Progress and challenges in virus genomic epidemiology.

Genomic epidemiology, which links pathogen genomes with associated metadata to understand disease transmission, has become a key component of outbreak response. Decreasing costs of genome sequencing and increasing computational power provide opportunities to generate and analyse large viral genomic datasets that aim to uncover the spatial scales of transmission, the demographics contributing to transmission patterns, and to forecast epidemic trends. Emerging sources of genomic data and associated metadata provide new opportunities to further unravel transmission patterns. Key challenges include how to integrate genomic data with metadata from multiple sources, how to generate efficient computational algorithms to cope with large datasets, and how to establish sampling frameworks to enable robust conclusions. Genomic epidemiology enables tracking of pathogen transmission over all spatial scales, from local outbreaks to global pandemics, thereby highlighting the scale of interventions required. Combining genomic data with individual-level metadata can identify demographic factors driving transmission patterns. The power of genomic epidemiology is increasing due to better models, methods, and novel technologies, including new sample-collection protocols and metadata. Future integration of virus genomic data may enable forecasting of the spatial spread and ignition/decline of epidemics. [ABSTRACT FROM AUTHOR]