Research

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. My 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.

Core Research Themes

Epidemiological Associations

I am 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. As part of my Schmidt Science Fellowship I am developing models to identify meteorological and air pollution drivers of invasive pneumococcal disease. In addition, I am also investigating how the interaction between human mobility and climatic factors shapes dengue virus dynamics as part of E4Warning

Biological Mechanisms

I am interested in identifying the biological mechanisms by which environmental factors shape microbial evolution. I am working to identify signals of genomic evolutionary selection in microbial populations exposed to high levels of air pollution or other environmental factors.

Genomic and Environmental Data Integration

I am developing frameworks to bring pathogen genomic data to similar space-time scales as enviornmental and sociodemographic datasets enabling further exploration of their interactions.

Previous Research

Streptococcus pneumoniae Spatiotemporal Dynamics

My doctoral research at the Wellcome Sanger Institute and the University of Cambridge focused on the spatiotemporal dynamics of Streptococcus pneumoniae. Using thousands of genomes combined with human mobility data, I developed methods to quantify pathogen migration and fitness across global scales. This work provided critical insights into how this pathogen evolves and spreads between countries, with results published in Nature (2024) and G3: Genes, Genomes, Genetics (2024). Additionally, I investigated the emergence of multidrug-resistant lineages (The Lancet Microbe, 2022) and reconstructed the evolutionary history of ancient streptococcal groups (Microbial Genomics, 2022).