Details view: C) Learning from history

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C) Learning from history

There are lessons to be learned from our historical responses to emerging infectious disease outbreaks.

In 2003, linkages were developed throughout Canada between public health officials and mathematical modellers in academia in response to the SARS-CoV-1 outbreak, leading to the creation of the Centre for Disease Modelling at York University. These linkages were leveraged to grow impactful interactions between the modeling community and the then newly created PHAC and the Federal, Provincial and Territorial Committee on Pandemic Preparedness as well as those preparing rapid responses to pandemic influenza. As the concerns over major disease outbreaks declined, interactions slowly faded due to a lack of coordinated support. This was a lost opportunity for creating and sustaining a national network of experts both in academia and public health agencies that can respond quickly to emerging public health threats.

The emergence of the SARS-CoV-2 in 2019 brought this missed opportunity into stark focus. Once again, a functioning network of experts from both public health agencies and academia was built from the ground up, and the delay that resulted had real public health and economic costs. One of the greatest bottlenecks during this period was the time it took both to conduct the necessary research that decision-makers required and to build an effective pipeline through which such fundamental research and scientific expert advice could be channeled to relevant governmental decision-makers. In addition to these lessons about pandemic preparedness, the COVID-19 pandemic also taught us that new collaborations and partnerships need to be formed, particularly between those with expertise in public health and infectious disease modelling, their adjacent scientific communities (e.g., epidemiology, immunology, public health, virology), and those with expertise in economics, education, international relations, policy-making, and the many other aspects of society that are affected by, and impact, the state of public health.

Very often during the COVID-19 pandemic, the “epidemiological good” of potential interventions was pitted against the “economic good” or the “psychological good” of not employing an intervention. In retrospect, it is now clear that in many ways this was a false dichotomy (see, for example, Sokolov et al. 2020). This mistaken perspective stemmed, in part, from the dearth of appropriate analyses that integrated infectious disease modelling with broader societal perspectives. The most powerful way to avoid similar mistakes and misinformation moving forward is to ensure that linkages between these diverse researchers are both fostered and sustained so that we can respond immediately when novel infectious disease crises arise.