Sophie Belman, PhD, MSc

The environment (climatic or sociodemographic) shapes the patterns of infectious disease dynamics by, for example, changing the survival of microbes during transmission, altering host behaviors, and shaping which microbial strains or genes cause disease. By building frameworks which incorporate environmental, sociodemographic, epidemiological, and microbial genomic surveillance data we can better anticipate both infectious disease outbreaks - and the particular strains or genes driving them.

Our research aims to understand how the environment shapes evolutionary selection among microbial populations to explain and predict disease burden and dynamics. Understanding these relationships enhances our ability to anticipate how environmental changes (e.g. increasing temperatures, prolonged drought, wildfire smoke) shape microbial populations (e.g. antimicrobial resistance, virulent strains, or genes under selection) and focus our public health strategies on the most vulnerable regions and populations.

Biological, Sociodemographic, and Environmental Data Integration

We are developing frameworks to bring pathogen genomic data to similar space-time scales as environmental and sociodemographic datasets enabling further exploration of their interactions in both epidemiological and bioinformatic frameworks.

Epidemiological Associations

We are interested in understanding how environmental factors together with other human factors shape disease dynamics, especially for infectious diseases for which we have a limited understanding of the climatic sensitivity.

Biological Mechanisms

We are working towards identifying the biological mechanisms by which environmental factors shape microbial evolution, as well as how microbes modify environmental risk. We are developing frameworks to identify signals of evolutionary selection among microbial populations exposed to high levels of air pollution across different climates and human populations.