'Small worlds' and the evolution of virulence: infection occurs locally and at a distance

Dynamic, spatial models of parasite transmission in wildlife: Their structure, applications and remaining challenges

Individual differences in contact rate can arise from host, group and landscape heterogeneity and can result in different patterns of spatial spread for diseases in wildlife populations with concomitant implications for disease control in wildlife of conservation concern, livestock and humans. While dynamic disease models can provide a better understanding of the drivers of spatial spread, the effects of landscape heterogeneity have only been modelled in a few well-studied wildlife systems such as rabies and bovine tuberculosis. Such spatial models tend to be either purely theoretical with intrinsic limiting assumptions or individual-based models that are often highly species- and system-specific, limiting the breadth of their utility. Our goal was to review studies that have utilized dynamic, spatial models to answer questions about pathogen transmission in wildlife and identify key gaps in the literature. We begin by providing an overview of the main types of dynamic, spatial models (e.g., metapopulation, network, lattice, cellular automata, individual-based and continuous-space) and their relation to each other. We investigate different types of ecological questions that these models have been used to explore: pathogen invasion dynamics and range expansion, spatial heterogeneity and pathogen persistence, the implications of management and intervention strategies and the role of evolution in host-pathogen dynamics. We reviewed 168 studies that consider pathogen transmission in free-ranging wildlife and classify them by the model type employed, the focal host-pathogen system, and their overall research themes and motivation. We observed a significant focus on mammalian hosts, a few well-studied or purely theoretical pathogen systems, and a lack of studies occurring at the wildlife-public health or wildlife-livestock interfaces. Finally, we discuss challenges and future directions in the context of unprecedented human-mediated environmental change. Spatial models may provide new insights into understanding, for example, how global warming and habitat disturbance contribute to disease maintenance and emergence. Moving forward, better integration of dynamic, spatial disease models with approaches from movement ecology, landscape genetics/genomics and ecoimmunology may provide new avenues for investigation and aid in the control of zoonotic and emerging infectious diseases.

Parasite dispersal risk tolerance is mediated by its reproductive value

Parasite dispersal theory draws heavily upon epidemiological SIR models in which host status (susceptible (S), infected (I), or recovered (R)) is used to study parasite dispersal evolution. In contrast to these extrinsically host-centric drivers, in this study we focus on an intrinsic driver, the parasite's reproductive value (predicted future offspring) as a regulator of the extent to which the individual will engage in risky dispersal behaviour. As a model system we use the honeybee Apis mellifera and its ectoparasite, the mite Varroa destructor. Mite reproduction happens exclusively inside cells of bee brood, and newly emerged fecund mites may parasitize either a homocolonial brood cell (low risk dispersal) or emigrate to a new bee colony via phoretic attachment to mature forager bees (high risk dispersal). In an empirical bioassay, prepartum mites (high reproductive value) and postpartum mites (low reproductive value) were offered a choice of newly emerged homocolonial worker bees (low risk), homocolonial pollen forager bees (high risk), or heterocolonial pollen foragers (high risk). A preference for newly emerged bees was earlier and more strongly sustained among prepartum mites. This suggests comparatively greater dispersal risk tolerance among postpartum mites with lower reproductive value. A dangerous bid for dispersal may be adaptive if the individual has already successfully reproduced and the rewards for successful dispersal are sufficiently large.

Ecological and evolutionary approaches to managing honeybee disease

Honeybee declines are a serious threat to global agricultural security and productivity. Although multiple factors contribute to these declines, parasites are a key driver. Disease problems in honeybees have intensified in recent years, despite increasing attention to addressing them. Here we argue that we must focus on the principles of disease ecology and evolution to understand disease dynamics, assess the severity of disease threats, and control these threats via honeybee management. We cover the ecological context of honeybee disease, including both host and parasite factors driving current transmission dynamics, and then discuss evolutionary dynamics including how beekeeping management practices may drive selection for more virulent parasites. We then outline how ecological and evolutionary principles can guide disease mitigation in honeybees, including several practical management suggestions for addressing short- and long-term disease dynamics and consequences.

Multiple interacting factors have contributed to the rapid decline of honeybee populations worldwide. Here, the authors review the impact of parasites and pathogens, and how ecological and evolutionary principles can guide management practices.

Host population structure impedes reversion to drug sensitivity after discontinuation of treatment

Intense use of antibiotics for the treatment of diseases such as tuberculosis, malaria, Staphylococcus aureus or gonorrhea has led to rapidly increasing population levels of drug resistance. This has generally necessitated a switch to new drugs and the discontinuation of older ones, after which resistance often only declines slowly or even persists indefinitely. These long-term effects are usually ascribed to low fitness costs of resistance in absence of the drug. Here we show that structure in the host population, in particular heterogeneity in number of contacts, also plays an important role in the reversion dynamics. Host contact structure acts both during the phase of intense treatment, leading to non-random distributions of the resistant strain among the infected population, and after the discontinuation of the drug, by affecting the competition dynamics resulting in a mitigation of fitness advantages. As a consequence, we observe both a lower rate of reversion and a lower probability that reversion to sensitivity on the population level occurs after treatment is stopped. Our simulations show that the impact of heterogeneity in the host structure is maximal in the biologically most plausible parameter range, namely when fitness costs of resistance are small.

Global change, parasite transmission and disease control: lessons from ecology

Parasitic infections are ubiquitous in wildlife, livestock and human populations, and healthy ecosystems are often parasite rich. Yet, their negative impacts can be extreme. Understanding how both anticipated and cryptic changes in a system might affect parasite transmission at an individual, local and global level is critical for sustainable control in humans and livestock. Here we highlight and synthesize evidence regarding potential effects of 'system changes' (both climatic and anthropogenic) on parasite transmission from wild host-parasite systems. Such information could inform more efficient and sustainable parasite control programmes in domestic animals or humans. Many examples from diverse terrestrial and aquatic natural systems show how abiotic and biotic factors affected by system changes can interact additively, multiplicatively or antagonistically to influence parasite transmission, including through altered habitat structure, biodiversity, host demographics and evolution. Despite this, few studies of managed systems explicitly consider these higher-order interactions, or the subsequent effects of parasite evolution, which can conceal or exaggerate measured impacts of control actions. We call for a more integrated approach to investigating transmission dynamics, which recognizes these complexities and makes use of new technologies for data capture and monitoring, and to support robust predictions of altered parasite dynamics in a rapidly changing world.This article is part of the themed issue 'Opening the black box: re-examining the ecology and evolution of parasite transmission'.

Infectious Disease Dynamics in Heterogeneous Landscapes

Infectious diseases dynamics are affected by both spatial and temporal heterogeneity in their environments. Our ability to quantify and predict how this heterogeneity impacts risks of infection and disease emergence is the key to successful disease prevention efforts. Here, we review the literature on infectious diseases from human, agricultural, and wildlife ecosystems to describe the rapid ecological and evolutionary responses in pathogens to environmental heterogeneity, with expected impacts on their epidemiology. To date, the underlying network structures through which disease transmission proceeds have been notoriously difficult to quantify because of this variation. We show that with recent advances in statistical methods and genomic approaches, it is now more feasible than ever to trace disease transmission networks, the molecular underpinning of infection, and the environmental variation relevant to disease dynamics. We end by identifying major new opportunities and challenges in understanding disease dynamics in an ever-changing world.

Predation and selection for antibiotic resistance in natural environments

Genes encoding resistance to antibiotics appear, like the antibiotics themselves, to be ancient, originating long before the rise of the era of anthropogenic antibiotics. However, detailed understanding of the specific biological advantages of antibiotic resistance in natural environments is still lacking, thus limiting our efforts to prevent environmental influx of resistance genes. Here, we propose that antibiotic-resistant cells not only evade predation from antibiotic producers but also take advantage of nutrients released from cells that are killed by the antibiotic-producing bacteria. Thus, predation is potentially an important mechanism for driving antibiotic resistance during slow or stationary phase of growth when nutrients are deprived. This adds to explain the ancient nature and widespread occurrence of antibiotic resistance in natural environments unaffected by anthropogenic antibiotics. In particular, we suggest that nutrient-poor environments including indoor environments, for example, clean rooms and intensive care units may serve as a reservoir and source for antibiotic-producing as well as antibiotic-resistant bacteria.

Disease Outbreaks: Critical Biological Factors and Control Strategies

Disease outbreaks remain a major threat to human health and welfare especially in urban areas in both developed and developing countries. A large body of theoretical work has been devoted to modeling disease emergence, and critical factors that predict outbreak occurrence and severity have been proposed. In this chapter, we focus on biological factors that underlie both theoretical models and urban planning. We describe the SARS 2002–2003 pandemic as a case study of epidemic control of a human infectious disease. We then describe theoretical analyses of disease dynamics and control strategies. An important conclusion is that epidemic control will be strongly dependent on particular aspects of pathogen biology including host breadth, virulence, incubation time, and/or mutation rate. The probability, and potential cost, of future outbreaks, may be high and lessons from both past cases and theoretical work should inform urban design and policy. Interdisciplinary collaboration in planning, swiftness of information dissemination and response, and willingness to forgo personal liberties during a crisis may be key factors in resilience to infectious disease outbreaks.

Quantifying the reliability of dispersal paths in connectivity networks

Many biological systems, from fragmented landscapes to host populations, can be represented as networks of connected habitat patches. Links between patches in these connectivity networks can represent equally diverse processes, from individuals moving through the landscape to pathogen transmissions or successive colonization events in metapopulations. Any of these processes can be characterized as stochastic, with functional links among patches that exist with various levels of certainty. This stochasticity then needs to be reflected in the algorithms that aim to predict the dispersal routes in these networks. Here we adapt the concept of reliability to characterize the likelihood that a specific path will be used for dispersal in a probabilistic connectivity network. The most reliable of the paths that connect two patches will then identify the most likely sequence of intermediate steps between these patches. Path reliability will be sensitive to targeted disruptions of individual links that form the path, and this can then be used to plan the interventions aimed at either preserving or disrupting the dispersal along that path. The proposed approach is general, and can be used to identify the most likely dispersal routes in various contexts, such as predicting patterns of migrations, colonizations, invasions and epidemics.

Virulence evolution at the front line of spreading epidemics

Understanding and predicting the spatial spread of emerging pathogens is a major challenge for the public health management of infectious diseases. Theoretical epidemiology shows that the speed of an epidemic is governed by the life-history characteristics of the pathogen and its ability to disperse. Rapid evolution of these traits during the invasion may thus affect the speed of epidemics. Here we study the influence of virulence evolution on the spatial spread of an epidemic. At the edge of the invasion front, we show that more virulent and transmissible genotypes are expected to win the competition with other pathogens. Behind the front line, however, more prudent exploitation strategies outcompete virulent pathogens. Crucially, even when the presence of the virulent mutant is limited to the edge of the front, the invasion speed can be dramatically altered by pathogen evolution. We support our analysis with individual-based simulations and we discuss the additional effects of demographic stochasticity taking place at the front line on virulence evolution. We confirm that an increase of virulence can occur at the front, but only if the carrying capacity of the invading pathogen is large enough. These results are discussed in the light of recent empirical studies examining virulence evolution at the edge of spreading epidemics.

The adaptive evolution of virulence: a review of theoretical predictions and empirical tests

Why is it that some parasites cause high levels of host damage (i.e. virulence) whereas others are relatively benign? There are now numerous reviews of virulence evolution in the literature but it is nevertheless still difficult to find a comprehensive treatment of the theory and data on the subject that is easily accessible to non-specialists. Here we attempt to do so by distilling the vast theoretical literature on the topic into a set of relatively few robust predictions. We then provide a comprehensive assessment of the available empirical literature that tests these predictions. Our results show that there have been some notable successes in integrating theory and data but also that theory and empiricism in this field do not ‘speak’ to each other very well. We offer a few suggestions for how the connection between the two might be improved.

The Need for Evolutionarily Rational Disease Interventions: Vaccination Can Select for Higher Virulence

There is little doubt evolution has played a major role in preventing the control of infectious disease through antibiotic and insecticide resistance, but recent theory suggests disease interventions such as vaccination may lead to evolution of more harmful parasites. A new study published in PLOS Biology by Andrew Read and colleagues shows empirically that vaccination against Marek's disease has favored higher virulence; without intervention, the birds die too quickly for any transmission to occur, but vaccinated hosts can both stay alive longer and shed the virus. This is an elegant empirical demonstration of how evolutionary theory can predict potentially dangerous responses of infectious disease to human interventions.

Population mixing promotes arms race host-parasite coevolution

The consequences of host–parasite coevolution are highly contingent on the qualitative coevolutionary dynamics: whether selection fluctuates (fluctuating selection dynamic; FSD), or is directional towards increasing infectivity/resistance (arms race dynamic; ARD). Both genetics and ecology can play an important role in determining whether coevolution follows FSD or ARD, but the ecological conditions under which FSD shifts to ARD, and vice versa, are not well understood. The degree of population mixing is thought to increase host exposure to parasites, hence selecting for greater resistance and infectivity ranges, and we hypothesize this promotes ARD. We tested this by coevolving bacteria and viruses in soil microcosms and found that population mixing shifted bacteria–virus coevolution from FSD to ARD. A simple theoretical model produced qualitatively similar results, showing that mechanisms that increase host exposure to parasites tend to push dynamics towards ARD. The shift from FSD to ARD with increased population mixing may help to explain variation in coevolutionary dynamics between different host–parasite systems, and more specifically the observed discrepancies between laboratory and field bacteria–virus coevolutionary studies.

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.

The causes and consequences of changes in virulence following pathogen host shifts

Emerging infectious diseases are often the result of a host shift, where the pathogen originates from a different host species. Virulence--the harm a pathogen does to its host-can be extremely high following a host shift (for example Ebola, HIV, and SARs), while other host shifts may go undetected as they cause few symptoms in the new host. Here we examine how virulence varies across host species by carrying out a large cross infection experiment using 48 species of Drosophilidae and an RNA virus. Host shifts resulted in dramatic variation in virulence, with benign infections in some species and rapid death in others. The change in virulence was highly predictable from the host phylogeny, with hosts clustering together in distinct clades displaying high or low virulence. High levels of virulence are associated with high viral loads, and this may determine the transmission rate of the virus.

Effects of the transmissibility and virulence of pathogens on intraguild predation in fragmented landscapes

It is well known that pathogenic infection can have a profound effect on the outcome of competition and predation, however the role of pathogenic infection in systems where predators and prey also compete for other resources is yet to be explored (i.e. in systems of intraguild predation). Using a cellular automaton model, we here explore the effect of pathogenic infection on the spatial dynamics of species that also engage in intraguild predation (IGP) in a fragmented landscape. First, the shared pathogen by the predator and prey can enhance species coexistence in the IGP system, consistent with results for non-spatial IGP systems. Second, equilibrium population sizes of the predator and prey depend crucially on the pathogen virulence to the predator but are insensitive to the change in the virulence to the prey. This asymmetric response to virulence change is due to the fact that the predator species has to juggle between predation, resource competition and pathogenic infection. Finally, the response of the pathogen to habitat fragmentation is largely determined by its life-history strategy (transmissibility and virulence) and the trophic level of its host. These results enrich our understanding on the role of pathogens in the ecosystem functioning of eco-epidemiological systems.

Evolution of pathogen virulence across space during an epidemic

We explore pathogen virulence evolution during the spatial expansion of an infectious disease epidemic in the presence of a novel host movement trade-off, using a simple, spatially explicit mathematical model. This work is motivated by empirical observations of the Mycoplasma gallisepticum invasion into North American house finch (Haemorhous mexicanus) populations; however, our results likely have important applications to other emerging infectious diseases in mobile hosts. We assume that infection reduces host movement and survival and that across pathogen strains the severity of these reductions increases with pathogen infectiousness. Assuming these trade-offs between pathogen virulence (host mortality), pathogen transmission, and host movement, we find that pathogen virulence levels near the epidemic front (that maximize wave speed) are lower than those that have a short-term growth rate advantage or that ultimately prevail (i.e., are evolutionarily stable) near the epicenter and where infection becomes endemic (i.e., that maximize the pathogen basic reproductive ratio). We predict that, under these trade-offs, less virulent pathogen strains will dominate the periphery of an epidemic and that more virulent strains will increase in frequency after invasion where disease is endemic. These results have important implications for observing and interpreting spatiotemporal epidemic data and may help explain transient virulence dynamics of emerging infectious diseases.

Evolution and emergence of infectious diseases in theoretical and real-world networks

One of the most important advancements in theoretical epidemiology has been the development of methods that account for realistic host population structure. The central finding is that heterogeneity in contact networks, such as the presence of 'superspreaders', accelerates infectious disease spread in real epidemics. Disease control is also complicated by the continuous evolution of pathogens in response to changing environments and medical interventions. It remains unclear, however, how population structure influences these adaptive processes. Here we examine the evolution of infectious disease in empirical and theoretical networks. We show that the heterogeneity in contact structure, which facilitates the spread of a single disease, surprisingly renders a resident strain more resilient to invasion by new variants. Our results suggest that many host contact structures suppress invasion of new strains and may slow disease adaptation. These findings are important to the natural history of disease evolution and the spread of drug-resistant strains.

Virulence and resistance in a mosquito-microsporidium interaction

We review the results of a series of experiments involving Aedes aegypti and its microsporidian parasite Vavraia culicis to illustrate how intra-specific competition and parasitism shape life history traits. More specifically these experiments showed that some major components of virulence are host condition-dependent in this system, while others are not. We also briefly discuss the ways through which V. culicis modifies the physiological functioning of its host. We discuss the implications of these results for studies of host – parasite interactions in general and propose ways through which our studies could contribute to vector control and management programs.

Quantifying transmission by stage of infection in the field: the example of SIV-1 and STLV-1 infecting mandrills

The early stage of viral infection is often followed by an important increase of viral load and is generally considered to be the most at risk for pathogen transmission. Most methods quantifying the relative importance of the different stages of infection were developed for studies aimed at measuring HIV transmission in Humans. However, they cannot be transposed to animal populations in which less information is available. Here we propose a general method to quantify the importance of the early and late stages of the infection on micro-organism transmission from field studies. The method is based on a state space dynamical model parameterized using Bayesian inference. It is illustrated by a 28 years dataset in mandrills infected by Simian Immunodeficiency Virus type-1 (SIV-1) and the Simian T-Cell Lymphotropic Virus type-1 (STLV-1). For both viruses we show that transmission is predominant during the early stage of the infection (transmission ratio for SIV-1: 1.16 [0.0009; 18.15] and 9.92 [0.03; 83.8] for STLV-1). However, in terms of basic reproductive number (R0 ), which quantifies the weight of both stages in the spread of the virus, the results suggest that the epidemics of SIV-1 and STLV-1 are mainly driven by late transmissions in this population.

Lyssaviruses and bats: emergence and zoonotic threat

The continued detection of zoonotic viral infections in bats has led to the microbial fauna of these mammals being studied at a greater level than ever before. Whilst numerous pathogens have been discovered in bat species, infection with lyssaviruses is of particular significance from a zoonotic perspective as, where human infection has been reported, it is invariably fatal. Here we review the detection of lyssaviruses within different bat species and overview what is understood regarding their maintenance and transmission following both experimental and natural infection. We discuss the relevance of these pathogens as zoonotic agents and the threat of newly discovered viruses to human populations.

Evolutionary dynamics of infectious diseases in finite populations

In infectious disease epidemiology the basic reproductive ratio, R0, is defined as the average number of new infections caused by a single infected individual in a fully susceptible population. Many models describing competition for hosts between non-interacting pathogen strains in an infinite population lead to the conclusion that selection favors invasion of new strains if and only if they have higher R0 values than the resident. Here we demonstrate that this picture fails in finite populations. Using a simple stochastic SIS model, we show that in general there is no analogous optimization principle. We find that successive invasions may in some cases lead to strains that infect a smaller fraction of the host population, and that mutually invasible pathogen strains exist. In the limit of weak selection we demonstrate that an optimization principle does exist, although it differs from R0 maximization. For strains with very large R0, we derive an expression for this local fitness function and use it to establish a lower bound for the error caused by neglecting stochastic effects. Furthermore, we apply this weak selection limit to investigate the selection dynamics in the presence of a trade-off between the virulence and the transmission rate of a pathogen.

The evolutionary and ecological consequences of animal social networks: emerging issues

The first generation of research on animal social networks was primarily aimed at introducing the concept of social networks to the fields of animal behaviour and behavioural ecology. More recently, a diverse body of evidence has shown that social fine structure matters on a broader scale than initially expected, affecting many key ecological and evolutionary processes. Here, we review this development. We discuss the effects of social network structure on evolutionary dynamics (genetic drift, fixation probabilities, and frequency-dependent selection) and social evolution (cooperation and between-individual behavioural differences). We discuss how social network structure can affect important coevolutionary processes (host-pathogen interactions and mutualisms) and population stability. We also discuss the potentially important, but poorly studied, role of social network structure on dispersal and invasion. Throughout, we highlight important areas for future research.

Evolution of acuteness in pathogen metapopulations: conflicts between "classical" and invasion-persistence trade-offs

Classical life-history theory predicts that acute, immunizing pathogens should maximize between-host transmission. When such pathogens induce violent epidemic outbreaks, however, a pathogen's short-term advantage at invasion may come at the expense of its ability to persist in the population over the long term. Here, we seek to understand how the classical and invasion-persistence trade-offs interact to shape pathogen life-history evolution as a function of the size and structure of the host population. We develop an individual-based infection model at three distinct levels of organization: within an individual host, among hosts within a local population, and among local populations within a metapopulation. We find a continuum of evolutionarily stable pathogen strategies. At one end of the spectrum-in large well-mixed populations-pathogens evolve to greater acuteness to maximize between-host transmission: the classical trade-off theory applies in this regime. At the other end of the spectrum-when the host population is broken into many small patches-selection favors less acute pathogens, which persist longer within a patch and thereby achieve enhanced between-patch transmission: the invasion-persistence tradeoff dominates in this regime. Between these extremes, we explore the effects of the size and structure of the host population in determining pathogen strategy. In general, pathogen strategies respond to evolutionary pressures arising at both scales.

Can host ecology and kin selection predict parasite virulence?

Parasite virulence, or the damage a parasite does to its host, is measured in terms of both host costs (reductions in host growth, reproduction and survival) and parasite benefits (increased transmission and parasite numbers) in the literature. Much work has shown that ecological and genetic factors can be strong selective forces in virulence evolution. This review uses kin selection theory to explore how variations in host ecological parameters impact the genetic relatedness of parasite populations and thus virulence. We provide a broad overview of virulence and population genetics studies and then draw connections to existing knowledge about natural parasite populations. The impact of host movement (transporting parasites) and host resistance (filtering parasites) on the genetic structure and virulence of parasite populations is explored, and empirical studies of these factors using Plasmodium and trematode systems are proposed.

We'll meet again: revealing distributional and temporal patterns of social contact

What are the dynamics and regularities underlying social contact, and how can contact with the people in one's social network be predicted? In order to characterize distributional and temporal patterns underlying contact probability, we asked 40 participants to keep a diary of their social contacts for 100 consecutive days. Using a memory framework previously used to study environmental regularities, we predicted that the probability of future contact would follow in systematic ways from the frequency, recency, and spacing of previous contact. The distribution of contact probability across the members of a person's social network was highly skewed, following an exponential function. As predicted, it emerged that future contact scaled linearly with frequency of past contact, proportionally to a power function with recency of past contact, and differentially according to the spacing of past contact. These relations emerged across different contact media and irrespective of whether the participant initiated or received contact. We discuss how the identification of these regularities might inspire more realistic analyses of behavior in social networks (e.g., attitude formation, cooperation).

Dynamics of infectious diseases

Modern infectious disease epidemiology has a strong history of using mathematics both for prediction and to gain a deeper understanding. However the study of infectious diseases is a highly interdisciplinary subject requiring insights from multiple disciplines, in particular a biological knowledge of the pathogen, a statistical description of the available data and a mathematical framework for prediction. Here we begin with the basic building blocks of infectious disease epidemiology--the SIS and SIR type models--before considering the progress that has been made over the recent decades and the challenges that lie ahead. Throughout we focus on the understanding that can be developed from relatively simple models, although accurate prediction will inevitably require far greater complexity beyond the scope of this review. In particular, we focus on three critical aspects of infectious disease models that we feel fundamentally shape their dynamics: heterogeneously structured populations, stochasticity and spatial structure. Throughout we relate the mathematical models and their results to a variety of real-world problems.

Spatial structure mitigates fitness costs in host-parasite coevolution

The extent of population mixing is known to influence the coevolutionary outcomes of many host and parasite traits, including the evolution of generalism (the ability to resist or infect a broad range of genotypes). While the segregation of populations into interconnected demes has been shown to influence the evolution of generalism, the role of local interactions between individuals is unclear. Here, we combine an individual-based model of microbial communities with a well-established framework of genetic specificity that matches empirical observations of bacterium-phage interactions. We find the evolution of generalism in well-mixed populations to be highly sensitive to the severity of associated fitness costs, but the constraining effect of costs on the evolution of generalism is lessened in spatially structured populations. The contrasting outcomes between the two environments can be explained by different scales of competition (i.e., global vs. local). These findings suggest that local interactions may have important effects on the evolution of generalism in host-parasite interactions, particularly in the presence of high fitness costs.

Fitness benefits of low infectivity in a spatially structured population of bacteriophages

For a parasite evolving in a spatially structured environment, an evolutionarily advantageous strategy may be to reduce its transmission rate or infectivity. We demonstrate this empirically using bacteriophage (phage) from an evolution experiment where spatial structure was maintained over 550 phage generations on agar plates. We found that a single substitution in the major capsid protein led to slower adsorption of phage to host cells with no change in lysis time or burst size. Plaques formed by phage isolates containing this mutation were not only larger but also contained more phage per unit area. Using a spatially explicit, individual-based model, we showed that when there is a trade-off between adsorption and diffusion (i.e. less 'sticky' phage diffuse further), slow adsorption can maximize plaque size, plaque density and overall productivity. These findings suggest that less infective pathogens may have an advantage in spatially structured populations, even when well-mixed models predict that they will not.

Interactions between social structure, demography, and transmission determine disease persistence in primates

Catastrophic declines in African great ape populations due to disease outbreaks have been reported in recent years, yet we rarely hear of similar disease impacts for the more solitary Asian great apes, or for smaller primates. We used an age-structured model of different primate social systems to illustrate that interactions between social structure and demography create 'dynamic constraints' on the pathogens that can establish and persist in primate host species with different social systems. We showed that this varies by disease transmission mode. Sexually transmitted infections (STIs) require high rates of transmissibility to persist within a primate population. In particular, for a unimale social system, STIs require extremely high rates of transmissibility for persistence, and remain at extremely low prevalence in small primates, but this is less constrained in longer-lived, larger-bodied primates. In contrast, aerosol transmitted infections (ATIs) spread and persist at high prevalence in medium and large primates with moderate transmissibility;, establishment and persistence in small-bodied primates require higher relative rates of transmissibility. Intragroup contact structure - the social network - creates different constraints for different transmission modes, and our model underscores the importance of intragroup contacts on infection prior to intergroup movement in a structured population. When alpha males dominate sexual encounters, the resulting disease transmission dynamics differ from when social interactions are dominated by mother-infant grooming events, for example. This has important repercussions for pathogen spread across populations. Our framework reveals essential social and demographic characteristics of primates that predispose them to different disease risks that will be important for disease management and conservation planning for protected primate populations.

The impact of spatial scale and habitat configuration on patterns of trait variation and local adaptation in a wild plant parasite

Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host-pathogen interactions. Yet, we lack empirical data to translate the theory to natural host-parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Åland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0-40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host-parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health.

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.

Predator attack rate evolution in space: the role of ecology mediated by complex emergent spatial structure and self-shading

Predation interactions are an important element of ecological communities. Population spatial structure has been shown to influence predator evolution, resulting in the evolution of a reduced predator attack rate; however, the evolutionary role of traits governing predator and prey ecology is unknown. The evolutionary effect of spatial structure on a predator's attack rate has primarily been explored assuming a fixed metapopulation spatial structure, and understood in terms of group selection. But endogenously generated, emergent spatial structure is common in nature. Furthermore, the evolutionary influence of ecological traits may be mediated through the spatial self-structuring process. Drawing from theory on pathogens, the evolutionary effect of emergent spatial structure can be understood in terms of self-shading, where a voracious predator limits its long-term invasion potential by reducing local prey availability. Here we formalize the effects of self-shading for predators using spatial moment equations. Then, through simulations, we show that in a spatial context self-shading leads to relationships between predator-prey ecology and the predator's attack rate that are not expected in a non-spatial context. Some relationships are analogous to relationships already shown for host-pathogen interactions, but others represent new trait dimensions. Finally, since understanding the effects of ecology using existing self-shading theory requires simplifications of the emergent spatial structure that do not apply well here, we also develop metrics describing the complex spatial structure of the predator and prey populations to help us explain the evolutionary effect of predator and prey ecology in the context of self-shading. The identification of these metrics may provide a step towards expansion of the predictive domain of self-shading theory to more complex spatial dynamics.

Bacterial motility confers fitness advantage in the presence of phages

Dispersal provides the opportunity to escape harm and colonize new patches, enabling populations to expand and persist. However, the benefits of dispersal associated with escaping harm will be dependent on the structure of the environment and the likelihood of escape. Here, we empirically investigate how the spatial distribution of a parasite influences the evolution of host dispersal. Bacteriophages are a strong and common threat for bacteria in natural environments and offer a good system with which to explore parasite-mediated selection on host dispersal. We used two transposon mutants of the opportunistic bacteria, Pseudomonas aeruginosa, which varied in their motility (a disperser and a nondisperser), and the lytic bacteriophage ФKZ. The phage was distributed either in the central point of colony inoculation only, thus offering an escape route for the dispersing bacteria; or, present throughout the agar, where benefits of dispersal might be lost. Surprisingly, we found dispersal to be equally advantageous under both phage conditions relative to when phages were absent. A general explanation is that dispersal decreased the spatial structuring of host population, reducing opportunities for parasite transmission, but other more idiosyncratic mechanisms may also have contributed. This study highlights the crucial role the parasites can play on the evolution of dispersal and, more specifically, that bacteriophages, which are ubiquitous, are likely to select for bacterial motility.

Influence of vectors' risk-spreading strategies and environmental stochasticity on the epidemiology and evolution of vector-borne diseases: the example of Chagas' disease

Insects are known to display strategies that spread the risk of encountering unfavorable conditions, thereby decreasing the extinction probability of genetic lineages in unpredictable environments. To what extent these strategies influence the epidemiology and evolution of vector-borne diseases in stochastic environments is largely unknown. In triatomines, the vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas’ disease, juvenile development time varies between individuals and such variation most likely decreases the extinction risk of vector populations in stochastic environments. We developed a simplified multi-stage vector-borne SI epidemiological model to investigate how vector risk-spreading strategies and environmental stochasticity influence the prevalence and evolution of a parasite. This model is based on available knowledge on triatomine biodemography, but its conceptual outcomes apply, to a certain extent, to other vector-borne diseases. Model comparisons between deterministic and stochastic settings led to the conclusion that environmental stochasticity, vector risk-spreading strategies (in particular an increase in the length and variability of development time) and their interaction have drastic consequences on vector population dynamics, disease prevalence, and the relative short-term evolution of parasite virulence. Our work shows that stochastic environments and associated risk-spreading strategies can increase the prevalence of vector-borne diseases and favor the invasion of more virulent parasite strains on relatively short evolutionary timescales. This study raises new questions and challenges in a context of increasingly unpredictable environmental variations as a result of global climate change and human interventions such as habitat destruction or vector control.

Adaptive dynamics with interaction structure

Evolutionary dynamics depend critically on a population's interaction structure-the pattern of which individuals interact with which others, depending on the state of the population and the environment. Previous research has shown, for example, that cooperative behaviors disfavored in well-mixed populations can be favored when interactions occur only between spatial neighbors or group members. Combining the adaptive dynamics approach with recent advances in evolutionary game theory, we here introduce a general mathematical framework for analyzing the long-term evolution of continuous game strategies for a broad class of evolutionary models, encompassing many varieties of interaction structure. Our main result, the canonical equation of adaptive dynamics with interaction structure, characterizes expected evolutionary trajectories resulting from any such model, thereby generalizing a central tool of adaptive dynamics theory. Interestingly, the effects of different interaction structures and update rules on evolutionary trajectories are fully captured by just two real numbers associated with each model, which are independent of the considered game. The first, a structure coefficient, quantifies the effects on selection pressures and thus on the shapes of expected evolutionary trajectories. The second, an effective population size, quantifies the effects on selection responses and thus on the expected rates of adaptation. Applying our results to two social dilemmas, we show how the range of evolutionarily stable cooperative behaviors systematically varies with a model's structure coefficient.

Sexually transmitted infections in polygamous mating systems

Sexually transmitted infections (STIs) are often associated with chronic diseases and can have severe impacts on host reproductive success. For airborne or socially transmitted pathogens, patterns of contact by which the infection spreads tend to be dispersed and each contact may be of very short duration. By contrast, the transmission pathways for STIs are usually characterized by repeated contacts with a small subset of the population. Here we review how heterogeneity in sexual contact patterns can influence epidemiological dynamics, and present a simple model of polygyny/polyandry to illustrate the impact of biased mating systems on disease incidence and pathogen virulence.

Ecology of zoonotic infectious diseases in bats: current knowledge and future directions

Bats are hosts to a range of zoonotic and potentially zoonotic pathogens. Human activities that increase exposure to bats will likely increase the opportunity for infections to spill over in the future. Ecological drivers of pathogen spillover and emergence in novel hosts, including humans, involve a complex mixture of processes, and understanding these complexities may aid in predicting spillover. In particular, only once the pathogen and host ecologies are known can the impacts of anthropogenic changes be fully appreciated. Cross-disciplinary approaches are required to understand how host and pathogen ecology interact. Bats differ from other sylvatic disease reservoirs because of their unique and diverse lifestyles, including their ability to fly, often highly gregarious social structures, long lifespans and low fecundity rates. We highlight how these traits may affect infection dynamics and how both host and pathogen traits may interact to affect infection dynamics. We identify key questions relating to the ecology of infectious diseases in bats and propose that a combination of field and laboratory studies are needed to create data-driven mechanistic models to elucidate those aspects of bat ecology that are most critical to the dynamics of emerging bat viruses. If commonalities can be found, then predicting the dynamics of newly emerging diseases may be possible. This modelling approach will be particularly important in scenarios when population surveillance data are unavailable and when it is unclear which aspects of host ecology are driving infection dynamics.