Infection Status Of Individuals Research Articles

A performance comparison of two (electro) chemiluminescence immunoassays for detection and quantitation of serum anti-spike antibodies according to SARS-CoV-2 vaccination and infections status.

The information provided by SARS-CoV-2 spike (S)-targeting immunoassays can be instrumental in clinical-decision making. We compared the performance of the Elecsys® Anti-SARS-CoV-2 S assay (Roche Diagnostics) and the LIAISON® SARS-CoV-2 TrimericS IgG assay (DiaSorin) using a total of 1176 sera from 797 individuals, of which 286 were from vaccinated-SARS-CoV-2/experienced (Vac-Ex), 581 from vaccinated/naïve (Vac-N), 147 from unvaccinated/experienced (Unvac-Ex), and 162 from unvaccinated/naïve (Unvac-N) individuals. The Roche assay returned a higher number of positive results (907 vs. 790; p = 0.45; overall sensitivity: 89.3% vs. 77.6%). The concordance between results provided by the two immunoassays was higher for sera from Vac-N (ϰ: 0.58; interquartile ranges[IQR]:0.50-0.65) than for sera from Vac-Ex (ϰ: 0.19; IQR:-0.14 to 0.52) or Unvac-Ex (ϰ: 0.18; IQR:0.06-0.30). Discordant results occurred more frequently among sera from Unvac-Ex (34.7%) followed by Vac-N (14.6%) and Vac-Ex (2.7%). Antibody levels quantified by both immunoassays were not significantly different when <250 (p = 0.87) or <1000 BAU/ml (p = 0.13); in contrast, for sera ≥1000 BAU/ml, the Roche assay returned significantly higher values than the DiaSorin assay (p < 0.008). Neutralizing antibody titers (NtAb) were measured in 127 sera from Vac-Ex or Vac-N using a S-pseudotyped virus neutralization assay of Wuhan-Hu-1, Omicron BA.1, and Omicron BA.2. The correlation between antibody levels and NtAb titers was higher for sera from Vac-N than those from Vac-Ex, irrespective of the (sub)variant considered. In conclusion, neither qualitative nor quantitative results returned by both immunoassays are interchangeable. The performance of both assays was found to be greatly influenced by the vaccination and SARS-CoV-2 infection status of individuals.

Using Timeliness in Tracking Infections.

We consider real-time timely tracking of infection status (e.g., COVID-19) of individuals in a population. In this work, a health care provider wants to detect both infected people and people who have recovered from the disease as quickly as possible. In order to measure the timeliness of the tracking process, we use the long-term average difference between the actual infection status of the people and their real-time estimate by the health care provider based on the most recent test results. We first find an analytical expression for this average difference for given test rates, infection rates and recovery rates of people. Next, we propose an alternating minimization-based algorithm to find the test rates that minimize the average difference. We observe that if the total test rate is limited, instead of testing all members of the population equally, only a portion of the population may be tested in unequal rates calculated based on their infection and recovery rates. Next, we characterize the average difference when the test measurements are erroneous (i.e., noisy). Further, we consider the case where the infection status of individuals may be dependent, which occurs when an infected person spreads the disease to another person if they are not detected and isolated by the health care provider. In addition, we consider an age of incorrect information-based error metric where the staleness metric increases linearly over time as long as the health care provider does not detect the changes in the infection status of the people. Through extensive numerical results, we observe that increasing the total test rate helps track the infection status better. In addition, an increased population size increases diversity of people with different infection and recovery rates, which may be exploited to spend testing capacity more efficiently, thereby improving the system performance. Depending on the health care provider’s preferences, test rate allocation can be adjusted to detect either the infected people or the recovered people more quickly. In order to combat any errors in the test, it may be more advantageous for the health care provider to not test everyone, and instead, apply additional tests to a selected portion of the population. In the case of people with dependent infection status, as we increase the total test rate, the health care provider detects the infected people more quickly, and thus, the average time that a person stays infected decreases. Finally, the error metric needs to be chosen carefully to meet the priorities of the health care provider, as the error metric used greatly influences who will be tested and at what test rate.

Assessing rates of parasite coinfection and spatiotemporal strain variation via metabarcoding: Insights for the conservation of European turtle doves Streptopelia turtur.

Understanding the frequency, spatiotemporal dynamics and impacts of parasite coinfections is fundamental to developing control measures and predicting disease impacts. The European turtle dove (Streptopelia turtur) is one of Europe's most threatened bird species. High prevalence of infection by the protozoan parasite Trichomonas gallinae has previously been identified, but the role of this and other coinfecting parasites in turtle dove declines remains unclear. Using a high‐throughput sequencing approach, we identified seven strains of T. gallinae, including two novel strains, from ITS1/5.8S/ITS2 ribosomal sequences in turtle doves on breeding and wintering grounds, with further intrastrain variation and four novel subtypes revealed by the iron‐hydrogenase gene. High spatiotemporal turnover was observed in T. gallinae strain composition, and infection was prevalent in all populations (89%–100%). Coinfection by multiple Trichomonas strains was rarer than expected (1% observed compared to 38.6% expected), suggesting either within‐host competition, or high mortality of coinfected individuals. In contrast, coinfection by multiple haemosporidians was common (43%), as was coinfection by haemosporidians and T. gallinae (90%), with positive associations between strains of T. gallinae and Leucocytozoon suggesting a mechanism such as parasite‐induced immune modulation. We found no evidence for negative associations between coinfections and host body condition. We suggest that longitudinal studies involving the recapture and investigation of infection status of individuals over their lifespan are crucial to understand the epidemiology of coinfections in natural populations.

Emergence of a Novel Dengue Virus 3 (DENV-3) Genotype-I Coincident with Increased DENV-3 Cases in Yangon, Myanmar between 2017 and 2019.

Dengue fever, caused by the mosquito-borne dengue virus (DENV), has been endemic in Myanmar since 1970 and it has become a significant public health burden. It is crucial that circulating DENV strains are identified and monitored, and that their transmission efficiency and association with disease severity is understood. In this study, we analyzed DENV-1, DENV-2, DENV-3, and DENV-4 serotypes in 1235 serum samples collected in Myanmar between 2017 and 2019. Whole-genome sequencing of DENV-1–4 demonstrated that most DENV-1–4 strains had been circulating in Myanmar for several years. We also identified the emergence of DENV-3 genotype-I in 2017 samples, which persisted through 2018 and 2019. The emergence of the strain coincided with a period of increased DENV-3 cases and marked changes in the serotype dynamics. Nevertheless, we detected no significant differences between serum viral loads, disease severity, and infection status of individuals infected with different DENV serotypes during the 3-year study. Our results not only identify the spread of a new DENV-3 genotype into Yangon, Myanmar, but also support the importance of DENV evolution in changing the epidemic dynamics in endemic regions.

Emulation‐based inference for spatial infectious disease transmission models incorporating event time uncertainty

AbstractMechanistic models of infectious disease spread are key to inferring spatiotemporal infectious disease transmission dynamics. Ideally, covariate data and the infection status of individuals over time would be used to parameterize such models. However, in reality, complete data are rarely available; for example, infection times are almost never observed. Bayesian data‐augmented Markov chain Monte Carlo (MCMC) methods are commonly used to allow us to infer such missing or censored data. However, for large disease systems, these methods can be highly computationally expensive. In this paper, we propose two methods of approximate inference for such situations based on so‐called emulation techniques. Here, both methods are set in a Bayesian MCMC framework but replace the computationally expensive likelihood function by a Gaussian process‐based likelihood approximation. In the first method, we build an emulator of the discrepancy between summary statistics of simulated and observed epidemic data. In the second method, we develop an emulator of an importance sampling‐based likelihood approximation. We show how both methods offer substantial computational efficiency gains over standard Bayesian MCMC‐based method, and can be used to infer the transmission of complex infectious disease systems. We also show that importance sampling‐based methods tend to perform more satisfactorily.

Modelling the utility of group testing for public health surveillance.

In epidemic or pandemic situations, resources for testing the infection status of individuals may be scarce. Although group testing can help to significantly increase testing capabilities, the (repeated) testing of entire populations can exceed the resources of any country. We thus propose an extension of the theory of group testing that takes into account the fact that definitely specifying the infection status of each individual is impossible. Our theory builds on assigning to each individual an infection status (healthy/infected), as well as an associated cost function for erroneous assignments. This cost function is versatile, e.g., it could take into account that false negative assignments are worse than false positive assignments and that false assignments in critical areas, such as health care workers, are more severe than in the general population. Based on this model, we study the optimal use of a limited number of tests to minimize the expected cost. More specifically, we utilize information-theoretic methods to give a lower bound on the expected cost and describe simple strategies that can significantly reduce the expected cost over currently known strategies. A detailed example is provided to illustrate our theory.

Infection Status as the Basis for Habitat Choices in a Wild Amphibian

AbstractAnimals challenged with disease may select specific habitat conditions that help prevent or reduce infection. Whereas preinfection avoidance of habitats with a high risk of disease exposure has been documented in both captive and free-ranging animals, evidence of switching habitats after infection to support the clearing of the infection is limited to laboratory experiments. The extent to which wild animals proximately modify habitat choices in response to infection status thus remains unclear. We investigated preinfection behavioral avoidance and postinfection habitat switching using wild, radio-tracked boreal toads (Anaxyrus boreas boreas) in a population challenged with Batrachochytrium dendrobatidis (Bd), a pathogenic fungus responsible for a catastrophic panzootic affecting hundreds of amphibian species worldwide. Boreal toads did not preemptively avoid microhabitats with conditions conducive to Bd growth. Infected individuals, however, selected warmer, more open habitats, which were associated with elevated body temperature and the subsequent clearing of infection. Our results suggest that disease can comprise an important selective pressure on animal habitat and space use. Habitat selection models, therefore, may be greatly improved by including variables that quantify infection risk and/or the infection status of individuals through time.

Avian haemosporidian prevalence and its relationship to host traits in Western Tennessee

Avian malaria and related haemosporidian parasites (genera Plasmodium and Parahaemoproteus) are the most common parasites in many bird populations and are known to affect survival and reproduction. We analyze how species-level and individual-level traits influence parasite prevalence among species and infection status among individuals. We collected blood samples of 625 individuals from 35 host species and used PCR to screen for infection status. We found that 44% of the individuals were infected, and 38 unique lineages of haemosporidian parasites were obtained. Total prevalence and prevalence of Plasmodium and Parahaemoproteus separately were significantly heterogeneous across species, ranging from 0 to 100%. Total and Plasmodium prevalence increased significantly with host species abundance, but Parahaemoproteus prevalence did not. Parasite prevalence did not vary with other species-level traits, including species mass, annual survival, nest type, nesting or foraging height, and degree of sexual dimorphism. Individual-level traits, such as age and sex, did not predict infection status of individuals. Our research documents a high diversity of haemosporidian parasites and substantial variation in parasite prevalence across host species. However, contrary to expectations, haemosporidian prevalence is not strongly related to many host life history traits. Future studies that examine vector abundance and parasite prevalence across habitat types might be especially productive.

Characterisation of serum IgG(T) responses to potential diagnostic antigens for equine cyathostominosis

Cyathostomins are ubiquitous parasitic nematodes of horses. These worms spend substantial periods as intestinal wall stage encysted larvae, which can comprise up to 90% of the total burden. Several million larvae have been reported in individuals. Emergence of these larvae from the gut wall can lead to life-threatening colitis. Faecal egg count tests, increasingly used by horse owners to inform anthelmintic treatments, do not correlate with the intra-host burden of cyathostomins; this represents a key gap in the diagnostic toolbox. Previously, a cyathostomin Gut Associated Larval Antigen was identified as a promising marker for the intra-host stages of infection. Here, cyathostomin Gut Associated Larval Antigen and an additional protein, Cyathostomin Immuno-diagnostic antigen, were investigated to examine their value in providing information on cyathostomin burden. ELISA analyses examined serum IgG(T) responses to recombinant proteins derived from individual cyathostomin species. Receiver Operator Characteristic curve analysis was performed on the ELISA data; proteins with the highest Area Under the Curve values were selected to test protein combinations to investigate which were the most informative in identifying the infection status of individuals. Three cocktail combinations were tested, comprising: (a) Cy-GALA proteins from two species and a Cy-CID protein from a third species (CT3), (b) Cy-GALA proteins from five species (CT5), and (c) all CT5 components, plus a Cy-CID protein from an additional species (CT6). The best predictive values for infection were obtained using CT3 and CT6, with similar values achieved for both. Proteins in CT3 are derived from the most commonly reported species, Cyathostomum catinatum, Cylicocyclus nassatus and Cylicostephanus longibursatus. This combination was selected for future development since it represents a more commercially viable format for a diagnostic test.

Inference of the infection status of individuals using longitudinal testing data from cryptic populations: Towards a probabilistic approach to diagnosis

Effective control of many diseases requires the accurate detection of infected individuals. Confidently ascertaining whether an individual is infected can be challenging when diagnostic tests are imperfect and when some individuals go for long periods of time without being observed or sampled. Here, we use a multi-event capture-recapture approach to model imperfect observations of true epidemiological states. We describe a method for interpreting potentially disparate results from individuals sampled multiple times over an extended period, using empirical data from a wild badger population naturally infected with Mycobacterium bovis as an example. We examine the effect of sex, capture history and current and historical diagnostic test results on the probability of being truly infected, given any combination of diagnostic test results. In doing so, we move diagnosis away from the traditional binary classification of apparently infected versus uninfected to a probability-based interpretation which is updated each time an individual is re-sampled. Our findings identified temporal variation in infection status and suggest that capture probability is influenced by year, season and infection status. This novel approach to combining ecological and epidemiological data may aid disease management decision-making by providing a framework for the integration of multiple diagnostic test data with other information.

Social and environmental factors affect tuberculosis related mortality in wild meerkats.

Summary Tuberculosis (TB) is an important and widespread disease of wildlife, livestock and humans world‐wide, but long‐term empirical datasets describing this condition are rare. A population of meerkats (Suricata suricatta) in South Africa's Kalahari Desert have been diagnosed with Mycobacterium suricattae, a novel strain of TB, causing fatal disease in this group‐living species.This study aimed to find characteristics associated with clinical TB in meerkats. These characteristics could subsequently be used to identify ‘at‐risk’ animals within a population, and target these individuals for control measures.We conducted a retrospective study based on a unique, long‐term life‐history dataset of over 2000 individually identified animals covering a 14‐year period after the first confirmatory diagnosis of TB in this population in 2001. Individual‐ and group‐level risk factors were analysed using time‐dependent Cox regression to examine their potential influence on the time to development of end‐stage TB.Cases of disease involved 144 individuals in 27 of 73 social groups, across 12 of 14 years (an incidence rate of 3·78 cases/100 study years). At the individual level, increasing age had the greatest effect on risk of disease with a hazard ratio of 4·70 (95% CI: 1·92–11·53, P < 0·01) for meerkats aged 24–48 months, and a hazard ratio of 9·36 (3·34–26·25, P < 0·001) for animals aged over 48 months (both age categories compared with animals aged below 24 months). Previous group history of TB increased the hazard by a factor of 4·29 (2·00–9·17, P < 0·01), and an interaction was found between this variable and age. At a group level, immigrations of new group members in the previous year increased hazard by a factor of 3·00 (1·23–7·34, P = 0·016). There was weaker evidence of an environmental effect with a hazard ratio for a low rainfall (<200 mm) year of 2·28 (0·91–5·72, P = 0·079).Our findings identify potential individual characteristics on which to base targeted control measures such as vaccination. Additional data on the dynamics of the infection status of individuals and how this changes over time would complement these findings by enhancing understanding of disease progression and transmission, and thus the implications of potential management measures.

Outdoor biting by Anopheles mosquitoes on Bioko Island does not currently impact on malaria control.

BackgroundThere have been many recent reports that the rate of outdoor biting by malaria vectors has increased. This study examined the impact this might have on malaria transmission by assessing the association between exposure to outdoor bites and malaria infection on Bioko Island, Equatorial Guinea.MethodsResponses to questions about time spent outside the previous night from a malaria indicator survey were combined with human landing catch measurements of hourly rates of outdoor and indoor biting for the whole island to estimate the number of outdoor and indoor bites received by each survey respondent. The association between RDT measured malaria infection status of individuals and outdoor bites received was investigated.ResultsThe average number of bites received per person per night was estimated as 3.51 in total, of which 0.69 (19.7%) would occur outdoors. Malaria infection was not significantly higher in individuals who reported spending time outside between 7 pm and 6 am the previous night compared to those not spending time outside in both adults (18.9% vs 17.4%, p = 0.20) and children (29.2% vs 27.1%, p = 0.20). Malaria infection in neither adults (p = 0.56) nor in children (p = 0.12) was associated with exposure to outdoor bites, even after adjusting for confounders.ConclusionsMalaria vector mosquitoes in Bioko do bite humans outdoors, and this has the potential to reduce the effectiveness of vector control. However, outdoor biting is currently not a major factor influencing the malaria burden, mainly because more than 95% of the population are indoors during the middle of the night, which is the peak biting period for malaria vector mosquitoes. The majority of resources should remain with control measures that target indoor biting and resting such as LLINs and IRS.

The reliability of observational approaches for detecting interspecific parasite interactions: comparison with experimental results

Interactions among coinfecting parasites have the potential to alter host susceptibility to infection, the progression of disease and the efficacy of disease control measures. It is therefore essential to be able to accurately infer the occurrence and direction of such interactions from parasitological data. Due to logistical constraints, perturbation experiments are rarely undertaken to directly detect interactions, therefore a variety of approaches are commonly used to infer them from patterns of parasite association in observational data. However, the reliability of these various approaches is not known. We assess the ability of a range of standard analytical approaches to detect known interactions between infections of nematodes and intestinal coccidia (Eimeria) in natural small-mammal populations, as revealed by experimental perturbations. We show that correlation-based approaches are highly unreliable, often predicting strong and highly significant associations between nematodes and Eimeria in the opposite direction to the underlying interaction. The most reliable methods involved longitudinal analyses, in which the nematode infection status of individuals at one month is related to the infection status by Eimeria the next month. Even then, however, we suggest these approaches are only viable for certain types of infections and datasets. Overall we suggest that, in the absence of experimental approaches, careful consideration be given to the choice of statistical approach when attempting to infer interspecific interactions from observational data.

The first step toward genetic selection for host tolerance to infectious pathogens: obtaining the tolerance phenotype through group estimates.

Reliable phenotypes are paramount for meaningful quantification of genetic variation and for estimating individual breeding values on which genetic selection is based. In this paper, we assert that genetic improvement of host tolerance to disease, although desirable, may be first of all handicapped by the ability to obtain unbiased tolerance estimates at a phenotypic level. In contrast to resistance, which can be inferred by appropriate measures of within host pathogen burden, tolerance is more difficult to quantify as it refers to change in performance with respect to changes in pathogen burden. For this reason, tolerance phenotypes have only been specified at the level of a group of individuals, where such phenotypes can be estimated using regression analysis. However, few stsudies have raised the potential bias in these estimates resulting from confounding effects between resistance and tolerance. Using a simulation approach, we demonstrate (i) how these group tolerance estimates depend on within group variation and co-variation in resistance, tolerance, and vigor (performance in a pathogen free environment); and (ii) how tolerance estimates are affected by changes in pathogen virulence over the time course of infection and by the timing of measurements. We found that in order to obtain reliable group tolerance estimates, it is important to account for individual variation in vigor, if present, and that all individuals are at the same stage of infection when measurements are taken. The latter requirement makes estimation of tolerance based on cross-sectional field data challenging, as individuals become infected at different time points and the individual onset of infection is unknown. Repeated individual measurements of within host pathogen burden and performance would not only be valuable for inferring the infection status of individuals in field conditions, but would also provide tolerance estimates that capture the entire time course of infection.

A Framework for the Joint Modeling of Longitudinal Diagnostic Outcome Data and Latent Infection Status: Application to Investigating the Temporal Relationship between Infection and Disease

For many diseases the infection status of individuals cannot be observed directly, but can only be inferred from biomarkers that are subject to measurement error. Diagnosis of infection based on observed symptoms can itself be regarded as an imperfect test of infection status. The temporal relationship between infection and marker outcomes may be complex, especially for recurrent diseases where individuals can experience multiple bouts of infection. We propose an approach that first models the unobserved longitudinal infection status of individuals conditional on relevant covariates, and then jointly models the longitudinal sequence of biomarker outcomes conditional on infection status and covariate information through time, thus resulting in a joint model for longitudinal infection and biomarker sequences. This model can be used to investigate the temporal dynamics of infection, and to evaluate the usefulness of biomarkers for monitoring purposes. Our work is motivated and illustrated by a longitudinal study of bovine digital dermatitis (BDD) on commercial dairy farms in North West England and North Wales, in which the infection of interest is Treponeme spp., and the biomarkers of interest are a continuous enzyme-linked immunosorbent assay test outcome and a dichotomous outcome, foot lesion status. BDD is known to be one of the possible causes of foot lesions in cows.

The impact of sexually abstaining groups on persistence of sexually transmitted infections in populations with ephemeral pair bonds

Individuals often stop reproducing some time before they die. In this paper we compose and analyze a logistic two-sex population model in which individuals form pairs just to mate (i.e. pair bonds are ephemeral) and later move on to sexually abstaining groups. Using this model, we study the impact of sexually abstaining groups on persistence of a benign sexually transmitted infection (STI) in populations with such ephemeral pair bonds. We observe that the presence of sexually abstaining groups cannot prevent an STI from invasion or eliminate it when already present if the transition rates to the sexually abstaining groups are independent of the infection status of individuals (susceptible or infected). On the other hand, if they depend on that status, the presence of sexually abstaining groups can prevent an STI from invasion or eliminate it when present. Specifically, in the simple case of sex-independent vital parameters, this happens if the transition rate of the infected individuals to the sexually abstaining group is higher than the transition rate of the susceptible ones. These results contrast the earlier results based on assuming long-term, stable pair bonds, in which case one is capable of preventing or eliminating the disease with the same isolation rate for the susceptible and infected individuals.

Immunoepidemiology of Wuchereria bancrofti infection in two East African communities: Antibodies to the microfilarial sheath and their role in regulating host microfilaraemia

The response pattern of specific antibodies to the microfilarial sheath (sheath-Ab) of the mosquito-borne filarial parasite Wuchereria bancrofti was investigated in individuals from two East African communities with different levels of endemicity. Individuals from both communities presented a strong inverse relationship between positivity for sheath-Ab and being positive for microfilariae (mf) and circulating filarial antigens (CFA). The prevalence of sheath-Ab positivity was highest in young individuals, but peaked at a younger age in the high (1–14 years) than the low (15–19 years) endemicity community. IgG1, IgG2, IgG3 and IgE intensities to a crude adult filarial worm antigen were higher, and IgG4 intensities were lower, in sheath-Ab positive than in sheath-Ab negative individuals, probably reflecting the infection status of individuals. From the study it appears that individuals become sheath-Ab positive before mf and/or CFA can be detected in the peripheral blood, and only after later disappearance of sheath-Ab from the circulation can CFA and mf be diagnosed. In light of the findings, possible roles of the distinct sheath-Ab in the host–parasite relationship are discussed, and a hypothesis is proposed which suggests that sheath-Ab play an important role in the regulation of host microfilaraemia.

DISPERSAL IN A PARASITIC WORM AND ITS TWO HOSTS: CONSEQUENCE FOR LOCAL ADAPTATION

Characterizing host and parasite population genetic structure and estimating gene flow among populations is essential for understanding coevolutionary interactions between hosts and parasites. We examined the population genetic structure of the trematode Schistosoma mansoni and its two host species (the definitive host Rattus rattus and the intermediate host Biomphalaria glabrata) using microsatellite markers. Parasites were sampled from rats. The study was conducted in five sites of the Guadeloupe Island, Lesser Antilles. Mollusks display a pattern of isolation by distance whereas such a pattern is not found neither in schistosomes nor in rats. The comparison of the distribution of genetic variability in S. mansoni and its two host species strongly suggests that migration of parasites is principally determined by that of the vertebrate host in the marshy focus of Guadeloupe. However, the comparison between genetic differentiation values in schistosomes and rats suggests that the efficacy of the schistosome rat-mediated dispersal between transmission sites is lower than expected given the prevalence, parasitic load and migration rate of rats among sites. This could notably suggest that rat migration rate could be negatively correlated to the age or the infection status of individuals. Models made about the evolution of local adaptation in function of the dispersal rates of hosts and parasites suggest that rats and mollusks should be locally adapted to their parasites.

DISPERSAL IN A PARASITIC WORM AND ITS TWO HOSTS: CONSEQUENCE FOR LOCAL ADAPTATION

Characterizing host and parasite population genetic structure and estimating gene flow among populations is essential for understanding coevolutionary interactions between hosts and parasites. We examined the population genetic structure of the trematode Schistosoma mansoni and its two host species (the definitive host Rattus rattus and the intermediate host Biomphalaria glabrata) using microsatellite markers. Parasites were sampled from rats. The study was conducted in five sites of the Guadeloupe Island, Lesser Antilles. Mollusks display a pattern of isolation by distance whereas such a pattern is not found neither in schistosomes nor in rats. The comparison of the distribution of genetic variability in S. mansoni and its two host species strongly suggests that migration of parasites is principally determined by that of the vertebrate host in the marshy focus of Guadeloupe. However, the comparison between genetic differentiation values in schistosomes and rats suggests that the efficacy of the schistosome rat-mediated dispersal between transmission sites is lower than expected given the prevalence, parasitic load and migration rate of rats among sites. This could notably suggest that rat migration rate could be negatively correlated to the age or the infection status of individuals. Models made about the evolution of local adaptation in function of the dispersal rates of hosts and parasites suggest that rats and mollusks should be locally adapted to their parasites.

Prevailing triple infection with Wolbachia in Callosobruchus chinensis (Coleoptera: Bruchidae).

Prevailing triple infection with three distinct Wolbachia strains was identified in Japanese populations of the adzuki bean beetle, Callosobruchus chinensis. When a polymerase chain reaction (PCR) assay was conducted using universal primers for ftsZ and wsp, Wolbachia was detected in all the individuals examined, 288 males and 334 females from nine Japanese populations. PCR-restriction fragment length polymorphism (RFLP) analysis of cloned wsp gene fragments from single insects revealed that three types of wsp sequences coexist in the insects. Molecular phylogenetic analysis of the wsp sequences unequivocally demonstrated that C. chinensis harbours three phylogenetically distinct Wolbachia, tentatively designated as wBruCon, wBruOri and wBruAus, respectively. Diagnostic PCR analysis using specific primers demonstrated that, of 175 males and 235 females from nine local populations, infection frequencies with wBruCon, wBruOri and wBruAus were 100%, 96.3% and 97.0%, respectively. As for the infection status of individuals, triple infection (93.7%) dominated over double infection (6.1%) and single infection (0.2%). The amounts of wBruCon, wBruOri and wBruAus in field-collected adult insects were analysed by using a quantitative PCR technique in terms of wsp gene copies per individual insect. Irrespective of original populations, wBruCon and wBruOri (107 -108 wsp copies/insect) were consistently greater in amount than wBruAus (106 -107 wsp copies/insect), suggesting that the population sizes of the three Wolbachia strains are controlled, although the mechanism is unknown. Mating experiments suggested that the three Wolbachia cause cytoplasmic incompatibility at different levels of intensity.