[Canadian Journal of Public Health, Editorial, 26 July 2024]

This issue of the Journal includes an important paper by Xia and colleagues (Xia et al., 2024 ) describing recent pandemic experiments modeling the disease. Throughout the pandemic, health officials and government leaders showed graphs of projected epidemic curves, and alternative curves depending on whether a particular intervention like physical distancing or school closures was implemented.

Underlying these projections are computer simulation models. Xia et al. ( 2024 ) surveyed and characterized the variety of these models for six provinces where information was available. There was some informal information sharing among these modelers and regular cross-country virtual conversations agreed by the Public Health Agency of Canada (PHAC). Still, important lessons merit being more widely shared, for which this CJPH article provides an important starting point.

As in all models, the veracity of the projections depends critically on the quality of the data on which they are based, and the methodologies applied. Canada is well endowed with infectious disease modeling expertise, primarily based in universities. However, the data needed to support these modeling efforts were too often limited. In many cases, the data does not exist; for example, at the start of the pandemic, accurate counts of new infections, hospitalizations, and deaths due to COVID, as well as the availability of ventilators and personal protective equipment (PPE) were unavailable.

In other cases, the data existed digitally but were not shared, even within provinces and the same or closely affiliated agencies. For example, data in one agency on infected individuals could have been linked to data in another agency that was capturing the virus' genotype at the individual level, but were not shared—thus depriving modelers of critical information on the virulence of evolving mutations. Another example was the failure to link detailed individual-level data on infections, vaccinations, and hospital admissions within the same province. Doing so would have enabled inputs and analysis greatly improving mathematical modeling.

Notwithstanding repeated claims that health care is a provincial responsibility, the federal government constitutionally has important powers as well and plays an overarching and coordinating role as health is a shared jurisdiction. Specifically for health crises like the pandemic, the Constitution grants the federal government powers regarding quarantine.

The federal government played a major role in procuring vaccines and test kits, and providing large cash transfers to individuals and businesses to help them bear the economic hardships of lockdowns and other measures intended to stem pandemic spread. Statistics Canada's legislated authorities and flexible data collection capabilities were available, though underutilized.

The federally funded COVID-19 Immunity Task Force (COVID-19 Immunity Task Force, nd ) played a key role, including producing seroprevalence estimates, albeit mostly pulling data from various existing sources including blood donations, cohort studies, and lab tests, sources that were not designed to provide unbiased surveillance. The Canadian COVID-19 Antibody and Health Survey (CCAHS) (Statistics Canada, 2023 ) made extensive efforts to provide unbiased sampling, an area that merits major improvements.

PHAC further has important responsibilities regarding infectious disease outbreaks, including modeling. This and other information are required to brief the federal Minister of Health and Cabinet on how the pandemic was likely to evolve. However, even though the provinces signed agreements more than a decade ago to share key data, such as individual-level data on cases of infection, these data often did not flow, or were seriously incomplete…

[CMAJ, 9 December 2024]

Key Points:

• In Canada, patient health data are held by many organizations in different databases that are not currently interoperable.

• Interoperability means that authorized users, including patients, health care providers, and researchers, can access all relevant data across all databases, which is important for high-quality care and assessing health system performance.

• Patient access to their entire electronic medical records, provider access to a patient’s entire electronic medical record, and analyst access to data needed for assessment of health care quality are 3 valid, focused, and sentinel indicators of interoperability.