MS03 - MEPI-11

Advances in infectious disease modelling: towards a unifying framework to support the needs of small and large jurisdictions (Part 1)

Tuesday, July 15 at 10:20am

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Organizers:

Amy Hurford (Memorial University), Michael Li, Public Health Agency of Canada

Description:

Homogeneous mixing and the aggregation of diverse population groups into one group are frequent simplifying assumptions that may produce erroneous models and recommendations that exacerbate health inequities. Yet, models that make these simplifying assumptions have well-understood dynamics, and can be quickly solved, facilitating data fitting and uncertainty analysis that can support policy recommendations. Advancing the methodology around these model-building tensions is needed, and the best modelling approach may depend on the application. The motivation for developing these modelling approaches is from the COVID-19 pandemic in Canada. Atlantic Canada, the Canadian territories, and other small Canadian jurisdictions experienced different epidemiology, and needed different types of modelling support, than the larger Canadian provinces. There is a need to advance infectious disease modelling to support jurisdictions at all levels, and this session furthers this goal by including talks that describe: infectious disease spread in structured communities; importations and mobility networks; models that were developed for specific small jurisdictions, methods for calculating the reproduction number, estimating healthcare demand, and describing how the needs of small jurisdictions can be integrated into pandemic preparedness plans.



Michael WZ Li

Public Health Agency of Canada
"Modeling and Prospects to Support Small Jurisdiction Public Health in Canada"
Mathematical modeling has been critical in supporting public health initiatives, providing valuable insights into disease dynamics, intervention strategies, and resource allocation. Many regional heterogeneity effects and challenges from small jurisdictions and communities were masked by the larger jurisdictions during the pandemic, however, risk exist in both directions and in many forms. In this talk, I will discuss prospects working towards supporting small-jurisdiction public health, in particular, the challenges with awareness, communication, uncertainty of information and feedbacks.



Wendy Xie

National Collaborating Centre for Infectious Diseases
"Lessons learned from the In the Equation Workshop: Towards Indigenous-led infectious disease modelling"
The In the Equation Workshop was held February 18-19, 2025 with the goal of initiating discussions towards Indigenous-led infectious disease modelling. Over the course of 1.5 days, presentations from the Chiefs of Ontario, First Nations Health and Social Secretariat of Manitoba, First Nations Information Governance Centre, and Inuit Tapiriit Kanatami highlighted ongoing work to advance data sovereignty and capacity building for First Nations and Inuit health research and programming. Participants engaged in facilitated discussions focused on what community-based infectious disease research means for First Nations, Métis, and Inuit communities, and how mathematical modellers can better support Indigenous-led health research. The knowledge shared at this workshop underscores the need for formal training in Two-Eyed Seeing approaches in infectious disease research and emphasizes the importance of continued relationship building among First Nations, Métis, and Inuit community leaders and modelling researchers.



James Watmough

University of New Brunswick
"Predicting population level immune landscapes in small communities."
Roughly speaking, outbreaks of respiratory infectious, such as measles, CoViD-19, and influenza, are shaped by two main factors: (1) the patterns and nature of contacts between individual hosts, and (2) the distribution of immunity locally and regionally within the host population. The strength and duration of an individual host's immune response depends on individual traits and the characteristics of exposure, which are at least partially dependant on the nature of contacts between hosts. Thus, the dynamics of disease spread and waning immunity at the host-population level are driven by a fixed landscape of immune-traits based on demographics, comorbidities, and other individual factors affecting disease severity, and a dynamic immune landscape shaped by prior outbreaks. Contact patterns between hosts reflect community structure and the relative strengths of within group and between group contacts. This contact structure can be very different for smaller isolated communities and small communities nestled in larger metropolises. The main objective of this talk is to present preliminary results from simple compartmental and individual-based models designed to predict population-level distributions of disease burden and immunity from host community structure and within-host virus and immune dynamics. Of particular interest is the role of community structure in determining the size and severity of outbreaks in smaller jurisdictions.



Abdou Fofana and Amy Hurford

Memorial University
"Fitting and counterfactual scenarios for epidemiological data describing intermittent periods of travel-related cases and community spread"
When infectious disease dynamics are dominated by community spread there are established methods to estimate the transmission rate for an epidemic compartment model and for how to do counterfactual scenarios. But how should this same analysis be done if infectious disease spread occurs as intermittent periods of travel-related cases and community outbreaks? In this talk, we will describe the importation-community spread switch model. This model considers data describing infections that arise from contact with an infectious person in another community (travel-related cases) or with an infectious person in the local community (community cases). The importation-community spread switch model includes a spillover model that describes the probability that a travel-related case initiates a community outbreak. We fit the importation-community spread switch model to COVID-19 data from the Canadian province of Newfoundland and Labrador. We describe how the estimated parameters are used in a counterfactual simulation framework. Canada consists of large jurisdictions and small jurisdictions, such as Newfoundland and Labrador. The importation-community spread switch model generalizes fitting and simulation approaches so that they can be applied to a broader range of Canadian jurisdictions.



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