Parasite evolution of host manipulation strategies with fluctuating ecological dynamics.

Trophically transmitted parasites often infect an intermediate prey host and manipulate their behaviour to make predation more likely, thus facilitating parasite transmission to the definitive host. However, it is unclear when such a manipulation strategy should be expected to evolve. We develop the first evolutionary invasion model to explore the evolution of manipulation strategies that are in a trade-off with parasite production of free-living spores. We find that the size of the susceptible prey population together with the threat of predation drives manipulation evolution. We find that it is only when the susceptible prey population is large and the threat of predation is relatively small that selection favours manipulation strategies over spore production. We also confirm that the system exhibits cyclic population dynamics, and this can influence the qualitative direction of selection.

The impact of sterility-mortality tolerance and recovery-transmission trade-offs on host-parasite coevolution.

Understanding the coevolutionary dynamics of hosts and their parasites remains a major focus of much theoretical literature. Despite empirical evidence supporting the presence of sterility-mortality tolerance trade-offs in hosts and recovery-transmission trade-offs in parasites, none of the current models have explored the potential outcomes when both trade-offs are considered within a coevolutionary framework. In this study, we consider a model where the host evolves sterility tolerance at the cost of increased mortality and the parasite evolves higher transmission rate at the cost of increased recovery rate (reduced infection duration), and use adaptive dynamics to predict the coevolutionary outcomes under such trade-off assumptions. We particularly aim to understand how our coevolutionary dynamics compare with single species evolutionary models. We find that evolutionary branching in the host can drive the parasite population to branch, but that cycles in the population dynamics can prevent the coexisting strains from reaching their extremes. We also find that varying crowding does not impact the recovery rate when only the parasite evolves, yet coevolution reduces recovery as crowding intensifies. We conclude by discussing how different host and parasite trade-offs shape coevolutionary outcomes, underscoring the pivotal role of trade-offs in coevolution.

A Sterility-Mortality Tolerance Trade-Off Leads to Within-Population Variation in Host Tolerance.

While experimental studies have demonstrated within-population variation in host tolerance to parasitism, theoretical studies rarely predict for polymorphism to arise. However, most theoretical models do not consider the crucial distinction between tolerance to the effects of infection-induced deaths (mortality tolerance) and tolerance to the parasite-induced reduction in the reproduction of infected hosts (sterility tolerance). While some studies have examined trade-offs between host tolerance and resistance mechanisms, none has considered a correlation within different tolerance mechanisms. We assume that sterility tolerance and mortality tolerance are directly traded-off in a host population subjected to a pathogen and use adaptive dynamics to study their evolutionary behaviour. We find that such a trade-off between the two tolerance strategies can drive the host population to branch into dimorphic strains, leading to coexistence of strains with sterile hosts that have low mortality and fully fertile with high mortality rates. Further, we find that a wider range of trade-off shapes allows branching at intermediate- or high-infected population size. Our other significant finding is that sterility tolerance is maximised (and mortality tolerance minimised) at an intermediate disease-induced mortality rate. Additionally, evolution entirely reverses the disease prevalence pattern corresponding to the recovery rate, compared to when no strategies evolve. We provide novel predictions on the evolutionary behaviour of two tolerance strategies concerning such a trade-off.

Clonal population expansion of Staphylococcus aureus occurs due to escape from a finite number of intraphagocyte niches.

Staphylococcus aureus is a human commensal and also an opportunist pathogen causing life threatening infections. During S. aureus disease, the abscesses that characterise infection can be clonal, whereby a large bacterial population is founded by a single or few organisms. Our previous work has shown that macrophages are responsible for restricting bacterial growth such that a population bottleneck occurs and clonality can emerge. A subset of phagocytes fail to control S. aureus resulting in bacterial division, escape and founding of microabscesses that can seed other host niches. Here we investigate the basis for clonal microabscess formation, using in vitro and in silico models of S. aureus macrophage infection. Macrophages that fail to control S. aureus are characterised by formation of intracellular bacterial masses, followed by cell lysis. High-resolution microscopy reveals that most macrophages had internalised only a single S. aureus, providing a conceptual framework for clonal microabscess generation, which was supported by a stochastic individual-based, mathematical model. Once a threshold of masses was reached, increasing the number of infecting bacteria did not result in greater mass numbers, despite enhanced phagocytosis. This suggests a finite number of permissive, phagocyte niches determined by macrophage associated factors. Increased understanding of the parameters of infection dynamics provides avenues for development of rational control measures.

How Local Interactions Impact the Dynamics of an Epidemic.

Susceptible-Infected-Recovered (SIR) models have long formed the basis for exploring epidemiological dynamics in a range of contexts, including infectious disease spread in human populations. Classic SIR models take a mean-field assumption, such that a susceptible individual has an equal chance of catching the disease from any infected individual in the population. In reality, spatial and social structure will drive most instances of disease transmission. Here we explore the impacts of including spatial structure in a simple SIR model. We combine an approximate mathematical model (using a pair approximation) and stochastic simulations to consider the impact of increasingly local interactions on the epidemic. Our key development is to allow not just extremes of 'local' (neighbour-to-neighbour) or 'global' (random) transmission, but all points in between. We find that even medium degrees of local interactions produce epidemics highly similar to those with entirely global interactions, and only once interactions are predominantly local do epidemics become substantially lower and later. We also show how intervention strategies to impose local interactions on a population must be introduced early if significant impacts are to be seen.

Simultaneous evolution of host resistance and tolerance to parasitism.

Tolerance and resistance are two modes of defence mechanisms used by hosts when faced with parasites. Here, we assume tolerance reduces infection-induced mortality rate and resistance reduces the susceptibility of getting infected. Importantly, a negative association between these two strategies has often been found experimentally. We study the simultaneous evolution of resistance and tolerance in a host population where they are related by such a trade-off. Using evolutionary invasion theory, we examine the patterns of optimal investment in each defence strategy, under different ecological scenarios. Our focus is on predicting which of the two strategies is favoured under various epidemiological and ecological conditions. Our key findings surround the impact of recovery and sterility of infected hosts. As the rate at which infected hosts recover from the infection, that is the recovery rate increases, the investment in tolerance increases (resistance decreases) when infected hosts are sterile, but this pattern reverses when infected hosts can reproduce. We further found that a change in the parameter determining the intraspecies competition for resources leading to a reduction in birth rate, that is the crowding factor affects investments in tolerance and resistance only when infected hosts can reproduce. These results emphasize the role of fecundity in driving the evolutionary dynamics of a host. We also find that disease prevalence can increase or decrease depending on whether or not the host evolves: prevalence is highest at low recovery rates when the host does not evolve, but the feedback of a change in tolerance and resistance reverses this pattern, leading to lower prevalence at low recovery rates as host evolves.

The impact of varying class sizes on epidemic spread in a university population.

A common non-pharmaceutical intervention (NPI) during the COVID-19 pandemic has been group size limits. Furthermore, educational settings of schools and universities have either fully closed or reduced their class sizes. As countries begin to reopen classrooms, a key question will be how large classes can be while still preventing local outbreaks of disease. Here, we develop and analyse a simple, stochastic epidemiological model where individuals (considered as students) live in fixed households and are assigned to a fixed class for daily lessons. We compare key measures of the epidemic-the peak infected, the total infected by day 180 and the calculated R 0-as the size of class is varied. We find that class sizes of 10 could largely restrict outbreaks and often had overlapping inter-quartile ranges with our most cautious case of classes of five. However, class sizes of 30 or more often result in large epidemics. Reducing the class size from 40 to 10 can reduce R 0 by over 30%, as well as significantly reducing the numbers infected. Intermediate class sizes show considerable variation, with the total infected varying by as much as from 10% to 80% for the same class size. We show that additional in-class NPIs can limit the epidemic still further, but that reducing class sizes appears to have a larger effect on the epidemic. We do not specifically tailor our model for COVID-19, but our results stress the importance of small class sizes for preventing large outbreaks of infectious disease.

Herd immunity.

Herd immunity is an important yet often misunderstood concept in epidemiology. As immunity accumulates in a population - naturally during the course of an epidemic or through vaccination - the spread of an infectious disease is limited by the depletion of susceptible hosts. If a sufficient proportion of the population is immune - above the 'herd immunity threshold' - then transmission generally cannot be sustained. Maintaining herd immunity is therefore critical to long-term disease control. In this primer, we discuss the concept of herd immunity from first principles, clarify common misconceptions, and consider the implications for disease control.

The evolution of host resistance and parasite infectivity is highest in seasonal resource environments that oscillate at intermediate amplitudes.

Seasonal environments vary in their amplitude of oscillation but the effects of this temporal heterogeneity for host-parasite coevolution are poorly understood. Here, we combined mathematical modelling and experimental evolution of a coevolving bacteria-phage interaction to show that the intensity of host-parasite coevolution peaked in environments that oscillate in their resource supply with intermediate amplitude. Our experimentally parameterized mathematical model explains that this pattern is primarily driven by the ecological effects of resource oscillations on host growth rates. Our findings suggest that in host-parasite systems where the host's but not the parasite's population growth dynamics are subject to seasonal forcing, the intensity of coevolution will peak at intermediate amplitudes but be constrained at extreme amplitudes of environmental oscillation.

A mathematical model shows macrophages delay Staphylococcus aureus replication, but limitations in microbicidal capacity restrict bacterial clearance.

S. aureus is a leading cause of bacterial infection. Macrophages, the first line of defence in the human immune response, phagocytose and kill S. aureus but the pathogen can evade these responses. Therefore, the exact role of macrophages is incompletely defined. We develop a mathematical model of macrophage - S. aureus dynamics, built on recent experimental data. We demonstrate that, while macrophages may not clear infection, they significantly delay its growth and potentially buy time for recruitment of further cells. We find that macrophage killing is a major obstacle to controlling infection and ingestion capacity also limits the response. We find bistability such that the infection can be limited at low doses. Our combination of experimental data, mathematical analysis and model fitting provide important insights in to the early stages of S. aureus infections, showing macrophages play an important role limiting bacterial replication but can be overwhelmed with large inocula.

The effect of temporal fluctuations on the evolution of host tolerance to parasitism.

There are many mechanisms that hosts can evolve to defend against parasites, two of which are resistance and tolerance. These defences often have different evolutionary behaviours, and it is important to consider how each individual mechanism may respond to changes in environment. In particular, host defence through tolerance is predicted to be unlikely to lead to variation, despite many observations of diversity in both animal and plant systems. Hence understanding the drivers of diversity in host defence and parasite virulence is vital for predicting future evolutionary changes in infectious disease dynamics. It has been suggested that heterogeneous environments might generally promote diversity, but the effect of temporal fluctuations has received little attention theoretically or empirically, and there has been no examination of how temporal fluctuations affects the evolution of host tolerance. In this study, we use a mathematical model to investigate the evolution of host tolerance in a temporally fluctuating environment. We show that investment in tolerance increases in more variable environments, giving qualitatively different evolutionary behaviours when compared to resistance. Once seasonality is introduced evolutionary branching though tolerance can occur and create diversity within the population, although potentially only temporarily. This branching behaviour arises due to the emergence of a negative feedback with the maximum infected density on a cycle, which is strongest when the infected population is large. This work reinforces the qualitative differences between tolerance and resistance evolution, but also provides theoretical evidence for the theory that heterogeneous environments promote host-parasite diversity, hence constant environment assumptions may omit important evolutionary outcomes.

The paradox of tolerance: Parasite extinction due to the evolution of host defence.

Host defence against parasite infection can rely on two broad strategies: resistance and tolerance. The spread of resistance traits usually lowers parasite prevalence and decreases selection for higher defence. Conversely, tolerance mechanisms increase parasite prevalence and foster selection for more tolerance. Here we examine the potential for the host to drive parasites to extinction through the evolution of one or other defence mechanism. We analysed theoretical models of resistance and tolerance evolution in both the absence and the presence of a trade-off between defence and reproduction. In the absence of costs, resistance evolves towards maximisation and, consequently, parasite extinction. Tolerance also evolves towards maximisation but the positive feedback between tolerance and disease prevents the disappearance of the parasite. On the contrary, when defence comes with costs it is impossible for the host to eliminate the infection through resistance, because costly resistance is selected against when parasites are at low prevalence. We uncover that the only path to disease clearance in the presence of costs is through tolerance. Paradoxically, however, it is by lowering tolerance -and hence increasing disease-induced mortality- that extinction can occur. We also show that such extinction can occur even in the case of parasite counter-adaptation. Our results emphasise the importance of tolerance as a defence strategy, and identify key questions for future research.

The Impact of Selective Predation on Host-Parasite SIS Dynamics.

While models of host-parasite interactions are widespread in the theoretical literature, we still have limited understanding of the impact of community dynamics on infectious disease dynamics. When the wider host ecology is taken into account, the underlying inter-species feedbacks can lead to counter-intuitive results. For example, the 'healthy herd' hypothesis posits that the removal of a predator species may not be beneficial for a prey population infected by an endemic disease. In this work, we focus on the effects of including a predator species in a susceptible-infected-susceptible model. Specifically, a key role is played by predator selectivity for either healthy or infected prey. We explored both cases and found important differences in the asymptotic behaviours of the system. Independently from selectivity, large portions of parameter space allow for the coexistence of the three species. However, when predators feed mainly on susceptible prey we find that a fold bifurcation can occur, leading to a region of bi-stability between coexistence and parasite extinction. Conversely, when predator selection is strongly towards infected prey, total prey population density can be maximal when the three species coexist, consistent with the 'healthy herd' hypothesis. Our work further highlights the importance of community interactions to infectious disease dynamics.

Understanding the role of eco-evolutionary feedbacks in host-parasite coevolution.

It is widely recognised that eco-evolutionary feedbacks can have important implications for evolution. However, many models of host-parasite coevolution omit eco-evolutionary feedbacks for the sake of simplicity, typically by assuming the population sizes of both species are constant. It is often difficult to determine whether the results of these models are qualitatively robust if eco-evolutionary feedbacks are included. Here, by allowing interspecific encounter probabilities to depend on population densities without otherwise varying the structure of the models, we provide a simple method that can test whether eco-evolutionary feedbacks per se affect evolutionary outcomes. Applying this approach to explicit genetic and quantitative trait models from the literature, our framework shows that qualitative changes to the outcome can be directly attributable to eco-evolutionary feedbacks. For example, shifting the dynamics between stable monomorphism or polymorphism and cycling, as well as changing the nature of the cycles. Our approach, which can be readily applied to many different models of host-parasite coevolution, offers a straightforward method for testing whether eco-evolutionary feedbacks qualitatively change coevolutionary outcomes.

Host-pathogen coevolution in the presence of predators: fluctuating selection and ecological feedbacks.

Host-pathogen coevolution is central to shaping natural communities and is the focus of much experimental and theoretical study. For tractability, the vast majority of studies assume the host and pathogen interact in isolation, yet in reality, they will form one part of complex communities, with predation likely to be a particularly key interaction. Here, I present, to my knowledge, the first theoretical study to assess the impact of predation on the coevolution of costly host resistance and pathogen transmission. I show that fluctuating selection is most likely when predators selectively prey upon infected hosts, but that saturating predation, owing to large handling times, dramatically restricts the potential for fluctuations. I also show how host evolution may drive either enemy to extinction, and demonstrate that while predation selects for low host resistance and high pathogen infectivity, ecological feedbacks mean this results in lower infection rates when predators are present. I emphasize the importance of accounting for varying population sizes, and place the models in the context of recent experimental studies.

The evolution of constitutive and induced defences to infectious disease.

In response to infectious disease, hosts typically mount both constitutive and induced defences. Constitutive defence prevents infection in the first place, while induced defence typically shortens the infectious period. The two routes to defence, therefore, have very different implications not only to individuals but also to the epidemiology of the disease. Moreover, the costs of constitutive defences are likely to be paid even in the absence of disease, while induced defences are likely to incur the most substantial costs when they are used in response to infection. We examine theoretically the evolutionary implications of these fundamental differences. A key result is that high virulence in the parasite typically selects for higher induced defences even if they result in immunopathology leading to very high disease mortality. Disease impacts on fecundity are critical to the relative investment in constitutive and induced defence with important differences found when parasites castrate their hosts. The trade-off between constitutive and induced defence has been cited as a cause of the diversity in defence, but we show that the trade-off alone is unlikely to lead to diversity. Our models provide a framework to examine relative investment in different defence components both experimentally and in the field.

The evolution of host defence to parasitism in fluctuating environments.

Given rapidly changing environments, it is important for us to understand how the evolution of host defence responds to fluctuating environments. Here we present the first theoretical study of evolution of host resistance to parasitism in a classic epidemiological model where the host birth rate varies seasonally. We show that this form of seasonality has clear qualitative and quantitative impacts on the evolution of resistance. When the host can recover from infection, it evolves a lower level of defence when the amplitude is high. However, when recovery is absent, the host increases its defence for higher amplitudes. Between these different behaviours we find a region of parameter space that allows evolutionary bistability. When this occurs, the level of defence the host evolves depends on initial conditions, and in some cases a switch between attractors can lead to different periods in the population dynamics at each of the evolutionary stable strategies. Crucially, we find that evolutionary behaviour found in a constant environment for this model doesn't always hold for hosts with highly variable birth rates. Hence we argue that seasonality must be taken into account if we want to make predictions about evolutionary trends in real-world host-parasite systems.

Host-parasite fluctuating selection in the absence of specificity.

Fluctuating selection driven by coevolution between hosts and parasites is important for the generation of host and parasite diversity across space and time. Theory has focused primarily on infection genetics, with highly specific 'matching-allele' frameworks more likely to generate fluctuating selection dynamics (FSD) than 'gene-for-gene' (generalist-specialist) frameworks. However, the environment, ecological feedbacks and life-history characteristics may all play a role in determining when FSD occurs. Here, we develop eco-evolutionary models with explicit ecological dynamics to explore the ecological, epidemiological and host life-history drivers of FSD. Our key result is to demonstrate for the first time, to our knowledge, that specificity between hosts and parasites is not required to generate FSD. Furthermore, highly specific host-parasite interactions produce unstable, less robust stochastic fluctuations in contrast to interactions that lack specificity altogether or those that vary from generalist to specialist, which produce predictable limit cycles. Given the ubiquity of ecological feedbacks and the variation in the nature of specificity in host-parasite interactions, our work emphasizes the underestimated potential for host-parasite coevolution to generate fluctuating selection.

Evolution of Host Defense against Multiple Enemy Populations.

Natural and managed populations are embedded within complex ecological communities, where they face multiple enemies. Experimental studies have shown that the evolution of host defense mechanisms to a focal enemy is impacted by the surrounding enemy community. Theoretically, the evolution of host defenses against a single enemy population, typically parasites, has been widely studied, but only recently has the impact of community interactions on host-parasite evolution been looked at. In this article, we theoretically examine the evolutionary behavior of a host population that must allocate defenses between two enemy populations, parasites and predators, with defense against one enemy constraining defense against the other. We show that in simpler models the composition of the enemy community plays the key role in determining the defense strategy of the hosts, with the hosts building up defenses against the enemy population posing a larger threat. However, this simple driver is shown to break down when there is significant recovery and reproduction from infected hosts. Additionally, we find that most host diversity is likely to occur when there is a combined high risk of infection and predation, in common with experimental studies. Our results therefore provide vital insight into the ecological feedbacks that drive the evolution of host defense against multiple enemy populations.