Epidemiological Feedbacks Research Articles

Spatial spread of infectious diseases with conditional vector preferences.

We explore the spatial spread of vector-borne infections with conditional vector preferences, meaning that vectors do not visit hosts at random. Vectors may be differentially attracted toward infected and uninfected hosts depending on whether they carry the pathogen or not. The model is expressed as a system of partial differential equations with vector diffusion. We first study the non-spatial model. We show that conditional vector preferences alone (in the absence of any epidemiological feedback on their population dynamics) may result in bistability between the disease-free equilibrium and an endemic equilibrium. A backward bifurcation may allow the disease to persist even though its basic reproductive number is less than one. Bistability can occur only if both infected and uninfected vectors prefer uninfected hosts. Back to the model with diffusion, we show that bistability in the local dynamics may generate travelling waves with either positive or negative spreading speeds, meaning that the disease either invades or retreats into space. In the monostable case, we show that the disease spreading speed depends on the preference of uninfected vectors for infected hosts, but also on the preference of infected vectors for uninfected hosts under some circumstances (when the spreading speed is not linearly determined). We discuss the implications of our results for vector-borne plant diseases, which are the main source of evidence for conditional vector preferences so far.

Digest: Evolutionary rescue following the introduction of a pathogen.

To what extent can adaptive evolution rescue a population from extinction following the introduction of a pathogen? Searle and Christie (2021) show how evolutionary rescues in host-pathogen systems may differ from those that occur in response to abiotic changes. In particular, they pinpoint how epidemiological feedback and pathogen evolution, inherent to host-pathogen systems, can greatly affect the likelihood of rescue.

Feedback between coevolution and epidemiology can help or hinder the maintenance of genetic variation in host‐parasite models

Antagonistic coevolution has long been suggested to help maintain host genetic variation. Although ecological and epidemiological feedbacks are known to have important consequences on coevolutionary allele-frequency dynamics, their effects on the maintenance of genetic variation remains poorly understood. Here, we extend previous work on the maintenance of genetic variation in a classic matching alleles coevolutionary model by exploring the effects of ecological and epidemiological feedbacks, where both allele frequencies and population sizes are allowed to vary over time. We find that coevolution rarely maintains more host genetic variation than expected under neutral genetic drift alone. When and if coevolution maintains or depletes genetic variation relative to neutral drift is determined, predominantly, by two factors: the deterministic stability of the Red Queen allele-frequency cycles and the chance of allele fixation in the pathogen, as this results in directional selection and depletion of genetic variation in the host. Compared to purely coevolutionary models with constant host and pathogen population sizes, ecological and epidemiological feedbacks stabilize Red Queen cycles deterministically, but population fluctuations in the pathogen increase the rate of allele fixation in the pathogen, especially in epidemiological models. Our results illustrate the importance of considering the ecological and epidemiological context in which coevolution occurs when examining the impact of Red Queen cycles on geneticvariation.

Explaining vaccination decisions: A system dynamics model of the interaction between epidemiological and behavioural factors

The WHO goal of eradicating measles is delayed by widespread scepticism of parents against the recommended MMR vaccination. In this context, a model of the prevalence of measles that incorporates behavioural aspects is desirable. Parental decisions can be influenced by epidemiological and behavioural factors. The former include vaccination coverage and its impact on the prevalence of the disease. The latter include perceptions of the risk to be infected, which affects vaccination decisions, as well as government campaigns to affect vaccination behaviour, vaccination scares or changes in disease control policies. We develop a model that incorporates both kinds of effects. In particular, we illustrate how incorporating parental response to a change in the prevalence of the disease impacts the outcome of governmental policies aiming to increase the vaccination coverage. While calibrated to measles, this model is also applicable to other childhood diseases, such as pertussis or diphtheria. Different scenarios illustrate the long-term consequences of the interaction between health policies (in particular, vaccination campaigns) or the agenda of social institutions (e.g., drawing attention to specific events to create vaccination scares) and parental reactions. Periodic ups and downs of the disease's prevalence, characteristic of epidemiological feedback, are the consequence of the interaction between parental behaviour and events such as vaccination campaigns or vaccination scares. International and national health authorities, pursuing the fight against measles, may be helped by the potential of the model to provide understanding in the way different predictors of vaccination behaviour interact.

Coevolution of virulence and immunosuppression in multiple infections.

Many components of host-parasite interactions have been shown to affect the way virulence (i.e. parasite-induced harm to the host) evolves. However, coevolution of multiple parasite traits is often neglected. We explore how an immunosuppressive adaptation of parasites affects and coevolves with virulence in multiple infections. Applying the adaptive dynamics framework to epidemiological models with coinfection, we show that immunosuppression is a double-edged sword for the evolution of virulence. On one hand, it amplifies the adaptive benefit of virulence by increasing the abundance of coinfections through epidemiological feedbacks. On the other hand, immunosuppression hinders host recovery, prolonging the duration of infection and elevating the cost of killing the host (as more opportunities for transmission will be forgone if the host dies). The balance between the cost and benefit of immunosuppression varies across different background mortality rates of hosts. In addition, we find that immunosuppression evolution is influenced considerably by the precise trade-off shape determining the effect of immunosuppression on host recovery and susceptibility to further infection. These results demonstrate that the evolution of virulence is shaped by immunosuppression while highlighting that the evolution of immune evasion mechanisms deserves further research attention.

Assessing the public health impact of tolerance-based therapies with mathematical models.

Disease tolerance is a defense strategy against infections that aims at maintaining host health even at high pathogen replication or load. Tolerance mechanisms are currently intensively studied with the long-term goal of exploiting them therapeutically. Because tolerance-based treatment imposes less selective pressure on the pathogen it has been hypothesised to be “evolution-proof”. However, the primary public health goal is to reduce the incidence and mortality associated with a disease. From this perspective, tolerance-based treatment bears the risk of increasing the prevalence of the disease, which may lead to increased mortality. We assessed the promise of tolerance-based treatment strategies using mathematical models. Conventional treatment was implemented as an increased recovery rate, while tolerance-based treatment was assumed to reduce the disease-related mortality of infected hosts without affecting recovery. We investigated the endemic phase of two types of infections: acute and chronic. Additionally, we considered the effect of pathogen resistance against conventional treatment. We show that, for low coverage of tolerance-based treatment, chronic infections can cause even more deaths than without treatment. Overall, we found that conventional treatment always outperforms tolerance-based treatment, even when we allow the emergence of pathogen resistance. Our results cast doubt on the potential benefit of tolerance-based over conventional treatment. Any clinical application of tolerance-based treatment of infectious diseases has to consider the associated detrimental epidemiological feedback.

Coevolutionary Epidemiology: Disease Spread, Local Adaptation, and Sex.

How does evolution in parasite populations affect the rate of disease spread? In the present study, I derived the mean reproductive rate ([Formula: see text]) for a genetically diverse parasite population that is evolving with a similarly diverse host population. Assuming a matching-alleles model, I found that [Formula: see text] is a positive function of the covariance between the frequencies of "matching" host and parasite genotypes. Computer simulations further showed that evolution in the parasite population tends to increase the covariance, which can lead to epidemiological feedbacks. However, the covariances can also become negative during counteradaptation by the host, leading to oscillatory dynamics in host and parasite fitness. Nonetheless, when parasite-mediated selection is strong, the covariance is positive on average, which facilitates the spread of disease. Positive covariances may also underlie patterns of local adaptation in parasite populations and increase the selective advantage of cross-fertilization in host populations.

Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure

The efficacy of vaccines is typically estimated prior to implementation, on the basis of randomized controlled trials. This does not preclude, however, subsequent assessment post-licensure, while mass-immunization and nonlinear transmission feedbacks are in place. In this paper we show how cross-sectional prevalence data post-vaccination can be interpreted in terms of pathogen transmission processes and vaccine parameters, using a dynamic epidemiological model. We advocate the use of such frameworks for model-based vaccine evaluation in the field, fitting trajectories of cross-sectional prevalence of pathogen strains before and after intervention. Using SI and SIS models, we illustrate how prevalence ratios in vaccinated and non-vaccinated hosts depend on true vaccine efficacy, the absolute and relative strength of competition between target and non-target strains, the time post follow-up, and transmission intensity. We argue that a mechanistic approach should be added to vaccine efficacy estimation against multi-type pathogens, because it naturally accounts for inter-strain competition and indirect effects, leading to a robust measure of individual protection per contact. Our study calls for systematic attention to epidemiological feedbacks when interpreting population level impact. At a broader level, our parameter estimation procedure provides a promising proof of principle for a generalizable framework to infer vaccine efficacy post-licensure.

The epidemiological feedbacks critical to the evolution of host immunity.

We examine in detail how epidemiological feedbacks combine with costs and benefits to determine the evolution of resistance by systematically analysing continuously stable strategies (CSS) for different host-parasite frameworks. The mode of resistance (innate versus acquired), the nature of the host (i.e. life-history and immunological memory) and the nature of the disease (effects on fertility or mortality) all impact on the feedbacks that are critical to the evolution of resistance. By identifying relationships between CSS investment and the underlying epidemiological feedback for each mode of resistance in each framework, we distil complex feedbacks into simple combinations of selection pressures. When the parasite does not affect fertility, CSS investment reflects only the benefit of resistance and we explain why this is markedly different for innate and acquired resistance. If infection has no effect on host fertility, CSS investment in acquired immunity increases with the square of disease prevalence. While in contrast for evolving innate resistance, CSS investment is greatest at intermediate prevalence. When disease impacts fertility, only a fraction of the host population reproduce, and this introduces new ecological feedbacks to both the cost of resistance and the damage from infection. The multiple feedbacks in this case lead to the alternative result that the higher the abundance of infecteds, the higher the investment in innate resistance. A key insight is that maximal investment occurs at intermediate lifespans in a range of different host-parasite interactions, but for disparate reasons which can only be understood by a detailed analysis of the feedbacks. We discuss the extension of our approach to structured host populations and parasite community dynamics.

From within-host interactions to epidemiological competition: a general model for multiple infections.

Many hosts are infected by several parasite genotypes at a time. In these co-infected hosts, parasites can interact in various ways thus creating diverse within-host dynamics, making it difficult to predict the expression and the evolution of virulence. Moreover, multiple infections generate a combinatorial diversity of cotransmission routes at the host population level, which complicates the epidemiology and may lead to non-trivial outcomes. We introduce a new model for multiple infections, which allows any number of parasite genotypes to infect hosts and potentially coexist in the population. In our model, parasites affect one another's within-host growth through density-dependent interactions and by means of public goods and spite. These within-host interactions determine virulence, recovery and transmission rates, which are then integrated in a transmission network. We use analytical solutions and numerical simulations to investigate epidemiological feedbacks in host populations infected by several parasite genotypes. Finally, we discuss general perspectives on multiple infections.

Long-term selection experiment produces breakdown of horizontal transmissibility in parasite with mixed transmission mode.

Evolutionary transitions from parasitism toward beneficial or mutualistic associations may encompass a change from horizontal transmission to (strict) vertical transmission. Parasites with both vertical and horizontal transmission are amendable to study factors driving such transitions. In a long-term experiment, microcosm populations of the protozoan Paramecium caudatum and its bacterial parasite Holospora undulata were exposed to three growth treatments, manipulating vertical transmission opportunities over ca. 800 host generations. In inoculation tests, horizontal transmission propagules produced by parasites from a "high-growth" treatment, with elevated host division rates increasing levels of parasite vertical transmission, showed a near-complete loss of infectivity. A similar reduction was observed for parasites from a treatment alternating between high growth and low growth (i.e., low levels of population turn-over). Parasites from a low-growth treatment had the highest infectivity on all host genotypes tested. Our results complement previous findings of reduced investment in horizontal transmission and increased vertical transmissibility of high-growth parasites. We explain the loss of horizontal transmissibility by epidemiological feedbacks and resistance evolution, reducing the frequency of susceptible hosts in the population and thereby decreasing the selective advantage of horizontal transmission. This illustrates how environmental conditions may push parasites with a mixed transmission mode toward becoming vertically transmitted nonvirulent symbionts.

How specificity and epidemiology drive the coevolution of static trait diversity in hosts and parasites.

There is typically considerable variation in the level of infectivity of parasites and the degree of resistance of hosts within populations. This trait variation is critical not only to the evolutionary dynamics but also to the epidemiology, and potentially the control of infectious disease. However, we lack an understanding of the processes that generate and maintain this trait diversity. We examine theoretically how epidemiological feedbacks and the characteristics of the interaction between host types and parasites strains determine the coevolution of host–parasite diversity. The interactions include continuous characterizations of the key phenotypic features of classic gene-for-gene and matching allele models. We show that when there are costs to resistance in the hosts and infectivity in the parasite, epidemiological feedbacks may generate diversity but this is limited to dimorphism, often of extreme types, in a broad range of realistic infection scenarios. For trait polymorphism, there needs to be both specificity of infection between host types and parasite strains as well as incompatibility between particular strains and types. We emphasize that although the high specificity is well known to promote temporal “Red Queen” diversity, it is costs and combinations of hosts and parasites that cannot infect that will promote static trait diversity.

Patient safety and prevention of unexpected events occurring during the intra-hospital transport of critically ill ICU patients.

Dear Sir, We read with great interest the recent article on the intra-hospital transport (IHT) of critically ill patients by Venkategowda et al.[1] We agree with the authors that despite improvements in IHT practices, unexpected events (UE) incidents remain high. Since UEs can be reduced when an intensivist accompanies a critically ill patient, this practice should be incorporated routinely. Epidemiological studies and feedback from intensive care societies have identified several risk factors related to patient, transport organization, technical, and human responsible for UE during IHT.[2] These risks can be overcome by developing a culture of safety and standardization of procedures. Addressing the competence of the transport team is not the only factor that needs to be considered. The first step starts even before ordering a diagnostic or therapeutic procedure, based on a benefit/risk analysis of IHT for a given patient.[3] Additionally, preparation and management are also crucial steps when transporting critically ill patients. Having stabilized the critically ill patient before transport, technical, organizational, and human factors must be the subsequent targets for the primary prevention of IHT-related UEs.[2,4] Overcoming the risks of IHT thus involves taking corrective action for all the causes at multiple levels and applying methods that have been proven to work in other sectors of activity. A more widespread use of checklists and proper training plans for teams are also expected to lead to an increase in IHT safety and a lowering of risks in the long term.

A limited host immune range facilitates the creation and maintenance of diversity in parasite virulence.

A vast theoretical literature has explored the evolutionary dynamics of parasite virulence. The classic result from this modelling work is that, assuming a saturating transmission-virulence trade-off, there is a single evolutionary optimum where the parasite optimizes the epidemiological R 0. However, there are an increasing number of models that have shown how ecological and epidemiological feedbacks to evolution can instead result in the creation and maintenance of multiple parasite strains. Here, we fully explore one such example, where recovered hosts have a limited 'immune range' resulting in partial cross-immunity to parasite strains that they have not previously encountered. Taking an adaptive dynamics approach, we show that, provided this immune range is not too wide, high levels of diversity can evolve and be maintained through multiple branching events. We argue that our model provides a more realistic picture of disease dynamics in vertebrate host populations and may be a key explanatory factor in the high levels of parasite diversity seen in natural systems.

Optimal immune defence in the light of variation in lifespan

There is good evidence for costs to both the uses of immune defences and their development and maintenance. The optimal defence will be a balance of these costs with the risk of infection and the virulence of the disease. It is therefore clear that the life-history characteristics of both host and parasite will impact the optimal level of defence, and that this may in part explain the variation in immune defence against different pathogens and parasites. For instance, it has traditionally been suggested that long-lived hosts should invest in immune memory. Ecological evolutionary theory can be used to examine in detail how different host characteristics will affect the optimal immune response that evolves. Here, we review theoretical studies on the impact of host lifespan on various immune defence characteristics including acquired immunity and highlight the importance of population-level epidemiological feedbacks on the outcome. In particular, we discuss when longer-lived hosts may invest less in acquired immunity and develop new theory to highlight the importance of the mechanism of host population regulation to the outcome. We finish by discussing where more theory is needed and how comparative and experimental studies may test the theory.

The evolutionary dynamics of within-generation immune priming in invertebrate hosts.

While invertebrates lack the machinery necessary for 'acquired immunity', there is increasing empirical evidence that exposure to low levels of disease may 'prime' an invertebrate's immune response, increasing its defence to subsequent exposure. Despite this increasing empirical data, there has been little theoretical attention paid to immune priming. Here, we investigate the evolution of immune priming, focusing on the role of the unique feedbacks generated by a newly developed susceptible-primed-infected epidemiological model. Contrasting our results with previous models on the evolution of acquired immunity, we highlight that there are important implications to the evolution of immunity through priming owing to these different epidemiological feedbacks. In particular, we find that in contrast to acquired immunity, priming is strongly selected for at high as well as intermediate pathogen virulence. We also find that priming may be greatest at either intermediate or high host lifespans depending on the severity of disease. Furthermore, hosts faced with more severe pathogens are more likely to evolve diversity in priming. Finally, we show when the evolution of priming leads to the exclusion of the pathogens or hosts experiencing population cycles. Overall the model acts as a baseline for understanding the evolution of priming in host-pathogen systems.

Evolution of Host Life-History Traits in a Spatially Structured Host-Parasite System

Most models for the evolution of host defense against parasites assume that host populations are not spatially structured. Yet local interactions and limited dispersal can strongly affect the evolutionary outcome, because they significantly alter epidemiological feedbacks and the spatial genetic structuring of the host and pathogen populations. We provide a general framework to study the evolution of a number of host life-history traits in a spatially structured host population infected by a horizontally transmitted parasite. Our analysis teases apart the selective pressures on hosts and helps disentangle the direct fitness effect of mutations and their indirect effects via the influence of spatial structure on the genetic, demographic, and epidemiological structure of the host population. We then illustrate the evolutionary consequences of spatial structure by focusing on the evolution of two host defense strategies against parasitism: suicide upon infection and reduced transmission. Because they bring no direct fitness benefit, these strategies are counterselected or selectively neutral in a nonspatial setting, but we show that they can be selected for in a spatially structured environment. Our study thus sheds light on the evolution of altruistic defense mechanisms that have been observed in various biological systems.

Within-host parasite cooperation and the evolution of virulence

Infections by multiple genotypes are common in nature and are known to select for higher levels of virulence for some parasites. When parasites produce public goods (PGs) within the host, such co-infections have been predicted to select for lower levels of virulence. However, this prediction is based on simplifying assumptions regarding epidemiological feedbacks on the multiplicity of infections (MOI). Here, we analyse the case of parasites producing a PG (for example, siderophore-producing bacteria) using a nested model that ties together within-host and epidemiological processes. We find that the prediction that co-infection should select for less virulent strains for PG-producing parasites is only valid if both parasite transmission and virulence are linear functions of parasite density. If there is a trade-off relationship such that virulence increases more rapidly than transmission, or if virulence also depends on the total amount of PGs produced, then more complex relationships between virulence and the MOI are predicted. Our results reveal that explicitly taking into account the distribution of parasite strains among hosts could help better understand the selective pressures faced by parasites at the population level.

The Evolution of Host‐Parasite Range

Understanding the coevolution of hosts and parasites is one of the key challenges for evolutionary biology. In particular, it is important to understand the processes that generate and maintain variation. Here, we examine a coevolutionary model of hosts and parasites where infection does not depend on absolute rates of transmission and defense but is approximately all-or-nothing, depending on the relative levels of defense and infectivity of the host and the parasite. We show that considerable diversity can be generated and maintained because of epidemiological feedbacks, with strains differing in the range of host and parasite types they can respectively infect or resist. Parasites with broad and narrow ranges therefore coexist, as do broadly and narrowly resistant hosts, but this diversity occurs without the assumption of highly specific gene interactions. In contrast to gene-for-gene models, cycling in strain types is found only under a restrictive set of circumstances. The generation of diversity in both hosts and parasites is dependent on the shape of the trade-off relationships but is more likely in long-lived hosts and chronic disease with long infectious periods. Overall, our model shows that significant diversity in infectivity and resistance range can evolve and be maintained from initially monomorphic populations.

An epidemiological model of host–parasite coevolution and sex

The Red Queen hypothesis posits a promising way to explain the widespread existence of sexual reproduction despite the cost of producing males. The essence of the hypothesis is that coevolutionary interactions between hosts and parasites select for the genetic diversification of offspring via cross-fertilization. Here, I relax a common assumption of many Red Queen models that each host is exposed to one parasite. Instead, I assume that the number of propagules encountered by each host depends on the number of infected hosts in the previous generation, which leads to additional complexities. The results suggest that epidemiological feedbacks, combined with frequency-dependent selection, could lead to the long-term persistence of sex under biologically reasonable conditions.