Research
Chair
Tier 2 Canada Research Chair in Global Environmental Change and Infectious Diseases
Kate Zinszer, PhD
In October 2024, Dr. Kate Zinszer was named Tier 2 Canada Research Chair in Global Environmental Change and Infectious Diseases, a prestigious appointment supported by the Canadian Institutes of Health Research. She is also an Associate Professor in the School of Public Health at Université de Montréal and a researcher at the Centre de recherche en santé publique.
Her work sits at the intersection of epidemiology, public health, informatics, and climate science. As global temperatures rise, mosquito-borne illnesses like dengue, West Nile virus, and malaria are appearing in new regions — including parts of Canada. Dr. Zinszer’s research aims to close critical knowledge gaps in the spread of these diseases and to improve prevention strategies at local and global scales.
Through her leadership, the chair focuses on understanding the epidemiology of emerging and epidemic infectious diseases, identifying and forecasting disease trends, and assessing the impact of large-scale interventions. Working with partners across disciplines and continents, her team builds data-driven models to better predict outbreaks and inform public health responses. Her work is grounded in collaboration, rigour, and a deep commitment to advancing equitable health outcomes in a changing world.
RESEARCH AXES AND OBJECTIVES
The Global Environmental Change and Infectious Diseases Chair is organized in three research themes (axes).
AXIS 1
Understanding the epidemiology of emerging and epidemic infectious diseases.
This axis involves designing and conducting primary research through cohort or case control studies and analyzing secondary data sources such as surveillance and clinical data to better understand the epidemiological profile of certain emerging and epidemic infectious diseases. An important part of this research is to understand the significant drivers of disease at the population level and to identify vulnerable communities, which are often marginalized.
Identifying the spatio-temporal patterns of infectious diseases and building accurate forecasting models.
AXIS 2
This axis aims to understand the patterns of infectious disease spread over time and space in order to help inform targeted intervention programs. We often work with high resolution disease surveillance data in conjunction with other data sources such as national surveys, censuses, and remote sensing data. Various statistical methods are used ranging from time series forecasting, machine learning algorithms, to Bayesian spatio-temporal models.
AXIS 3
Evaluating public health inventions through impact and mixed method evaluations.
This axis involves conducting experimental and quasi-experimental studies, often using mixed-methods designs to evaluate the effectiveness of different public health interventions. We often conducted mixed method evaluations that include impact evaluations and different evaluations such as process, acceptability, and fidelity, providing essential information needed for scaling up or out an intervention.