Unifying the spatial epidemiology and molecular evolution of emerging epidemics

Abstract

We introduce a conceptual bridge between the previously unlinked fields of phylogenetics and mathematical spatial ecology, which enables the spatial parameters of an emerging epidemic to be directly estimated from sampled pathogen genome sequences. By using phylogenetic history to correct for spatial autocorrelation, we illustrate how a fundamental spatial variable, the diffusion coefficient, can be estimated using robust nonparametric statistics, and how heterogeneity in dispersal can be readily quantified. We apply this framework to the spread of the West Nile virus across North America, an important recent instance of spatial invasion by an emerging infectious disease. We demonstrate that the dispersal of West Nile virus is greater and far more variable than previously measured, such that its dissemination was critically determined by rare, long-range movements that are unlikely to be discerned during field observations. Our results indicate that, by ignoring this heterogeneity, previous models of the epidemic have substantially overestimated its basic reproductive number. More generally, our approach demonstrates that easily obtainable genetic data can be used to measure the spatial dynamics of natural populations that are otherwise difficult or costly to quantify.phylogeny | phylogeography | transmission T he explanation of spatial patterns of infectious disease, particularly those of emerging pathogens, has remained a central problem of epidemiology since its inception (1). The existence and nature of traveling waves of infection were first explained in theoretical models (2, 3) and later quantified in empirical studies of rabies and the Black Death (4, 5). These and other studies highlighted the fundamental problem of spatial autocorrelation: observations of infection are statistically dependent due to transmission among proximate individuals, greatly complicating the analysis of spatiotemporal incidence. Consequently, many recent analyses of spatial epidemic behavior use detailed mathematical models of spatial structure to account for autocorrelation (6). Entirely independently, in the field of evolutionary biology there has developed a separate body of work, now termed phylogeography, which focuses on reconstructing past movement events from the genome sequences of sampled organisms (7-10). However, these evolutionary tools typically generate descriptive results that, though informative, remain divorced from epidemiological theory. Crucially neither approach can be considered complete when applied to rapidly evolving viruses, whose spatial, epidemic, and evolutionary dynamics occur on the same timescale (11), necessitating the development of methods that consider all these processes together.Here we introduce a unique approach that integrates the disciplines of spatial epidemiology and phylogenetics. To illustrate the utility of this approach, we show how, from pathogen genomes alone, it can estimate the diffusion coefficient (D) of an epidemic as well as variation in the process of spatial spread. D is...

Fluid Spatial Dynamics of West Nile Virus in the United States: Rapid Spread in a Permissive Host Environment

“…Although we have documented some evidence that phylogenetic structure is shaped by avian flyway, a pattern that has also been observed for avian influenza virus (51), it is difficult to distinguish the impact of avian flyway from other geographic effects on these data. It is also likely that long distance viral movements, rather than simple homogenous dispersal, have impacted the continental spread of WNV (52). Interestingly, the relatively weak geographical clustering observed here is in contrast to the pattern seen for St. Louis encephalitis virus (SLEV), the only other avian arthropod-borne virus known be associated with encephalitis in humans in the United States prior to the emergence of WNV and that was first isolated in 1933 (53,54).…”

Emerging predictable features of replicated biological invasion fronts

“…We confirm that deterministic models can be applied to describe ecological processes and show that additional information on the stochasticity acting at the mesoscopic scale allows us to estimate fluctuations at the macroscopic scale. We believe that our results might have implications for the dynamics of phenomena other than species' invasions, such as morphogenesis (23,47), tumor growth (23,25,36), and the spreading of epidemics (23,30,34,35), which have been traditionally modeled with reaction-diffusion equations.…”

“…Modeling of biological dispersal established the theoretical framework of reaction-diffusion processes (1-3, 23-25), which now finds common application in dispersal ecology (5,14,22,(26)(27)(28)(29)(30) and in other fields (17,23,25,(31)(32)(33)(34)(35)(36). Reaction-diffusion models have also been applied to model human colonization processes (31), such as the Neolithic transition in Europe (25,37,38).…”

Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes

“…It remains unclear whether the risk of TBD propagates locally, generating a rabies disease-like invasion front [11,16] or if TBD risk is driven by long-distance dispersal as occurs for West Nile Virus fever [28]. Although several studies have identified possible ecological correlates of TBD prevalence in humans, including density of infected ticks [29], and correlates of the distribution of infected ticks, including proximity to water bodies [30] and, for babesiosis, prevalence of Lyme disease [31], the ecological factors driving spread of reported TBD at the scale of the northeast United States remain unresolved.…”