Genomic epidemiology on the frontline: Inferring disease dynamics from pathogen genomes and supporting genomic analysis in applied public health settings.

Abstract

Within infectious disease epidemiology, genomic epidemiology is a field that seeks to describe pathogen transmission dynamics using evolutionary analysis of pathogen genome sequences and associated metadata. Genomic data have a wealth of information; we can use them to group related cases of disease, detect cryptic disease transmission, differentiate source and sink populations, and describe how introductions and sustained transmission contribute to an epidemic. In this dissertation I describe two genomic epidemiological studies of Zika virus, one in Colombia and the other in the United States Virgin Islands. I describe how each country's outbreak was shaped by regional seeding events and endemic transmission after introduction. These studies indicate differences in introduction frequency between the two countries, possibly related to the timing of their outbreaks and the number of other countries having concurrent outbreaks. In the last chapter, I describe recommendations for supporting open pathogen genomic analysis in public health agencies. These recommendations were developed from long-form interviews with public health agencies, and are designed to facilitate the development of genomic epidemiology outside of academia. Taken together, this body of work describes the application of genomic epidemiologic techniques and demonstrates possible strategies for operationalizing genomic surveillance.