Staphylococcus aureus Host Spectrum Correlates with Methicillin Resistance in a Multi-Species Ecosystem.

Although antibiotic resistance is a major issue for both human and animal health, very few studies have investigated the role of the bacterial host spectrum in its dissemination within natural ecosystems. Here, we assessed the prevalence of methicillin resistance among Staphylococcus aureus (MRSA) isolates from humans, non-human primates (NHPs), micromammals and bats in a primatology center located in southeast Gabon, and evaluated the plausibility of four main predictions regarding the acquisition of antibiotic resistance in this ecosystem. MRSA strain prevalence was much higher in exposed species (i.e., humans and NHPs which receive antibiotic treatment) than in unexposed species (micromammals and bats), and in NHP species living in enclosures than those in captivity-supporting the assumption that antibiotic pressure is a risk factor in the acquisition of MRSA that is reinforced by the irregularity of drug treatment. In the two unexposed groups of species, resistance prevalence was high in the generalist strains that infect humans or NHPs, supporting the hypothesis that MRSA strains diffuse to wild species through interspecific transmission of a generalist strain. Strikingly, the generalist strains that were not found in humans showed a higher proportion of MRSA strains than specialist strains, suggesting that generalist strains present a greater potential for the acquisition of antibiotic resistance than specialist strains. The host spectrum is thus a major component of the issue of antibiotic resistance in ecosystems where humans apply strong antibiotic pressure.

Surgical Treatment of Oesophagostomum spp. Nodular Infection in a Chimpanzee at the CIRMF Primatology Center, Gabon.

Oesophagostomosis is a zoonotic disease caused by nematodes of the genus Oesophagostomum in the intestinal walls of many species, including ruminants, pigs, humans, and nonhuman primates. Although great apes appear to tolerate the parasite in the wild, they can develop a clinical form that can lead to death in captivity and the natural environment. At the Primatology Centre of the International Centre for Medical Research in Franceville (CIRMF) in Gabon, we recorded 4 deaths of chimpanzees (Pan t. troglodytes) caused by Oesophagostomum spp. between 2015 and 2019. In each case, coprological analysis was positive for strongylid eggs and abdominal ultrasound revealed nodules about 4 cm in diameter on the intestinal and abdominal walls. Albendazole treatments administered by mouth in two doses of 400 mg six months apart resulted in the disappearance of the parasite in coprological samples but the chimpanzees still died. Autopsies carried out on all four chimpanzees revealed a rupture of the cysts and a discharge of pus into the abdomen in each case. We report surgical management involving the removal of Oesophagostomum spp. cysts from a chimpanzee following coprological analysis and abdominal ultrasound examination. Surgical exploration confirmed the fragility of the cystic walls, the rupture of which we avoided. This 5th new case of Oesophagostomum ssp. nodules recovered without complications following the operation and could rejoin his group. We suggest that surgical intervention should be considered in similar cases in captive primates, especially chimpanzees.

Pathogens Shape Sex Differences in Mammalian Aging.

Understanding the origin of sex differences in lifespan and aging patterns remains a salient challenge in both biogerontology and evolutionary biology. Different factors have been studied but the potential influence of pathogens has never been investigated. Sex differences, especially in hormones and resource allocation, generate a differential response to pathogens and thereby shape sex differences in lifespan or aging. We provide an integrative framework linking host pathogenic environment with both sex-specific selections on immune performance and mortality trajectories. We propose future directions to fill existing knowledge gaps about mechanisms that link sex differences, not only to exposition and sensitivity to pathogens, but also to mortality patterns, whilst emphasizing the urgent need to consider the role of sex in medicine.

Bacterial Transformation Buffers Environmental Fluctuations through the Reversible Integration of Mobile Genetic Elements.

Horizontal gene transfer (HGT) promotes the spread of genes within bacterial communities. Among the HGT mechanisms, natural transformation stands out as being encoded by the bacterial core genome. Natural transformation is often viewed as a way to acquire new genes and to generate genetic mixing within bacterial populations. Another recently proposed function is the curing of bacterial genomes of their infectious parasitic mobile genetic elements (MGEs). Here, we propose that these seemingly opposing theoretical points of view can be unified. Although costly for bacterial cells, MGEs can carry functions that are at points in time beneficial to bacteria under stressful conditions (e.g., antibiotic resistance genes). Using computational modeling, we show that, in stochastic environments, an intermediate transformation rate maximizes bacterial fitness by allowing the reversible integration of MGEs carrying resistance genes, although these MGEs are costly for host cell replication. Based on this dual function (MGE acquisition and removal), transformation would be a key mechanism for stabilizing the bacterial genome in the long term, and this would explain its striking conservation.IMPORTANCE Natural transformation is the acquisition, controlled by bacteria, of extracellular DNA and is one of the most common mechanisms of horizontal gene transfer, promoting the spread of resistance genes. However, its evolutionary function remains elusive, and two main roles have been proposed: (i) the new gene acquisition and genetic mixing within bacterial populations and (ii) the removal of infectious parasitic mobile genetic elements (MGEs). While the first one promotes genetic diversification, the other one promotes the removal of foreign DNA and thus genome stability, making these two functions apparently antagonistic. Using a computational model, we show that intermediate transformation rates, commonly observed in bacteria, allow the acquisition then removal of MGEs. The transient acquisition of costly MGEs with resistance genes maximizes bacterial fitness in environments with stochastic stress exposure. Thus, transformation would ensure both a strong dynamic of the bacterial genome in the short term and its long-term stabilization.

Pollen limitation as a main driver of fruiting dynamics in oak populations.

In many perennial wind-pollinated plants, the dynamics of seed production is commonly known to be highly fluctuating from year to year and synchronised among individuals within populations. The proximate causes of such seeding dynamics, called masting, are still poorly understood in oak species that are widespread in the northern hemisphere, and whose fruiting dynamics dramatically impacts forest regeneration and biodiversity. Combining long-term surveys of oak airborne pollen amount and acorn production over large-scale field networks in temperate areas, and a mechanistic modelling approach, we found that the pollen dynamics is the key driver of oak masting. Mechanisms at play involved both internal resource allocation to pollen production synchronised among trees and spring weather conditions affecting the amount of airborne pollen available for reproduction. The sensitivity of airborne pollen to weather conditions might make oak masting and its ecological consequences highly sensitive to climate change.

Coexistence of two sympatric cryptic bat species in French Guiana: insights from genetic, acoustic and ecological data.

BACKGROUND: The distinction between lineages of neotropical bats from the Pteronotus parnellii species complex has been previously made according to mitochondrial DNA, and especially morphology and acoustics, in order to separate them into two species. In these studies, either sample sizes were too low when genetic and acoustic or morphological data were gathered on the same individuals, or genetic and other data were collected on different individuals. In this study, we intensively sampled bats in 4 caves and combined all approaches in order to analyse genetic, morphologic, and acoustic divergence between these lineages that live in the same caves in French Guiana. RESULTS: A multiplex of 20 polymorphic microsatellite markers was developed using the 454-pyrosequencing technique to investigate for the first time the extent of reproductive isolation between the two lineages and the population genetic structure within lineages. We genotyped 748 individuals sampled between 2010 and 2015 at the 20 nuclear microsatellite loci and sequenced a portion of the cytochrome c oxydase I gene in a subset of these. Two distinct, non-overlapping haplogroups corresponding to cryptic species P. alitonus and P. rubiginosus were revealed, in accordance with previous findings. No spatial genetic structure between caves was detected for both species. Hybridization appeared to be quite limited (0.1-4%) using microsatellite markers whereas introgression was more common (7.5%) and asymmetric for mitochondrial DNA (mtDNA). CONCLUSIONS: The extremely low rate of hybridization could be explained by differences in life cycle phenology between species as well as morphological and acoustical distinction between sexes in one or the other species. Taken together, these results add to our growing understanding of the nature of species boundaries in Pteronotus parnelli, but deserve more in-depth studies to understand the evolutionary processes underlying asymmetric mtDNA introgression in this group of cryptic species.

Linking influenza epidemic onsets to covariates at different scales using a dynamical model.

BACKGROUND: Evaluating the factors favoring the onset of influenza epidemics is a critical public health issue for surveillance, prevention and control. While past outbreaks provide important insights for understanding epidemic onsets, their statistical analysis is challenging since the impact of a factor can be viewed at different scales. Indeed, the same factor can explain why epidemics are more likely to begin (i) during particular weeks of the year (global scale); (ii) earlier in particular regions (spatial scale) or years (annual scale) than others and (iii) earlier in some years than others within a region (spatiotemporal scale). METHODS: Here, we present a statistical approach based on dynamical modeling of infectious diseases to study epidemic onsets. We propose a method to disentangle the role of covariates at different scales and use a permutation procedure to assess their significance. Epidemic data gathered from 18 French regions over six epidemic years were provided by the Regional Influenza Surveillance Group (GROG) sentinel network. RESULTS: Our results failed to highlight a significant impact of mobility flows on epidemic onset dates. Absolute humidity had a significant impact, but only at the spatial scale. No link between demographic covariates and influenza epidemic onset dates could be established. DISCUSSION: Dynamical modeling presents an interesting basis to analyze spatiotemporal variations in the outcome of epidemic onsets and how they are related to various types of covariates. The use of these models is quite complex however, due to their mathematical complexity. Furthermore, because they attempt to integrate migration processes of the virus, such models have to be much more explicit than pure statistical approaches. We discuss the relation of this approach to survival analysis, which present significant differences but may constitute an interesting alternative for non-methodologists.

The host specificity of ape malaria parasites can be broken in confined environments.

Recent studies have revealed a large diversity of Plasmodium spp. among African great apes. Some of these species are related to Plasmodium falciparum, the most virulent agent of human malaria (subgenus Laverania), and others to Plasmodium ovale, Plasmodium malariae and Plasmodium vivax (subgenus Plasmodium), three other human malaria agents. Laverania parasites exhibit strict host specificity in their natural environment. Plasmodium reichenowi, Plasmodium billcollinsi, Plasmodium billbrayi and Plasmodium gaboni infect only chimpanzees, while Plasmodium praefalciparum, Plasmodium blacklocki and Plasmodium adleri are restricted to gorillas and Plasmodium falciparum is pandemic in humans. This host specificity may be due to genetic and/or environmental factors. Infrastructures hosting captive primates, such as sanctuaries and health centres, usually concentrate different primate species, thus favouring pathogen exchanges. Using molecular tools, we analysed blood samples from captive non-human primates living in Gabon to evaluate the risk of Plasmodium spp. transfers between host species. We also included blood samples from workers taking care of primates to assess whether primate-human parasite transfers occurred. We detected four transfers of Plasmodium from gorillas towards chimpanzees, one from chimpanzees to gorillas, three from humans towards chimpanzees and one from humans to mandrills. No simian Plasmodium was found in the blood samples from humans working with primates. These findings demonstrate that the genetic barrier that determines the apparent host specificity of Laverania is not completely impermeable and that parasite exchanges between gorillas and chimpanzees are possible in confined environments.

Quantifying the role of weather on seasonal influenza.

BACKGROUND: Improving knowledge about influenza transmission is crucial to upgrade surveillance network and to develop accurate predicting models to enhance public health intervention strategies. Epidemics usually occur in winter in temperate countries and during the rainy season for tropical countries, suggesting a climate impact on influenza spread. Despite a lot of studies, the role of weather on influenza spread is not yet fully understood. In the present study, we investigated this issue at two different levels. METHODS: First, we evaluated how weekly (intra-annual) incidence variations of clinical diseases could be linked to those of climatic factors. We considered that only a fraction of the human population is susceptible at the beginning of a year due to immunity acquired from previous years. Second, we focused on epidemic sizes (cumulated number of clinical reported cases) and looked at how their inter-annual and regional variations could be related to differences in the winter climatic conditions of the epidemic years over the regions. We quantified the impact of fifteen climatic variables in France using the Réseau des GROG surveillance network incidence data over eleven regions and nine years. RESULTS: At the epidemic scale, no impact of climatic factors was highlighted. At the intra-annual scale, six climatic variables had a significant impact: average temperature (5.54 ± 1.09 %), absolute humidity (5.94 ± 1.08 %), daily variation of absolute humidity (3.02 ± 1.17 %), sunshine duration (3.46 ± 1.06 %), relative humidity (4.92 ± 1.20 %) and daily variation of relative humidity (4.46 ± 1.24 %). Since in practice the impact of two highly correlated variables is very hard to disentangle, we performed a principal component analysis that revealed two groups of three highly correlated climatic variables: one including the first three highlighted climatic variables on the one hand, the other including the last three ones on the other hand. CONCLUSIONS: These results suggest that, among the six factors that appeared to be significant, only two (one per group) could in fact have a real effect on influenza spread, although it is not possible to determine which one based on a purely statistical argument. Our results support the idea of an important role of climate on the spread of influenza.

Parasite-Parasite Interactions in the Wild: How To Detect Them?

Inter-specific interactions between parasites impact on parasite intra-host dynamics, host health, and disease management. Identifying and understanding interaction mechanisms in the wild is crucial for wildlife disease management. It is however complex because several scales are interlaced. Parasite-parasite interactions are likely to occur via mechanisms at the within-host level, but also at upper levels (host population and community). Furthermore, interactions occurring at one level of organization spread to upper levels through cascade effects. Even if cascade effects are important confounding factors, we argue that we can also benefit from them because upper scales often provide a way to survey a wider range of parasites at lower cost. New protocols and theoretical studies (especially across scales) are necessary to take advantage of this opportunity.

Modes of transmission of Simian T-lymphotropic Virus Type 1 in semi-captive mandrills (Mandrillus sphinx).

Non-human primates (NHPs) often live in inaccessible areas, have cryptic behaviors, and are difficult to follow in the wild. Here, we present a study on the spread of the simian T-lymphotropic Virus Type 1 (STLV-1), the simian counterpart of the human T-lymphotropic virus type 1 (HTLV-1) in a semi-captive mandrill colony. This study combines 28 years of longitudinal monitoring, including behavioral data, with a dynamic mathematical model and Bayesian inference. Three transmission modes were suspected: aggressive, sexual and familial. Our results show that among males, STLV-1 transmission occurs preferentially via aggression. Because of their impressive aggressive behavior male mandrills can easily transmit the virus during fights. On the contrary, sexual activity seems to have little effect. Thus transmission appears to occur primarily via male-male and female-female contact. In addition, for young mandrills, familial transmission appears to play an important role in virus spread.

Unknown age in health disorders: A method to account for its cumulative effect and an application to feline viruses interactions.

Parasite interactions have been widely evidenced experimentally but field studies remain rare. Such studies are essential to detect interactions of interest and access (co)infection probabilities but face methodological obstacles. Confounding factors can create statistical associations, i.e. false parasite interactions. Among them, host age is a crucial covariate. It influences host exposition and susceptibility to many infections, and has a mechanical effect, older individuals being more at risk because of a longer exposure time. However, age is difficult to estimate in natural populations. Hence, one should be able to deal at least with its cumulative effect. Using a SI type dynamic model, we showed that the cumulative effect of age can generate false interactions theoretically (deterministic modeling) and with a real dataset of feline viruses (stochastic modeling). The risk to wrongly conclude to an association was maximal when parasites induced long-lasting antibodies and had similar forces of infection. We then proposed a method to correct for this effect (and for other potentially confounding shared risk factors) and made it available in a new R package, Interatrix. We also applied the correction to the feline viruses. It offers a way to account for an often neglected confounding factor and should help identifying parasite interactions in the field, a necessary step towards a better understanding of their mechanisms and consequences.

Quantifying transmission by stage of infection in the field: the example of SIV-1 and STLV-1 infecting mandrills.

The early stage of viral infection is often followed by an important increase of viral load and is generally considered to be the most at risk for pathogen transmission. Most methods quantifying the relative importance of the different stages of infection were developed for studies aimed at measuring HIV transmission in Humans. However, they cannot be transposed to animal populations in which less information is available. Here we propose a general method to quantify the importance of the early and late stages of the infection on micro-organism transmission from field studies. The method is based on a state space dynamical model parameterized using Bayesian inference. It is illustrated by a 28 years dataset in mandrills infected by Simian Immunodeficiency Virus type-1 (SIV-1) and the Simian T-Cell Lymphotropic Virus type-1 (STLV-1). For both viruses we show that transmission is predominant during the early stage of the infection (transmission ratio for SIV-1: 1.16 [0.0009; 18.15] and 9.92 [0.03; 83.8] for STLV-1). However, in terms of basic reproductive number (R0 ), which quantifies the weight of both stages in the spread of the virus, the results suggest that the epidemics of SIV-1 and STLV-1 are mainly driven by late transmissions in this population.

Early infections by myxoma virus of young rabbits (Oryctolagus cuniculus) protected by maternal antibodies activate their immune system and enhance herd immunity in wild populations.

The role of maternal antibodies is to protect newborns against acute early infection by pathogens. This can be achieved either by preventing any infection or by allowing attenuated infections associated with activation of the immune system, the two strategies being based on different cost/benefit ratios. We carried out an epidemiological survey of myxomatosis, which is a highly lethal infectious disease, in two distant wild populations of rabbits to describe the epidemiological pattern of the disease. Detection of specific IgM and IgG enabled us to describe the pattern of immunity. We show that maternal immunity attenuates early infection of juveniles and enables activation of their immune system. This mechanism associated with steady circulation of the myxoma virus in both populations, which induces frequent reinfections of immune rabbits, leads to the maintenance of high immunity levels within populations. Thus, myxomatosis has a low impact, with most infections being asymptomatic. This work shows that infection of young rabbits protected by maternal antibodies induces attenuated disease and activates their immune system. This may play a major role in reducing the impact of a highly lethal disease when ecological conditions enable permanent circulation of the pathogen.

Accounting for sampling error when inferring population synchrony from time-series data: a Bayesian state-space modelling approach with applications.

BACKGROUND: Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. METHODOLOGY/PRINCIPAL FINDINGS: The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. CONCLUSION/SIGNIFICANCE: The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates.

Natural simian immunodeficiency virus transmission in mandrills: a family affair?

Understanding how pathogens spread and persist in the ecosystem is critical for deciphering the epidemiology of diseases of significance for global health and the fundamental mechanisms involved in the evolution of virulence and host resistance. Combining long-term behavioural and epidemiological data collected in a naturally infected mandrill population and a Bayesian framework, the present study investigated unknown aspects of the eco-epidemiology of simian immunodeficiency virus (SIV), the recent ancestor of HIV. Results show that, in contrast to what is expected from aggressive and sexual transmission (i.e. the two commonly accepted transmission modes for SIV), cases of SIVmnd-1 subtype were significantly correlated among related individuals (greater than 30% of the observed cases). Challenging the traditional view of SIV, this finding suggests the inheritance of genetic determinants of susceptibility to SIV and/or a role for behavioural interactions among maternal kin affecting the transmission of the virus, which would highlight the underappreciated role of sociality in the spread of infectious diseases. Outcomes of this study also provide novel insights into the role of host social structure in the evolution of pathogens.

True versus false parasite interactions: a robust method to take risk factors into account and its application to feline viruses.

BACKGROUND: Multiple infections are common in natural host populations and interspecific parasite interactions are therefore likely within a host individual. As they may seriously impact the circulation of certain parasites and the emergence and management of infectious diseases, their study is essential. In the field, detecting parasite interactions is rendered difficult by the fact that a large number of co-infected individuals may also be observed when two parasites share common risk factors. To correct for these "false interactions", methods accounting for parasite risk factors must be used. METHODOLOGY/PRINCIPAL FINDINGS: In the present paper we propose such a method for presence-absence data (i.e., serology). Our method enables the calculation of the expected frequencies of single and double infected individuals under the independence hypothesis, before comparing them to the observed ones using the chi-square statistic. The method is termed "the corrected chi-square." Its robustness was compared to a pre-existing method based on logistic regression and the corrected chi-square proved to be much more robust for small sample sizes. Since the logistic regression approach is easier to implement, we propose as a rule of thumb to use the latter when the ratio between the sample size and the number of parameters is above ten. Applied to serological data for four viruses infecting cats, the approach revealed pairwise interactions between the Feline Herpesvirus, Parvovirus and Calicivirus, whereas the infection by FIV, the feline equivalent of HIV, did not modify the risk of infection by any of these viruses. CONCLUSIONS/SIGNIFICANCE: This work therefore points out possible interactions that can be further investigated in experimental conditions and, by providing a user-friendly R program and a tutorial example, offers new opportunities for animal and human epidemiologists to detect interactions of interest in the field, a crucial step in the challenge of multiple infections.

The role of recombination for the coevolutionary dynamics of HIV and the immune response.

The evolutionary implications of recombination in HIV remain not fully understood. A plausible effect could be an enhancement of immune escape from cytotoxic T lymphocytes (CTLs). In order to test this hypothesis, we constructed a population dynamic model of immune escape in HIV and examined the viral-immune dynamics with and without recombination. Our model shows that recombination (i) increases the genetic diversity of the viral population, (ii) accelerates the emergence of escape mutations with and without compensatory mutations, and (iii) accelerates the acquisition of immune escape mutations in the early stage of viral infection. We see a particularly strong impact of recombination in systems with broad, non-immunodominant CTL responses. Overall, our study argues for the importance of recombination in HIV in allowing the virus to adapt to changing selective pressures as imposed by the immune system and shows that the effect of recombination depends on the immunodominance pattern of effector T cell responses.

Can cat predation help competitors coexist in seabird communities?

On oceanic islands, nest site availability can be an important factor regulating seabird population dynamics. The potential for birds to secure a nest to reproduce can be an important component of their life histories. The dates at which different seabird species arrive at colonies to breed will have important consequences for their relative chances of success. Early arrival on the island allows birds to obtain nests more easily and have higher reproductive success. However, the presence of an introduced predator may reverse this situation. For instance, in the sub-Antarctic Kerguelen archipelago, early arriving birds suffer heavy predation from introduced cats. Cats progressively switch from seabirds to rabbits, since the local rabbit population starts to peak after early arriving seabird species have already returned to the colony. When late-arriving birds arrive, cat predation pressure on seabirds is thus weaker. In this paper, we investigate the assumption that the advantage of early nest mnopolization conferred to early arriving birds may be counterbalanced by the cost resulting from predation. We develop a mathematical model representing a simplified situation in which two insular seabird species differ only in their arrival date at the colony site and compete for nesting sites. We conclude that predation may ensure the coexistence of the two bird species or favor the late-arriving species, but only when seasonal variations in predation pressure are large. Interestingly, we conclude that arriving early is only favorable until a given level where high reproductive success no longer compensates for the long exposure to strong predation pressure. Our work suggests that predation can help to maintain the balance between species of different phenologies.

Using dynamic stochastic modelling to estimate population risk factors in infectious disease: the example of FIV in 15 cat populations.

BACKGROUND: In natural cat populations, Feline Immunodeficiency Virus (FIV) is transmitted through bites between individuals. Factors such as the density of cats within the population or the sex-ratio can have potentially strong effects on the frequency of fight between individuals and hence appear as important population risk factors for FIV. METHODOLOGY/PRINCIPAL FINDINGS: To study such population risk factors, we present data on FIV prevalence in 15 cat populations in northeastern France. We investigate five key social factors of cat populations; the density of cats, the sex-ratio, the number of males and the mean age of males and females within the population. We overcome the problem of dependence in the infective status data using sexually-structured dynamic stochastic models. Only the age of males and females had an effect (p = 0.043 and p = 0.02, respectively) on the male-to-female transmission rate. Due to multiple tests, it is even likely that these effects are, in reality, not significant. Finally we show that, in our study area, the data can be explained by a very simple model that does not invoke any risk factor. CONCLUSION: Our conclusion is that, in host-parasite systems in general, fluctuations due to stochasticity in the transmission process are naturally very large and may alone explain a larger part of the variability in observed disease prevalence between populations than previously expected. Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease.