Integrating environmental, clinical, and metadata streams for enhanced viral surveillance

Abstract

The global burden of respiratory viral infection is high, due not only to the severe disease and outbreak potential of specific viruses or viral variants, but also to the great diversity of circulating viruses. Genomic surveillance of these viruses serves many purposes, including: identification of an unknown agent of disease, classification of new variants, interpretation of disease spread during outbreaks, and data generation relevant for therapeutic or vaccine development. Traditionally, genomic surveillance has often been limited to sequencing clinical samples for only a specific pathogen of interest, i.e. single-pathogen approaches. In this dissertation, I demonstrate the relevance of integrating other tools and approaches into surveillance systems, including: wastewater monitoring and surveillance, sequencing of rapid tests, and pan-pathogen sequencing approaches. In Chapter 2, I demonstrate the efficacy of a multifaceted university surveillance program implemented in response to the COVID-19 pandemic during the 2020-2021 academic year. In Chapter 3, I optimize sequencing from SARS- CoV-2 rapid tests and implement this methodology to analyze an isolated outbreak in a senior housing facility in 2022. In Chapter 4, I introduce a new metadata standard for wastewater genomic surveillance projects, developed in 2023 alongside an international cohort of scientists and public health officials. In Chapter 5, I present an unbiased metagenomic sequencing approach and leverage it to simultaneously surveil dozens of viruses circulating in Boston during the 2023-2024 respiratory season. Collectively, these projects advance viral surveillance efforts through demonstrating where non-standard or underutilized tools can have high impact in our understanding of viral disease.