helping Public Health Units and community organizations plan local vaccination programs. In addition, ICES is a key component of the Ontario Health Data Platform, which provides scientists with data access to conduct COVID-19 research and analyses. Discussion and Conclusion ICES was well-positioned to provide rapid analyses for decision-makers to respond to the evolving public health emergency, and continues to contribute to Ontario's pandemic response by providing timely, relevant reports to health system stakeholders and facilitating data access for externally-funded COVID-19 research.

COVID-19

Published in International Journal of Population Data Science

ISSN: 2399-4908 (Online)
Publisher: Swansea University
Country of publisher: United Kingdom
LCC subjects: Social Sciences: Economic theory. Demography: Demography. Population. Vital events
Website: https://ijpds.org

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