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.

Habitat suitability map of Ixodes ricinus tick in France using multi-criteria analysis.

The tick Ixodes ricinus is widely distributed across Europe and is responsible for the transmission of several pathogens to humans and animals. In this study, we used a knowledge-based method to map variations in habitat suitability for I. ricinus ticks throughout continental France and Corsica. The multi-criteria decision analysis (MCDA) integrated four major biotic and abiotic factors known to influence tick populations: climate, land cover, altitude and the density of wild ungulates. For each factor, habitat suitability index (HSI) values were attributed to different locations based on knowledge regarding its impact on tick populations. For the MCDA, two methods of factor combination were tested, additive and multiplicative, both which were evaluated at the spatial scales of departments and local municipalities. The resulting habitat suitability maps (resolution=100x100 m) revealed that conditions are suitable for I. ricinus over most of France and Corsica. Particularly suitable habitats were located in central, north-eastern and south-western France, while less-suitable habitats were found in the Mediterranean and mountainous regions. To validate the approach, the HSI scores were compared to field data of I. ricinus nymph abundance. Regardless of scale, the correlation between abundance indicator and HSI score was stronger for the additive than for the multiplicative approach. Overall, this study demonstrates the value of MCDA for estimating habitat suitability maps for I. ricinus abundance, which could be especially useful in highlighting areas of the tick's distribution where preventive measures should be prioritised.

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.

Quantitative estimation of genetic risk for atypical scrapie in French sheep and potential consequences of the current breeding programme for resistance to scrapie on the risk of atypical scrapie.

BACKGROUND: Since 2002, active surveillance programmes have detected numerous atypical scrapie (AS) and classical scrapie cases (CS) in French sheep with almost all the PrP genotypes. The aim of this study was 1) to quantify the genetic risk of AS in French sheep and to compare it with the risk of CS, 2) to quantify the risk of AS associated with the increase of the ARR allele frequency as a result of the current genetic breeding programme against CS. METHODS: We obtained genotypes at codons 136, 141, 154 and 171 of the PRNP gene for representative samples of 248 AS and 245 CS cases. We used a random sample of 3,317 scrapie negative animals genotyped at codons 136, 154 and 171 and we made inferences on the position 141 by multiple imputations, using external data. To estimate the risk associated with PrP genotypes, we fitted multivariate logistic regression models and we estimated the prevalence of AS for the different genotypes. Then, we used the risk of AS estimated for the ALRR-ALRR genotype to analyse the risk of detecting an AS case in a flock homogenous for this genotype. RESULTS: Genotypes most at risk for AS were those including an AFRQ or ALHQ allele while genotypes including a VLRQ allele were less commonly associated with AS. Compared to ALRQ-ALRQ, the ALRR-ALRR genotype was significantly at risk for AS and was very significantly protective for CS. The prevalence of AS among ALRR-ALRR animals was 0.6 per thousand and was not different from the prevalence in the general population. CONCLUSION: In conclusion, further selection of ALRR-ALRR animals will not result in an overall increase of AS prevalence in the French sheep population although this genotype is clearly susceptible to AS. However the probability of detecting AS cases in flocks participating in genetic breeding programme against CS should be considered.

Rarity of microbial species: In search of reliable associations.

The role of microbial interactions in defining the properties of microbiota is a topic of key interest in microbial ecology. Microbiota contain hundreds to thousands of operational taxonomic units (OTUs), most of them rare. This feature of community structure can lead to methodological difficulties: simulations have shown that methods for detecting pairwise associations between OTUs, which presumably reflect interactions, yield problematic results. The performance of association detection tools is impaired when there is a high proportion of zeros in OTU tables. Our goal was to understand the impact of OTU rarity on the detection of associations. We explored the utility of common statistics for testing associations; the sensitivity of alternative association measures; and the performance of network inference tools. We found that a large proportion of pairwise associations, especially negative associations, cannot be reliably tested. This constraint could hamper the identification of candidate biological agents that could be used to control rare pathogens. Identifying testable associations could serve as an objective method for filtering datasets in lieu of current empirical approaches. This trimming strategy could significantly reduce the computational time needed to infer networks and network inference quality. Different possibilities for improving the analysis of associations within microbiota are discussed.

Swab cloths as a tool for revealing environmental contamination by Q fever in ruminant farms.

Q fever is a zoonotic abortive disease of ruminants mostly transmitted by inhalation of aerosols contaminated by Coxiella burnetii. Clusters of cases or even epidemics regularly occur in humans but, to date, there is no consensus about the best way to carry out outbreak investigations in order to identify potential farms at risk. Although environmental samples might be useful during such investigations, there are few baseline data on the presence of C. burnetii in the environment of ruminant farms. We thus investigated dust samples from cattle, sheep and goat farm buildings in order to (a) estimate C. burnetii detection frequency and bacterial loads in the environment, and (b) determine whether this environmental contamination is associated with series of abortions attributed to Q fever. We considered 113 herds with a recent abortive episode potentially related (n = 60) or not (n = 53) to C. burnetii. Dust was sampled using a swab cloth and tested by a quantitative PCR method targeting the IS1111 gene. Coxiella burnetii DNA was detected on 9 of 50 cattle farms, 13 of 19 goat farms and 30 of 40 sheep farms. On 16 cloths, bacterial loads were higher than 108 genome equivalents, levels as high as in infectious materials such as placentas and aborted foetuses. Overall, the probability of detecting C. burnetii DNA was higher on small ruminant farms than cattle farms, in herds suspected of Q fever and in large herds. We conclude that swab cloths are a putative indicator of contamination of ruminant farms by C. burnetii.

Seroprevalence of horses to Coxiella burnetii in an Q fever endemic area.

Coxiella burnetii can infect many animal species, but its circulation dynamics in and through horses is still unclear. This study evaluated horse exposure in an area known to be endemic for ruminants and humans. We assessed antibody prevalence in horse serum by ELISA, and screened by qPCR horse blood, ticks found on horses and dust from stables. Horse seroprevalence was 4% (n = 335, 37 stables) in 2015 and 12% (n = 294, 39 stables) in 2016. Of 199 horses sampled both years, 13 seroconverted, eight remained seropositive, and one seroreverted. Seropositive horses were located close to reported human cases, yet none displayed Q fever-compatible syndromes. Coxiella DNA was detected in almost 40% of collected ticks (n = 59/148 in 2015; n = 103/305 in 2016), occasionally in dust (n = 3/46 in 2015; n = 1/14 in 2016) but never in horse blood. Further studies should be implemented to evaluate if horses may be relevant indicators of zoonotic risk in urban and suburban endemic areas.

A new standard model for milk yield in dairy cows based on udder physiology at the milking-session level.

Milk production in dairy cow udders is a complex and dynamic physiological process that has resisted explanatory modelling thus far. The current standard model, Wood's model, is empirical in nature, represents yield in daily terms, and was published in 1967. Here, we have developed a dynamic and integrated explanatory model that describes milk yield at the scale of the milking session. Our approach allowed us to formally represent and mathematically relate biological features of known relevance while accounting for stochasticity and conditional elements in the form of explicit hypotheses, which could then be tested and validated using real-life data. Using an explanatory mathematical and biological model to explore a physiological process and pinpoint potential problems (i.e., "problem finding"), it is possible to filter out unimportant variables that can be ignored, retaining only those essential to generating the most realistic model possible. Such modelling efforts are multidisciplinary by necessity. It is also helpful downstream because model results can be compared with observed data, via parameter estimation using maximum likelihood and statistical testing using model residuals. The process in its entirety yields a coherent, robust, and thus repeatable, model.

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.

Population genetics, community of parasites, and resistance to rodenticides in an urban brown rat (Rattus norvegicus) population.

Brown rats are one of the most widespread urban species worldwide. Despite the nuisances they induce and their potential role as a zoonotic reservoir, knowledge on urban rat populations remains scarce. The main purpose of this study was to characterize an urban brown rat population from Chanteraines park (Hauts-de-Seine, France), with regards to haematology, population genetics, immunogenic diversity, resistance to anticoagulant rodenticides, and community of parasites. Haematological parameters were measured. Population genetics was investigated using 13 unlinked microsatellite loci. Immunogenic diversity was assessed for Mhc-Drb. Frequency of the Y139F mutation (conferring resistance to rodenticides) and two linked microsatellites were studied, concurrently with the presence of anticoagulant residues in the liver. Combination of microscopy and molecular methods were used to investigate the occurrence of 25 parasites. Statistical approaches were used to explore multiple parasite relationships and model parasite occurrence. Eighty-six rats were caught. The first haematological data for a wild urban R. norvegicus population was reported. Genetic results suggested high genetic diversity and connectivity between Chanteraines rats and surrounding population(s). We found a high prevalence (55.8%) of the mutation Y139F and presence of rodenticide residues in 47.7% of the sampled individuals. The parasite species richness was high (16). Seven potential zoonotic pathogens were identified, together with a surprisingly high diversity of Leptospira species (4). Chanteraines rat population is not closed, allowing gene flow and making eradication programs challenging, particularly because rodenticide resistance is highly prevalent. Parasitological results showed that co-infection is more a rule than an exception. Furthermore, the presence of several potential zoonotic pathogens, of which four Leptospira species, in this urban rat population raised its role in the maintenance and spread of these pathogens. Our findings should stimulate future discussions about the development of a long-term rat-control management program in Chanteraines urban park.

Prevalence of Anaplasma phagocytophilum, Rickettsia sp. and Borrelia burgdorferi sensu lato DNA in questing Ixodes ricinus ticks from France.

A total of 4701 Ixodes ricinus, collected during the summer of 2003, were analyzed for three pathogens. DNA was detected from the three pathogens. Co-detection of more than one pathogen was observed.

Hedgehogs and Mustelid Species: Major Carriers of Pathogenic Leptospira, a Survey in 28 Animal Species in France (20122015).

Human leptospirosis is a zoonotic and potentially fatal disease that has increasingly been reported in both developing and developed countries, including France. However, our understanding of the basic aspects of the epidemiology of this disease, including the source of Leptospira serogroup Australis infections in humans and domestic animals, remains incomplete. We investigated the genetic diversity of Leptospira in 28 species of wildlife other than rats using variable number tandem repeat (VNTR) and multispacer sequence typing (MST). The DNA of pathogenic Leptospira was detected in the kidney tissues of 201 individuals out of 3,738 tested individuals. A wide diversity, including 50 VNTR profiles and 8 MST profiles, was observed. Hedgehogs and mustelid species had the highest risk of being infected (logistic regression, OR = 66.8, CI95% = 30.9-144 and OR = 16.7, CI95% = 8.7-31.8, respectively). Almost all genetic profiles obtained from the hedgehogs were related to Leptospira interrogans Australis, suggesting the latter as a host-adapted bacterium, whereas mustelid species were infected by various genotypes, suggesting their interaction with Leptospira was different. By providing an inventory of the circulating strains of Leptospira and by pointing to hedgehogs as a potential reservoir of L. interrogans Australis, our study advances current knowledge on Leptospira animal carriers, and this information could serve to enhance epidemiological investigations in the future.

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.

Co-infection of Ticks: The Rule Rather Than the Exception.

INTRODUCTION: Ticks are the most common arthropod vectors of both human and animal diseases in Europe, and the Ixodes ricinus tick species is able to transmit a large number of bacteria, viruses and parasites. Ticks may also be co-infected with several pathogens, with a subsequent high likelihood of co-transmission to humans or animals. However few data exist regarding co-infection prevalences, and these studies only focus on certain well-known pathogens. In addition to pathogens, ticks also carry symbionts that may play important roles in tick biology, and could interfere with pathogen maintenance and transmission. In this study we evaluated the prevalence of 38 pathogens and four symbionts and their co-infection levels as well as possible interactions between pathogens, or between pathogens and symbionts. METHODOLOGY/PRINCIPAL FINDINGS: A total of 267 Ixodes ricinus female specimens were collected in the French Ardennes and analyzed by high-throughput real-time PCR for the presence of 37 pathogens (bacteria and parasites), by rRT-PCR to detect the presence of Tick-Borne encephalitis virus (TBEV) and by nested PCR to detect four symbionts. Possible multipartite interactions between pathogens, or between pathogens and symbionts were statistically evaluated. Among the infected ticks, 45% were co-infected, and carried up to five different pathogens. When adding symbiont prevalences, all ticks were infected by at least one microorganism, and up to eight microorganisms were identified in the same tick. When considering possible interactions between pathogens, the results suggested a strong association between Borrelia garinii and B. afzelii, whereas there were no significant interactions between symbionts and pathogens. CONCLUSION/SIGNIFICANCE: Our study reveals high pathogen co-infection rates in ticks, raising questions about possible co-transmission of these agents to humans or animals, and their consequences to human and animal health. We also demonstrated high prevalence rates of symbionts co-existing with pathogens, opening new avenues of enquiry regarding their effects on pathogen transmission and vector competence.

The importance of multiparasitism: examining the consequences of co-infections for human and animal health.

Most parasites co-occur with other parasites, although the importance of such multiparasitism has only recently been recognised. Co-infections may result when hosts are independently infected by different parasites at the same time or when interactions among parasite species facilitate co-occurrence. Such interactions can have important repercussions on human or animal health because they can alter host susceptibility, infection duration, transmission risks, and clinical symptoms. These interactions may be synergistic or antagonistic and thus produce diverse effects in infected humans and animals. Interactions among parasites strongly influence parasite dynamics and therefore play a major role in structuring parasite populations (both within and among hosts) as well as host populations. However, several methodological challenges remain when it comes to detecting parasite interactions. The goal of this review is to summarise current knowledge on the causes and consequences of multiparasitism and to discuss the different methods and tools that researchers have developed to study the factors that lead to multiparasitism. It also identifies new research directions to pursue.

Emerging horizons for tick-borne pathogens: from the 'one pathogen-one disease' vision to the pathobiome paradigm.

Ticks, as vectors of several notorious zoonotic pathogens, represent an important and increasing threat for human and animal health in Europe. Recent applications of new technology revealed the complexity of the tick microbiome, which may affect its vectorial capacity. Appreciation of these complex systems is expanding our understanding of tick-borne pathogens, leading us to evolve a more integrated view that embraces the 'pathobiome'; the pathogenic agent integrated within its abiotic and biotic environments. In this review, we will explore how this new vision will revolutionize our understanding of tick-borne diseases. We will discuss the implications in terms of future research approaches that will enable us to efficiently prevent and control the threat posed by ticks.

To be or not to be associated: power study of four statistical modeling approaches to identify parasite associations in cross-sectional studies.

A growing number of studies are reporting simultaneous infections by parasites in many different hosts. The detection of whether these parasites are significantly associated is important in medicine and epidemiology. Numerous approaches to detect associations are available, but only a few provide statistical tests. Furthermore, they generally test for an overall detection of association and do not identify which parasite is associated with which other one. Here, we developed a new approach, the association screening approach, to detect the overall and the detail of multi-parasite associations. We studied the power of this new approach and of three other known ones (i.e., the generalized chi-square, the network and the multinomial GLM approaches) to identify parasite associations either due to parasite interactions or to confounding factors. We applied these four approaches to detect associations within two populations of multi-infected hosts: (1) rodents infected with Bartonella sp., Babesia microti and Anaplasma phagocytophilum and (2) bovine population infected with Theileria sp. and Babesia sp. We found that the best power is obtained with the screening model and the generalized chi-square test. The differentiation between associations, which are due to confounding factors and parasite interactions was not possible. The screening approach significantly identified associations between Bartonella doshiae and B. microti, and between T. parva, T. mutans, and T. velifera. Thus, the screening approach was relevant to test the overall presence of parasite associations and identify the parasite combinations that are significantly over- or under-represented. Unraveling whether the associations are due to real biological interactions or confounding factors should be further investigated. Nevertheless, in the age of genomics and the advent of new technologies, it is a considerable asset to speed up researches focusing on the mechanisms driving interactions between parasites.

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.

Introduced Siberian chipmunks (Tamias sibiricus barberi) contribute more to lyme borreliosis risk than native reservoir rodents.

The variation of the composition in species of host communities can modify the risk of disease transmission. In particular, the introduction of a new host species can increase health threats by adding a new reservoir and/or by amplifying the circulation of either exotic or native pathogens. Lyme borreliosis is a multi-host vector-borne disease caused by bacteria belonging to the Borrelia burgdorferi sensu lato complex. It is transmitted by the bite of hard ticks, especially Ixodes ricinus in Europe. Previous studies showed that the Siberian chipmunk, Tamias sibiricus barberi, an introduced ground squirrel in the Forest of Sénart (near Paris, France) was highly infested by I. ricinus, and consequently infected by B. burgdorferi sl. An index of the contribution of chipmunks to the density of infected questing nymphs on the vegetation (i.e., the acarological risk for humans) was compared to that of bank voles (Myodes glareolus) and of wood mice (Apodemus sylvaticus), two known native and sympatric competent reservoir hosts. Chipmunks produced nearly 8.5 times more infected questing nymphs than voles and mice. Furthermore, they contribute to a higher diversity of B. burgdorferi sl genospecies (B. afzelii, B. burgdorferi sensu stricto and B. garinii). The contribution of chipmunks varied between years and seasons, according to tick availability. As T. s. barberi must be a competent reservoir, it should amplify B. burgdorferi sl infection, hence increasing the risk of Lyme borreliosis in humans.

A probabilistic model in cross-sectional studies for identifying interactions between two persistent vector-borne pathogens in reservoir populations.

BACKGROUND: In natural populations, individuals are infected more often by several pathogens than by just one. In such a context, pathogens can interact. This interaction could modify the probability of infection by subsequent pathogens. Identifying when pathogen associations correspond to biological interactions is a challenge in cross-sectional studies where the sequence of infection cannot be demonstrated. METHODOLOGY/PRINCIPAL FINDINGS: Here we modelled the probability of an individual being infected by one and then another pathogen, using a probabilistic model and maximum likelihood statistics. Our model was developed to apply to cross-sectional data, vector-borne and persistent pathogens, and to take into account confounding factors. Our modelling approach was more powerful than the commonly used Chi-square test of independence. Our model was applied to detect potential interaction between Borrelia afzelii and Bartonella spp. that infected a bank vole population at 11% and 57% respectively. No interaction was identified. CONCLUSIONS/SIGNIFICANCE: The modelling approach we proposed is powerful and can identify the direction of potential interaction. Such an approach can be adapted to other types of pathogens, such as non-persistents. The model can be used to identify when co-occurrence patterns correspond to pathogen interactions, which will contribute to understanding how organism communities are assembled and structured. In the long term, the model's capacity to better identify pathogen interactions will improve understanding of infectious risk.