Population biology of multispecies helminth infection: interspecific interactions and parasite distribution

Novel epidemiological model of gastrointestinal nematode infection to assess grazing cattle resilience by integrating host growth, parasite, grass and environmental dynamics

Gastrointestinal nematode (GIN) infections are ubiquitous and often cause morbidity and reduced performance in livestock. Emerging anthelmintic resistance and increasing change in climate patterns require evaluation of alternatives to traditional treatment and management practices. Mathematical models of parasite transmission between hosts and the environment have contributed towards the design of appropriate control strategies in ruminants, but have yet to account for relationships between climate, infection pressure, immunity, resources, and growth. Here, we develop a new epidemiological model of GIN transmission in a herd of grazing cattle, including host tolerance (body weight and feed intake), parasite burden and acquisition of immunity, together with weather-dependent development of parasite free-living stages, and the influence of grass availability on parasite transmission. Dynamic host, parasite and environmental factors drive a variable rate of transmission. Using literature sources, the model was parametrised for Ostertagia ostertagi, the prevailing pathogenic GIN in grazing cattle populations in temperate climates. Model outputs were validated on published empirical studies from first season grazing cattle in northern Europe. These results show satisfactory qualitative and quantitative performance of the model; they also indicate the model may approximate the dynamics of grazing systems under co-infection by O. ostertagi and Cooperia oncophora, a second GIN species common in cattle. In addition, model behaviour was explored under illustrative anthelmintic treatment strategies, considering impacts on parasitological and performance variables. The model has potential for extension to explore altered infection dynamics as a result of management and climate change, and to optimise treatment strategies accordingly. As the first known mechanistic model to combine parasitic and free-living stages of GIN with host feed-intake and growth, it is well suited to predict complex system responses under non-stationary conditions. We discuss the implications, limitations and extensions of the model, and its potential to assist in the development of sustainable parasite control strategies.

Using lizards to evaluate the influence of average abundance on the variance of endoparasites in semiarid areas: dispersion and assemblage structure

The distribution of parasites within host populations and communities, and the mechanisms responsible for these patterns, are poorly understood aspects of wildlife parasitology. Here, we evaluate the influence of the average abundance of endoparasite variance, using endoparasites of lizards from the Caatinga domain (semiarid region), north-eastern Brazil. We hypothesized that, due to the high number of generalist endoparasite species, they may occur randomly throughout host populations in an aggregate pattern. In addition, we evaluated the degree to which sample variance is influenced by the average abundance of endoparasite species, patterns of co-occurrence and dominance among endoparasite species and similarities between abundance and the richness of endoparasite infracommunities in several host species. Between September 2015 and February 2016, 2141 lizards (1233 infected) from 16 species were collected from six Caatinga areas. In total, 25,687 endoparasites were collected, which belonged to 13 species including nematodes, pentastomids, cestodes, trematodes and acanthocephalans. Parasite-host associations documented here included 39 newly identified interactions. Endoparasites occurred in a typical aggregate pattern of distribution within their hosts; there was no measurable preference related to the acquisition of hosts by endoparasites. Despite the new records, endoparasites found were commonly associated with lizards in Caatinga environments, which may reflect fauna composed of generalist endoparasite species.

The Dynamics of Ascaris lumbricoides Infections

The Anderson-May model of human parasite infections and specifically that for the intestinal worm Ascaris lumbricoides is reconsidered, with a view to deriving the observed characteristic negative binomial distribution which is frequently found in human communities. The means to obtaining this result lies in reformulating the continuous Anderson-May model as a stochastic process involving two essential populations, the density of mature worms in the gut, and the density of mature eggs in the environment. The resulting partial differential equation for the generating function of the joint probability distribution of eggs and worms can be partially solved in the appropriate limit where the worm lifetime is much greater than that of the mature eggs in the environment. Allowing for a mean field nonlinearity, and for egg immigration from neighbouring communities, a negative binomial worm distribution can be predicted, whose parameters are determined by those in the continuous Anderson-May model; this result assumes no variability in predisposition to the infection.

The role of models in translating within-host dynamics to parasite evolution

Mathematical modelling provides an effective way to challenge conventional wisdom about parasite evolution and investigate why parasites ‘do what they do’ within the host. Models can reveal when intuition cannot explain observed patterns, when more complicated biology must be considered, and when experimental and statistical methods are likely to mislead. We describe how models of within-host infection dynamics can refine experimental design, and focus on the case study of malaria to highlight how integration between models and data can guide understanding of parasite fitness in three areas: (1) the adaptive significance of chronic infections; (2) the potential for tradeoffs between virulence and transmission; and (3) the implications of within-vector dynamics. We emphasize that models are often useful when they highlight unexpected patterns in parasite evolution, revealing instead why intuition yields the wrong answer and what combination of theory and data are needed to advance understanding.

Modelling parasite aggregation: disentangling statistical and ecological approaches

The overdispersion in macroparasite infection intensity among host populations is commonly simulated using a constant negative binomial aggregation parameter. We describe an alternative to utilising the negative binomial approach and demonstrate important disparities in intervention efficacy projections that can come about from opting for pattern-fitting models that are not process-explicit. We present model output in the context of the epidemiology and control of soil-transmitted helminths due to the significant public health burden imposed by these parasites, but our methods are applicable to other infections with demonstrable aggregation in parasite numbers among hosts.

Identifying the interaction between influenza and pneumococcal pneumonia using incidence data

The association between influenza virus and the bacterium Streptococcus pneumoniae (pneumococcus) has been proposed as a polymicrobial system, whereby transmission and pathogenicity of one pathogen (the bacterium) are affected by interactions with the other (the virus). However, studies focusing on different scales of resolution have painted an inconsistent picture: Individual-scale animal experiments have unequivocally demonstrated an association, whereas epidemiological support in human populations is, at best, inconclusive. We integrate weekly incidence reports and a mechanistic transmission model within a likelihood-based inference framework to characterize the nature, timing, and magnitude of this interaction. We find support for a strong but short-lived interaction, with influenza infection increasing susceptibility to pneumococcal pneumonia ~100-fold. We infer modest population-level impacts arising from strong processes at the level of an individual, thereby resolving the dichotomy in seemingly inconsistent observations across scales. An accurate characterization of the influenza-pneumococcal interaction can form a basis for more effective clinical care and public health measures for pneumococcal pneumonia.

Slaving and release in co-infection control

BACKGROUND

Animal and human infection with multiple parasite species is the norm rather than the exception, and empirical studies and animal models have provided evidence for a diverse range of interactions among parasites. We demonstrate how an optimal control strategy should be tailored to the pathogen community and tempered by species-level knowledge of drug sensitivity with use of a simple epidemiological model of gastro-intestinal nematodes.

METHODS

We construct a fully mechanistic model of macroparasite co-infection and use it to explore a range of control scenarios involving chemotherapy as well as improvements to sanitation.

RESULTS

Scenarios are presented whereby control not only releases a more resistant parasite from antagonistic interactions, but risks increasing co-infection rates, exacerbating the burden of disease. In contrast, synergisms between species result in their becoming epidemiologically slaved within hosts, presenting a novel opportunity for controlling drug resistant parasites by targeting co-circulating species.

CONCLUSIONS

Understanding the effects on control of multi-parasite species interactions, and vice versa, is of increasing urgency in the advent of integrated mass intervention programmes.

Pathogen diversity and hidden regimes of apparent competition

Competition through cross-reacting host immune responses, a form of apparent competition, is a major driver of pathogen evolution and diversity. Most models of pathogens have focused on intraspecific interactions to explain observed patterns. Two recent experiments suggested that Haemophilus influenzae, a common nasopharyngeal colonizer of humans, might alter the immune environment in a way that favors otherwise less fit serotypes of another common pathogen, pneumococcus. Using a computational model, we demonstrate that H. influenzae, if it consistently raises the fitness of the less fit serotypes, can strongly promote pneumococcal diversity. However, the effects of H. influenzae are so sensitive to the prevalence of H. influenzae that this species is unlikely to be the main driver of serotype coexistence. Interactions that significantly affect diversity could furthermore be extremely difficult to detect through co-occurrence analysis alone. These results suggest that small differences in strains' adaptations to different immunological regimes, which are shaped by coinfections with other pathogens, can have dramatic effects on strain dynamics and patterns of phenotypic variation. Studies of microbial communities might therefore benefit from the use of varied approaches to infer the presence of indirect interactions.

A research agenda for helminth diseases of humans: modelling for control and elimination

Mathematical modelling of helminth infections has the potential to inform policy and guide research for the control and elimination of human helminthiases. However, this potential, unlike in other parasitic and infectious diseases, has yet to be realised. To place contemporary efforts in a historical context, a summary of the development of mathematical models for helminthiases is presented. These efforts are discussed according to the role that models can play in furthering our understanding of parasite population biology and transmission dynamics, and the effect on such dynamics of control interventions, as well as in enabling estimation of directly unobservable parameters, exploration of transmission breakpoints, and investigation of evolutionary outcomes of control. The Disease Reference Group on Helminth Infections (DRG4), established in 2009 by the Special Programme for Research and Training in Tropical Diseases (TDR), was given the mandate to review helminthiases research and identify research priorities and gaps. A research and development agenda for helminthiasis modelling is proposed based on identified gaps that need to be addressed for models to become useful decision tools that can support research and control operations effectively. This agenda includes the use of models to estimate the impact of large-scale interventions on infection incidence; the design of sampling protocols for the monitoring and evaluation of integrated control programmes; the modelling of co-infections; the investigation of the dynamical relationship between infection and morbidity indicators; the improvement of analytical methods for the quantification of anthelmintic efficacy and resistance; the determination of programme endpoints; the linking of dynamical helminth models with helminth geostatistical mapping; and the investigation of the impact of climate change on human helminthiases. It is concluded that modelling should be embedded in helminth research, and in the planning, evaluation, and surveillance of interventions from the outset. Modellers should be essential members of interdisciplinary teams, propitiating a continuous dialogue with end users and stakeholders to reflect public health needs in the terrain, discuss the scope and limitations of models, and update biological assumptions and model outputs regularly. It is highlighted that to reach these goals, a collaborative framework must be developed for the collation, annotation, and sharing of databases from large-scale anthelmintic control programmes, and that helminth modellers should join efforts to tackle key questions in helminth epidemiology and control through the sharing of such databases, and by using diverse, yet complementary, modelling approaches.

Detecting interspecific macroparasite interactions from ecological data: patterns and process

There is great interest in the occurrence and consequences of interspecific interactions among co-infecting parasites. However, the extent to which interactions occur is unknown, because there are no validated methods for their detection. We developed a model that generated abundance data for two interacting macroparasite (e.g., helminth) species, and challenged the data with various approaches to determine whether they could detect the underlying interactions. Current approaches performed poorly - either suggesting there was no interaction when, in reality, there was a strong interaction occurring, or inferring the presence of an interaction when there was none. We suggest the novel application of a generalized linear mixed modelling (GLMM)-based approach, which we show to be more reliable than current approaches, even when infection rates of both parasites are correlated (e.g., via a shared transmission route). We suggest that the lack of clarity regarding the presence or absence of interactions in natural systems may be largely attributed to the unreliable nature of existing methods for detecting them. However, application of the GLMM approach may provide a more robust method of detection for these potentially important interspecific interactions from ecological data.

Modelling stochastic transmission processes in helminth infections

The number of helminths within a host can only increase by the host encountering additional infectious stages, so it is important to consider not only whether a host is infected, but also the severity of its infection. Stochastic models consider explicitly the number of parasites within the host and treat infection, death and other demographic events as random processes. I discuss stochastic helminth population models of increasing degrees of complexity, starting with the infection dynamics within a single host and finishing with the full parasite lifecycle among a population of hosts. I demonstrate the mathematical techniques that can help to analyse these models and discuss the insights into parasite population biology that these methods can bring.

Modelling multi-species parasite transmission

Some models are presented for the dynamics of a host population with two parasite species. The models differ in two main aspects: whether they include direct competition among parasites and whether the analysis is based on some approximation and which one. If the analysis is not constrained by a priori assumptions about parasite distributions, it is found that species coexistence is very unlikely without some kind of direct competition among parasites; on the other hand, coexistence generally occurs when inter-specific competition is lower than intraspecific, similarly to standard theory for free-living species. If hosts differ in their predisposition to infection, but not in an identical way towards the two parasite species, then species coexistence becomes feasible even if inter-specific competition is as strong as intraspecific; in this case, coexistence becomes easier as the variance in predisposition increases. These models do not yield universal predictions for patterns of parasite distributions; an analysis of the mechanisms of interaction in each specific system is necessary for that.

Helminth species richness in wild wood mice, Apodemus sylvaticus, is enhanced by the presence of the intestinal nematode Heligmosomoides polygyrus

We analysed 3 independently collected datasets of fully censused helminth burdens in wood mice, Apodemus sylvaticus, testing the a priori hypothesis of Behnke et al. (2005) that the presence of the intestinal nematode Heligmosomoides polygyrus predisposes wood mice to carrying other species of helminths. In Portugal, mice carrying H. polygyrus showed a higher prevalence of other helminths but the magnitude of the effect was seasonal. In Egham, mice with H. polygyrus showed a higher prevalence of other helminth species, not confounded by other factors. In Malham Tarn, mice carrying H. polygyrus were more likely to be infected with other species, but only among older mice. Allowing for other factors, heavy residual H. polygyrus infections carried more species of other helminths in both the Portugal and Egham data; species richness in Malham was too low to conduct a similar analysis, but as H. polygyrus worm burdens increased, so the prevalence of other helminths also increased. Our results support those of Behnke et al. (2005), providing firm evidence that at the level of species richness a highly predictable element of co-infections in wood mice has now been defined: infection with H. polygyrus has detectable consequences for the susceptibility of wood mice to other intestinal helminth species.

Measuring immune system variation to help understand host-pathogen community dynamics

Carefully chosen immunological measurements, informed by recent advances in our understanding of the diversity and control of immune mechanisms, can add great interpretative value to ecological studies of infection. This is especially so for co-infection studies, where interactions between species are often mediated via the host's immune response. Here we consider how immunological measurements can strengthen inference in different types of co-infection analysis. In particular, we identify how measuring immune response variables in field studies can help reveal inter-species interactions otherwise obscured by confounding processes operating on count or prevalence data. Furthermore, we suggest that, due to the difficulty of quantifying microbial pathogen communities in field studies, innate responses against broad pathogen types (mediated by pattern response receptors) may be useful quantitative markers of exposure to bacteria and viruses. An ultimate goal of ecological co-infection studies may also be to understand how dynamics within host-parasite assemblages emerge from trade-offs involving different arms of the immune system. We reflect on the phenotypic measures that might best represent levels of responsiveness and bias in immune function. These include mediators associated with different T-helper cell subsets and innate responses controlled by pattern response receptors, such as the Toll-like receptors (TLRs).

Structure in parasite component communities in wild rodents: predictability, stability, associations and interactions .... or pure randomness?

Experimental data establish that interactions exist between species of intestinal helminths during concurrent infections in rodents, the strongest effects being mediated through the host's immune responses. Detecting immune-mediated relationships in wild rodent populations has been fraught with problems and published data do not support a major role for interactions in structuring helminth communities. Helminths in wild rodents show predictable patterns of seasonal, host age-dependent and spatial variation in species richness and in abundance of core species. When these are controlled for, patterns of co-infection compatible with synergistic interactions can be demonstrated. At least one of these, the positive relationship between Heligmosomoides polygyrus and species richness of other helminths has been demonstrated in three totally independent data-sets. Collectively, they explain only a small percentage of the variance/deviance in abundance data and at this level are unlikely to play a major role in structuring helminth communities, although they may be important in the more heavily infected wood mice. Current worm burdens underestimate the possibility that earlier interactions through the immune system have taken place, and therefore interactions may have a greater role to play than is immediately evident from current worm burdens. Longitudinal studies are proposed to resolve this issue.

Worms and germs: the population dynamic consequences of microparasite-macroparasite co-infection

Hosts are typically simultaneously co-infected by a variety of microparasites (e.g. viruses and bacteria) and macroparasites (e.g. parasitic helminths). However, the population dynamical consequences of such co-infections and the implications for the effectiveness of imposed control programmes have yet to be fully realised. Mathematical models may provide an important framework for exploring such issues and have proved invaluable in helping to understand the factors affecting the epidemiology of single parasitic infections. Here the first population dynamic model of microparasite-macroparasite co-infection is presented and used to explore how co-infection alters the predictions of the existing single-species models. It is shown that incorporating an additional parasite species into existing models can greatly stabilise them, due to the combined density-dependent impacts on the host population, but co-infection can also restrict the region of parameter space where each species could persist alone. Overall it is concluded that the dynamic feedback between host, microparasite and macroparasite means that it is difficult to appreciate the factors affecting parasite persistence and predict the effectiveness of control by just studying one component in isolation.

The dynamic influence of genetic variation on the susceptibility of sheep to gastrointestinal nematode infection

The interaction between sheep and the nematode Teladorsagia circumcincta is one of the best understood of all host-parasite interactions. Following infection, there is considerable variation among lambs in the number of nematode eggs produced, the number of early fourth-stage larvae and the number of adult worms in the mucosa. These traits have a high variance to mean ratio (i.e. they are overdispersed or aggregated among hosts), they are skewed and approximately negative binomially distributed. The sources of overdispersion are differences among lambs in the ingestion of infective larvae and the immune response. Both forces can produce aggregation but their relative importance is unknown. The key components of variation can be identified by variance analysis. The sum of the average effects of polymorphic genes is known as additive genetic variation and this increases essentially from zero at one month of age to quite high values at six months of age. The major mechanism underlying genetic variation appears to be the differences among individuals in immune responses. Two of the major sources of variation in immune responses are differences in antigen recognition and differences in the type of cytokines produced. Genes that influence both these sources of variation are associated with differences in resistance to nematode infection. Therefore, much of the heterogeneity among animals in parasite transmission appears to be due to genetic variation in immune responsiveness.

Variation in host susceptibility and infectiousness generated by co-infection: the myxoma-Trichostrongylus retortaeformis case in wild rabbits

One of the conditions that can affect host susceptibility and parasite transmission is the occurrence of concomitant infections. Parasites interact directly or indirectly within an individual host and often these interactions are modulated by the host immune response. We used a free-living rabbit population co-infected with the nematode Trichostrongylus retortaeformis, which appears to stimulate an acquired immune response, and the immunosuppressive poxvirus myxoma. Modelling was used to examine how myxoma infection alters the immune-mediated establishment and death/expulsion of T. retortaeformis, and consequently affects parasite intensity and duration of the infection. Simulations were based on the general T_H1–T_H2 immunological paradigm that proposes the polarization of the host immune response towards one of the two subsets of T helper cells. Our findings suggest that myxoma infections contribute to alter host susceptibility to the nematode, as co-infected rabbits showed higher worm intensity compared with virus negative hosts. Results also suggest that myxoma disrupts the ability of the host to clear T. retortaeformis as worm intensities were consistently high and remained high in old rabbits. However, the co-infection model has to include some immune-mediated nematode regulation to be consistent with field data, indicating that the T_H1–T_H2 dichotomy is not complete. We conclude that seasonal myxoma outbreaks enhance host susceptibility to the nematode and generate highly infected hosts that remain infectious for a longer time. Finally, the virus–nematode co-infection increases heterogeneities among individuals and potentially has a large effect on parasite transmission.

Density-dependent host choice by disease vectors: epidemiological implications of the ideal free distribution

The proportion of vector blood meals taken on humans (the human blood index, h) appears as a squared term in classical expressions of the basic reproduction ratio (R(0)) for vector-borne infections. Consequently, R(0) varies non-linearly with h. Estimates of h, however, constitute mere snapshots of a parameter that is predicted, from evolutionary theory, to vary with vector and host abundance. We test this prediction using a population dynamics model of river blindness assuming that, before initiation of vector control or chemotherapy, recorded measures of vector density and human infection accurately represent endemic equilibrium. We obtain values of h that satisfy the condition that the effective reproduction ratio (R(e)) must equal 1 at equilibrium. Values of h thus obtained decrease with vector density, decrease with the vector:human ratio and make R(0) respond non-linearly rather than increase linearly with vector density. We conclude that if vectors are less able to obtain human blood meals as their density increases, antivectorial measures may not lead to proportional reductions in R(0) until very low vector levels are achieved. Density dependence in the contact rate of infectious diseases transmitted by insects may be an important non-linear process with implications for their epidemiology and control.

Heterogeneous interspecific interactions in a host-parasite system

Macroparasites of vertebrates usually occur in multi-species communities, producing infections whose outcome in individual hosts or host populations may depend on the dynamics of interactions amongst the different component species. Within a single co-infection, competition can occur between conspecific and heterospecific parasite individuals, either directly or via the host's physiological and immune responses. We studied a natural single-host, multi-parasite model infection system (polystomes in the anuran Xenopus laevis victorianus) in which the parasite species show total interspecific competitive exclusion as adults in host individuals. Multi-species infection experiments indicated that competitive outcomes were dependent on infection species composition and strongly influenced by the intraspecific genetic identity of the interacting organisms. Our results also demonstrate the special importance of temporal heterogeneity (the sequence of infection by different species) in competition and co-existence between parasite species and predict that developmental plasticity in inferior competitors, and the induction of species-specific host resistance, will partition the within-host-individual habitat over time. We emphasise that such local (within-host) context-dependent processes are likely to be a fundamental determinant of population dynamics in multi-species parasite assemblages.

Co-infection withOnchocerca volvulusandLoa loamicrofilariae in central Cameroon: are these two species interacting?

Ivermectin treatment may induce severe adverse reactions in some individuals heavily infected withLoa loa. This hampers the implementation of mass ivermectin treatment against onchocerciasis in areas whereOnchocerca volvulusandL. loaare co-endemic. In order to identify factors, including co-infections, which may explain the presence of highL. loamicrofilaraemia in some individuals, we analysed data collected in 19 villages of central Cameroon. Two standardized skin snips and 30 μl of blood were obtained from each of 3190 participants and the microfilarial (mf) loads of bothO. volvulusandL. loawere quantified. The data were analysed using multivariate hierarchical models. Individual-level variables were: age, sex, mf presence, and mf load; village-related variables included the endemicity levels for each infection. The two species show a certain degree of ecological separation in the study area. However, for a given individual host, the presence of microfilariae of one species was positively associated with the presence of microfilariae of the other (OR=1·79, 95% CI [1·43–2·24]). Among individuals harbouringLoamicrofilariae, there was a slight positive relationship between theL. loaandO. volvulusmf loads which corresponded to an 11% increase inL. loamf load per 100O. volvulusmicrofilariae. Co-infection withO. volvulusis not sufficient to explain the very highL. loamf loads harboured by some individuals.