The Effect of Income and Wealth on Behavioral Strategies, Personality Traits, and Preferences

Individuals living in either harsh or favorable environments display well-documented psychological and behavioral differences. For example, people in favorable environments tend to be more future-oriented, trust strangers more, and have more explorative preferences. To account for such differences, psychologists have turned to evolutionary biology and behavioral ecology, in particular, the literature on life-history theory and pace-of-life syndrome. However, critics have found that the theoretical foundations of these approaches are fragile and that differences in life expectancy cannot explain vast psychological and behavioral differences. In this article, we build on the theory of optimal resource allocation to propose an alternative framework. We hypothesize that the quantity of resources available, such as income, has downstream consequences on psychological traits, leading to the emergence of behavioral syndromes. We show that more resources lead to more long-term orientation, more tolerance of variance, and more investment in low marginal-benefit needs. At the behavioral level, this translates, among others, into more large-scale cooperation, more investment in health, and more exploration. These individual-level differences in behavior, in turn, account for cultural phenomena such as puritanism, authoritarianism, and innovation.

Peace is a form of cooperation, and so are the cultural technologies which make peace possible

While necessary parts of the puzzle, cultural technologies are insufficient to explain peace. They are a form of second-order cooperation - a cooperative interaction designed to incentivize first-order cooperation. We propose an explanation for peacemaking cultural technologies, and therefore peace, based on the reputational incentives for second-order cooperation.

Reciprocal contracts - not competitive acquisition - explain the moral psychology of ownership

We applaud Boyer's attempt to ground the psychology of ownership partly in a cooperative logic. In this commentary, we propose to go further and ground the psychology of ownership solely in a cooperative logic. The predictions of bargaining theory, we argue, completely contradict the actual features of ownership intuitions. Ownership is only about the calculation of mutually beneficial, reciprocal contracts.

The puritanical moral contract: Purity, cooperation, and the architecture of the moral mind

Commentators raise fundamental questions about the notion of purity (sect. R1), the architecture of moral cognition (sect. R2), the functional relationship between morality and cooperation (sect. R3), the role of folk-theories of self-control in moral judgment (sect. R4), and the cultural variation of morality (sect. R5). In our response, we address all these issues by clarifying our theory of puritanism, responding to counter-arguments, and incorporating welcome corrections and extensions.

Human-environment feedback and the consistency of proenvironmental behavior

Addressing global environmental crises such as anthropogenic climate change requires the consistent adoption of proenvironmental behavior by a large part of a population. Here, we develop a mathematical model of a simple behavior-environment feedback loop to ask how the individual assessment of the environmental state combines with social interactions to influence the consistent adoption of proenvironmental behavior, and how this feeds back to the perceived environmental state. In this stochastic individual-based model, individuals can switch between two behaviors, 'active' (or actively proenvironmental) and 'baseline', differing in their perceived cost (higher for the active behavior) and environmental impact (lower for the active behavior). We show that the deterministic dynamics and the stochastic fluctuations of the system can be approximated by ordinary differential equations and a Ornstein-Uhlenbeck type process. By definition, the proenvironmental behavior is adopted consistently when, at population stationary state, its frequency is high and random fluctuations in frequency are small. We find that the combination of social and environmental feedbacks can promote the spread of costly proenvironmental behavior when neither, operating in isolation, would. To be adopted consistently, strong social pressure for proenvironmental action is necessary but not sufficient-social interactions must occur on a faster timescale compared to individual assessment, and the difference in environmental impact must be small. This simple model suggests a scenario to achieve large reductions in environmental impact, which involves incrementally more active and potentially more costly behavior being consistently adopted under increasing social pressure for proenvironmentalism.

Cultural evolution from the producers' standpoint

Standard approaches to cultural evolution focus on the recipients or consumers. This does not take into account the fitness costs incurred in producing the behaviours or artefacts that become cultural, i.e. widespread in a social group. We argue that cultural evolution models should focus on these fitness costs and benefits of cultural production, particularly in the domain of 'symbolic' culture. In this approach, cultural products can be considered as a part of the extended phenotype of producers, which can affect the fitness of recipients in a positive way (through cooperation) but also in a detrimental way (through manipulation and exploitation). Taking the producers' perspective may help explain the specific features of many kinds of cultural products.

Moral disciplining: The cognitive and evolutionary foundations of puritanical morality

Why do many societies moralize apparently harmless pleasures, such as lust, gluttony, alcohol, drugs, and even music and dance? Why do they erect temperance, asceticism, sobriety, modesty, and piety as cardinal moral virtues? According to existing theories, this puritanical morality cannot be reduced to concerns for harm and fairness: It must emerge from cognitive systems that did not evolve for cooperation (e.g., disgust-based "purity" concerns). Here, we argue that, despite appearances, puritanical morality is no exception to the cooperative function of moral cognition. It emerges in response to a key feature of cooperation, namely that cooperation is (ultimately) a long-term strategy, requiring (proximately) the self-control of appetites for immediate gratification. Puritanical moralizations condemn behaviors which, although inherently harmless, are perceived as indirectly facilitating uncooperative behaviors, by impairing the self-control required to refrain from cheating. Drinking, drugs, immodest clothing, and unruly music and dance are condemned as stimulating short-term impulses, thus facilitating uncooperative behaviors (e.g., violence, adultery, free-riding). Overindulgence in harmless bodily pleasures (e.g., masturbation, gluttony) is perceived as making people slave to their urges, thus altering abilities to resist future antisocial temptations. Daily self-discipline, ascetic temperance, and pious ritual observance are perceived as cultivating the self-control required to honor prosocial obligations. We review psychological, historical, and ethnographic evidence supporting this account. We use this theory to explain the fall of puritanism in western, educated, industrialized, rich, and democratic (WEIRD) societies, and discuss the cultural evolution of puritanical norms. Explaining puritanical norms does not require adding mechanisms unrelated to cooperation in our models of the moral mind.

Cooperation as a signal of time preferences

Many evolutionary models explain why we cooperate with non-kin, but few explain why cooperative behaviour and trust vary. Here, we introduce a model of cooperation as a signal of time preferences, which addresses this variability. At equilibrium in our model (i) future-oriented individuals are more motivated to cooperate, (ii) future-oriented populations have access to a wider range of cooperative opportunities, and (iii) spontaneous and inconspicuous cooperation reveal stronger preference for the future, and therefore inspire more trust. Our theory sheds light on the variability of cooperative behaviour and trust. Since affluence tends to align with time preferences, results (i) and (ii) explain why cooperation is often associated with affluence, in surveys and field studies. Time preferences also explain why we trust others based on proxies for impulsivity, and, following result (iii), why uncalculating, subtle and one-shot cooperators are deemed particularly trustworthy. Time preferences provide a powerful and parsimonious explanatory lens, through which we can better understand the variability of trust and cooperation.

Policy search with rare significant events: Choosing the right partner to cooperate with

This paper focuses on a class of reinforcement learning problems where significant events are rare and limited to a single positive reward per episode. A typical example is that of an agent who has to choose a partner to cooperate with, while a large number of partners are simply not interested in cooperating, regardless of what the agent has to offer. We address this problem in a continuous state and action space with two different kinds of search methods: a gradient policy search method and a direct policy search method using an evolution strategy. We show that when significant events are rare, gradient information is also scarce, making it difficult for policy gradient search methods to find an optimal policy, with or without a deep neural architecture. On the other hand, we show that direct policy search methods are invariant to the rarity of significant events, which is yet another confirmation of the unique role evolutionary algorithms has to play as a reinforcement learning method.

Nothing better to do? Environment quality and the evolution of cooperation by partner choice

The effects of partner choice have been documented in a large number of biological systems such as sexual markets, interspecific mutualisms, or human cooperation. There are, however, a number of situations in which one would expect this mechanism to play a role, but where no such effect has ever been demonstrated. This is the case in particular in many intraspecific interactions, such as collective hunts, in non-human animals. Here we use individual-based simulations to solve this apparent paradox. We show that the conditions for partner choice to operate are in fact restrictive. They entail that individuals can compare social opportunities and choose the best. The challenge is that social opportunities are often rare because they necessitate the co-occurrence of (i) at least one available partner, and (ii) a resource to exploit together with this partner. This has three consequences. First, partner choice cannot lead to the evolution of cooperation when resources are scarce, which explains that this mechanism could never be observed in many cases of intraspecific cooperation in animals. Second, partner choice can operate when partners constitute in themselves a resource, which is the case in sexual interactions and interspecific mutualisms. Third, partner choice can lead to the evolution of cooperation when individuals live in a rich environment, and/or when they are highly efficient at extracting resources from their environment.

The emergence of cooperation by evolutionary generalization

In principle, any cooperative behaviour can be evolutionarily stable as long as it is incentivized by a reward from the beneficiary, a mechanism that has been called reciprocal cooperation. However, what makes this mechanism so powerful also has an evolutionary downside. Reciprocal cooperation faces a chicken-and-egg problem of the same kind as communication: it requires two functions to evolve at the same time-cooperation and response to cooperation. As a result, it can only emerge if one side first evolves for another reason, and is then recycled into a reciprocal function. Developing an evolutionary model in which we make use of machine learning techniques, we show that this occurs if the fact to cooperate and reward others' cooperation become general abilities that extend beyond the set of contexts for which they have initially been selected. Drawing on an evolutionary analogy with the concept of generalization, we identify the conditions necessary for this to happen. This allows us to understand the peculiar distribution of reciprocal cooperation in the wild, virtually absent in most species-or limited to situations where individuals have partially overlapping interests, but pervasive in the human species.

Cultural evolution by capital accumulation

In this article, we model cultural knowledge as a capital in which individuals invest at a cost. To this end, following other models of cultural evolution, we explicitly consider the investments made by individuals in culture as life history decisions. Our aim is to understand what then determines the dynamics of cultural accumulation. We show that culture can accumulate provided it improves the efficiency of people's lives in such a way as to increase their productivity or, said differently, provided the knowledge created by previous generations improves the ability of subsequent generations to invest in new knowledge. Our central message is that this positive feedback allowing cultural accumulation can occur for many different reasons. It can occur if cultural knowledge increases people's productivity, including in domains that have no connection with knowledge, because it frees up time that people can then spend learning and/or innovating. We also show that it can occur if cultural knowledge, and thus the higher level of resources that results from increased productivity, leads individuals to modify their life history decisions through phenotypic plasticity. Finally, we show that it can occur if technical knowledge reduces the effective cost of its own acquisition via division of labour. These results suggest that culture should not be defined only as a set of knowledge and skills but, more generally, as all the capital that has been produced by previous generations and that continues to affect current generations.

Why cooperation is not running away

A growing number of experimental and theoretical studies show the importance of partner choice as a mechanism to promote the evolution of cooperation, especially in humans. In this paper, we focus on the question of the precise quantitative level of cooperation that should evolve under this mechanism. When individuals compete to be chosen by others, their level of investment in cooperation evolves towards higher values, a process called competitive altruism, or runaway cooperation. Using a classic adaptive dynamics model, we first show that when the cost of changing partner is low, this runaway process can lead to a profitless escalation of cooperation. In the extreme, when partner choice is entirely frictionless, cooperation even increases up to a level where its cost entirely cancels out its benefit. That is, at evolutionary equilibrium, individuals gain the same payoff than if they had not cooperated at all. Second, importing models from matching theory in economics we, however, show that when individuals can plastically modulate their choosiness in function of their own cooperation level, partner choice stops being a runaway competition to outbid others and becomes a competition to form the most optimal partnerships. In this case, when the cost of changing partner tends towards zero, partner choice leads to the evolution of the socially optimum level of cooperation. This last result could explain the observation that human cooperation seems to be often constrained by considerations of social efficiency.

On the evolutionary origins of equity

Equity, defined as reward according to contribution, is considered a central aspect of human fairness in both philosophical debates and scientific research. Despite large amounts of research on the evolutionary origins of fairness, the evolutionary rationale behind equity is still unknown. Here, we investigate how equity can be understood in the context of the cooperative environment in which humans evolved. We model a population of individuals who cooperate to produce and divide a resource, and choose their cooperative partners based on how they are willing to divide the resource. Agent-based simulations, an analytical model, and extended simulations using neural networks provide converging evidence that equity is the best evolutionary strategy in such an environment: individuals maximize their fitness by dividing benefits in proportion to their own and their partners’ relative contribution. The need to be chosen as a cooperative partner thus creates a selection pressure strong enough to explain the evolution of preferences for equity. We discuss the limitations of our model, the discrepancies between its predictions and empirical data, and how interindividual and intercultural variability fit within this framework.

Evolutionary robotics simulations help explain why reciprocity is rare in nature

The relative rarity of reciprocity in nature, contrary to theoretical predictions that it should be widespread, is currently one of the major puzzles in social evolution theory. Here we use evolutionary robotics to solve this puzzle. We show that models based on game theory are misleading because they neglect the mechanics of behavior. In a series of experiments with simulated robots controlled by artificial neural networks, we find that reciprocity does not evolve, and show that this results from a general constraint that likely also prevents it from evolving in the wild. Reciprocity can evolve if it requires very few mutations, as is usually assumed in evolutionary game theoretic models, but not if, more realistically, it requires the accumulation of many adaptive mutations.

To Cooperate or Not to Cooperate: Why Behavioural Mechanisms Matter

Mutualistic cooperation often requires multiple individuals to behave in a coordinated fashion. Hence, while the evolutionary stability of mutualistic cooperation poses no particular theoretical difficulty, its evolutionary emergence faces a chicken and egg problem: an individual cannot benefit from cooperating unless other individuals already do so. Here, we use evolutionary robotic simulations to study the consequences of this problem for the evolution of cooperation. In contrast with standard game-theoretic results, we find that the transition from solitary to cooperative strategies is very unlikely, whether interacting individuals are genetically related (cooperation evolves in 20% of all simulations) or unrelated (only 3% of all simulations). We also observe that successful cooperation between individuals requires the evolution of a specific and rather complex behaviour. This behavioural complexity creates a large fitness valley between solitary and cooperative strategies, making the evolutionary transition difficult. These results reveal the need for research on biological mechanisms which may facilitate this transition.

Partner choice creates fairness in humans

Many studies demonstrate that partner choice has played an important role in the evolution of human cooperation, but little work has tested its impact on the evolution of human fairness. In experiments involving divisions of money, people become either over-generous or over-selfish when they are in competition to be chosen as cooperative partners. Hence, it is difficult to see how partner choice could result in the evolution of fair, equal divisions. Here, we show that this puzzle can be solved if we consider the outside options on which partner choice operates. We conduct a behavioural experiment, run agent-based simulations and analyse a game-theoretic model to understand how outside options affect partner choice and fairness. All support the conclusion that partner choice leads to fairness only when individuals have equal outside options. We discuss how this condition has been met in our evolutionary history, and the implications of these findings for our understanding of other aspects of fairness less specific than preferences for equal divisions of resources.

Contingency in the evolutionary emergence of reciprocal cooperation

Reciprocity is characterized by individuals actively making it beneficial for others to cooperate by responding to them. This makes it a particularly powerful generator of mutual interest, because the benefits accrued by an individual can be redistributed to another. However, reciprocity is a composite biological function, entailing at least two subfunctions: (i) a behavioral ability to provide fitness benefits to others and (ii) a cognitive ability to evaluate the benefits received from others. For reciprocity to evolve, these two subfunctions must appear together, which raises an evolutionary problem of bootstrapping. In this article, I develop mathematical models to study the necessary conditions for the gradual emergence of reciprocity in spite of this bootstrapping problem. I show that the evolution of reciprocity is based on three conditions. First, there must be some variability in behavior. Second, cooperation must pre-evolve for reasons independent of reciprocity. Third, and most significantly, selection favors conditional cooperation only if the cooperation expressed by others is already conditional, that is, if some reciprocity is already present in the first place. In the discussion, I show that these three conditions help explain the specific features of the instances in which reciprocity does occur in the wild. For instance, it accounts for the role of spatial symmetry (as in ungulate allogrooming), the importance of synergistic benefits (as in nuptial gifts), the facilitating role of collective actions (as in many instances of human cooperation), and the potential role of kinship (as in primate grooming).

Identification of venous signal on arterial spin labeling improves diagnosis of dural arteriovenous fistulas and small arteriovenous malformations

BACKGROUND AND PURPOSE

DAVFs and small AVMs are difficult to detect on conventional MR imaging/MRA or CTA examinations and often require DSA for definitive diagnosis. The purpose of this study was to assess the value of venous signal intensity on ASL imaging for making this diagnosis.

MATERIALS AND METHODS

Two neuroradiologists and 1 neurologist reviewed MR imaging studies in 26 patients, 15 of whom had DSA-proved DAVFs or small (<2 cm) AVMs. Pseudocontinuous ASL was performed at 1.5T with background-suppressed 3D-FSE readout. Using a 5-point scale, these readers assessed the likelihood of positive findings on a DSA study before and after reviewing the ASL findings. Agreement on imaging findings, including venous ASL signal intensity, was performed by using κ statistics. Logistic regression and ROC analysis were performed to determine which imaging findings improved diagnosis.

RESULTS

Venous ASL signal intensity was seen frequently in cases with positive findings on DSA. The sensitivity and specificity of venous ASL signal intensity for predicting positive findings on a DSA study were 78% and 85%, respectively. On ROC analysis, there was a significant increase in the AUC after review of the ASL images (AUC = 0.798 pre-ASL, AUC = 0.891 post-ASL; P = .02). Multivariate regression identified venous ASL signal intensity as the strongest predictor of positive findings on a DSA study, with an odds ratio of 17.3 (95% CI, 3.3-90.4).

CONCLUSIONS

Identifying venous ASL signal intensity improved detection of DAVFs and small AVMs. Attention to this finding may improve triage to DSA in patients with suspected small vascular malformations.

Social opportunities and the evolution of fairness

We model the evolution of the division of a resource between two individuals, according to a bargaining mechanism akin to the ultimatum game, in which a dominant proposer makes an offer that his partner can only accept or refuse. Individuals are randomly drawn from an infinite population and paired two-by-two. In each pair, a proposer is chosen. The proposer offers a division of resources to his partner. If the offer is accepted it is implemented; otherwise both partners pay a cost and move on to the next social opportunity. When the role that individuals play in each interaction is chosen at random, our analysis shows that each individual receives a fraction corresponding to at least 1/2-c of the resource at evolutionary equilibrium, where c represents the cost of postponing the interaction. A quasi-fair division thus evolves as long as c is low. We show that fairness, in this model, is a consequence of the existence of an outside option for dominated individuals: namely the possibility of playing on terms more favorable to them in the future if they reject the current interaction. We discuss the interpretation and empirical implications of this result for the case of human behavior.

The evolutionary emergence of pandemic influenza

Pandemic influenza remains a serious public health threat and the processes involved in the evolutionary emergence of pandemic influenza strains remain incompletely understood. Here, we develop a stochastic model for the evolutionary emergence of pandemic influenza, and use it to address three main questions. (i) What is the minimum annual number of avian influenza virus infections required in humans to explain the historical rate of pandemic emergence? (ii) Are such avian influenza infections in humans more likely to give rise to pandemic strains if they are driven by repeated cross-species introductions, or by low-level transmission of avian influenza viruses between humans? (iii) What are the most effective interventions for reducing the probability that an influenza strain with pandemic potential will evolve? Our results suggest that if evolutionary emergence of past pandemics has occurred primarily through viral reassortment in humans, then thousands of avian influenza virus infections in humans must have occurred each year for the past 250 years. Analyses also show that if there is epidemiologically significant variation among avian influenza virus genotypes, then avian virus outbreaks stemming from repeated cross-species transmission events result in a greater likelihood of a pandemic strain evolving than those caused by low-level transmission between humans. Finally, public health interventions aimed at reducing the duration of avian virus infections in humans give the greatest reduction in the probability that a pandemic strain will evolve.

Perfect reciprocity is the only evolutionarily stable strategy in the continuous iterated prisoner's dilemma

Theoretical studies have shown that cooperation tends to evolve when interacting individuals have positively correlated phenotypes. In the present article, we explore the situation where this correlation results from information exchange between social partners, and behavioral flexibility. We consider the game 'continuous iterated prisoner's dilemma'. The level of cooperation expressed by individuals in this game, together with their ability to respond to one another, both evolve as two aspects of their behavioral strategy. The conditions for a strategy to be evolutionarily stable in this game are degenerate, and earlier works were thus unable to find a single ESS. However, a detailed invasion analysis, together with the study of evolution in finite populations, reveals that natural selection favors strategies whereby individuals respond to their opponent's actions in a perfectly mirrored (i.e., correlated) fashion. As a corollary, the overall payoff of social interactions (i.e., the amount of cooperation) is maximized because couples of correlated partners effectively become the units of selection.

The evolutionary consequences of plasticity in host-pathogen interactions

Interactions between individuals such as hosts and pathogens are often characterized by substantial phenotypic plasticity. Pathogens sometimes alter their exploitation strategies in response to defensive strategies adopted by their host and vice versa. Nevertheless, most game-theoretic models developed to explain the evolution of pathogen and host characteristics assume that no such plasticity occurs. Allowing for phenotypic plasticity in these models is difficult because one must focus on the evolution of pathogen and host reaction norms, and then allow for the potentially indefinite reciprocal changes in pathogen and host behaviour that occur during an infection as a result of their interacting reaction norms. Here, we begin to address these issues for a simple host-pathogen system in which the pathogen exhibits a level of virulence and the host exhibits a level of immune clearance. We find, quite generally, that plasticity promotes the evolution of higher levels of cooperation, in this case leading to reduced levels of both virulence and clearance.

The effect of disease life history on the evolutionary emergence of novel pathogens

We present a general analytical result for the probability that a newly introduced pathogen will evolve adaptations that allow it to maintain itself within any novel host population, as a function of disease life-history parameters. We demonstrate that this probability of "evolutionary emergence" depends on two key properties of the disease life history: (i) the basic reproduction number and (ii) the expected duration of an infection. These parameters encapsulate all of the relevant information and can be combined in a very simple expression, with estimates for the rates of adaptive mutation, to predict the probability of emergence for any novel pathogen. In general, diseases that initially have a large reproductive number and/or that cause relatively long infections are the most prone to evolutionary adaptation.

Within-host evolution and virulence in microparasites

An important aspect of microparasite biology is the fact that infections are populations of thousands of microbes. As any population, infections are hence subject to two main types of changes: demographic and evolutionary. Here we analyse the consequences of within-host evolutionary changes. We build an epidemiological model where infections are regularly invaded by locally favored mutations affecting various infectious traits (virulence, transmissibility and clearance). Our results are the following. In durable infections, where within-host evolution is an important matter, a drop of transmissibility is only slightly deleterious to the infection, while a reduction of infection lifespan is very costly. In consequence, locally favored mutations reducing transmissibility reach a larger frequency, or even the complete fixation, and the suboptimality accumulated in infections owing to within-host evolution affects more their transmission than their duration. Conversely, taking an infection at random and observing the events of within-host evolution, one is more likely to observe reductions of infection length than reductions of transmissibility, because the mutations affecting transmissibility are often already present in infections. We then discuss the interpretation of these results in terms of deleterious mutations, and we also emphasize that the management of within-host evolution could be used as a novel therapeutic approach to the treatment of infection.

The evolution of mutation rate in finite asexual populations

In this article, we model analytically the evolution of mutation rate in asexual organisms. Three selective forces are present. First, everything else being equal, individuals with higher mutation rate have a larger fitness, thanks to the energy and time saved by not replicating DNA accurately. Second, as a flip side, the genome of these individuals is replicated with errors that may negatively affect fitness. Third, and conversely, replication errors have a potential benefit if beneficial mutations are to be generated. Our model describes the fate of modifiers of mutation rate under the three forces and allows us to predict the long-term evolutionary trajectory of mutation rate. We obtain three major results. First, in asexuals, the needs for both adaptation and genome preservation are not evolutionary forces that can stabilize mutation rate at an intermediate optimum. When adaptation has a significant role, it primarily destabilizes mutation rate and yields the emergence of strong-effect mutators. Second, in contrast to what is usually believed, the appearance of modifiers with large mutation rate is more likely when the fitness cost of each deleterious mutation is weak, because the cost of replication errors is then paid after a delay. Third, in small populations, and even if adaptations are needed, mutation rate is always blocked at the minimum attainable level, because the rate of adaptation is too slow to play a significant role. Only populations whose size is above a critical mass see their mutation rate affected by the need for adaptation.

Vaccination, within-host dynamics, and virulence evolution

We explore the potential consequences of vaccination on parasite epidemiology and evolution. Our model combines a microscopic (within-host dynamics) and a macroscopic (epidemiological dynamics) description of the interaction between the parasite and its host. This approach allows relevant epidemiological traits such as parasite transmission, parasite virulence, and host recovery to emerge from a mechanistic model of acute infection describing the interaction between the parasite and the host immune system. We model the effect of a vaccine as an activator of immunity enhancing the replication rate of lymphocytes, their initial density at infection's initiation, their efficacy to kill the parasite, or their activation delay after infection. We analyze the evolution of the replication rate of parasites and show that vaccination may promote the evolution of faster replicating and, consequently, more virulent strains. We also show that intermediate vaccination coverage may lead to the coexistence of two different parasite strategies (a low-virulence strain adapted to naive hosts, and a high-virulence strain, more generalist, adapted to both naive and vaccinated hosts). We discuss the consequences of various vaccination strategies under different epidemiological situations using several distinct measures to evaluate the cost induced by the parasite on individuals and entire host populations.

Virulence evolution in emerging infectious diseases

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

Within-host parasite dynamics, emerging trade-off, and evolution of virulence with immune system

Virulence is an evolutionary paradox because parasites never benefit from their host's death. The adaptive explanation of virulence is classically based upon the existence of physiological constraints that create a trade-off between parasites' epidemiological traits (virulence, transmissibility, and clearance). Here we develop an epidemiological model where infections are dynamic processes and we demonstrate how these dynamics generate a trade-off between emerging epidemiological parameters. We then study how host's immune strength modifies this trade-off and hence influences virulence evolution. We found that in acute infections, where parasites are engaged in a race with immune cells, immunity restrains more the duration of the infection than its intensity. As a consequence parasites evolve to provoke more virulent but shorter infections in strongly immunized hosts.