Research Chair
RESEARCH CHAIR
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.
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 forecasting disease trends, assessing the impact of large-scale interventions, and strengthening surveillance systems. Working with partners across disciplines and continents, her team builds data-driven models to better predict outbreaks and inform public health responses.
Dr. Zinszer is also an Assistant Professor in the Department of Social and Preventive Medicine at Université de Montréal and a researcher at the Institut de recherche en santé publique. Her work is grounded in collaboration, rigour, and a deep commitment to advancing equitable health outcomes in a changing world.
Kate Zinszer, PhD
Tier 2 Canada Research Chair in Global Environmental Change and Infectious Diseases
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. Multi-level approaches are often used to consider both individual-level and area-level risk factors such as neighbourhood and broader scale environmental/ climatic risk factors. 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 and poor.
AXIS 2
Identifying the spatio-temporal patterns of infectious diseases and building accurate forecasting models.
Mosquito-borne diseases are thriving and expanding globally despite decades of large-scale control efforts. This axis aims to understand the patterns of infectious disease spread over time and space in order to help inform targeted intervention programs including education campaigns or vector elimination interventions. An accurate disease forecasting method would allow clinical and public health services to proactively plan and implement control and prevention measures. We often work with high resolution disease surveillance data in conjunction with other data sources such as national surveys, censuses, and environmental/climate data. Various statistical methods are used ranging from time series forecasting, machine learning algorithms such as random forests, to Bayesian spatio-temporal regression models.
AXIS 2
Evaluating public health inventions through impact and mixed method evaluations
Improving the evidence for effective interventions for infectious diseases is an urgent priority in endemic and at-risk regions, particularly environmentally sustainable approaches to control. Mixed method evaluations that include impact evaluation and different evaluations such as process, acceptability, and fidelity, provide essential information that is required for scaling up or out an intervention. For impact evaluations, we use secondary data such as cohort or surveillance data to measure the effectiveness of an intervention.