Evaluation using latent class models of the diagnostic performances of three ELISA tests commercialized for the serological diagnosis of Coxiella burnetii infection in domestic ruminants.

ELISA methods are the diagnostic tools recommended for the serological diagnosis of Coxiella burnetii infection in ruminants but their respective diagnostic performances are difficult to assess because of the absence of a gold standard. This study focused on three commercial ELISA tests with the following objectives (1) assess their sensitivity and specificity in sheep, goats and cattle, (2) assess the between- and within-herd seroprevalence distribution in these species, accounting for diagnostic errors, and (3) estimate optimal sample sizes considering sensitivity and specificity at herd level. We comparatively tested 1413 cattle, 1474 goat and 1432 sheep serum samples collected in France. We analyzed the cross-classified test results with a hierarchical zero-inflated beta-binomial latent class model considering each herd as a population and conditional dependence as a fixed effect. Potential biases and coverage probabilities of the model were assessed by simulation. Conditional dependence for truly seropositive animals was high in all species for two of the three ELISA methods. Specificity estimates were high, ranging from 94.8% [92.1; 97.8] to 99.2% [98.5; 99.7], whereas sensitivity estimates were generally low, ranging from 39.3 [30.7; 47.0] to 90.5% [83.3; 93.8]. Between- and within-herd seroprevalence estimates varied greatly among geographic areas and herds. Overall, goats showed higher within-herd seroprevalence levels than sheep and cattle. The optimal sample size maximizing both herd sensitivity and herd specificity varied from 3 to at least 20 animals depending on the test and ruminant species. This study provides better interpretation of three widely used commercial ELISA tests and will make it possible to optimize their implementation in future studies. The methodology developed may likewise be applied to other human or animal diseases.

Bayesian hierarchical models for disease mapping applied to contagious pathologies.

Disease mapping aims to determine the underlying disease risk from scattered epidemiological data and to represent it on a smoothed colored map. This methodology is based on Bayesian inference and is classically dedicated to non-infectious diseases whose incidence is low and whose cases distribution is spatially (and eventually temporally) structured. Over the last decades, disease mapping has received many major improvements to extend its scope of application: integrating the temporal dimension, dealing with missing data, taking into account various a prioris (environmental and population covariates, assumptions concerning the repartition and the evolution of the risk), dealing with overdispersion, etc. We aim to adapt this approach to model rare infectious diseases proposing specific and generic variants of this methodology. In the context of a contagious disease, the outcome of a primary case can in addition generate secondary occurrences of the pathology in a close spatial and temporal neighborhood; this can result in local overdispersion and in higher spatial and temporal dependencies due to direct and/or indirect transmission. In consequence, we test models including a Negative Binomial distribution (instead of the usual Poisson distribution) to deal with local overdispersion. We also use a specific spatio-temporal link in order to better model the stronger spatial and temporal dependencies due to the transmission of the disease. We have proposed and tested 60 Bayesian hierarchical models on 400 simulated datasets and bovine tuberculosis real data. This analysis shows the relevance of the CAR (Conditional AutoRegressive) processes to deal with the structure of the risk. We can also conclude that the negative binomial models outperform the Poisson models with a Gaussian noise to handle overdispersion. In addition our study provided relevant maps which are congruent with the real risk (simulated data) and with the knowledge concerning bovine tuberculosis (real data).

Sex-Specific Linkages Between Taxonomic and Functional Profiles of Tick Gut Microbiomes.

Ticks transmit the most diverse array of disease agents and harbor one of the most diverse microbial communities. Major progress has been made in the characterization of the taxonomic profiles of tick microbiota. However, the functional profiles of tick microbiome have been comparatively less studied. In this proof of concept we used state-of-the-art functional metagenomics analytical tools to explore previously reported datasets of bacteria found in male and female Ixodes ovatus, Ixodes persulcatus, and Amblyomma variegatum. Results showed that both taxonomic and functional profiles have differences between sexes of the same species. KEGG pathway analysis revealed that male and female of the same species had major differences in the abundance of genes involved in different metabolic pathways including vitamin B, amino acids, carbohydrates, nucleotides, and antibiotics among others. Partial reconstruction of metabolic pathways using KEGG enzymes suggests that tick microbiome form a complex metabolic network that may increase microbial community resilience and adaptability. Linkage analysis between taxonomic and functional profiles showed that among the KEGG enzymes with differential abundance in male and female ticks only 12% were present in single bacterial genera. The rest of these enzymes were found in more than two bacterial genera, and 27% of them were found in five up to ten bacterial genera. Comparison of bacterial genera contributing to the differences in the taxonomic and functional profiles of males and females revealed that while a small group of bacteria has a dual-role, most of the bacteria contribute only to functional or taxonomic differentiation between sexes. Results suggest that the different life styles of male and female ticks exert sex-specific evolutionary pressures that act independently on the phenomes (set of phenotypes) and genomes of bacteria in tick gut microbiota. We conclude that functional redundancy is a fundamental property of male and female tick microbiota and propose that functional metagenomics should be combined with taxonomic profiling of microbiota because both analyses are complementary.

Molecular epidemiology of Coxiella burnetii in French livestock reveals the existence of three main genotype clusters and suggests species-specific associations as well as regional stability.

Q fever is a worldwide zoonosis caused by the bacterium Coxiella burnetii. In domestic ruminants, Q fever main clinical manifestations are abortions. Although the clinical signs may differ between ruminant species, C. burnetii's genetic diversity remains understudied in enzootic areas. Here, we focused on France, where Q fever is enzootic, with the aims to (a) identify potential associations between C. burnetii genotypes and ruminant host species; (b) assess the distribution of C. burnetii genotypes both within French farms and across France's major livestock-farming regions; and (c) suggest a subset of markers for future genotypic studies. We used DNA samples collected between 2006 and 2015 from 301 females (160 cows, 76 ewes, 65 goats) aborted of Q fever within 7 different farming regions. C. burnetii diversity was determined using a multiple-locus variable-number of tandem repeat analysis (MLVA) considering 17 markers. Using a phylogenetic approach, we identified 3 main genotypic clusters divided into 12 sub-clusters. These clusters were significantly associated with ruminant species: almost all the cattle genotypes were found in a "cattle-specific" cluster whereas small ruminants genotypes essentially grouped into the two other clusters. The clusters also proved stable over space and time, some genotypes being more specifically observed in certain farming regions. We also observed some within-farm diversity but this diversity was restricted to a same genotypic cluster. Finally, we identified 6 MLVA markers that maximized the representativeness of the diversity described. Overall, we highlighted that molecular epidemiology is a relevant approach to assess C. burnetii's genetic diversity and to reveal the existence of species-specific associations and regional stability. These results will be valuable in the field to trace genotype circulation among ruminants and from ruminants to humans. Ultimately, the potential links between genotypes and virulence traits need to be investigated to adapt control measures in livestock farms.

Multiple independent transmission cycles of a tick-borne pathogen within a local host community.

Many pathogens are maintained by multiple host species and involve multiple strains with potentially different phenotypic characteristics. Disentangling transmission patterns in such systems is often challenging, yet investigating how different host species contribute to transmission is crucial to properly assess and manage disease risk. We aim to reveal transmission cycles of bacteria within the Borrelia burgdorferi species complex, which include Lyme disease agents. We characterized Borrelia genotypes found in 488 infected Ixodes ricinus nymphs collected in the Sénart Forest located near Paris (France). These genotypes were compared to those observed in three sympatric species of small mammals and network analyses reveal four independent transmission cycles. Statistical modelling shows that two cycles involving chipmunks, an introduced species, and non-sampled host species such as birds, are responsible for the majority of tick infections. In contrast, the cycle involving native bank voles only accounts for a small proportion of infected ticks. Genotypes associated with the two primary transmission cycles were isolated from Lyme disease patients, confirming the epidemiological threat posed by these strains. Our work demonstrates that combining high-throughput sequence typing with networks tools and statistical modeling is a promising approach for characterizing transmission cycles of multi-host pathogens in complex ecological settings.

How to survey classical swine fever in wild boar (Sus scrofa) after the completion of oral vaccination? Chasing away the ghost of infection at different spatial scales.

Oral mass vaccination (OMV) is considered as an efficient strategy for controlling classical swine fever (CSF) in wild boar. After the completion of vaccination, the presence of antibodies in 6-12 month-old hunted wild boars was expected to reflect a recent CSF circulation. Nevertheless, antibodies could also correspond to the long-lasting of maternal antibodies. This paper relates an experience of surveillance which lasted 4 years after the completion of OMV in a formerly vaccinated area, in north-eastern France (2010-2014). First, we conducted a retrospective analysis of the serological data collected in 6-12 month-old hunted wild boars from 2010 up to 2013, using a spatial Bayesian model accounting for hunting data autocorrelation and heterogeneity. At the level of the whole area, seroprevalence in juvenile boars decreased from 28% in 2010-2011 down to 1% in 2012-2013, but remained locally high (above 5%). The model revealed the existence of one particular seroprevalence hot-spot where a longitudinal survey of marked animals was conducted in 2013-2014, for deciphering the origin of antibodies. Eleven out of 107 captured piglets were seropositive when 3-4 months-old, but their antibody titres progressively decreased until 6-7 months of age. These results suggest piglets were carrying maternal antibodies, few of them carrying maternal antibodies lasting until the hunting season. Our study shows that OMV may generate confusion in the CSF surveillance several years after the completion of vaccination. We recommend using quantitative serological tools, hunting data modelling and capture approaches for better interpreting serological results after vaccination completion. Surveillance perspectives are further discussed.

Diagnosis and incidence risk of clinical canine monocytic ehrlichiosis under field conditions in Southern Europe.

BACKGROUND: Canine Monocytic Ehrlichiosis (CME), due to the bacterium Ehrlichia canis and transmitted by the brown dog tick Rhipicephalus sanguineus, is a major tick-borne disease in southern Europe. In this area, infections with other vector-borne pathogens (VBP) are also described and result in similar clinical expression. The aim of the present study was to evaluate the incidence risk of clinical CME in those endemic areas and to assess the potential involvement of other VBP in the occurrence of clinical and/or biological signs evocative of the disease. METHODS: The study was conducted from April to November 2011 in veterinary clinics across Italy, Spain and Portugal. Sick animals were included when fitting at least three clinical and/or biological criteria compatible with ehrlichiosis. Serological tests (SNAP®4Dx, SNAP®Leish tests, Idexx, USA) and diagnostic PCR for E. canis, Anaplasma platys, Anaplasma phagocytophilum, Babesia spp, Hepatozoon canis and Leishmania infantum detection were performed to identify the etiological agents. Ehrlichiosis was considered when three clinical and/or biological suggestive signs were associated with at least one positive paraclinical test (serology or PCR). The annual incidence risk was calculated and data were geo-referenced for map construction. The probabilities of CME and other vector-borne diseases when facing clinical and/or biological signs suggestive of CME were then evaluated. RESULTS: A total of 366 dogs from 78 veterinary clinics were enrolled in the survey. Among them, 99 (27%) were confirmed CME cases, which allowed an estimation of the average annual incidence risk of CME amongst the investigated dog population to be 0.08%. Maps showed an increasing gradient of CME incidence risk from northern towards southern areas, in particular in Italy. It also suggested the existence of hot-spots of infections by VBP in Portugal. In addition, the detection of other VBP in the samples was common and the study demonstrated that a dog with clinical signs evocative of CME is as likely to be positive to Ehrlichia canis as to another VBP. CONCLUSIONS: The study confirms the endemicity of CME in southern Europe and highlights the difficulties encountered by veterinarians to differentiate CME from other vector-borne diseases under field conditions.

Comparative population genomics of the Borrelia burgdorferi species complex reveals high degree of genetic isolation among species and underscores benefits and constraints to studying intra-specific epidemiological processes.

Lyme borreliosis, one of the most frequently contracted zoonotic diseases in the Northern Hemisphere, is caused by bacteria belonging to different genetic groups within the Borrelia burgdorferi species complex, which are transmitted by ticks among various wildlife reservoirs, such as small mammals and birds. These features make the Borrelia burgdorferi species complex an attractive biological model that can be used to study the diversification and the epidemiology of endemic bacterial pathogens. We investigated the potential of population genomic approaches to study these processes. Sixty-three strains belonging to three species within the Borrelia burgdorferi complex were isolated from questing ticks in Alsace (France), a region where Lyme disease is highly endemic. We first aimed to characterize the degree of genetic isolation among the species sampled. Phylogenetic and coalescent-based analyses revealed clear delineations: there was a ∼50 fold difference between intra-specific and inter-specific recombination rates. We then investigated whether the population genomic data contained information of epidemiological relevance. In phylogenies inferred using most of the genome, conspecific strains did not cluster in clades. These results raise questions about the relevance of different strategies when investigating pathogen epidemiology. For instance, here, both classical analytic approaches and phylodynamic simulations suggested that population sizes and migration rates were higher in B. garinii populations, which are normally associated with birds, than in B. burgdorferi s.s. populations. The phylogenetic analyses of the infection-related ospC gene and its flanking region provided additional support for this finding. Traces of recombination among the B. burgdorferi s.s. lineages and lineages associated with small mammals were found, suggesting that they shared the same hosts. Altogether, these results provide baseline evidence that can be used to formulate hypotheses regarding the host range of B. burgdorferi lineages based on population genomic data.

Questionnaire-based survey on the distribution and incidence of canine babesiosis in countries of Western Europe.

The incidence of canine babesiosis may vary considerably from one country to another depending on the distribution of the causative parasite species and their specific vectors. The aim of the present study was to evaluate the clinical occurrence of canine babesiosis diagnosed in European veterinary clinics and propose an updated map of the disease distribution in Western Europe. Questionnaires were sent to companion animal veterinary clinics in Spain, France, Benelux, Germany and Austria. The annual number of babesiosis cases in 2010, the number of practitioners in the clinic and the location of the clinic were recorded. The total numbers of dogs and practitioners in each country were used for definition of the reference populations and the annual incidence of canine babesiosis was calculated by dividing the total number of reported babesiosis cases by the total number of dogs in the veterinary practices involved in the study. Data were georeferenced for distribution map construction. The overall annual incidence of clinical babesiosis amongst the investigated dog population was 0.7%, with significant variations amongst countries and regions. Three epidemiological situations were described: (i) Spain, with co-existence of several species of piroplasms and patchy distribution of babesiosis, (ii) France, with overall presence of babesiosis due to Babesia canis and local variations and (iii) Benelux, Germany and Austria, with overall low prevalence of the disease associated with localised description related either to imported cases or to small autochthonous foci of B. canis infection.

High-throughput sequence typing reveals genetic differentiation and host specialization among populations of the Borrelia burgdorferi species complex that infect rodents.

Lyme disease is a zoonosis caused by various species belonging to the Borrelia burgdorferi bacterial species complex. These pathogens are transmitted by ticks and infect multiple, taxonomically distinct, host species. From an epidemiological perspective, it is important to determine whether genetic variants within the species complex are able to spread freely through the whole host community or, instead, if certain variants are restricted to particular hosts. To this end, we characterized the genotypes of members of the B. burgdorferi species complex; the bacteria were isolated from more than two hundred individuals captured in the wild and belonging to three different rodent host species. For each individual, we used a high-throughput approach to amplify and sequence rplB, a housekeeping gene, and ospC, which is involved in infection. This approach allowed us to evaluate the genetic diversity both within and among species in the B. burgdorferi species complex. Strong evidence of genetic differentiation among host species was revealed by both genes, even though they are, a priori, not constrained by the same selective pressures. These data are discussed in the context of the advancements made possible by multi-locus high-throughput sequencing and current knowledge of Lyme disease epidemiology.

Questionnaire-based survey on distribution and clinical incidence of canine babesiosis in France.

BACKGROUND: The causative agent of canine babesiosis is the protozoan Babesia canis, transmitted by the tick Dermacentor reticulatus within France. While the parasite can be found everywhere in France however cases of infection are associated with distinct geographical foci. The aim of the study was to evaluate the clinical occurrence of canine babesiosis diagnosed in veterinary clinics in order to propose an updated map of the disease distribution in France. RESULTS: Questionnaires were sent via email to all canine veterinary clinics in continental France. Information collected included the number of babesiosis cases diagnosed in 2010, the number of veterinary practitioners and the location of the clinic. The total number of dogs and practitioners per administrative department were used to define the reference population. The annual incidence rate of canine babesiosis per department was calculated as the ratio between the number of babesiosis cases reported by the clinics and the total number of dogs in the clinics of the same department. Data were geo-referenced for map construction (Quantum GIS version 1.7.4). The overall annual incidence rate of clinical babesiosis among the surveyed population was 1.07% (CI95 1.05-1.09) with geographical variations between departments, ranging from 0.01% to 16.05%. Four enzootic areas were identified: South-West, Center, East and Paris area. The South-West region should be considered as a hyper-enzootic area with the higher incidence rates. CONCLUSION: Our results confirmed the burden of canine babesiosis in France. In the context of tick-borne disease emergence in Europe, the risk for canine babesiosis may become more significant in other European countries in the coming years.

Risk map and spatial determinants of pancreas disease in the marine phase of Norwegian Atlantic salmon farming sites.

BACKGROUND: Outbreaks of pancreas disease (PD) greatly contribute to economic losses due to high mortality, control measures, interrupted production cycles, reduced feed conversion and flesh quality in the aquaculture industries in European salmon-producing countries. The overall objective of this study was to evaluate an effect of potential factors contributing to PD occurrence accounting for spatial congruity of neighboring infected sites, and then create quantitative risk maps for predicting PD occurrence. The study population included active Atlantic salmon farming sites located in the coastal area of 6 southern counties of Norway (where most of PD outbreaks have been reported so far) from 1 January 2009 to 31 December 2010. RESULTS: Using a Bayesian modeling approach, with and without spatial component, the final model included site latitude, site density, PD history, and local biomass density. Clearly, the PD infected sites were spatially clustered; however, the cluster was well explained by the covariates of the final model. Based on the final model, we produced a map presenting the predicted probability of the PD occurrence in the southern part of Norway. Subsequently, the predictive capacity of the final model was validated by comparing the predicted probabilities with the observed PD outbreaks in 2011. CONCLUSIONS: The framework of the study could be applied for spatial studies of other infectious aquatic animal diseases.

Why did bluetongue spread the way it did? Environmental factors influencing the velocity of bluetongue virus serotype 8 epizootic wave in France.

Understanding where and how fast an infectious disease will spread during an epidemic is critical for its control. However, the task is a challenging one as numerous factors may interact and drive the spread of a disease, specifically when vector-borne diseases are involved. We advocate the use of simultaneous autoregressive models to identify environmental features that significantly impact the velocity of disease spread. We illustrate this approach by exploring several environmental factors influencing the velocity of bluetongue (BT) spread in France during the 2007-2008 epizootic wave to determine which ones were the most important drivers. We used velocities of BT spread estimated in 4,495 municipalities and tested sixteen covariates defining five thematic groups of related variables: elevation, meteorological-related variables, landscape-related variables, host availability, and vaccination. We found that ecological factors associated with vector abundance and activity (elevation and meteorological-related variables), as well as with host availability, were important drivers of the spread of the disease. Specifically, the disease spread more slowly in areas with high elevation and when heavy rainfall associated with extreme temperature events occurred one or two months prior to the first clinical case. Moreover, the density of dairy cattle was correlated negatively with the velocity of BT spread. These findings add substantially to our understanding of BT spread in a temperate climate. Finally, the approach presented in this paper can be used with other infectious diseases, and provides a powerful tool to identify environmental features driving the velocity of disease spread.

Environmental factors associated with the seroprevalence of Toxoplasma gondii in Wild Boars (Sus scrofa), France.

Toxoplasma gondii is a protozoan parasite infecting humans and animals. Wild boars Sus scrofa are a potential source of human infection and an appropriate biological model for analyzing T. gondii dynamics in the environment. Here, we aimed to identify environmental factors explaining the seroprevalence of toxoplasmosis in French wild boar populations. Considering 938 individuals sampled from 377 'communes', overall seroprevalence was 23% (95% confidence interval: [22-24]). Using a Poisson regression, we found that the number of seropositive wild boars detected per 'commune' was positively associated with the presence of European wildcats (Felis silvestris) and moderate winter temperatures.

Individual factors associated with L- and H-type Bovine Spongiform encephalopathy in France.

BACKGROUND: Cattle with L-type (L-BSE) and H-type (H-BSE) atypical Bovine Spongiform encephalopathy (BSE) were identified in 2003 in Italy and France respectively before being identified in other countries worldwide. As of December 2011, around 60 atypical BSE cases have currently been reported in 13 countries, with over one third in France. While the epidemiology of classical BSE (C-BSE) has been widely described, atypical BSEs are still poorly documented, but appear to differ from C-BSE. We analysed the epidemiological characteristics of the 12 cases of L-BSE and 11 cases of H-BSE detected in France from January 2001 to late 2009 and looked for individual risk factors. As L-BSE cases did not appear to be homogeneously distributed throughout the country, two complementary methods were used: spatial analysis and regression modelling. L-BSE and H-BSE were studied separately as both the biochemical properties of their pathological prion protein and their features differ in animal models. RESULTS: The median age at detection for L-BSE and H-BSE cases was 12.4 (range 8.4-18.7) and 12.5 (8.3-18.2) years respectively, with no significant difference between the two distributions. However, this median age differed significantly from that of classical BSE (7.0 (range 3.5-15.4) years). A significant geographical cluster was detected for L-BSE. Among animals over eight years of age, we showed that the risk of being detected as a L-BSE case increased with age at death. This was not the case for H-BSE. CONCLUSION: To the best of our knowledge this is the first study to describe the epidemiology of the two types of atypical BSE. The geographical cluster detected for L-BSE could be partly due to the age structure of the background-tested bovine population. Our regression analyses, which adjusted for the effect of age and birth cohort showed an age effect for L-BSE and the descriptive analysis showed a particular age structure in the area where the cluster was detected. No birth cohort effect was evident. The relatively small number of cases of atypical BSE and the few individual data available for the tested population limited our analysis to the investigation of age and cohort effect only. We conclude that it is essential to maintain BSE surveillance to further elucidate our findings.

Classification method for disease risk mapping based on discrete hidden Markov random fields.

Risk mapping in epidemiology enables areas with a low or high risk of disease contamination to be localized and provides a measure of risk differences between these regions. Risk mapping models for pooled data currently used by epidemiologists focus on the estimated risk for each geographical unit. They are based on a Poisson log-linear mixed model with a latent intrinsic continuous hidden Markov random field (HMRF) generally corresponding to a Gaussian autoregressive spatial smoothing. Risk classification, which is necessary to draw clearly delimited risk zones (in which protection measures may be applied), generally must be performed separately. We propose a method for direct classified risk mapping based on a Poisson log-linear mixed model with a latent discrete HMRF. The discrete hidden field (HF) corresponds to the assignment of each spatial unit to a risk class. The risk values attached to the classes are parameters and are estimated. When mapping risk using HMRFs, the conditional distribution of the observed field is modeled with a Poisson rather than a Gaussian distribution as in image segmentation. Moreover, abrupt changes in risk levels are rare in disease maps. The spatial hidden model should favor smoothed out risks, but conventional discrete Markov random fields (e.g. the Potts model) do not impose this. We therefore propose new potential functions for the HF that take into account class ordering. We use a Monte Carlo version of the expectation-maximization algorithm to estimate parameters and determine risk classes. We illustrate the method's behavior on simulated and real data sets. Our method appears particularly well adapted to localize high-risk regions and estimate the corresponding risk levels.

Estimating front-wave velocity of infectious diseases: a simple, efficient method applied to bluetongue.

Understanding the spatial dynamics of an infectious disease is critical when attempting to predict where and how fast the disease will spread. We illustrate an approach using a trend-surface analysis (TSA) model combined with a spatial error simultaneous autoregressive model (SAR(err) model) to estimate the speed of diffusion of bluetongue (BT), an infectious disease of ruminants caused by bluetongue virus (BTV) and transmitted by Culicoides. In a first step to gain further insight into the spatial transmission characteristics of BTV serotype 8, we used 2007-2008 clinical case reports in France and TSA modelling to identify the major directions and speed of disease diffusion. We accounted for spatial autocorrelation by combining TSA with a SAR(err) model, which led to a trend SAR(err) model. Overall, BT spread from north-eastern to south-western France. The average trend SAR(err)-estimated velocity across the country was 5.6 km/day. However, velocities differed between areas and time periods, varying between 2.1 and 9.3 km/day. For more than 83% of the contaminated municipalities, the trend SAR(err)-estimated velocity was less than 7 km/day. Our study was a first step in describing the diffusion process for BT in France. To our knowledge, it is the first to show that BT spread in France was primarily local and consistent with the active flight of Culicoides and local movements of farm animals. Models such as the trend SAR(err) models are powerful tools to provide information on direction and speed of disease diffusion when the only data available are date and location of cases.

Ecological factors characterizing the prevalence of bacterial tick-borne pathogens in Ixodes ricinus ticks in pastures and woodlands.

Ecological changes are recognized as an important driver behind the emergence of infectious diseases. The prevalence of infection in ticks depends upon ecological factors that are rarely taken into account simultaneously. Our objective was to investigate the influences of forest fragmentation, vegetation, adult tick hosts, and habitat on the infection prevalence of three tick-borne bacteria, Borrelia burgdorferi sensu lato, Anaplasma phagocytophilum, and Rickettsia sp. of the spotted fever group, in questing Ixodes ricinus ticks, taking into account tick characteristics. Samples of questing nymphs and adults were taken from 61 pastures and neighboring woodlands in central France. The ticks were tested by PCR of pools of nymphs and individual adults. The individual infection prevalence was modeled using multivariate regression. The highest infection prevalences were found in adult females collected in woodland sites for B. burgdorferi sensu lato and A. phagocytophilum (16.1% and 10.7%, respectively) and in pasture sites for Rickettsia sp. (8.7%). The infection prevalence in nymphs was lower than 6%. B. burgdorferi sensu lato was more prevalent in woodlands than in pastures. Forest fragmentation favored B. burgdorferi sensu lato and A. phagocytophilum prevalence in woodlands, and in pastures, the B. burgdorferi sensu lato prevalence was favored by shrubby vegetation. Both results are probably because large amounts of edges or shrubs increase the abundance of small vertebrates as reservoir hosts. The Rickettsia sp. prevalence was maximal on pasture with medium forest fragmentation. Female ticks were more infected by B. burgdorferi sensu lato than males and nymphs in woodland sites, which suggests an interaction between the ticks and the bacteria. This study confirms the complexity of the tick-borne pathogen ecology. The findings support the importance of small vertebrates as reservoir hosts and make a case for further studies in Europe on the link between the composition of the reservoir host community and the infection prevalence in ticks.

Anthropogenic factors and the risk of highly pathogenic avian influenza H5N1: prospects from a spatial-based model.

Beginning in 2003, highly pathogenic avian influenza (HPAI) H5N1 virus spread across Southeast Asia, causing unprecedented epidemics. Thailand was massively infected in 2004 and 2005 and continues today to experience sporadic outbreaks. While research findings suggest that the spread of HPAI H5N1 is influenced primarily by trade patterns, identifying the anthropogenic risk factors involved remains a challenge. In this study, we investigated which anthropogenic factors played a role in the risk of HPAI in Thailand using outbreak data from the "second wave" of the epidemic (3 July 2004 to 5 May 2005) in the country. We first performed a spatial analysis of the relative risk of HPAI H5N1 at the subdistrict level based on a hierarchical Bayesian model. We observed a strong spatial heterogeneity of the relative risk. We then tested a set of potential risk factors in a multivariable linear model. The results confirmed the role of free-grazing ducks and rice-cropping intensity but showed a weak association with fighting cock density. The results also revealed a set of anthropogenic factors significantly linked with the risk of HPAI. High risk was associated strongly with densely populated areas, short distances to a highway junction, and short distances to large cities. These findings highlight a new explanatory pattern for the risk of HPAI and indicate that, in addition to agro-environmental factors, anthropogenic factors play an important role in the spread of H5N1. To limit the spread of future outbreaks, efforts to control the movement of poultry products must be sustained.

Bovine spongiform encephalopathy and spatial analysis of the feed industry.

In France, despite the ban of meat-and-bone meal (MBM) in cattle feed, bovine spongiform encephalopathy (BSE) was detected in hundreds of cattle born after the ban. To study the role of MBM, animal fat, and dicalcium phosphate on the risk for BSE after the feed ban, we conducted a spatial analysis of the feed industry. We used data from 629 BSE cases as well as data on use of each byproduct and market area of the feed factories. We mapped risk for BSE in 951 areas supplied by the same factories and connection with use of byproducts. A disease map of BSE with covariates was built with the hierarchical Bayesian modeling methods, based on Poisson distribution with spatial smoothing. Only use of MBM was spatially linked to risk for BSE, which highlights cross-contamination as the most probable source of infection after the feed ban.