Processes Underlying Rabies Virus Incursions across US-Canada Border as Revealed by Whole-Genome Phylogeography.

Disease control programs aim to constrain and reduce the spread of infection. Human disease interventions such as wildlife vaccination play a major role in determining the limits of a pathogen's spatial distribution. Over the past few decades, a raccoon-specific variant of rabies virus (RRV) has invaded large areas of eastern North America. Although expansion into Canada has been largely prevented through vaccination along the US border, several outbreaks have occurred in Canada. Applying phylogeographic approaches to 289 RRV whole-genome sequences derived from isolates collected in Canada and adjacent US states, we examined the processes underlying these outbreaks. RRV incursions were attributable predominantly to systematic virus leakage of local strains across areas along the border where vaccination has been conducted but also to single stochastic events such as long-distance translocations. These results demonstrate the utility of phylogeographic analysis of pathogen genomes for understanding transboundary outbreaks.

The Role of Human Transportation Networks in Mediating the Genetic Structure of Seasonal Influenza in the United States.

Recent studies have demonstrated the importance of accounting for human mobility networks when modeling epidemics in order to accurately predict spatial dynamics. However, little is known about the impact these movement networks have on the genetic structure of pathogen populations and whether these effects are scale-dependent. We investigated how human movement along the aviation and commuter networks contributed to intra-seasonal genetic structure of influenza A epidemics in the continental United States using spatially-referenced hemagglutinin nucleotide sequences collected from 2003-2013 for both the H3N2 and H1N1 subtypes. Comparative analysis of these transportation networks revealed that the commuter network is highly spatially-organized and more heavily traveled than the aviation network, which instead is characterized by high connectivity between all state pairs. We found that genetic distance between sequences often correlated with distance based on interstate commuter network connectivity for the H1N1 subtype, and that this correlation was not as prevalent when geographic distance or aviation network connectivity distance was assessed against genetic distance. However, these patterns were not as apparent for the H3N2 subtype at the scale of the continental United States. Finally, although sequences were spatially referenced at the level of the US state of collection, a community analysis based on county to county commuter connections revealed that commuting communities did not consistently align with state geographic boundaries, emphasizing the need for the greater availability of more specific sequence location data. Our results highlight the importance of utilizing host movement data in characterizing the underlying genetic structure of pathogen populations and demonstrate a need for a greater understanding of the differential effects of host movement networks on pathogen transmission at various spatial scales.

The landscape genetics of infectious disease emergence and spread.

The spread of parasites is inherently a spatial process often embedded in physically complex landscapes. It is therefore not surprising that infectious disease researchers are increasingly taking a landscape genetics perspective to elucidate mechanisms underlying basic ecological processes driving infectious disease dynamics and to understand the linkage between spatially dependent population processes and the geographic distribution of genetic variation within both hosts and parasites. The increasing availability of genetic information on hosts and parasites when coupled to their ecological interactions can lead to insights for predicting patterns of disease emergence, spread and control. Here, we review research progress in this area based on four different motivations for the application of landscape genetics approaches: (i) assessing the spatial organization of genetic variation in parasites as a function of environmental variability, (ii) using host population genetic structure as a means to parameterize ecological dynamics that indirectly influence parasite populations, for example, gene flow and movement pathways across heterogeneous landscapes and the concurrent transport of infectious agents, (iii) elucidating the temporal and spatial scales of disease processes and (iv) reconstructing and understanding infectious disease invasion. Throughout this review, we emphasize that landscape genetic principles are relevant to infection dynamics across a range of scales from within host dynamics to global geographic patterns and that they can also be applied to unconventional 'landscapes' such as heterogeneous contact networks underlying the spread of human and livestock diseases. We conclude by discussing some general considerations and problems for inferring epidemiological processes from genetic data and try to identify possible future directions and applications for this rapidly expanding field.

Rabies virus in raccoons, Ohio, 2004.

In 2004, the raccoon rabies virus variant emerged in Ohio beyond an area where oral rabies vaccine had been distributed to prevent westward spread of this variant. Our genetic investigation indicates that this outbreak may have begun several years before 2004 and may have originated within the vaccination zone.

Wave-like spread of Ebola Zaire.

In the past decade the Zaire strain of Ebola virus (ZEBOV) has emerged repeatedly into human populations in central Africa and caused massive die-offs of gorillas and chimpanzees. We tested the view that emergence events are independent and caused by ZEBOV variants that have been long resident at each locality. Phylogenetic analyses place the earliest known outbreak at Yambuku, Democratic Republic of Congo, very near to the root of the ZEBOV tree, suggesting that viruses causing all other known outbreaks evolved from a Yambuku-like virus after 1976. The tendency for earlier outbreaks to be directly ancestral to later outbreaks suggests that outbreaks are epidemiologically linked and may have occurred at the front of an advancing wave. While the ladder-like phylogenetic structure could also bear the signature of positive selection, our statistical power is too weak to reach a conclusion in this regard. Distances among outbreaks indicate a spread rate of about 50 km per year that remains consistent across spatial scales. Viral evolution is clocklike, and sequences show a high level of small-scale spatial structure. Genetic similarity decays with distance at roughly the same rate at all spatial scales. Our analyses suggest that ZEBOV has recently spread across the region rather than being long persistent at each outbreak locality. Controlling the impact of Ebola on wild apes and human populations may be more feasible than previously recognized.

Predictive spatial dynamics and strategic planning for raccoon rabies emergence in Ohio.

Rabies is an important public health concern in North America because of recent epidemics of a rabies virus variant associated with raccoons. The costs associated with surveillance, diagnostic testing, and post-exposure treatment of humans exposed to rabies have fostered coordinated efforts to control rabies spread by distributing an oral rabies vaccine to wild raccoons. Authorities have tried to contain westward expansion of the epidemic front of raccoon-associated rabies via a vaccine corridor established in counties of eastern Ohio, western Pennsylvania, and West Virginia. Although sporadic cases of rabies have been identified in Ohio since oral rabies vaccine distribution in 1998, the first evidence of a significant breach in this vaccine corridor was not detected until 2004 in Lake County, Ohio. Herein, we forecast the spatial spread of rabies in Ohio from this breach using a stochastic spatial model that was first developed for exploratory data analysis in Connecticut and next used to successfully hind-cast wave-front dynamics of rabies spread across New York. The projections, based on expansion from the Lake County breach, are strongly affected by the spread of rabies by rare, but unpredictable long-distance translocation of rabid raccoons; rabies may traverse central Ohio at a rate 2.5-fold greater than previously analyzed wildlife epidemics. Using prior estimates of the impact of local heterogeneities on wave-front propagation and of the time lag between surveillance-based detection of an initial rabies case to full-blown epidemic, specific regions within the state are identified for vaccine delivery and expanded surveillance effort.

Spatial dynamics and genetics of infectious diseases on heterogeneous landscapes.

Explicit spatial analysis of infectious disease processes recognizes that host-pathogen interactions occur in specific locations at specific times and that often the nature, direction, intensity and outcome of these interactions depend upon the particular location and identity of both host and pathogen. Spatial context and geographical landscape contribute to the probability of initial disease establishment, direction and velocity of disease spread, the genetic organization of resistance and susceptibility, and the design of appropriate control and management strategies. In this paper, we review the manner in which the physical organization of the landscape has been shown to influence the population dynamics and spatial genetic structure of host-pathogen interactions, and how we might incorporate landscape architecture into spatially explicit population models of the infectious disease process to increase our ability to predict patterns of disease occurrence and optimally design vaccination and control policies.

Inferring the population structure and demographic history of the tick, Amblyomma americanum Linnaeus.

A hierarchial population genetic study was conducted on 703 individual Amblyomma americanum from nine populations in Georgia, U.S.A. Populations were sampled from the Coastal Plain, midland Piedmont region, and the upper Piedmont region. Twenty-nine distinct haplotypes were found. A minimum spanning tree was constructed that indicated these haplotypes comprised two lineages, the root of which was distinctly star-like. The majority of the variation found was among ticks within each population, indicating high amounts of gene flow and little genetic differentiation between the three regions. An overall F(ST) value of 0.006 supported the lack of genetic structuring between collection sites in Georgia. Mantel regression analysis revealed no isolation by distance. Signatures of population expansion were detected in the shapes of the mismatch distribution and tests of neutrality. The absence of genetic differentiation combined with the rejection of the null model of isolation by distance may indicate recent range expansion in Georgia or insufficient time to reach an equilibrium where genetic drift may have affected allele frequencies. Alternatively, the high degree of panmixia found within A. americanum in Georgia may be due to bird-mediated dispersal of ticks increasing the genetic similarity between geographically separated populations.

Ecological theory to enhance infectious disease control and public health policy.

Through the work of international public health organizations and advancements in the biological and technological sciences, substantial progress has been made in our ability to prevent, control, locally eliminate, and in one case eradicate infectious diseases. Yet each successful control or local elimination has been met with the emergence of new pathogens, the evolution of novel strains, or different epidemiological circumstances that have limited or reversed control methods. To respond to the increasing threat of emerging infectious diseases and bioterrorism it is vital that we design and implement efficient programs that prevent and control infectious pathogen transmission. The theoretical tools of ecology and epidemiology may be the cornerstone in constructing future programs aimed at preventing and controlling infectious diseases throughout the world.

INTEGRATING PARASITES AND PATHOGENS INTO THE STUDY OF GEOGRAPHIC RANGE LIMITS.

The geographic distributions of all species are limited, and the determining factors that set these limits are of fundamental importance to the fields of ecology and evolutionary biology. Plant and animal ranges have been of primary concern, while those of parasites, which represent much of the Earth's biodiversity, have been neglected. Here, we review the determinants of the geographic ranges of parasites and pathogens, and explore how parasites provide novel systems with which to investigate the ecological and evolutionary processes governing host/parasite spatial distributions. Although there is significant overlap in the causative factors that determine range borders of parasites and free-living species, parasite distributions are additionally constrained by the geographic range and ecology of the host species' population, as well as by evolutionary factors that promote host-parasite coevolution. Recently, parasites have been used to infer population demographic and ecological information about their host organisms and we conclude that this strategy can be further exploited to understand geographic range limitations of both host and parasite populations.

A priori prediction of disease invasion dynamics in a novel environment.

Directly transmitted infectious diseases spread through wildlife populations as travelling waves away from the sites of original introduction. These waves often become distorted through their interaction with environmental and population heterogeneities and by long-distance translocation of infected individuals. Accurate a priori predictions of travelling waves of infection depend upon understanding and quantifying these distorting factors. We assess the effects of anisotropies arising from the orientation of rivers in relation to the direction of disease-front propagation and the damming effect of mountains on disease movement in natural populations. The model successfully predicts the local and large-scale prevaccination spread of raccoon rabies through New York State, based on a previous spatially heterogeneous model of raccoon-rabies invasion across the state of Connecticut. Use of this model provides a rare example of a priori prediction of an epidemic invasion over a naturally heterogeneous landscape. Model predictions matched to data can also be used to evaluate the most likely points of disease introduction. These results have general implications for predicting future pathogen invasions and evaluating potential containment strategies.

Effects of recent experience on foraging decisions by bumble bees.

The temporal and spatial scales employed by foraging bees in sampling their environment and making foraging decisions should depend both on the limits of bumble bee memory and on the spatial and temporal pattern of rewards in the habitat. We analyzed data from previous experiments to determine how recent foraging experience by bumble bees affects their flight distances to subsequent flowers. A single visit to a flower as sufficient to affect the flight distance to the next flower. However, longer sequences of two or three visits had an additional effect on the subsequent flight distance of individual foragers. This suggests that bumble bees can integrate information from at least three flowers for making a subsequent foraging decision. The existence of memory for floral characteristics at least at this scale may have significance for floral selection in natural environments.

Habitat structure and animal movement: the behaviour of bumble bees in uniform and random spatial resource distributions.

Foraging organisms (like bumble bees) move between resource points (like flowers) whose natural distributions vary enormously: from hyperdispersed to random to clumped. These differences in habitat structure may significantly influence the fitness of both plant and pollinator. To examine the effect of habitat structure on pollinator movement and fitness, we observed captive worker bumble bees collecting nectar from artificial flowers containing equal volumes of reward and arranged in two spatial configurations: a hexagonal array with constant distances between flowers ("constant"), and an "exploded hexagonal" array, with variable distances between flowers ("variable"). The mean nearest-neighbour distance was the same in both arrays, as was the general hexagonal appearance. The experiment therefore compares how resource dispersion, independent of nearest-neighbour distance, influences bee behaviour. Bees in the variable array showed decreased directionality, higher revisitation frequencies, and greater inter-flower flight distances than shown in the constant array. As a consequence, bees in the variable array had a 19% lower gross rate of nectar collection. Our results suggest that wild-foraging bees should prefer regularly spaced flowers (when all else, including mean nearest-neighbour distance, is equal), and that plants can decrease self-pollination by regular spacing between flowers, inflorescences, or individuals.

Molecular evolutionary signatures reveal the role of host ecological dynamics in viral disease emergence and spread.

RNA viruses account for numerous emerging and perennial infectious diseases, and are characterized by rapid rates of molecular evolution. The ecological dynamics of most emerging RNA viruses are still poorly understood and difficult to ascertain. The availability of genome sequence data for many RNA viruses, in principle, could be used to infer ecological dynamics if changes in population numbers produced a lasting signature within the pattern of genome evolution. As a result, the rapidly emerging phylogeographic structure of a pathogen, shaped by the rise and fall in the number of infections and their spatial distribution, could be used as a surrogate for direct ecological assessments. Based on rabies virus as our example, we use a model combining ecological and evolutionary processes to test whether variation in the rate of host movement results in predictive diagnostic patterns of pathogen genetic structure. We identify several linearizable relationships between host dispersal rate and measures of phylogenetic structure suggesting genetic information can be used to directly infer ecological process. We also find phylogenetic structure may be more revealing than demography for certain ecological processes. Our approach extends the reach of current analytic frameworks for infectious disease dynamics by linking phylogeography back to underlying ecological processes.

Structuring targeted surveillance for monitoring disease emergence by mapping observational data onto ecological process.

An efficient surveillance system is a crucial factor in identifying, monitoring and tackling outbreaks of infectious diseases. Scarcity of data and limited amounts of economic resources require a targeted effort from public health authorities. In this paper, we propose a mathematical method to identify areas where surveillance is critical and low reporting rates might leave epidemics undetected. Our approach combines the use of reference-based susceptible-exposed-infectious models and observed reporting data; We propose two different specifications, for constant and time-varying surveillance, respectively. Our case study is centred around the spread of the raccoon rabies epidemic in the state of New York, using data collected between 1990 and 2007. Both methods offer a feasible solution to analyse and identify areas of intervention.

Mathematical models for rabies.

Rabies virus and its associated host-pathogen population dynamics have proven a remarkable model system for developing mathematical models of infectious disease emergence and spread. Beginning with simple susceptible-infectious-removed (SIR) compartment models of fox rabies emergence and spread across Western Europe, mathematical models have now been developed to incorporate dynamics across heterogeneous landscapes, host demographic variation, and environmental stochasticity. Model structures range from systems of ordinary differential equations (ODEs) to stochastic agent-based computational simulations. We have reviewed the variety of mathematical approaches now available for analyzing dynamics in different host populations; most notably rabies virus spread in raccoon hosts.

Molecular phylogenetics of the lyssaviruses--insights from a coalescent approach.

Technical improvements over the past 2 decades have enormously facilitated the generation of nucleotide sequence data for lyssavirus collections. These databases are amenable to methods of phylogenetic analysis, which attempt to define the taxonomic structure of this genus and predict the evolutionary relationships of current circulating strains. Coupled with a range of mathematical tools to explore the appropriateness of nucleotide substitution models and test for positive selection, the evolutionary process is being explored in detail. Despite the potential for high viral mutation levels, the operation of purifying selection appears to effectively constrain lyssavirus evolution. The recent development of coalescent theory has provided additional approaches to data analysis whereby the time frame of emergence of viral lineages can be most reliably estimated. Such studies suggest that all currently circulating rabies viruses have emerged within the past 1500 years. Moreover, through the capability of analyzing viral population dynamics and determining patterns of population size variation, coalescent approaches can provide insight into the demographics of viral outbreaks. Whereas human-assisted movement of reservoir host species has clearly facilitated transfer of rabies between continents, topographical landscape features significantly influence the rate and extent of contiguous disease spread. Together with empirical studies on virus diversity, the application of coalescent approaches will help to better understand lyssavirus emergence, evolution, and spread. In particular, such methods are presently facilitating exploration of the factors operating to limit the ability of lyssaviruses to establish new persistent virus-host associations and ultimately control the emergence of new species of this genus.

Strong seasonality produces spatial asynchrony in the outbreak of infectious diseases.

Models for infectious diseases usually assume a fixed demographic structure. Yet, a disease can spread over a region encountering different local demographic variations that may significantly alter local dynamics. Spatial heterogeneity in the resulting dynamics can lead to important differences in the design of surveillance and control strategies. We illustrate this by exploring the north-south gradient in the seasonal demography of raccoon rabies over the eastern USA. We find that the greater variance in the timing of spring births characteristic of southern populations can lead to the spatial synchronization of southern epidemics, while the narrow birth-pulse associated with northern populations can lead to an irregular patchwork of epidemics. These results indicate that surveillance in the southern states can be reduced relative to northern locations without loss of detection ability. This approach could yield significant savings in vaccination programmes. The importance of seasonality in many widely distributed diseases indicates that our findings will find applications beyond raccoon rabies.

Optimal control of a rabies epidemic model with a birth pulse.

A system of ordinary differential equations describes the population dynamics of a rabies epidemic in raccoons. The model accounts for the dynamics of a vaccine, including loss of vaccine due to animal consumption and loss from factors other than racoon uptake. A control method to reduce the spread of disease is introduced through temporal distribution of vaccine packets. This work incorporates the effect of the seasonal birth pulse in the racoon population and the attendant increase in new-borns which are susceptible to the diseases, analysing the impact of the timing and length of this pulse on the optimal distribution of vaccine packets. The optimization criterion is to minimize the number of infected raccoons while minimizing the cost of distributing the vaccine. Using an optimal control setting, numerical results illustrate strategies for distributing the vaccine depending on the timing of the infection outbreak with respect to the birth pulse.