Conceptualizing a Novel Quasi-Continuous Bayesian Phylogeographic Framework for Spatiotemporal Hypothesis Testing

Continuous phylogeography is a growing approach to studying the spatiotemporal origins of RNA viruses because of its realistic spatial reconstruction advantages over discrete phylogeography. While the generalized linear model has been demonstrated as an effective tool for simultaneously assessing the drivers impacting viral diffusion in discrete phylogeography, there is no similar testing method in the continuous phylogeographic framework. In this paper, we take a step toward bridging that gap by conceptualizing a novel quasi-continuous approach which enables the addition of discrete locations beyond the known sampling locations of the virus. Our model, when fully developed into phylogeographic software, will enable spatiotemporal hypothesis testing of viral diffusion without being strictly limited to observed sampling locations. This model can still assess the impact of local epidemiological variables on virus spread and could provide public health agencies with more realistic estimates of key predictors and locations by utilizing a more continuous landscape.