Over the course of the pandemic, more than 53,000 Canadians died and nearly five million contracted COVID-19.
While Canada had lower numbers of cases and deaths and higher vaccination rates than most other G10 countries, these successes mask inequities across communities, socio-economic conditions and demography. They also hide challenges in data sharing and loss of public trust over time, evidenced by the “freedom convoy” movement that occupied Canada’s capital, Ottawa, in early 2022.
These and other challenges are laid out in a series of articles published in the British Medical Journal (BMJ) on July 24, that we co-authored with other clinical, research and public health experts across Canada. Now is the time to learn from the COVID-19 response through an action-oriented, independent inquiry focused on implementation and accountability.
Loss of Public Trust
Canada’s public health response was hampered by fragmentation in decision-making, shared between federal and provincial/territorial and sometimes municipal governments. The Public Health Agency of Canada, which was created in the wake of the first SARS outbreak in 2003, develops national clinical and public health guidelines while provincial and territorial health agencies make decisions for their individual jurisdictions.
In the absence of a co-ordinated planning and delivery authority, different public health measures were implemented in different locales. For example, measures like vaccine eligibility and mandates, masking and school closures varied among provinces.
The rationale and supporting evidence for these different approaches were unclear. Some variations addressed local risk factors as evidence evolved, but insufficient availability and sharing of data and analyses — combined with a lack of transparency — made it hard to explain the variation to the public. Over time, this led to a loss of confidence in public health guidance.
Part of the problem is outdated data infrastructure that isn’t able to support public health decision-making in real time. Health information systems lack integration and interoperability between data sources, even after $130 million of investment over the past eight years.
However, other problems are legal and cultural. Canada’s health data privacy and protection laws, developed before the era of big data applications, create legal impediments to using and analyzing data across jurisdictions.
These impediments were exacerbated by a culture of risk aversion among the custodians of data in different jurisdictions and organizations. This culture requires a shift from a safeguarding mindset to one of stewardship for public good.
Technological advances mean data no longer need to be pooled across jurisdictions. Data need never leave their secure data environments; instead, de-identified data may be accessed and analyzed across independent systems using federated data structures. Unfortunately, these structures were not in place at the start of the pandemic and have not been implemented over the past three years.
Improved data access also presumes that data are fit for purpose, and that was not the case. Comparisons between jurisdictions were difficult for several reasons, including policy differences in testing eligibility, types of tests, how test results were reported and how hospitalizations or deaths were attributed to COVID-19.
Over the course of the pandemic, most jurisdictions reported COVID-19 case numbers, but data about demographics or location were withheld due to privacy concerns. This lack of nuanced data left people with a lack of understanding of their personal or community-level risk factors. The lack of ability to make informed decisions contributed to loss of public trust over time.
Even worse, the initial pandemic response was ill-designed to address the socio-economic and structural inequities that led to disproportionate burdens of the pandemic.
Highest rates of COVID-19 cases and deaths were among racialized people, recent immigrants, lower-wage essential workers and those living in higher density and multigenerational households.
Case rates were highest where high-density living intersected with high-density working conditions, and were amplified by barriers to testing, vaccination and ability to isolate. This trend did not resolve over the successive waves of the pandemic.
Health data that include not only locale, but also racial identity, occupations, household size and income can help unpack social determinants of infection and health outcomes, and can be used to tailor public health programs. However, the collection of such data give rise to responsibilities to reduce inequalities, not just describe them.
Sadly, decisions to collect such data can be politicized. Ontario only collected relevant data after pressure from community activists and Québec resisted similar community pressure to collect race-based data.
Canada’s diversity was also not adequately represented at decision-making or advisory tables, nor was it represented in research that generated evidence for the public health response.
Public health decisions involve health, social and economic tradeoffs that need to be informed not only by standard epidemiological data, but also by social science data. These data can illuminate the social determinants of health, the spread of misinformation and disinformation and political factors, such as the rise in social unrest due to public health measures. Evidence generation needs to be inclusive of diverse voices, specifically from those communities that bore the greatest burden of the pandemic.
Public Inquiry and Reforms
It is clear that some public trust in public health, science and government has been lost in Canada and around the world. This does not bode well for future threats, such as emerging pandemics, and current threats from the opioid crisis and climate change.
For these reasons, we call for a different kind of inquiry, agreeing that another expert report packed with recommendations will gather dust and not serve to rebuild public trust.
We need political will to call an independent inquiry that is inclusive of a diversity of voices, accountable to communities and with a mandate to implement change. Reforms to data generation, access and use are essential in preparing for the next public health emergency.
ABOUT THE AUTHORS
Tania Bubela, Professor and Dean of the Faculty of Health Sciences, Simon Fraser University. Dr. Bubela is a Fellow of the Royal Society of Canada (2019) and a Fellow of the Canadian Academy of Health Sciences (2018). Previously she was Professor, School of Public Health and Adjunct Professor, Alberta School of Business at the University of Alberta, Canada. She holds a PhD in biology from the University of Sydney and a JD from U Alberta. She joined the faculty of U Alberta in 2004 after clerking at the Supreme Court of Canada and being admitted to the Law Society of Alberta in 2005. Her research program in intellectual property and health law related to translational biomedical research brings together her legal training and a PhD in biology and expertise in genetics and molecular biology. It focuses on large collaborative science networks in genomics, gene therapy, and stem cell biology, addressing barriers to the effective translation of new technologies. These are varied and include ethical issues, effective communication of risks and benefits among stakeholder groups, commercialization and regulation. She provides advice for government health and science agencies as well as life sciences research communities, and patient organizations. Her research is funded by Canadian Institutes of Health Research, the Canadian Stem Cell Network, Genome Canada, and Alberta Innovates, BioCanRx, and the Michael Smith Foundation for Health Research, among others. She co-leads CLEONet, funded by Genome Canada and others, on implementation of precision oncology in Canada. She has over a hundred publications in law, ethics and biomedical journals including Nature, Nature Biotechnology, Cell Stem Cell, PLoS Biology, Trends in Biotechnology, American Journal of Bioethics, Science and Science Translational Medicine.
Kimberlyn McGrail, Professor of Health Services and Policy Research, University of British Columbia. Dr. McGrail is population data scientist with expertise in health services, health policy, ethics as it relates to data access governance and use, and pubic deliberation. Dr. McGrail receives funding from the Canadian Institutes of Health Research.
Sharmistha Mishra, Associate Professor of Medicine, University of Toronto. Dr. Mishra is an infectious disease physician (MD, FRCPC) and mathematical modeler and infectious disease epidemiologist (MSc, PhD). She holds a Tier 2 Canada Research Chair in Mathematical Modeling and Program Science and is an Associate Professor at University of Toronto Department of Medicine, and a Scientist at the Li Ka Shing Knowledge Institute, Unity Health Toronto.
This article is courtesy of the The Conversation.