Uncovering the rules of dispersal and the consequences for the distribution, dynamics, and persistence of pathogens and their hosts.

Description: Managing disease risk requires mechanistic understanding of the dynamics and persistence of pathogens and their hosts. Host population dynamics can influence pathogen eco-evolutionary dynamics, but spatial (connectivity, barriers to dispersal) and demographic (colonisation and extinction) processes likely dictate host-pathogen interactions, and hence their emergent dynamics and persistence with far-reaching consequences for livestock or human health.

This project seeks to advance understanding of the links between the distribution, dynamics, and diversity of pathogens, and host dispersal using data from a long-term landscape-scale study of a multi-host model metacommunity. Bartonella infections in rodents are ideal for examining these issues.

Bartonella species, including several associated with human disease, have high genetic diversity and prevalence, and exhibit a wide range of host specificity. In our metacommunity system (Assynt, Northwest Scotland), we study bartonella and two bartonella hosts: the water vole, the primary host and a habitat specialist restricted to 5000) and field voles (n>1500); host-specific Bartonella infection information; and sequencing-based host-specificity of different bartonella genotypes. Integrating data and knowledge from genomics, epidemiology, metacommunity theory, and statistical ecology, the student will develop and apply state-of-the-art molecular and statistical methods to advance ecological and epidemiological theory. The specific aims are to:

1. Infer disease-transmission corridors by reconstructing dispersal routes using host-specific pedigree analysis.

2. Quantify spatiotemporal patterns of Bartonella diversity and persistence using whole-genome-sequencing.

3. Integrate objectives 1&2 to develop spatially-explicit multihost-pathogen metacommunity models to predict emergent transmission and infection landscapes.