Summary
The COVID-19 pandemic underscored the critical role of human behavior in the spread of infectious diseases, with challenges like vaccine hesitancy, pandemic fatigue, and shifting public compliance. A collaborative research initiative, led by Dr. Monica Cojocaru from the University of Guelph, aims to model how decision-making at individual and population levels affects pathogen transmission. The project will explore demographic and psychological factors, such as risk perception and discomfort with health measures, using innovative mathematical models.
Partnering with universities across Canada, industry leaders like Sanofi Global, and government agencies, the initiative is supported by $300,000 in funding. The research will train two PhD and three Master’s students and develop tools and dashboards for public use. Results, expected next year, will offer actionable insights for policymakers to design more effective public health strategies, enhancing preparedness for future respiratory epidemics.
The COVID-19 pandemic highlighted the profound impact of human behavior on the spread of infectious diseases. From mask-wearing and social distancing to vaccine hesitancy and pandemic fatigue, the dynamics of human behavior proved to be a critical challenge for governments and health agencies. The constantly evolving science and the public’s willingness to adopt health measures often left policymakers struggling to keep pace. To address these complexities, a groundbreaking collaboration between academia, industry, and government agencies aims to quantify how populations perceive and adopt public health policies. This partnership will investigate decision-making mechanisms at individual, group, and population levels, assessing how these behaviors influence the dynamics of pathogen transmission over time and across diverse geographic and socio-demographic categories.
Led by Dr. Monica Cojocaru from the Department of Mathematics and Statistics at the University of Guelph, this initiative seeks to create innovative mathematical models that capture the heterogeneity of public behavior. This heterogeneity is viewed not only through demographic differences but also through varying perceptions of risk and discomfort with public health measures.
The team plans to publish results within the next year, showcasing how behavioral factors influence the spread of infectious diseases. This work will provide actionable insights and tools for policymakers to better design and implement public health measures in future outbreaks.
The research is being conducted in collaboration with the Universities of Guelph, Calgary, British Columbia (Okanagan), and Université de Montréal, along with industry partner Sanofi Global and government stakeholders. The project also involves contributions from Spectus.AI, L’Observatoire Québécois de l’Adaptation aux Changements Climatiques (OQACC – hosted at Universite Laval) , and the upcoming Center of Excellence for Respiratory Pathogens (CERP), hosted at Les Hospices Civils de Lyon’s University Hospital Network.
With funding from the NSERC Alliance Option 2 ($200,000) and an additional $100,000 from Sanofi Global, this initiative will support the training of two PhD students and three Master’s students. These young researchers will play a key role in developing and applying advanced mathematical and statistical models to real-world data.
The team aims to publicize their results by next year, offering new mathematical and statistical models, together with analytical tools, to use relevant data from the pandemic in Canada and demonstrate how human behavioural factors into the spread of a pathogen. The findings will be accessible for public use via tailored dashboards and code packages. This innovative research bridges the gap between mathematics, behavioral science, and public health to improve epidemic preparedness.
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