Infecting epidemiology with genetics: a new frontier in disease ecology Elizabeth A. Archie 1, 2 , Gordon Luikart 1, 3 and Vanessa O. Ezenwa 1 1 Division of Biological Sciences, University of Montana, Missoula, MT 59812, USA 2 Current address: Biology Department, Fordham University, 441 E. Fordham Road, Bronx, NY 10458, USA 3 Centro de Investigacao em Biodiversidade e Recursos Geneticos, University of Portugal, Vaira˜ o 4485-661, Portugal Disease ecologists strive to understand the causes and consequences of parasite infection, including the emer- gence, spread, persistence and evolution of infectious disease. These processes can be illuminated by parasite genetic markers, which can be used to track parasite spread and infer population history. Recently, a growing number of studies have used molecular tools to examine questions on the ecology of infectious diseases. We review this burgeoning area of research by focusing on three topics where genetic tools will increasingly make major contributions: inferring parasite trans- mission, reconstructing epidemiological history and identifying physical and environmental drivers of dis- ease spread. We also discuss areas for future research and highlight the promise of multidisciplinary collabor- ations among geneticists, ecologists and epidemiolo- gists. The value of genetics to disease ecology Molecular and computational tools from population genetics and phylogenetics hold enormous promise for disease ecology. This is in part because the research pro- blems that concern phylogeneticists and population geneti- cists—for example, using molecular genetic data to infer population history, understand migration and gene flow and predict evolutionary dynamics—are analogous to pro- cesses necessary to understand the ecology and evolution of parasites. Specifically, molecular approaches enhance research in disease ecology because they enable the re- construction of evolutionary relationships between para- sites on a wide range of spatial scales—ranging from within individual hosts to between geographic locations. This fundamental feature improves our ability to track parasite movements, identify parasite origins and under- stand environmental factors influencing their spread. At a minimum, molecular tools complement and corroborate traditional, epidemiological approaches; at best, these tools greatly improve the resolution of epidemiological methods and allow researchers to address new questions that would be difficult or impossible using traditional epidemiological tools alone. Although researchers have been applying molecular markers to parasite populations for well over a decade (e.g. [1–4]), in the last few years, new statistical methods [5–9] and increasing collaboration between disease ecolo- gists and population geneticists [10–14] have greatly Review Glossary Assignment test: a statistical test of the hypothesis that the multilocus genotype of an individual arose in a particular population. Sometimes refers to methods that cluster individuals into groups that are genetically related or randomly mating (see Table 2). Basic reproductive number (R 0 ): the average number of secondary infections derived from a single infection in an entirely susceptible population. The value of R 0 determines whether a parasite can invade a host population and how fast it spreads upon invasion. Bayesian: a framework of statistical inference that begins with prior distribu- tions for model parameters and updates these based on observed data to arrive at a posterior probability distribution. Coalescent: a theory that describes the genealogy of chromosomes or genes. Relevant to parasites, this theory describes the shape of a gene genealogy (i.e. the statistical distribution of its branch lengths) under different demographic histories (e.g. exponential growth, stasis or population bottlenecks) in order to date a most recent common ancestor or infer population growth rates (see also Box 1). Disease ecology: the study of interactions between parasites and their hosts, including parasite transmission dynamics; factors underlying patterns of variation in infection; parasite effects on host behavior, population dynamics and community structure; and coevolutionary relationships between hosts and parasites. Effective population size: the size of an ideal population (as defined by population genetics; a stable population with random mating, random variation in reproductive success, equal sex ratio, and nonoverlapping generations) that would experience the same rate of genetic change through genetic drift as the observed population. Epidemiological history: important events and processes occurring in parasite population dynamics, especially the timing of disease outbreaks, and the rate and timing of the parasite population growth rate over the course of one or more epidemics. Gene flow: the movement of genetic material from one population to another, also referred to as migration. Landscape ecology: the study of interactions between spatial patterns and ecological processes, and the spatial extent and configuration of ecological processes. A focus is on understanding the relationship between spatial heterogeneity (anthropogenic-induced and natural) and ecological processes. Landscape epidemiology: assesses the influence of landscape features, environmental variables and spatial heterogeneity on disease spread. Often combines temporal data, spatial data and modeling to predict patterns of disease transmission. Landscape genetics: the use of molecular tools to study how landscape features and environmental variables influence (i) gene flow and the move- ment of organisms, and (ii) the spatial distribution of genetic diversity at both neutral and functional genetic loci. Landscape genetics is similar to phylogeo- graphy (a combination of phylogenetics and biogeography), but is especially useful at finer spatial scales (e.g. when individual hosts or parasites are the unit of study), and for macroparasites, because many of the analytical methods can accommodate multilocus genotypes and nonequilibrium population genetic assumptions. Least-cost modeling: a statistical modeling approach that uses raster-based data inputs to measure the effective distance and connectivity between habitat patches or other geographic areas. Migration: the movement of individuals from one genetically distinct popula- tion to another, resulting in gene flow. Migration rate is computed as the probability that a randomly chosen individual (or allele) in each population is a migrant. Multilocus genotype: the combination of the genotypes at each of multiple genetic loci in an individual. Common genetic markers that are used to construct multilocus genotypes include microsatellites and single-nucleotide Corresponding author: Archie, E.A. (earchie@fordham.edu). 0169-5347/$ – see front matter ß 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.tree.2008.08.008 Available online 21 November 2008 21