Real-time approach to the molecular epidemiology and evolutionary investigation and surveillance of acute viral epidemics.
Genomic analyses have revealed critical insights into the evolution and transmission of infectious agents in recent viral outbreaks, and offered tantalizing examples of the potential value of this approach to future outbreak control efforts. However, the scale and impact of new DNA technologies in these outbreaks has largely been stunted, due to the lack of a systematic and concerted effort. This proposal aims to overcome these challenges by establishing a statistically rigorous analysis framework and information-sharing platform that allows efficiently incorporating viral genomic data as an epidemic unfolds.
For this purpose, we will build on the time-measured phylogenetic methodology in the BEAST framework and adopt state-of-the-art statistical techniques to accommodate a continuous process of data acquisition and inference. We will complement this with advanced Bayesian inference procedures that can be coupled to parallel computation to deal with the computational burden associated with large data sets. Finally we will develop a web-based visualization platform where the outputs of the statistical analyses can be interrogated for epidemiological insights within days of sampling. The data-sharing policy of our system will prioritize public health efforts without jeopardizing scientific publication.
We anticipate that this research will prepare us for the next outbreak and ensure that viral genome sequencing is positioned to have full impact on the public health response.