About

Our mission is to inform public health decision-making by developing cutting-edge, quantitative, and robust models to understand, predict, and improve population health outcomes at scale.

Population health modeling

Main projects themes

Across departments and faculties, members of GEM² conduct applied, interdisciplinary research at the intersection of epidemiology and mathematical modeling to address major population health challenges. Our work focuses on surveillance and the transmission dynamics, prevention, and control of infectious diseases—including HIV, human papillomavirus (HPV), and other sexually transmitted and blood-borne infections (STBBIs) such as syphilis, gonorrhea, chlamydia, and hepatitis C—as well as emerging and re-emerging pathogens such as SARS-CoV-2 and highly pathogenic avian influenza. We investigate how public health strategies can be optimized to achieve disease control and elimination goals.

We develop and apply advanced population-level modeling approaches, including transmission-dynamic, decision-analytic, and Bayesian frameworks, to measure burden, evaluate impact, cost-effectiveness, and equity implications of interventions such as vaccination, screening, treatment, and behavioral and structural programs. Our research integrates diverse data sources—from surveillance systems and clinical cohorts to population-based surveys—to generate rigorous, policy-relevant evidence on disease burden, health inequalities, and population impact. A focus of our work is understanding how interventions affect key populations disproportionately impacted by infectious diseases, including sexual and gender minorities, people who use drugs, and other structurally marginalized groups.

The research program spans scales, linking biological and within-host processes to population-level transmission and policy outcomes. By combining methodological innovation with real-world applications, GEM² generates actionable insights to inform public health policy and practice across diverse settings.