Charting a Future
Charting a Future for Emerging Infectious Disease Modelling in Canada – April 2023 [1]

Executive Summary

We propose an independent institute of emerging infectious disease modellers and policy experts, with an academic core, capable of renewing itself as needed. This institute will combine science and knowledge translation to inform decision-makers at all levels of government and ensure the highest level of preparedness (and readiness) for the next public health emergency. [1]

The Public Health Modelling Institute will provide cost-effective, science-based modelling for public policymakers in an easily visualizable, integrated framework, which can respond in an agile manner to changing needs, questions, and data.

To be effective, the Institute must link to modelling groups within government, who are best able to pose questions and convey results for use by public policymakers.

Quantitative models form a flexible suite of methods that can synthesize information from diverse fields, present this information intuitively and visually, support evidence-based policy, aid in communicating with the public, and quantify and manage uncertainty. Models can provide projections and scenarios and can support operational planning across multiple domains. The recent Emerging Infectious Disease Modelling (EIDM) program, created jointly by the Public Health Agency of Canada (PHAC) and Natural Sciences and Engineering Research Council of Canada (NSERC) in 2021, brought together over 100 modellers and other investigators from coast to coast. In collaboration with public health agencies (federal, provincial, and territorial), it fostered partnerships, collaboration, and trust across academic teams, government organizations, and public health institutions. It trained a high-quality workforce, and created state-of-the-art datasets and an arsenal of applied, interpretable models to support decision-making during the pandemic and beyond.

Recent experience from the pandemic underscores the need for a lasting capacity for integrated, multi-disciplinary, whole-of-society analysis that can be rapidly deployed in an emergency, with sustained and direct linkages between infectious disease research, modelling, public health, evolution, economics, socio-economics, and policymaking. We need to ensure that there is a robust, trusted platform for rapid synthesis and consensus, spanning multiple domains and scales, ready to support decision-makers and decision-making.

We envision a permanent institute to provide this capacity. In coordination with federal, provincial, and territorial public health agencies and Indigenous groups, it will:

  • undertake and harmonize research in this space across institutions,
  • provide funding for continued modelling and capacity-building across a broad range of expertise, and
  • ensure that Canada can better deal with future crises.

The institute will be an independent, apolitical authority that can help to formulate consensus “serviceable truths” in an emergency, rapidly bringing researchers together to work on policy activities when the next crisis does occur. Its core functions will also support robust pathogen surveillance, data access, and real-time analysis, and train a high-quality workforce in the requisite scientific, communication and collaboration skills.

The Institute will connect a broad group of researchers on an ongoing basis. Importantly, its success will build upon the current bridges that have been developed between academic researchers and modellers, and those within public health agencies (federal, provincial, and territorial), who are best able to inform research directions and relay key messages to policy-makers.

The Institute will have a permanent team of administrative staff, including an executive director, knowledge translation experts, and others. Together, these groups of people will form the core of long-lasting strategic relationships between the academic community and the policy advisors. The Institute will include mechanisms for compensating researchers (or their home institutions) when they are more intensively involved, for example as director, or as advisors in times of emergency. Formation of the Institute is a crucial step towards providing cost-effective, science-based modelling that can respond to changing needs, questions and data and ensuring the highest level of preparedness for the next public health emergency.


As the world emerges from its most severe pandemic in over one hundred years, it is important to reflect on what happened so that we can better plan for the future. The crisis of COVID-19 galvanised a broad group of epidemiological modellers from academia who interacted with the Public Health Agency of Canada and provincial health authorities across Canada to help make informed decisions. The successes that were achieved are a testament to the enormous effort and dedication shown by individuals to build the required infrastructure and relationships for effective modelling and advising. This infrastructure, consisting of research groups with the relevant scientific expertise and those skilled in knowledge transfer, needs to be maintained and strengthened so that it can be readily deployed when new crises arise.

Decisions during pandemics always require some form of modelling to integrate diverse data into an interpretable framework, to compare possible scenarios for trajectories over time, to evaluate interventions, and to estimate the likelihood of different outcomes and their associated costs and benefits. While models can be implicit, based on intuition or experience, the large number of factors at play make outcomes difficult to predict without explicitly incorporating key factors into a clear quantitative, scientific framework that can be used to make projections. Explicit quantitative models have been shown to be particularly useful when outcomes are unintuitive and policy options are not clear (e.g., informing vaccine rollout strategies (Aruffo et al. 2022a; Aruffo et al. 2022b), stay-at-home policy (Yuan et al. 2022b), school and community reopening (Yuan et al. 2022a), synergistic roles of different interventions (Tang et al., 2020), impact of public health interventions on different age groups and settings (McCarthy et al., 2020) or predicting future healthcare burdens (Tuite et al. 2020; Anderson et al. 2020; Zimmerman et al. 2021; Mishra et al. 2020)). In these cases, modellers, interacting with the broader scientific community, have a history of providing a “serviceable truth” (Jasanoff 2015), bringing together information from fields as disparate as evolutionary biology, immunology, epidemiology, and economics to formulate a scientific consensus that can help to provide a transparent and effective foundation for decision-making.

The world was caught unprepared for COVID-19 modelling, with insufficient initial capacity for connecting modelling, the broader scientific community, and public health policy. Despite this slow start, the Canadian infectious disease modelling community has had many successes during the COVID-19 pandemic. These include the establishment of the first national COVID-19 modeling rapid response task force. In concert with the PHAC External Expert Modelling Group this task force informed and enabled PPE procurement and pharmaceutical purchasing needs (Betti et al. 2021b), predicting when Alpha, Gamma and Delta variants would begin to drive rising case numbers (BC COVID-19 Modelling Group 2021; Public Health Agency of Canada 2022), quantifying the conditions on public health measures to mitigate a pandemic wave (McCarthy et al. 2020; Tang et al. 2020), aiding the design of effective vaccine rollouts (Mulberry et al. 2021; Aruffo et al. 2022b; Betti et al. 2021a), defining and communicating the benefits of “flattening the curve” (Jackson 2020), and informing cost-effectiveness of policies with long- and short-term impacts (Cotton et al. 2022; Feng et al. 2022). Canadian modellers have built many new links, for example with the COVID-19 Genomics UK Consortium (, the Canadian COVID-19 Genomics Network (, the Coronavirus Variants Rapid Response Network (, and the COVID-19 Immunity Taskforce ( Importantly, they have developed collaborative links with all of the provinces (see, for example, ON Science and Modelling tables (Hillmer et al. 2021 and and some of the territories. Models have been incorporated explicitly into provincial analyses of COVID-19 (see, for example, Government of Manitoba 2022; Government of Alberta 2021; Government of Nova Scotia 2020; Government of Prince Edward Island 2020; Government of New Brunswick 2020; Brisson et al. 2022)).

The PHAC convened weekly meetings of modellers throughout the country (the External Expert Modelling Group) to share methods, questions, results, and analyses; these meetings fostered networking in the Canadian modelling community from the start of the pandemic. These relationships provided a starting point for another success in building capacity in Canada: the Emerging Infectious Disease Modelling (EIDM) program. This joint venture between PHAC and the Natural Sciences and Engineering Research Council of Canada (NSERC) provided short-term funding to five key networks focused on public health, mathematics, statistics, One Health (human-wildlife-domestic animal-environment), evolution, and economic modelling, as well as the interactions among these themes. However, the EIDM funding is very short-term. Maintaining the strengths that have been developed requires a well-articulated long-term vision for emerging infectious disease modelling in Canada that builds on current successes and relationships.

The goal of this paper [1] is to use our past experiences and connections to propose a long-term vision for connecting quantitative scientists and public health bodies in Canada.

Networks »Networks
Charting a Future
A) What is emerging infectious disease modelling? »A) What is emerging infectious disease modelling?
B) Benefits of continued emerging infectious disease modelling? »B) Benefits of continued emerging infectious disease modelling?
C) Learning from history »C) Learning from history
D) Successes of the existing EIDM program? »D) Successes of the existing EIDM program?
E) Vision for future research and training »E) Vision for future research and training
F) Call for Investment in a Public Health Modelling Institute »F) Call for Investment in a Public Health Modelling Institute
G) Future Research and Challenges »G) Future Research and Challenges
H) Translating modelling into public health gains »H) Translating modelling into public health gains
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MfPH – Publications »MfPH – Publications
OMNI – Publications »OMNI – Publications
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