Beyond R0 Maximisation: On Pathogen Evolution and Environmental Dimensions

Within-Host Viral Growth and Immune Response Rates Predict Foot-and-Mouth Disease Virus Transmission Dynamics for African Buffalo

AbstractInfectious disease dynamics operate across biological scales: pathogens replicate within hosts but transmit among populations. Functional changes in the pathogen-host interaction thus generate cascading effects across organizational scales. We investigated within-host dynamics and among-host transmission of three strains (SAT-1, -2, -3) of foot-and-mouth disease viruses (FMDVs) in their wildlife host, African buffalo. We combined data on viral dynamics and host immune responses with mathematical models to ask the following questions: How do viral and immune dynamics vary among strains? Which viral and immune parameters determine viral fitness within hosts? And how do within-host dynamics relate to virus transmission? Our data reveal contrasting within-host dynamics among viral strains, with SAT-2 eliciting more rapid and effective immune responses than SAT-1 and SAT-3. Within-host viral fitness was overwhelmingly determined by variation among hosts in immune response activation rates but not by variation among individual hosts in viral growth rate. Our analyses investigating across-scale linkages indicate that viral replication rate in the host correlates with transmission rates among buffalo and that adaptive immune activation rate determines the infectious period. These parameters define the virus's relative basic reproductive number (ℛ0), suggesting that viral invasion potential may be predictable from within-host dynamics.

How infection-triggered pathobionts influence virulence evolution

Host-pathogen interactions can be influenced by the host microbiota, as the microbiota can facilitate or prevent pathogen infections. In addition, members of the microbiota can become virulent. Such pathobionts can cause co-infections when a pathogen infection alters the host immune system and triggers dysbiosis. Here we performed a theoretical investigation of how pathobiont co-infections affect the evolution of pathogen virulence. We explored the possibility that the likelihood of pathobiont co-infection depends on the evolving virulence of the pathogen. We found that, in contrast to the expectation from classical theory, increased virulence is not always selected for. For an increasing likelihood of co-infection with increasing pathogen virulence, we found scenario-specific selection for either increased or decreased virulence. Evolutionary changes, however, in pathogen virulence do not always translate into similar changes in combined virulence of the pathogen and the pathobiont. Only in one of the scenarios where pathobiont co-infection is triggered above a specific virulence level we found a reduction in combined virulence. This was not the case when the probability of pathobiont co-infection linearly increased with pathogen virulence. Taken together, our study draws attention to the possibility that host-microbiota interactions can be both the driver and the target of pathogen evolution. This article is part of the theme issue 'Sculpting the microbiome: how host factors determine and respond to microbial colonization'.

Rapid Evolution of Resistance and Tolerance Leads to Variable Host Recoveries following Disease-Induced Declines

AbstractRecoveries of populations that have suffered severe disease-induced declines are being observed across disparate taxa. Yet we lack theoretical understanding of the drivers and dynamics of recovery in host populations and communities impacted by infectious disease. Motivated by disease-induced declines and nascent recoveries in amphibians, we developed a model to ask the following question: How does the rapid evolution of different host defense strategies affect the transient recovery trajectories of hosts following pathogen invasion and disease-induced declines? We found that while host life history is predictably a major driver of variability in population recovery trajectories (including declines and recoveries), populations that use different host defense strategies (i.e., tolerance, avoidance resistance, and intensity-reduction resistance) experience notably different recoveries. In single-species host populations, populations evolving tolerance recovered on average four times slower than populations evolving resistance. Moreover, while populations using avoidance resistance strategies had the fastest potential recovery rates, these populations could get trapped in long transient states at low abundance prior to recovery. In contrast, the recovery of populations evolving intensity-reduction resistance strategies were more consistent across ecological contexts. Overall, host defense strategies strongly affect the transient dynamics of population recovery and may affect the ultimate fate of real populations recovering from disease-induced declines.

Markets as drivers of selection for highly virulent poultry pathogens

Theoretical models have successfully predicted the evolution of poultry pathogen virulence in industrialized farm contexts of broiler chicken populations. Whether there are ecological factors specific to more traditional rural farming that affect virulence is an open question. Within non-industrialized farming networks, live bird markets are known to be hotspots of transmission, but whether they could shift selection pressures on the evolution of poultry pathogen virulence has not been addressed. Here, we revisit predictions for the evolution of virulence for viral poultry pathogens, such as Newcastle's disease virus, Marek's disease virus, and influenza virus, H5N1, using a compartmental model that represents transmission in rural markets. We show that both the higher turnover rate and higher environmental persistence in markets relative to farms could select for higher optimal virulence strategies. In contrast to theoretical results modeling industrialized poultry farms, we find that cleaning could also select for decreased virulence in the live poultry market setting. Additionally, we predict that more virulent strategies selected in markets could circulate solely within poultry located in markets. Thus, we recommend the close monitoring of markets not only as hotspots of transmission, but as potential sources of more virulent strains of poultry pathogens.

Robustness versus productivity during evolutionary community assembly: short-term synergies and long-term trade-offs

The realization that evolutionary feedbacks need to be considered to fully grasp ecological dynamics has sparked interest in the effect of evolution on community properties like coexistence and productivity. However, little is known about the evolution of community robustness and productivity along diversification processes in species-rich systems. We leverage the recent structural approach to coexistence together with adaptive dynamics to study such properties and their relationships in a general trait-based model of competition on a niche axis. We show that the effects of coevolution on coexistence are two-fold and contrasting depending on the time scale considered. In the short term, evolution of niche differentiation strengthens coexistence, while long-term diversification leads to niche packing and decreased robustness. Moreover, we find that coevolved communities tend to be on average more robust and more productive than non-evolutionary assemblages. We illustrate how our theoretical predictions echo in observed empirical patterns and the implications of our results for empiricists and applied ecologists. We suggest that some of our results such as the improved robustness of Evolutionarily Stable Communities could be tested experimentally in suitable model systems.

Immunity-driven evolution of virulence and diversity in respiratory diseases

The time-honored paradigm in the theory of virulence evolution assumes a positive relation between infectivity and harmfulness. However, the etiology of respiratory diseases yields a negative relation, with diseases of the lower respiratory tract being less infective and more harmful. We explore the evolutionary consequences in a simple model incorporating cross-immunity between disease strains that diminishes with their distance in the respiratory tract, assuming that docking rate follows the match between the local mix of cell surface types and the pathogen's surface and cross-immunity the similarity of the pathogens' surfaces. The assumed relation between fitness components causes virulent strains infecting the lower airways to evolve to milder more transmissible variants. Limited cross-immunity, generally, causes a readiness to diversify that increases with host population density. In respiratory diseases that diversity will be highest in the upper respiratory tract. More tentatively, emerging respiratory diseases are likely to start low and virulent, to evolve up, and become milder. Our results extend to a panoply of realistic generalizations of the disease's ecology to including additional epitope axes. These extensions allow us to apply our results quantitatively to elucidate the differences in diversification between rhino- and coronavirus caused common colds.

Evolutionary stability of antigenically escaping viruses

Antigenic variation is the main immune escape mechanism for RNA viruses like influenza or SARS-CoV-2. While high mutation rates promote antigenic escape, they also induce large mutational loads and reduced fitness. It remains unclear how this cost-benefit trade-off selects the mutation rate of viruses. Using a traveling wave model for the coevolution of viruses and host immune systems in a finite population, we investigate how immunity affects the evolution of the mutation rate and other nonantigenic traits, such as virulence. We first show that the nature of the wave depends on how cross-reactive immune systems are, reconciling previous approaches. The immune-virus system behaves like a Fisher wave at low cross-reactivities, and like a fitness wave at high cross-reactivities. These regimes predict different outcomes for the evolution of nonantigenic traits. At low cross-reactivities, the evolutionarily stable strategy is to maximize the speed of the wave, implying a higher mutation rate and increased virulence. At large cross-reactivities, where our estimates place H3N2 influenza, the stable strategy is to increase the basic reproductive number, keeping the mutation rate to a minimum and virulence low.

Evolution of pathogens with cross-immunity in response to healthcare interventions

Cross-immunity, as an evolutionary driver, can contribute to pathogen evolution, particularly pathogen diversity. Healthcare interventions aimed at reducing disease severity or transmission are commonly used to control diseases and can also induce pathogen evolution. Understanding pathogen evolution in the context of cross-immunity and healthcare interventions is crucial for infection control. This study starts by modelling cross-immunity, the extent of which is determined by strain traits and host characteristics. Given that all hosts have the same characteristics, full cross-immunity between residents and mutants occurs when mutation step sizes are small enough. Cross-immunity can be partial when the step size is large. The presence of partial cross-immunity reduces pathogen load and shortens the infectious period inside hosts, reducing transmission between hosts and improving host population survival and recovery. This study focuses on how pathogens evolve through small and large mutational steps and how healthcare interventions affect pathogen evolution. Using the theory of adaptive dynamics, we found that when mutational steps are small (only full cross-immunity is present), pathogen diversity cannot occur because it maximises the basic reproduction number. This results in intermediate values for both pathogen growth and clearance rates. However, when large mutational steps are allowed (with full and partial cross-immunity present), pathogens can evolve into multiple strains and induce pathogen diversity. The study also shows that different healthcare interventions can have varying effects on pathogen evolution. Generally, low levels of intervention are more likely to induce strain diversity, while high levels are more likely to result in strain reduction.

Extending eco-evolutionary theory with oligomorphic dynamics

Understanding the interplay between ecological processes and the evolutionary dynamics of quantitative traits in natural systems remains a major challenge. Two main theoretical frameworks are used to address this question, adaptive dynamics and quantitative genetics, both of which have strengths and limitations and are often used by distinct research communities to address different questions. In order to make progress, new theoretical developments are needed that integrate these approaches and strengthen the link to empirical data. Here, we discuss a novel theoretical framework that bridges the gap between quantitative genetics and adaptive dynamics approaches. 'Oligomorphic dynamics' can be used to analyse eco-evolutionary dynamics across different time scales and extends quantitative genetics theory to account for multimodal trait distributions, the dynamical nature of genetic variance, the potential for disruptive selection due to ecological feedbacks, and the non-normal or skewed trait distributions encountered in nature. Oligomorphic dynamics explicitly takes into account the effect of environmental feedback, such as frequency- and density-dependent selection, on the dynamics of multi-modal trait distributions and we argue it has the potential to facilitate a much tighter integration between eco-evolutionary theory and empirical data.

Investigating and combatting the key drivers of viral zoonoses in Africa: an analysis of eight epidemics

Investigating the interplay of factors that result in a viral zoonotic outbreak is difficult, though it is increasingly important. As anthropogenic influences shift the delicate balance of ecosystems, new zoonoses emerge in humans. Sub-Saharan Africa is a notable hotspot for zoonotic disease due to abundant competent mammalian reservoir hosts. Furthermore, poverty, corruption, and an overreliance on natural resources play considerable roles in depleting biological resources, exacerbating the population's susceptibility. Unsurprisingly, viral zoonoses have emerged in Africa, including HIV/AIDS, Ebola, Avian influenza, Lassa fever, Zika, and Monkeypox. These diseases are among the principal causes of death in endemic areas. Though typically distinct in their manifestations, viral zoonoses are connected by underlying, definitive factors. This review summarises vital findings on viral zoonoses in Africa using nine notable case studies as a benchmark for future studies. We discuss the importance of ecological recuperation and protection as a central strategy to control zoonotic diseases. Emphasis was made on moderating key drivers of zoonotic diseases to forestall future pandemics. This is in conjunction with attempts to redirect efforts from reactive to pre-emptive through a multidisciplinary "one health" approach.

Growth bound and threshold dynamic for nonautonomous nondensely defined evolution problems

We propose a general framework for simultaneously calculating the threshold value for population growth and determining the sign of the growth bound of the evolution family generated by the problem below [Formula: see text]where [Formula: see text] is a Hille-Yosida linear operator (possibly unbounded, non-densely defined) on a Banach space [Formula: see text], and the maps [Formula: see text], [Formula: see text] are p-periodic in time and continuous in the operator norm topology. We give applications of our approach for two general examples of an age-structured model, and a delay differential system. Other examples concern the dynamics of a nonlocal problem arising in population genetics and the dynamics of a structured human-vector malaria model.

Coevolutionary Dynamics of Host Immune and Parasite Virulence Based on an Age-Structured Epidemic Model

Hosts can activate a defensive response to clear the parasite once being infected. To explore how host survival and fecundity are affected by host-parasite coevolution for chronic parasitic diseases, in this paper, we proposed an age-structured epidemic model with infection age, in which the parasite transmission rate and parasite-induced mortality rate are structured by the infection age. By use of critical function analysis method, we obtained the existence of the host immune evolutionary singular strategy which is a continuous singular strategy (CSS). Assume that parasite-induced mortality begins at infection age [Formula: see text] and is constant v thereafter. We got that the value of the CSS, [Formula: see text], monotonically decreases with respect to infection age [Formula: see text] (see Case (I)), while it is non-monotone if the constant v positively depends on the immune trait c (see Case (II)). This non-monotonicity is verified by numerical simulations and implies that the direction of immune evolution depends on the initial value of immune trait. Besides that, we adopted two special forms of the parasite transmission rate to study the parasite's virulence evolution, by maximizing the basic reproduction ratio [Formula: see text]. The values of the convergence stable parasite's virulence evolutionary singular strategies [Formula: see text] and [Formula: see text] increase monotonically with respect to time lag L (i.e., the time lag between the onset of transmission and mortality). At the singular strategy [Formula: see text] and [Formula: see text], we further obtained the expressions of the case mortalities [Formula: see text] and how they are affected by the time lag L. Finally, we only presented some preliminary results about host and parasite coevolution dynamics, including a general condition under which the coevolutionary singular strategy [Formula: see text] is evolutionarily stable.

Virulence evolution of Toxoplasma gondii within a multi‐host system

Current research on the virulence evolution of Toxoplasma gondii is mainly conducted via experiments, and studies using mathematical models are still limited. Here, we constructed a complex cycle model of T. gondii in a multi-host system considering multiple transmission routes and cat-mouse interaction. Based on this model, we studied how the virulence of T. gondii evolves with the factors related to transmission routes and the regulation of infection on host behavior under an adaptive dynamics framework. The study shows that all factors that enhance the role of mice favored decreased virulence of T. gondii, except the decay rate of oocysts that led to different evolutionary trajectories under different vertical transmission. The same was true of the environmental infection rate of cats, whose effect was different under different vertical transmission. The effect of the regulation factor on the virulence evolution of T. gondii was the same as that of the inherent predation rate depending on its net effect on direct and vertical transmissions. The global sensitivity analysis on the evolutionary outcome suggests that changing the vertical infection rate and decay rate was most effective in regulating the virulence of T. gondii. Furthermore, the presence of coinfection would favor virulent T. gondii and make evolutionary bifurcation easy to occur. The results reveal that the virulence evolution of T. gondii had a compromise between adapting to different transmission routes and maintaining the cat-mouse interaction thereby leading to different evolutionary scenarios. This highlights the significance of evolutionary ecological feedback to evolution. In addition, the qualitative verification of T. gondii virulence evolution in different areas by the present framework will provide a new perspective for the study of evolution.

Study on the virulence evolution of SARS-CoV-2 and the trend of the epidemics of COVID-19

This is the first attempt to investigate the effects of the factors related to non-pharmaceutical interventions (NPIs) and the physical condition of the public on virulence evolution of SARS-CoV-2 and the trend of the epidemics of COVID-19 under an adaptive dynamics framework. Qualitative agreement of the prediction on the epidemics of COVID-19 with the actual situations convinced the rationality of the present model. The study showed that enhancing both NPIs (including public vigilance, quarantine measures, and hospitalization) and the physical condition of the public (including susceptibility and recovery speed) contributed to decreasing the prevalence of COVID-19 but only increasing public vigilance and decreasing the susceptibility of the public could also reduce the virulence of SARS-CoV-2. Therefore, controlling the contact rate and infection rate was the key to control not only the epidemic scale of COVID-19 but also the extent of its harm. On the other hand, the best way to control the epidemics was to increase the public vigilance and physical condition because both of them could reduce the prevalence and case fatality rate (CFR) of COVID-19. In addition, the enhancement of quarantine measures and hospitalization could bring the (slight) increase in the CFR of COVID-19.

Parasite-induced shifts in host movement may explain the transient coexistence of high- and low-pathogenic disease strains

Many parasites induce decreased host movement, known as lethargy, which can impact disease spread and the evolution of virulence. Mathematical models have investigated virulence evolution when parasites cause host death, but disease-induced decreased host movement has received relatively less attention. Here, we consider a model where, due to the within-host parasite replication rate, an infected host can become lethargic and shift from a moving to a resting state, where it can die. We find that when the lethargy and disease-induced mortality costs to the parasites are not high, then evolutionary bistability can arise, and either moderate or high virulence can evolve depending on the initial virulence and the magnitude of mutation. These results suggest, firstly, the coexistence of strains with different virulence, which may explain the transient coexistence of low- and high-pathogenic strains of avian influenza viruses, and secondly, that medical interventions to treat the symptoms of lethargy or prevent disease-induced host deaths can result in a large jump in virulence and the rapid evolution of high virulence. In complement to existing results that show bistability when hosts are heterogeneous at the population level, we show that evolutionary bistability may arise due to transmission heterogeneity at the individual host level.

Host phenology can drive the evolution of intermediate virulence strategies in some obligate-killer parasites

Traditional mechanistic trade-offs between transmission and virulence are the foundation of nearly all theory on parasite virulence evolution. For obligate-host killer parasites, evolution toward intermediate virulence depends on a trade-off between virulence (time to death) and transmission (the number of progeny released upon death). Although several ecological factors impact optimal virulence strategies constrained by trade-offs, these factors have been insufficient to explain the intermediate virulence levels observed in nature. The timing of seasonal activity, or phenology, is a factor that commonly influences ecological interactions but is difficult to incorporate into virulence evolution studies. We present a mathematical model of a seasonal obligate-killer parasite to study the impact of host phenology on virulence evolution. The model demonstrates that host phenology can select for intermediate parasite virulence even when a traditional mechanistic trade-off between transmission and virulence is omitted. The optimal virulence strategy is impacted by both the host activity period duration and the host emergence timing variation. Parasites with lower virulence strategies are favored in environments with longer host activity periods and when hosts emerge synchronously. The results demonstrate that host phenology can be sufficient to select for intermediate virulence strategies, providing an alternative driver of virulence evolution in some natural systems.

Evolution of prudent predation in complex food webs

Prudent predators catch sufficient prey to sustain their populations but not as much as to undermine their populations' survival. The idea that predators evolve to be prudent has been dismissed in the 1970s, but the arguments invoked then are untenable in the light of modern evolution theory. The evolution of prudent predation has repeatedly been demonstrated in two-species predator-prey metacommunity models. However, the vigorous population fluctuations that these models predict are not widely observed. Here we show that in complex model food webs prudent predation evolves as a result of consumer-mediated ('apparent') competitive exclusion of resources, which disadvantages aggressive consumers and does not generate such fluctuations. We make testable predictions for empirical signatures of this mechanism and its outcomes. Then we discuss how these predictions are borne out across freshwater, marine and terrestrial ecosystems. Demonstrating explanatory power of evolved prudent predation well beyond the question of predator-prey coexistence, the predicted signatures explain unexpected declines of invasive alien species, the shape of stock-recruitment relations of fish, and the clearance rates of pelagic consumers across the latitudinal gradient and 15 orders of magnitude in body mass. Specific research to further test this theory is proposed.

Tripartite interactions: how immunity, microbiota and pathogens interact and affect pathogen virulence evolution

The bipartite interactions between insect hosts and their bacterial gut microbiota, or their bacterial pathogens, are empirically and theoretically well-explored. However, direct, and indirect tripartite interactions will also likely occur inside a host. These interactions will almost certainly affect the trajectory of pathogen virulence evolution, an area that is currently under researched. The interactions within tripartite associations can be competitive, that is, exploitative-competition, interference-competition or apparent-competition. Competitive interactions will be significantly influenced by non-competitive effects, for example, immunopathology, immunosuppression, and microbiota-mediated tolerance. Considering a combination of these interactions and effects, will enable an increased understanding of the evolution of pathogen virulence. This new perspective allows us to identify several novel research questions, which we hope will be a useful framework for future research.

Host phenology regulates parasite-host demographic cycles and eco-evolutionary feedbacks

Parasite-host interactions can drive periodic population dynamics when parasites overexploit host populations. The timing of host seasonal activity, or host phenology, determines the frequency and demographic impact of parasite-host interactions, which may govern whether parasites sufficiently overexploit hosts to drive population cycles. We describe a mathematical model of a monocyclic, obligate-killer parasite system with seasonal host activity to investigate the consequences of host phenology on host-parasite dynamics. The results suggest that parasites can reach the densities necessary to destabilize host dynamics and drive cycling as they adapt, but only in some phenological scenarios such as environments with short seasons and synchronous host emergence. Furthermore, only parasite lineages that are sufficiently adapted to phenological scenarios with short seasons and synchronous host emergence can achieve the densities necessary to overexploit hosts and produce population cycles. Host-parasite cycles also generate an eco-evolutionary feedback that slows parasite adaptation to the phenological environment as rare advantageous phenotypes can be driven extinct due to a population bottleneck depending on when they are introduced in the cycle. The results demonstrate that seasonal environments can drive population cycling in a restricted set of phenological patterns and provide further evidence that the rate of adaptive evolution depends on underlying ecological dynamics.

The importance of ecological dynamics in evolutionary processes: a host-bacteriophage model revisited

A recent study of adaptive dynamics of lysis propensity in temperate phages suggested that full lysogeny emerges as the outcome of bacteriophage evolution in a simple host-phage system. The conclusion is based on the premise that mutant strains necessarily appear in equilibrium host-phage environments. Revisiting the model, we show that the ecological system exhibits richer asymptotic dynamics and that, in a certain parameter regime, evolution may in fact drive lysis propensity towards an evolutionary singularity in which a non-zero proportion of phages initiate infection in a lytic cycle. These singularities act as points of evolutionary diversification, leading to periodic coexistence of two distinct phage strains on the evolutionary time-scale. One of the two strains in the dimorphic evolutionary singularity is fully lysogenic (in the sense that cell infection always leads to lysogeny), while the other is partially lytic. Our study thus highlights the importance of ecological interactions as a driver of evolution.

The role of a programmatic immune response on the evolution of pathogen traits

In modelling pathogen evolution during epidemics, it is important to understand the interactions between within-host infection dynamics and between-host pathogen transmission. Multiscale models often assume an immune response that is highly responsive to pathogen dynamics. Empirical evidence, however, suggests that the immune response in acute infections is triggered and programmatic. This leads to somewhat more predictable infection trajectories where transition times and, consequently, the infectious window are non-exponentially distributed. Here, we develop a within-host model where the immune response is triggered by pathogen growth but otherwise develops independently, and use this to obtain analytic expressions for the infectious period and peak pathogen load. This allows us to model the basic reproductive number in terms of explicit functional relationships among within-host traits including the growth rate of the pathogen. We find that the dependence of pathogen load and the infectious window on within-host parameters constrains the evolution of the pathogen growth rate. At low growth rate, selection favours a higher pathogen load and therefore increasing pathogen growth rate. At high growth rates, selection for a longer infectious window trades off against selection against the effects of virulence. At intermediate growth rates the basic reproductive number is relatively insensitive to changes in the growth rate. The resulting "flat" region of the pathogen fitness landscape is due to the stability of the programmatic immune response in clearing the infection.

Antigenic escape selects for the evolution of higher pathogen transmission and virulence

Despite the propensity for complex and non-equilibrium dynamics in nature, eco-evolutionary analytical theory typically assumes that populations are at equilibria. In particular, pathogens often show antigenic escape from host immune defences, leading to repeated epidemics, fluctuating selection and diversification, but we do not understand how this impacts the evolution of virulence. We model the impact of antigenic drift and escape on the evolution of virulence in a generalized pathogen and apply a recently introduced oligomorphic methodology that captures the dynamics of the mean and variance of traits, to show analytically that these non-equilibrium dynamics select for the long-term persistence of more acute pathogens with higher virulence. Our analysis predicts both the timings and outcomes of antigenic shifts leading to repeated epidemics and predicts the increase in variation in both antigenicity and virulence before antigenic escape. There is considerable variation in the degree of antigenic escape that occurs across pathogens and our results may help to explain the difference in virulence between related pathogens including, potentially, human influenzas. Furthermore, it follows that these pathogens will have a lower R₀, with clear implications for epidemic behaviour, endemic behaviour and control. More generally, our results show the importance of examining the evolutionary consequences of non-equilibrium dynamics.

An epi-evolutionary model for predicting the adaptation of spore-producing pathogens to quantitative resistance in heterogeneous environments

We have modeled the evolutionary epidemiology of spore-producing plant pathogens in heterogeneous environments sown with several cultivars carrying quantitative resistances. The model explicitly tracks the infection-age structure and genetic composition of the pathogen population. Each strain is characterized by pathogenicity traits determining its infection efficiency and a time-varying sporulation curve taking into account lesion aging. We first derived a general expression of the basic reproduction number R 0 for fungal pathogens in heterogeneous environments. We show that the evolutionary attractors of the model coincide with local maxima of R 0 only if the infection efficiency is the same on all host types. We then studied the contribution of three basic resistance characteristics (the pathogenicity trait targeted, resistance effectiveness, and adaptation cost), in interaction with the deployment strategy (proportion of fields sown with a resistant cultivar), to (i) pathogen diversification at equilibrium and (ii) the shaping of transient dynamics from evolutionary and epidemiological perspectives. We show that quantitative resistance affecting only the sporulation curve will always lead to a monomorphic population, whereas dimorphism (i.e., pathogen diversification) can occur if resistance alters infection efficiency, notably with high adaptation costs and proportions of the resistant cultivar. Accordingly, the choice of the quantitative resistance genes operated by plant breeders is a driver of pathogen diversification. From an evolutionary perspective, the time to emergence of the evolutionary attractor best adapted to the resistant cultivar tends to be shorter when resistance affects infection efficiency than when it affects sporulation. Conversely, from an epidemiological perspective, epidemiological control is always greater when the resistance affects infection efficiency. This highlights the difficulty of defining deployment strategies for quantitative resistance simultaneously maximizing epidemiological and evolutionary outcomes.

SARS-CoV-2 virulence evolution: Avirulence theory, immunity and trade-offs

The COVID-19 pandemic has led to a resurgence of the debate on whether host-parasite interactions should evolve towards avirulence. In this review, we first show that SARS-CoV-2 virulence is evolving, before explaining why some expect the mortality caused by the epidemic to converge towards that of human seasonal alphacoronaviruses. Leaning on existing theory, we then include viral evolution into the picture and discuss hypotheses explaining why the virulence has increased since the beginning of the pandemic. Finally, we mention some potential scenarios for the future.

Integrating Infection Intensity into Within- and Between-Host Pathogen Dynamics: Implications for Invasion and Virulence Evolution

AbstractInfection intensity can dictate disease outcomes but is typically ignored when modeling infection dynamics of microparasites (e.g., bacteria, virus, and fungi). However, for a number of pathogens of wildlife typically categorized as microparasites, accounting for infection intensity and within-host infection processes is critical for predicting population-level responses to pathogen invasion. Here, we develop a modeling framework we refer to as reduced-dimension host-parasite integral projection models (reduced IPMs) that we use to explore how within-host infection processes affect the dynamics of pathogen invasion and virulence evolution. We find that individual-level heterogeneity in pathogen load-a nearly ubiquitous characteristic of host-parasite interactions that is rarely considered in models of microparasites-generally reduces pathogen invasion probability and dampens virulence-transmission trade-offs in host-parasite systems. The latter effect likely contributes to widely predicted virulence-transmission trade-offs being difficult to observe empirically. Moreover, our analyses show that intensity-dependent host mortality does not always induce a virulence-transmission trade-off, and systems with steeper than linear relationships between pathogen intensity and host mortality rate are significantly more likely to exhibit these trade-offs. Overall, reduced IPMs provide a useful framework to expand our theoretical and data-driven understanding of how within-host processes affect population-level disease dynamics.

Experimental evidence that host choice by parasites is age-dependent in a fish-monogenean system

Host age is known to influence the risk of parasite infection, but there is very little experimental evidence on whether parasites show preference towards potential hosts of a specific age. To investigate how host age affects host choice by parasites, we used the Nile tilapia (Oreochromis niloticus) as a fish parasite model and manipulated its gill ectoparasitic monogeneans in mesocosm experiments. Our experimental setting combined three age classes (juvenile, subadult, and adult) of both infected donor hosts and uninfected potential target hosts assigned to each treatment. We predicted that adult target hosts would be more susceptible to parasites than juveniles and adults because they represent high-quality habitat patches. Contrary to our prediction, we found that subadults were more susceptible to parasites than juvenile and adult target hosts. Our models confirmed that variation in target host age influenced parasite choice, suggesting that subadults might represent the most favourable option for parasites regarding a balance between host quality and susceptibility. We provide experimental evidence that host choice by parasites is age-dependent, and that this life-history trait can play a major role in structuring parasite populations.

The three Ts of virulence evolution during zoonotic emergence

There is increasing interest in the role that evolution may play in current and future pandemics, but there is often also considerable confusion about the actual evolutionary predictions. This may be, in part, due to a historical separation of evolutionary and medical fields, but there is a large, somewhat nuanced body of evidence-supported theory on the evolution of infectious disease. In this review, we synthesize this evolutionary theory in order to provide a framework for clearer understanding of the key principles. Specifically, we discuss the selection acting on zoonotic pathogens' transmission rates and virulence at spillover and during emergence. We explain how the direction and strength of selection during epidemics of emerging zoonotic disease can be understood by a three Ts framework: trade-offs, transmission, and time scales. Virulence and transmission rate may trade-off, but transmission rate is likely to be favoured by selection early in emergence, particularly if maladapted zoonotic pathogens have 'no-cost' transmission rate improving mutations available to them. Additionally, the optimal virulence and transmission rates can shift with the time scale of the epidemic. Predicting pathogen evolution, therefore, depends on understanding both the trade-offs of transmission-improving mutations and the time scales of selection.

Evolution of human respiratory virus epidemics

Background: Pathogens are often assumed to evolve towards reduced virulence, but counterexamples abound. Faced with a new pathogen, such as SARS-CoV-2, it is crucial to be able to forecast the case fatality rate (CFR) and the overall disease burden. Considerable effort has been invested towards developing a mathematical framework for predicting virulence evolution. Although many approaches accurately recapitulate complex outcomes, most rely on an assumed trade-off between CFR and infection rate. It is often impractical to empirically validate this constraint for human pathogens. Methods: A compartment model with parameters tuning the degree to which symptomatic individuals are isolated and the duration of immunity is constructed and evaluated at both short timescales and at equilibrium. Results: We reveal kinetic constraints whereby variation of multiple parameters in concert leads to decreased CFR and increased pathogen fitness, whereas independent variation of the parameters decreases pathogen fitness. Smallpox, SARS-CoV-2, and influenza are analyzed as diverse representatives of human respiratory viruses. We show that highly virulent viruses, such as smallpox, are often constrained by the host behavior, whereas moderately virulent viruses, such as SARS-CoV-2, appear to be typically constrained by the relationship between the duration of immunity and CFR. Conclusions: Evolution of human respiratory epidemics appears to be often kinetically constrained and a reduction in CFR should not be assumed. These results agree with previous work demonstrating an increase in virulence for smallpox and further predict that SARS-CoV-2 is likely to continue presenting a substantial disease burden. Herd immunity against SARS-CoV-2 and viruses with similar life history traits might be unachievable without vaccination. However, partial isolation of symptomatic individuals can have a major effect on the epidemic dynamics not only by reducing the number of fatalities in the short term but also by changing the evolutionary trajectory of moderate CFR viruses towards reduced CFR.

Evolution of human respiratory virus epidemics

Background: It is often assumed that pathogens evolve towards reduced virulence, but counterexamples abound. Faced with a new pathogen, such as SARS-CoV-2, it is highly desirable to be able to forecast the case fatality rate (CFR) and overall disease burden into the future. Considerable effort has been invested towards the development of a mathematical framework for predicting virulence evolution. Although many approaches accurately recapitulate complex outcomes, most rely on an assumed trade-off between CFR and infection rate. It is often impractical to empirically validate this constraint for human pathogens. Methods: A compartment model with parameters tuning the degree to which symptomatic individuals are isolated and the duration of immunity is constructed and evaluated at both short timescales and at equilibrium (when it exists). Results: We reveal kinetic constraints where the variation of multiple parameters in concert leads to decreased CFR and increased pathogen fitness, whereas independent variation of the parameters decreases pathogen fitness. Smallpox, SARS-CoV-2, and influenza are analyzed as diverse representatives of human respiratory viruses. We show that highly virulent viruses, such as smallpox, are likely often constrained by host behavior, whereas moderately virulent viruses, such as SARS-CoV-2, appear to be typically constrained by the relationship between the duration of immunity and CFR. Conclusions: Evolution of human respiratory epidemics appears to be often kinetically constrained and a reduction in CFR should not be assumed. Our findings imply that, without continued public health intervention, SARS-CoV-2 is likely to continue presenting a substantial disease burden. The existence of a parameter regime admitting endemic equilibrium suggests that herd immunity is unachievable. However, we demonstrate that even partial isolation of symptomatic individuals can have a major effect not only by reducing the number of fatalities in the short term but also by potentially changing the evolutionary trajectory of the virus towards reduced CFR.

Migration and tolerance shape host behaviour and response to parasite infection

Numerous theoretical models have demonstrated that migration, a seasonal animal movement behaviour, can minimize the risks and costs of parasite infection. Past work on migration-infection interactions assumes migration is the only strategy available to organisms for dealing with the parasite infection, that is they migrate to a different environment to recover or escape from infection. Thus, migration is similar to the non-spatial strategy of resistance, where hosts prevent infection or kill parasites once infected. However, an alternative defence strategy is to tolerate the infection and experience a lower cost to the infection. To our knowledge, no studies have examined how migration can change based on combining two host strategies (migration and tolerance) for dealing with parasites. In this paper, we aim to understand how both parasite transmission and infection tolerance can influence the host's migratory behaviour. We constructed a model that incorporates two host strategies (migration and tolerance) to understand whether allowing for tolerance affects the proportion of the population that migrates at equilibrium in response to infection. We show that the benefits of tolerance can either decrease or increase the host's migration. Also, if the benefit of migration is great, then individuals are more likely to migrate regardless of the presence of tolerance. Finally, we find that the transmission rate of parasite infection can either decrease or increase the tolerant host's migration, depending on the cost of migration. These findings highlight that adopting two defence strategies is not always beneficial to the hosts. Instead, a single strategy is often better, depending on the costs and benefits of the strategies and infection pressures. Our work further suggests that multiple host-defence strategies as a potential explanation for the evolution of migration to minimize the parasite infection. Moreover, migration can also affect the ecological and evolutionary dynamics of parasite-host interactions.

Epidemiological and evolutionary consequences of periodicity in treatment coverage

Host heterogeneity is a key driver of host-pathogen dynamics. In particular, the use of treatments against infectious diseases creates variation in quality among hosts, which can have both epidemiological and evolutionary consequences. We present a general theoretical model to highlight the consequences of different imperfect treatments on pathogen prevalence and evolution. These treatments differ in their action on host and pathogen traits. In contrast with previous studies, we assume that treatment coverage can vary in time, as in seasonal or pulsed treatment strategies. We show that periodic treatment strategies can limit both disease spread and virulence evolution, depending on the type of treatment. We also introduce a new method to analytically calculate the selection gradient in periodic environments, which allows our predictions to be interpreted using the concept of reproductive value, and can be applied more generally to analyse eco-evolutionary dynamics in class-structured populations and fluctuating environments.

Evolution and Maintenance of Mutualism between Tubeworms and Sulfur-Oxidizing Bacteria

AbstractTubeworms and sulfur-oxidizing bacteria mutualism, an essential part of the chemosynthetic ecosystem in the deep sea, has several puzzling features. After acquiring sulfur-oxidizing bacteria from the environment, tubeworms become fully dependent on their symbiont bacteria for nutrient intake. Once ingested by the tubeworm larva, no additional symbionts join from the environment, and no symbionts are released until the host tubeworm dies. Despite this very narrow window to acquire symbionts, some tubeworm species can live for >200 years. Such a restricted release of symbionts could lead to a shortage of symbiont bacteria in the environment without which tubeworms could not survive. In our study, we examine the conditions under which this mutualism can persist and whether the host mortality rate evolves toward a low value using a mathematical model for the tubeworm-symbiont bacteria system. Our model reveals that mutualism can persist only when the host mortality rate is within an intermediate range. With cohabitation of multiple symbionts strains in the same host, host mortality rate evolves toward a low value without driving either host or symbiont to extinction when competition among symbionts is weak and their growth within a host is slow. We also find the parameter conditions that lead to unlimited evolutionary escalation of host mortality rate toward coextinction of both tubeworms and symbionts populations (evolutionary double suicide). The generality of this evolutionary fragility in obligate mutualistic systems as well as the contrasting evolutionary robustness in host-parasite systems are discussed.

Population Genomics of Plant Viruses: The Ecology and Evolution of Virus Emergence

The genomics era has revolutionized studies of adaptive evolution by monitoring large numbers of loci throughout the genomes of many individuals. Ideally, the investigation of emergence in plant viruses requires examining the population dynamics of both virus and host, their interactions with each other, with other organisms and the abiotic environment. Genetic mechanisms that affect demographic processes are now being studied with high-throughput technologies, traditional genetics methods, and new computational tools for big-data. In this review, we discuss the utility of these approaches to monitor and detect changes in virus populations within cells and individuals, and over wider areas across species and communities of ecosystems. The advent of genomics in virology has fostered a multidisciplinary approach to tackling disease risk. The ability to make sense of the information now generated in this integrated setting is by far the most substantial obstacle to the ultimate goal of plant virology to minimize the threats to food security posed by disease. To achieve this goal, it is imperative to understand and forecast how populations respond to future changes in complex natural systems.

The SIR dynamic model of infectious disease transmission and its analogy with chemical kinetics

Mathematical models of the dynamics of infectious disease transmission are used to forecast epidemics and assess mitigation strategies. In this article, we highlight the analogy between the dynamics of disease transmission and chemical reaction kinetics while providing an exposition on the classic Susceptible–Infectious–Removed (SIR) epidemic model. Particularly, the SIR model resembles a dynamic model of a batch reactor carrying out an autocatalytic reaction with catalyst deactivation. This analogy between disease transmission and chemical reaction enables the exchange of ideas between epidemic and chemical kinetic modeling communities.

The problem of mediocre generalists: population genetics and eco-evolutionary perspectives on host breadth evolution in pathogens

Many of our theories for the generation and maintenance of diversity in nature depend on the existence of specialist biotic interactions which, in host-pathogen systems, also shape cross-species disease emergence. As such, niche breadth evolution, especially in host-parasite systems, remains a central focus in ecology and evolution. The predominant explanation for the existence of specialization in the literature is that niche breadth is constrained by trade-offs, such that a generalist is less fit on any particular environment than a given specialist. This trade-off theory has been used to predict niche breadth (co)evolution in both population genetics and eco-evolutionary models, with the different modelling methods providing separate, complementary insights. However, trade-offs may be far from universal, so population genetics theory has also proposed alternate mechanisms for costly generalism, including mutation accumulation. However, these mechanisms have yet to be integrated into eco-evolutionary models in order to understand how the mechanism of costly generalism alters the biological and ecological circumstances predicted to maintain specialism. In this review, we outline how population genetics and eco-evolutionary models based on trade-offs have provided insights for parasite niche breadth evolution and argue that the population genetics-derived mutation accumulation theory needs to be better integrated into eco-evolutionary theory.

Factors favouring the evolution of multidrug resistance in bacteria

The evolution of multidrug antibiotic resistance in commensal bacteria is an important public health concern. Commensal bacteria such as Escherichia coli, Streptococcus pneumoniae or Staphylococcus aureus, are also opportunistic pathogens causing a large fraction of the community-acquired and hospital-acquired bacterial infections. Multidrug resistance (MDR) makes these infections harder to treat with antibiotics and may thus cause substantial additional morbidity and mortality. Here, we develop an evolutionary epidemiology model to identify the factors favouring the evolution of MDR in commensal bacteria. The model describes the evolution of antibiotic resistance in a commensal bacterial species evolving in a host population subjected to multiple antibiotic treatments. We combine statistical analysis of a large number of simulations and mathematical analysis to understand the model behaviour. We find that MDR evolves more readily when it is less costly than expected from the combinations of single resistances (positive epistasis). MDR frequently evolves when bacteria are in contact with multiple drugs prescribed in the host population, even if individual hosts are only treated with a single drug at a time. MDR is favoured when the host population is structured in different classes that vary in their rates of antibiotic treatment. However, under most circumstances, recombination between loci involved in resistance does not meaningfully affect the equilibrium frequency of MDR. Together, these results suggest that MDR is a frequent evolutionary outcome in commensal bacteria that encounter the variety of antibiotics prescribed in the host population. A better characterization of the variability in antibiotic use across the host population (e.g. across age classes or geographical location) would help predict which MDR genotypes will most readily evolve.

Adaptation of Biotrophic Leaf Pathogens to Fertilization-Mediated Changes in Plant Traits: A Comparison of the Optimization Principle to Invasion Fitness

One of the conclusions of evolutionary ecology applied to agroecosystem management is that sustainable disease management strategies must be adaptive to overcome the immense adaptive potential of crop pathogens. In this context, knowledge of how pathogens adapt to changes in cultural practices is necessary. In this article we address the issue of the evolutionary response of biotrophic crop pathogens to changes in fertilization practices. For this purpose, we compare predictions of latent period evolution based on three empirical fitness measures (seasonal spore production, within-season exponential growth rate, and area under disease progress curves [AUDPCs]) with predictions based on the concept of invasion fitness from adaptive dynamics. We use pairwise invisibility plots to identify the evolutionarily stable strategies (ESSs) of the pathogen latent period. We find that the ESS latent period is in between the latent periods that maximize the seasonal spore production and the within-season exponential growth rate of the pathogen. The latent periods that maximize the AUDPC are similar to those of the ESS latent periods. The AUDPC may therefore be a critical variable to determine the issue of between-strain competition and shape pathogen evolution.

Flagellum expression and swimming activity by the zoonotic pathogen Escherichia albertii

Flagella are the well-known structural appendages used by bacteria for motility. Although generally reported to be non-motile, the enteropathogenic bacterial species Escherichia albertii produces flagella intermittently. We found that E. albertii expressed flagella under specific environmental conditions. After several generations (involving 4 to 12-h incubations), six of the twelve strains we investigated displayed swimming motility in various aquatic environments, including pond water containing nutrients from pigeon droppings (10% suspension) as well as in 20 × -diluted tryptic soy broth. The most significant motility determinant was a temperature between 15 and 30 °C. At 20 °C in the 10% pigeon-dropping suspension, microscopic observations revealed that some cells (1%-95% of six strains) showed swimming motility. Electron microscopy showed that the E. albertii cells expressed flagella. Lower concentrations of some substrates (including nutrients) may be of secondary importance for E. albertii flagella expression. Interestingly, the non-motile strains (n = 6/12) contained pseudogenes corresponding to essential flagella structural proteins. After being released from its host into surface water, E. albertii may express flagella to move toward nutrient sources or new hosts.

Modelling evolution of virulence in populations with a distributed parasite load

Modelling evolution of virulence in host-parasite systems is an actively developing area of research with ever-growing literature. However, most of the existing studies overlook the fact that individuals within an infected population may have a variable infection load, i.e. infected populations are naturally structured with respect to the parasite burden. Empirical data suggests that the mortality and infectiousness of individuals can strongly depend on their infection load; moreover, the shape of distribution of infection load may vary on ecological and evolutionary time scales. Here we show that distributed infection load may have important consequences for the eventual evolution of virulence as compared to a similar model without structuring. Mathematically, we consider an SI model, where the dynamics of the infected subpopulation is described by a von Förster-type equation, in which the infection load plays the role of age. We implement the adaptive dynamics framework to predict evolutionary outcomes in this model. We demonstrate that for simple trade-off functions between virulence, disease transmission and parasite growth rates, multiple evolutionary attractors are possible. Interestingly, unlike in the case of unstructured models, achieving an evolutionary stable strategy becomes possible even for a variation of a single ecological parameter (the parasite growth rate) and keeping the other parameters constant. We conclude that evolution in disease-structured populations is strongly mediated by alterations in the overall shape of the parasite load distribution.

Vector-borne parasite invasion in communities across space and time

While vector-borne parasite transmission often operates via generalist-feeding vectors facilitating cross-species transmission in host communities, theory describing the relationship between host species diversity and parasite invasion in these systems is underdeveloped. Host community composition and abundance vary across space and time, generating opportunities for parasite invasion. To explore how host community variation can modify parasite invasion potential, we develop a model for vector-borne parasite transmission dynamics that includes a host community of arbitrary richness and species' abundance. To compare invasion potential across communities, we calculate the community basic reproductive ratio of the parasite. We compare communities comprising a set of host species to their subsets, which allows for flexible scenario building including the introduction of novel host species and species loss. We allow vector abundance to scale with, or be independent of, community size, capturing regulation by feeding opportunities and non-host effects such as limited oviposition sites. Motivated by equivocal data relating host species competency to abundance, we characterize plausible host communities via phenomenological relationships between host species abundance and competency. We identify an underappreciated mechanism whereby changes to communities simultaneously alter average competency and the vector to host ratio and demonstrate that the interaction can profoundly influence invasion potential.

Antagonistic coevolution between hosts and sexually transmitted infections

Sexually transmitted infections (STIs) are predicted to play an important role in the evolution of host mating strategies, and vice versa, yet our understanding of host‐STI coevolution is limited. Previous theoretical work has shown mate choice can evolve to prevent runaway STI virulence evolution in chronic, sterilizing infections. Here, I generalize this theory to examine how a broader range of life‐history traits influence coevolution; specifically, how host preferences for healthy mates and STI virulence coevolve when infections are acute and can cause mortality or sterility, and hosts do not form long‐term sexual partnerships. I show that mate choice reduces both mortality and sterility virulence, with qualitatively different outcomes depending on the mode of virulence, costs associated with mate choice, recovery rates, and host lifespan. For example, fluctuating selection—a key finding in previous work—is most likely when hosts have moderate lifespans, STIs cause sterility and long infections, and costs of mate choice are low. The results reveal new insights into the coevolution of mate choice and STI virulence as different life‐history traits vary, providing increased support for parasite‐mediated sexual selection as a potential driver of host mate choice, and mate choice as a constraint on the evolution of virulence.

Vaccine-driven virulence evolution: consequences of unbalanced reductions in mortality and transmission and implications for pertussis vaccines

Many vaccines have heterogeneous effects across individuals. Additionally, some vaccines do not prevent infection, but reduce disease-associated mortality and transmission. Both of these factors will alter selection pressures on pathogens and thus shape the evolution of pathogen virulence. We use a mathematical modelling framework to show that (i) the balance of how vaccines reduce transmission versus mortality and (ii) individual variability in protection conferred both shape the evolution of pathogen virulence. Epidemiological (burden of disease) and evolutionary (pathogen virulence) outcomes are both worse when vaccines confer smaller reductions in transmission than in mortality. Furthermore, outcomes are modulated by variability in vaccine effects, with increased variability limiting the extent of virulence evolution but in some cases preventing eradication. These findings are pertinent to current concerns about the global resurgence of pertussis and the efficacy of pertussis vaccines, as the two classes of these vaccines may reduce disease symptoms without preventing infection and differ in their ability to reduce transmission. Furthermore, these findings point to the importance of generating precise predictions for virulence evolution in Bordetella pertussis (and other similar pathogens) by incorporating empirical characterizations of vaccine effects into models capturing the epidemiological details of this system.

Starving the Enemy? Feeding Behavior Shapes Host-Parasite Interactions

The loss of appetite that typically accompanies infection or mere exposure to parasites is traditionally considered a negative byproduct of infection, benefitting neither the host nor the parasite. Numerous medical and veterinary practices directly or indirectly subvert this 'illness-mediated anorexia'. However, the ecological factors that influence it, its effects on disease outcomes, and why it evolved remain poorly resolved. We explore how hosts use anorexia to defend against infection and how parasites manipulate anorexia to enhance transmission. Then, we use a coevolutionary model to illustrate how shifts in the magnitude of anorexia (e.g., via drugs) affect disease dynamics and virulence evolution. Anorexia could be exploited to improve disease management; we propose an interdisciplinary approach to minimize unintended consequences.