Work

A coupled disease-misinformation model of measles transmission in the Canadian context

Year: 2026

Type: article

Abstract: Infectious disease dynamics are increasingly shaped not only by biological processes but also by the spread of misinformation. This study presents a coupled disease-misinformation model, SMIRK, to evaluate the impact of misinformation on a recent measles outbreak in Canada. The model combines a standard SIR framework for measles transmission with an SIS-like KMK model for misinformation spread. Two misinformation recovery paradigms are explored: constant-rate recovery and recovery induced by contact with infected individuals. Parameters were estimated using least-squares fitting to epidemiological data from Health Canada and Public Health Ontario (December 2024 to March 2025). Model calibration suggests that misinformation rapidly reaches a stable equilibrium, effectively saturating the population regardless of recovery paradigm. Due to the rapid information homogenization of the population, measles is predicted to behave as a standard low-R0 infection under most calibrations. Despite its limitations, the SMIRK model offers a proof of concept for integrating misinformation into epidemiological models, underscoring the need for more nuanced modeling of informational dynamics in public health forecasting.

Source: Infectious Disease Modelling

DOI: 10.1016/j.idm.2025.12.014

Authors: Callandra Moore, David Fisman

Institution: University of Toronto

Language: English

Topic: Mathematical and Theoretical Epidemiology and Ecology Models

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,100