Image: Gabrielle Beans
Research group We develop mathematical models for studying the spread of infectious diseases. Our focus is on evolutionary models leveraging genome data.
Pathogens evolve as they spread through a host population. Under the right evolutionary and epidemiological conditions, the imprint left behind by evolution on pathogen genomes contains information about the process of disease transmission. We develop mathematical models which describe how these evolutionary histories (phylogenies) are linked to disease transmission dynamics in a population (phylodynamics) and its spread through space (phylogeography).
We primarily work on Bayesian statistical models. Bayesian inference is a powerful way to handle models that operate on many hierarchical levels, a useful way to incorporate many forms of information into a single model, and a convenient means to address uncertainty. As these models can get quite complex and intricate, we also take a strong interest in developing cutting-edge techniques for assessing the reliability and trustworthiness of their outputs.
For more on our research, check out our external website. As our work sits at the nexus of many fields, we take advantage of interdisciplinary communities around Umeå such as MIMS and the IceLab, and across Sweden with DDLS.
