Evolution of Virulence in Emerging Epidemics

Theory predicts that selection for pathogen virulence and horizontal transmission is highest at the onset of an epidemic but decreases thereafter, as the epidemic depletes the pool of susceptible hosts. We tested this prediction by tracking the competition between the latent bacteriophage λ and its virulent mutant λcI857 throughout experimental epidemics taking place in continuous cultures of Escherichia coli. As expected, the virulent λcI857 is strongly favored in the early stage of the epidemic, but loses competition with the latent virus as prevalence increases. We show that the observed transient selection for virulence and horizontal transmission can be fully explained within the framework of evolutionary epidemiology theory. This experimental validation of our predictions is a key step towards a predictive theory for the evolution of virulence in emerging infectious diseases.     

Landscape epidemiology and control of pathogens with cryptic and long-distance dispersal: sudden oak death in northern Californian forests

Exotic pathogens and pests threaten ecosystem service, biodiversity, and crop security globally. If an invasive agent can disperse asymptomatically over long distances, multiple spatial and temporal scales interplay, making identification of effective strategies to regulate, monitor, and control disease extremely difficult. The management of outbreaks is also challenged by limited data on the actual area infested and the dynamics of spatial spread, due to financial, technological, or social constraints. We examine principles of landscape epidemiology important in designing policy to prevent or slow invasion by such organisms, and use Phytophthora ramorum, the cause of sudden oak death, to illustrate how shortfalls in their understanding can render management applications inappropriate. This pathogen has invaded forests in coastal California, USA, and an isolated but fast-growing epidemic focus in northern California (Humboldt County) has the potential for extensive spread. The risk of spread is enhanced by the pathogen's generalist nature and survival. Additionally, the extent of cryptic infection is unknown due to limited surveying resources and access to private land. Here, we use an epidemiological model for transmission in heterogeneous landscapes and Bayesian Markov-chain-Monte-Carlo inference to estimate dispersal and life-cycle parameters of P. ramorum and forecast the distribution of infection and speed of the epidemic front in Humboldt County. We assess the viability of management options for containing the pathogen's northern spread and local impacts. Implementing a stand-alone host-free "barrier" had limited efficacy due to long-distance dispersal, but combining curative with preventive treatments ahead of the front reduced local damage and contained spread. While the large size of this focus makes effective control expensive, early synchronous treatment in newly-identified disease foci should be more cost-effective. We show how the successful management of forest ecosystems depends on estimating the spatial scales of invasion and treatment of pathogens and pests with cryptic long-distance dispersal.     

Do pathogens become more virulent as they spread? Evidence from the amphibian declines in Central America

The virulence of a pathogen can vary strongly through time. While cyclical variation in virulence is regularly observed, directional shifts in virulence are less commonly observed and are typically associated with decreasing virulence of biological control agents through coevolution. It is increasingly appreciated, however, that spatial effects can lead to evolutionary trajectories that differ from standard expectations. One such possibility is that, as a pathogen spreads through a naive host population, its virulence increases on the invasion front. In Central America, there is compelling evidence for the recent spread of pathogenic Batrachochytrium dendrobatidis (Bd) and for its strong impact on amphibian populations. Here, we re-examine data on Bd prevalence and amphibian population decline across 13 sites from southern Mexico through Central America, and show that, in the initial phases of the Bd invasion, amphibian population decline lagged approximately 9 years behind the arrival of the pathogen, but that this lag diminished markedly over time. In total, our analysis suggests an increase in Bd virulence as it spread southwards, a pattern consistent with rapid evolution of increased virulence on Bd''s invading front. The impact of Bd on amphibians might therefore be driven by rapid evolution in addition to more proximate environmental drivers.     

Spatial Structure,Transmission Modes and the Evolution of Viral Exploitation Strategies

Spatial structure and local migration are predicted to promote the evolution of less aggressive host exploitation strategies in horizontally transmitted pathogens. Here we explore the effect of spatial structure on the evolution of pathogens that can use both horizontal and vertical routes of transmission. First, we analyse theoretically how vertical transmission can alter evolutionary trajectories and confirm that space can impede the spread of virulent pathogens. Second, we test this prediction using the latent phage λ which transmits horizontally and vertically in Escherichia coli populations. We show that the latent phage λ wins competition against the virulent mutant λcI857 in spatially structured epidemics, but loses when spatial structure is eroded. The vertical transmission of phage λ immunizes its local host pool against superinfection and prevents the spread of the virulent λcI857. This effect breaks down when mixing facilitates horizontal transmission to uninfected hosts. We thus confirm the importance of spatial structure for the evolutionary maintenance of prudent infection strategies in latent viruses.     

Aerial Dispersal and Multiple-Scale Spread of Epidemic Disease

Disease spread has traditionally been described as a traveling wave of constant velocity. However, aerially dispersed pathogens capable of long-distance dispersal often have dispersal gradients with extended tails that could result in acceleration of the epidemic front. We evaluated empirical data with a simple model of disease spread that incorporates logistic growth in time with an inverse power function for dispersal. The scale invariance of the power law dispersal function implies its applicability at any spatial scale; indeed, the model successfully described epidemics ranging over six orders of magnitude, from experimental field plots to continental-scale epidemics of both plant and animal diseases. The distance traveled by epidemic fronts approximately doubled per unit time, velocity increased linearly with distance (slope ~½), and the exponent of the inverse power law was approximately 2. We found that it also may be possible to scale epidemics to account for initial outbreak focus size and the frequency of susceptible hosts. These relationships improve understanding of the geographic spread of emerging diseases, and facilitate the development of methods for predicting and preventing epidemics of plants, animals, and humans caused by pathogens that are capable of long-distance dispersal.     

Decelerating spread of West Nile virus by percolation in a heterogeneous urban landscape

Vector-borne diseases are emerging and re-emerging in urban environments throughout the world, presenting an increasing challenge to human health and a major obstacle to development. Currently, more than half of the global population is concentrated in urban environments, which are highly heterogeneous in the extent, degree, and distribution of environmental modifications. Because the prevalence of vector-borne pathogens is so closely coupled to the ecologies of vector and host species, this heterogeneity has the potential to significantly alter the dynamical systems through which pathogens propagate, and also thereby affect the epidemiological patterns of disease at multiple spatial scales. One such pattern is the speed of spread. Whereas standard models hold that pathogens spread as waves with constant or increasing speed, we hypothesized that heterogeneity in urban environments would cause decelerating travelling waves in incipient epidemics. To test this hypothesis, we analysed data on the spread of West Nile virus (WNV) in New York City (NYC), the 1999 epicentre of the North American pandemic, during annual epizootics from 2000-2008. These data show evidence of deceleration in all years studied, consistent with our hypothesis. To further explain these patterns, we developed a spatial model for vector-borne disease transmission in a heterogeneous environment. An emergent property of this model is that deceleration occurs only in the vicinity of a critical point. Geostatistical analysis suggests that NYC may be on the edge of this criticality. Together, these analyses provide the first evidence for the endogenous generation of decelerating travelling waves in an emerging infectious disease. Since the reported deceleration results from the heterogeneity of the environment through which the pathogen percolates, our findings suggest that targeting control at key sites could efficiently prevent pathogen spread to remote susceptible areas or even halt epidemics.     

The influence of host demography, pathogen virulence, and relationships with pathogen virulence on the evolution of pathogen transmission in a spatial context

A major challenge in evolutionary ecology is to explain extensive natural variation in transmission rates and virulence across pathogens. Host and pathogen ecology is a potentially important source of that variation. Theory of its effects has been developed through the study of non-spatial models, but host population spatial structure has been shown to influence evolutionary outcomes. To date, the effects of basic host and pathogen demography on pathogen evolution have not been thoroughly explored in a spatial context. Here we use simulations to show that space produces novel predictions of the influence of the shape of the pathogen’s transmission–virulence tradeoff, as well as host reproduction and mortality, on the pathogen’s evolutionary stable transmission rate. Importantly, non-spatial models predict that neither the slope of linear transmission–virulence relationships, nor the host reproduction rate will influence pathogen evolution, and that host mortality will only influence it when there is a transmission–virulence tradeoff. We show that this is not the case in a spatial context, and identify the ecological conditions under which spatial effects are most influential. Thus, these results may help explain observed natural variation among pathogens unexplainable by non-spatial models, and provide guidance about when space should be considered. We additionally evaluate the ability of existing analytical approaches to predict the influence of ecology, namely spatial moment equations closed with an improved pair approximation (IPA). The IPA is known to have limited accuracy, but here we show that in the context of pathogens the limitations are substantial: in many cases, IPA incorrectly predicts evolution to pathogen-driven extinction. Despite these limitations, we suggest that the impact of ecology can still be understood within the conceptual framework arising from spatial moment equations, that of “self-shading’’, whereby the spread of highly transmissible pathogens is impeded by local depletion of susceptible hosts.     

Confocal microscopy reveals in planta dynamic interactions between pathogenic,avirulent and non‐pathogenic Pseudomonas syringae strains

Recent advances in genomics and single‐cell analysis have demonstrated the extraordinary complexity reached by microbial populations within their hosts. Communities range from complex multispecies groups to homogeneous populations differentiating into lineages through genetic or non‐genetic mechanisms. Diversity within bacterial populations is recognized as a key driver of the evolution of animal pathogens. In plants, however, little is known about how interactions between different pathogenic and non‐pathogenic variants within the host impact on defence responses, or how the presence within a mixture may affect the development or the fate of each variant. Using confocal fluorescence microscopy, we analysed the colonization of the plant apoplast by individual virulence variants of Pseudomonas syringae within mixed populations. We found that non‐pathogenic variants can proliferate and even spread beyond the inoculated area to neighbouring tissues when in close proximity to pathogenic bacteria. The high bacterial concentrations reached at natural entry points promote such interactions during the infection process. We also found that a diversity of interactions take place at a cellular level between virulent and avirulent variants, ranging from dominant negative effects on proliferation of virulent bacteria to in trans suppression of defences triggered by avirulent bacteria. Our results illustrate the spatial dynamics and complexity of the interactions found within mixed infections, and their potential impact on pathogen evolution.     

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

Although heterogeneity in contact rate, physiology, and behavioral response to infection have all been empirically demonstrated in host–pathogen systems, little is known about how interactions between individual variation in behavior and physiology scale‐up to affect pathogen transmission at a population level. The objective of this study is to evaluate how covariation between the behavioral and physiological components of transmission might affect epidemic outcomes in host populations. We tested the consequences of contact rate covarying with susceptibility, infectiousness, and infection status using an individual‐based, dynamic network model where individuals initiate and terminate contacts with conspecifics based on their behavioral predispositions and their infection status. Our results suggest that both heterogeneity in physiology and subsequent covariation of physiology with contact rate could powerfully influence epidemic dynamics. Overall, we found that 1) individual variability in susceptibility and infectiousness can reduce the expected maximum prevalence and increase epidemic variability; 2) when contact rate and susceptibility or infectiousness negatively covary, it takes substantially longer for epidemics to spread throughout the population, and rates of epidemic spread remained suppressed even for highly transmissible pathogens; and 3) reductions in contact rate resulting from infection‐induced behavioral changes can prevent the pathogen from reaching most of the population. These effects were strongest for theoretical pathogens with lower transmissibility and for populations where the observed variation in contact rate was higher, suggesting that such heterogeneity may be most important for less infectious, more chronic diseases in wildlife. Understanding when and how variability in pathogen transmission should be modelled is a crucial next step for disease ecology.     

Virulence and community dynamics of fungal species with vertical and horizontal transmission on a plant with multiple infections

The virulence evolution of multiple infections of parasites from the same species has been modeled widely in evolution theory. However, experimental studies on this topic remain scarce, particularly regarding multiple infections by different parasite species. Here, we characterized the virulence and community dynamics of fungal pathogens on the invasive plant Ageratina adenophora to verify the predictions made by the model. We observed that A. adenophora was highly susceptible to diverse foliar pathogens with mixed vertical and horizontal transmission within leaf spots. The transmission mode mainly determined the pathogen community structure at the leaf spot level. Over time, the pathogen community within a leaf spot showed decreased Shannon diversity; moreover, the vertically transmitted pathogens exhibited decreased virulence to the host A. adenophora, but the horizontally transmitted pathogens exhibited increased virulence to the host. Our results demonstrate that the predictions of classical models for the virulence evolution of multiple infections are still valid in a complex realistic environment and highlight the impact of transmission mode on disease epidemics of foliar fungal pathogens. We also propose that seedborne fungi play an important role in structuring the foliar pathogen community from multiple infections within a leaf spot.     

Spatial pattern switching enables cyclic evolution in spatial epidemics

Infectious diseases often spread as spatial epidemic outbreak waves. A number of model studies have shown that such spatial pattern formation can have important consequences for the evolution of pathogens. Here, we show that such spatial patterns can cause cyclic evolutionary dynamics in selection for the length of the infectious period. The necessary reversal in the direction of selection is enabled by a qualitative change in the spatial pattern from epidemic waves to irregular local outbreaks. The spatial patterns are an emergent property of the epidemic system, and they are robust against changes in specific model assumptions. Our results indicate that emergent spatial patterns can act as a rich source for complexity in pathogen evolution.     

On the spatial spread of rabies among foxes

We present a simple model for the spatial spread of rabies among foxes and use it to quantify its progress in England if rabies were introduced. The model is based on the known ecology of fox behaviour and on the assumption that the main vector for the spread of the disease is the rabid fox. Known data and facts are used to determine real parameter values involved in the model. We calculate the speed of propagation of the epizootic front, the threshold for the existence of an epidemic, the period and distance apart of the subsequent cyclical epidemics which follow the main front, and finally we quantify a means for control of the spatial spread of the disease. By way of illustration we use the model to determine the progress of rabies up through the southern part of England if it were introduced near Southampton. Estimates for the current fox density in England were used in the simulations. These suggest that the disease would reach Manchester within about 3.5 years, moving at speeds as high as 100 km per year in the central region. The model further indicates that although it might seem that the disease had disappeared after the wave had passed it would reappear in the south of England after just over 6 years and at periodic times after that. We consider the possibility of stopping the spread of the disease by creating a rabies 'break' ahead of the front through vaccination to reduce the population to a level below the threshold for an epidemic to exist. Based on parameter values relevant to England, we estimate its minimum width to be about 15 km. The model suggests that vaccination has considerable advantages over severe culling.     

Virulence evolution in emerging infectious diseases

Models of virulence evolution generally consider the outcome of competition between resident and mutant parasite strains at or near endemic equilibrium. Less studied is what happens during the initial phases of invasion and adaptation. Understanding initial adaptive dynamics is particularly important in the context of emerging diseases in wildlife and humans, for which rapid and accurate intervention may be of the essence. To address the question of virulence evolution in emerging diseases, we employ a simple stochastic modeling framework. As is intuitive, the pathogen strains most likely to emerge are those with the highest net reproductive rates (R0). We find, however, that stochastic events shape the properties of emerging pathogens in sometimes unexpected ways. First, the mean virulence of emerging pathogens is expected to be larger in dense host populations and/or when transmission is high, due to less restrictive conditions for the spread of the pathogen. Second, a positive correlation between average virulence and transmissibility emerges due to a combination of drift and selection. We conclude that at least in the initial phases of adaptation, special assumptions about constraints need not be invoked to explain some virulence-transmission correlations and that virulence management practices should consider how residual variation in transmission and virulence can be selected to reduce the prevalence and/or virulence of emerging infectious diseases.     

Environmental variation enables invasions of environmental opportunist pathogens

Emerging infectious diseases are a persistent threat to humans and food production but the mechanisms promoting the emergence of novel pathogens are not fully understood. The widely discussed explanations for pathogen emergence include range shifts, coincidental evolution of virulence, and host immunity variation. Here we propose a novel mechanism of virulence evolution that relies on environmental variability. Our model combines an environmental community experiencing random or periodic variability, to a classical SIR epidemiological model. We assume that environmentally growing, potentially infective variants arise at low frequency from a resident, non‐infective (benign microbial) strain through random variation on genetic material. We found that environmental perturbations commonly promote establishment of sporadic infections or persistent epidemics, by creating transient periods of low competition, which can in turn be exploited by an infective strain. Given the ubiquitous nature of potentially pathogenic environmental micro‐organisms and environmental variability, this mechanism provides a plausible explanation for emerging diseases.     

Integrating life history and cross-immunity into the evolutionary dynamics of pathogens

Models for the diversity and evolution of pathogens have branched into two main directions: the adaptive dynamics of quantitative life-history traits (notably virulence) and the maintenance and invasion of multiple, antigenically diverse strains that interact with the host's immune memory. In a first attempt to reconcile these two approaches, we developed a simple modelling framework where two strains of pathogens, defined by a pair of life-history traits (infectious period and infectivity), interfere through a given level of cross-immunity. We used whooping cough as a potential example, but the framework proposed here could be applied to other acute infectious diseases. Specifically, we analysed the effects of these parameters on the invasion dynamics of one strain into a population, where the second strain is endemic. Whereas the deterministic version of the model converges towards stable coexistence of the two strains in most cases, stochastic simulations showed that transient epidemic dynamics can cause the extinction of either strain. Thus ecological dynamics, modulated by the immune parameters, eventually determine the adaptive value of different pathogen genotypes. We advocate an integrative view of pathogen dynamics at the crossroads of immunology, epidemiology and evolution, as a way towards efficient control of infectious diseases.     

Rates of spread of marine pathogens

Epidemics of marine pathogens can spread at extremely rapid rates. For example, herpes virus spread through pilchard populations in Australia at a rate in excess of 10 000 km year^?1, and morbillivirus infections in seals and dolphins have spread at more than 3000 km year^?1. In terrestrial environments, only the epidemics of myxomatosis and calicivirus in Australian rabbits and West Nile Virus in birds in North America have rates of spread in excess of 1000 km year^?1. The rapid rates of spread of these epidemics has been attributed to flying insect vectors, but flying vectors have not been proposed for any marine pathogen. The most likely explanation for the relatively rapid spread of marine pathogens is the lack of barriers to dispersal in some parts of the ocean, and the potential for long‐term survival of pathogens outside the host. These findings caution that pathogens may pose a particularly severe problem in the ocean. There is a need to develop epidemic models capable of generating these high rates of spread and obtain more estimates of disease spread rate.     

Spatial and temporal invasion dynamics of the 2014–2017 Zika and chikungunya epidemics in Colombia

Zika virus (ZIKV) and chikungunya virus (CHIKV) were recently introduced into the Americas resulting in significant disease burdens. Understanding their spatial and temporal dynamics at the subnational level is key to informing surveillance and preparedness for future epidemics. We analyzed anonymized line list data on approximately 105,000 Zika virus disease and 412,000 chikungunya fever suspected and laboratory-confirmed cases during the 2014–2017 epidemics. We first determined the week of invasion in each city. Out of 1,122, 288 cities met criteria for epidemic invasion by ZIKV and 338 cities by CHIKV. We analyzed risk factors for invasion using linear and logistic regression models. We also estimated that the geographic origin of both epidemics was located in Barranquilla, north Colombia. We assessed the spatial and temporal invasion dynamics of both viruses to analyze transmission between cities using a suite of (i) gravity models, (ii) Stouffer’s rank models, and (iii) radiation models with two types of distance metrics, geographic distance and travel time between cities. Invasion risk was best captured by a gravity model when accounting for geographic distance and intermediate levels of density dependence; Stouffer’s rank model with geographic distance performed similarly well. Although a few long-distance invasion events occurred at the beginning of the epidemics, an estimated distance power of 1.7 (95% CrI: 1.5–2.0) from the gravity models suggests that spatial spread was primarily driven by short-distance transmission. Similarities between the epidemics were highlighted by jointly fitted models, which were preferred over individual models when the transmission intensity was allowed to vary across arboviruses. However, ZIKV spread considerably faster than CHIKV.     

High host density favors greater virulence: a model of parasite–host dynamics based on multi-type branching processes

We use a multitype continuous time Markov branching process model to describe the dynamics of the spread of parasites of two types that can mutate into each other in a common host population. While most mathematical models for the virulence of infectious diseases focus on the interplay between the dynamics of host populations and the optimal characteristics for the success of the pathogen, our model focuses on how pathogen characteristics may change at the start of an epidemic, before the density of susceptible hosts decline. We envisage animal husbandry situations where hosts are at very high density and epidemics are curtailed before host densities are much reduced. The use of three pathogen characteristics: lethality, transmissibility and mutability allows us to investigate the interplay of these in relation to host density. We provide some numerical illustrations and discuss the effects of the size of the enclosure containing the host population on the encounter rate in our model that plays the key role in determining what pathogen type will eventually prevail. We also present a multistage extension of the model to situations where there are several populations and parasites can be transmitted from one of them to another. We conclude that animal husbandry situations with high stock densities will lead to very rapid increases in virulence, where virulent strains are either more transmissible or favoured by mutation. Further the process is affected by the nature of the farm enclosures.     

Adaptation to resistant hosts increases fitness on susceptible hosts in the plant parasitic nematode Globodera pallida

Trade‐offs between virulence (defined as the ability to infect a resistant host) and life‐history traits are of particular interest in plant pathogens for durable management of plant resistances. Adaptation to plant resistances (i.e., virulence acquisition) is indeed expected to be associated with a fitness cost on susceptible hosts. Here, we investigated whether life‐history traits involved in the fitness of the potato cyst nematode Globodera pallida are affected in a virulent lineage compared to an avirulent one. Both lineages were obtained from the same natural population through experimental evolution on resistant and susceptible hosts, respectively. Unexpectedly, we found that virulent lineages were more fit than avirulent lineages on susceptible hosts: they produced bigger cysts, containing more larvae and hatching faster. We thus discuss possible reasons explaining why virulence did not spread into natural G. pallida populations.     

Ecological genetics of the Bromus tectorum (Poaceae)-Ustilago bullata (Ustilaginaceae) pathosystem: A role for frequency-dependent selection?

? Premise of the study: Evolutionary processes that maintain genetic diversity in plants are likely to include selection imposed by pathogens. Negative frequency-dependent selection is a mechanism for maintenance of resistance polymorphism in plant-pathogen interactions. We explored whether such selection operates in the Bromus tectorum-Ustilago bullata pathosystem. Gene-for-gene relationships between resistance and avirulence loci have been demonstrated for this pathosystem. ? Methods: We used molecular markers and cross-inoculation trials to learn whether the SSR genotypes of the host exhibited resistance to co-occurring pathogen races, whether host genotypes within a population had equal disease probability, and whether a common resistance locus and its corresponding avirulence locus exhibited predicted allele frequency changes during an epidemic. ? Key results: Five of six putative resistance loci that conferred resistance to co-occurring pathogen races occurred in common host SSR genotypes. Some common genotypes within populations were more likely to be diseased than others, and genotype frequencies sometimes changed across years in patterns consistent with frequency-dependent selection. Observed changes in frequency of resistance and virulence alleles during an epidemic provided further support, but evidence was inconclusive. ? Conclusions: Frequency-dependent selection may operate at endemic disease levels in this pathosystem, but is difficult to detect because many susceptible plants escape infection. Most pathogen isolates were virulent on most host genotypes, minimizing the apparent importance of frequency-dependent selection even during epidemics.