Site-occupancy modelling as a novel framework for assessing test sensitivity and estimating wildlife disease prevalence from imperfect diagnostic tests

Leucocytozoon Infection Does Not Influence the Survival of Boreal Owl Aegolius funereus Nestlings

Leucocytozoon infection has been observed to impact the reproductive ecology and physiology of avian hosts, but its influence on nestling survival remains unclear. We investigated the effect of Leucocytozoon infection intensity, determined through triplicate PCR sample analyses, on the survival of 256 boreal owl (Aegolius funereus) nestlings during an 8-yr study. Contrary to our expectations, the survival probability of boreal owl nestlings was not influenced by their Leucocytozoon infection intensity. Nestling age and Leucocytozoon infection intensity in male and female parents also did not impact nestling survival. Instead, food abundance and hatching order were the key factors influencing nestling survival. Additionally, we observed a significantly higher Leucocytozoon infection intensity in male parents compared to female parents and nestlings. We suggest a distinct division of parental roles may lead females and nestlings staying within the nest boxes (cavities) to experience lower exposure to potential vectors transmitting blood parasites than their male counterparts. Our study shows that Leucocytozoon disease may not be lethal for boreal owl chicks, exhibiting a below-average infection intensity compared to their male parents.

Detection of lymphoproliferative disease virus in Iowa Wild Turkeys (Meleagris gallopavo): Comparison of two sections of the proviral genome

An accurate diagnostic test is an essential aspect of successfully monitoring and managing wildlife diseases. Lymphoproliferative Disease Virus (LPDV) is an avian retrovirus that was first identified in domestic turkeys in Europe and was first reported in a Wild Turkey (Meleagris gallopavo) in the United States in 2009. It has since been found to be widely distributed throughout North America. The majority of studies have utilized bone marrow and PCR primers targeting a 413-nucleotide sequence of the gag gene of the provirus to detect infection. While prior studies have evaluated the viability of other tissues for LPDV detection (whole blood, spleen, liver, cloacal swabs) none to date have studied differences in detection rates when utilizing different genomic regions of the provirus. This study examined the effectiveness of another section of the provirus, a 335-nucleotide sequence starting in the U3 region of the LTR (Long Terminal Repeat) and extending into the Matrix of the gag region (henceforth LTR), for detecting LPDV. Bone marrow samples from hunter-harvested Wild Turkeys (n = 925) were tested for LPDV with the gag gene and a subset (n = 417) including both those testing positive and those where LPDV was not detected was re-tested with LTR. The positive percent agreement (PPA) was 97.1% (68 of 70 gag positive samples tested positive with LTR) while the negative percent agreement (NPA) was only 68.0% (236 of 347 gag negative samples tested negative with LTR). Cohen's Kappa (κ = 0.402, Z = 10.26, p<0.0001) and the McNemar test (OR = 55.5, p<0.0001) indicated weak agreement between the two gene regions. We found that in Iowa Wild Turkeys use of the LTR region identified LPDV in many samples in which we failed to detect LPDV using the gag region and that LTR may be more appropriate for LPDV surveillance and monitoring. However, neither region of the provirus resulted in perfect detection and additional work is necessary to determine if LTR is more reliable in other geographic regions where LPDV occurs.

A cross-sectional investigation of Leptospira at the wildlife-livestock interface in New Zealand

There has been a recent upsurge in human cases of leptospirosis in New Zealand, with wildlife a suspected emerging source, but up-to-date knowledge on this topic is lacking. We conducted a cross-sectional study in two farm environments to estimate Leptospira seroprevalence in wildlife and sympatric livestock, PCR/culture prevalence in wildlife, and compare seroprevalence and prevalence between species, sex, and age groups. Traps targeting house mice (Mus musculus), black rats (Rattus rattus), hedgehogs (Erinaceus europaeus) and brushtail possums (Trichosurus vulpecula) were set for 10 trap-nights in March-April 2017 on a dairy (A) and a beef and sheep (B) farm. Trapped wild animals and an age-stratified random sample of domestic animals, namely cattle, sheep and working dogs were blood sampled. Sera were tested by microagglutination test for five serogroups and titres compared using a Proportional Similarity Index (PSI). Wildlife kidneys were sampled for culture and qPCR targeting the lipL32 gene. True prevalence in mice was assessed using occupancy modelling by collating different laboratory results. Infection profiles varied by species, age group and farm. At the MAT cut-point of ≥ 48, up to 78% of wildlife species, and 16-99% of domestic animals were seropositive. Five of nine hedgehogs, 23/105 mice and 1/14 black rats reacted to L. borgpetersenii sv Ballum. The sera of 4/18 possums and 4/9 hedgehogs reacted to L. borgpetersenii sv Hardjobovis whilst 1/18 possums and 1/9 hedgehogs reacted to Tarassovi. In ruminants, seroprevalence for Hardjobovis and Pomona ranged 0-90% and 0-71% depending on the species and age group. Titres against Ballum, Tarassovi and Copenhageni were also observed in 4-20%, 0-25% and 0-21% of domestic species, respectively. The PSI indicated rodents and livestock had the most dissimilar serological responses. Three of nine hedgehogs, 31/105 mice and 2/14 rats were carrying leptospires (PCR and/or culture positive). True prevalence estimated by occupancy modelling in mice was 38% [95% Credible Interval 26, 51%] on Farm A and 22% [11, 40%] on Farm B. In the same environment, exposure to serovars found in wildlife species was commonly detected in livestock. Transmission pathways between and within species should be assessed to help in the development of efficient mitigation strategies against Leptospira.

Estimating parasite infrapopulation size given imperfect detection: Proof-of-concept with ectoparasitic fleas on prairie dogs

Parasite infrapopulation size - the population of parasites affecting a single host - is a central metric in parasitology. However, parasites are small and elusive such that imperfect detection is expected. Repeated sampling of parasites during primary sampling occasions (e.g., each host capture) informs the detection process. Here, we estimate flea (Siphonaptera) infrapopulation size on black-tailed prairie dogs (Cynomys ludovicianus, BTPDs) as a proof-of-concept for estimating parasite infrapopulations given imperfect detection. From Jun-Aug 2011, we live-trapped 299 BTPDs for a total of 573 captures on 20 plots distributed among 13 colonies at the Vermejo Park Ranch, New Mexico, USA. During each capture, an anesthetized BTPD was combed 3 times consecutively, 15 s each, to remove and count fleas. Each flea (n = 4846) was linked to the BTPD from which it was collected and assigned an encounter history ('100', '010', '001'). We analyzed the encounter histories using Huggins closed captures models, setting recapture probabilities to 0, thereby accounting for flea removal from hosts. The probability of detecting an individual flea (p) increased with Julian date; field personnel may have become more efficient at combing fleas as the field season progressed. Combined p across 3 combings equaled 0.99. Estimates of flea infrapopulation size were reasonable and followed the negative binomial distribution. Our general approach may be broadly applicable to estimating infrapopulation sizes for parasites. The utility of this approach increases as p declines but, if p is very low, inference is likely limited.

Detecting Leishmania in dogs: A hierarchical-modeling approach to investigate the performance of parasitological and qPCR-based diagnostic procedures

BACKGROUND

Domestic dogs are primary reservoir hosts of Leishmania infantum, the agent of visceral leishmaniasis. Detecting dog infections is central to epidemiological inference, disease prevention, and veterinary practice. Error-free diagnostic procedures, however, are lacking, and the performance of those available is difficult to measure in the absence of fail-safe "reference standards". Here, we illustrate how a hierarchical-modeling approach can be used to formally account for false-negative and false-positive results when investigating the process of Leishmania detection in dogs.

METHODS/FINDINGS

We studied 294 field-sampled dogs of unknown infection status from a Leishmania-endemic region. We ran 350 parasitological tests (bone-marrow microscopy and culture) and 1,016 qPCR assays (blood, bone-marrow, and eye-swab samples with amplifiable DNA). Using replicate test results and site-occupancy models, we estimated (a) clinical sensitivity for each diagnostic procedure and (b) clinical specificity for qPCRs; parasitological tests were assumed 100% specific. Initial modeling revealed qPCR specificity < 94%; we tracked the source of this unexpected result to some qPCR plates having subtle signs of possible contamination. Using multi-model inference, we formally accounted for suspected plate contamination and estimated qPCR sensitivity at 49-53% across sample types and dog clinical conditions; qPCR specificity was high (95-96%), but fell to 81-82% for assays run in plates with suspected contamination. The sensitivity of parasitological procedures was low (~12-13%), but increased to ~33% (with substantial uncertainty) for bone-marrow culture in seriously-diseased dogs. Leishmania-infection frequency estimates (~49-50% across clinical conditions) were lower than observed (~60%).

CONCLUSIONS

We provide statistical estimates of key performance parameters for five diagnostic procedures used to detect Leishmania in dogs. Low clinical sensitivies likely reflect the absence of Leishmania parasites/DNA in perhaps ~50-70% of samples drawn from infected dogs. Although qPCR performance was similar across sample types, non-invasive eye-swabs were overall less likely to contain amplifiable DNA. Finally, modeling was instrumental to discovering (and formally accounting for) possible qPCR-plate contamination; even with stringent negative/blank-control scoring, ~4-5% of positive qPCRs were most likely false-positives. This work shows, in sum, how hierarchical site-occupancy models can sharpen our understanding of the problem of diagnosing host infections with hard-to-detect pathogens including Leishmania.

Complementary roles of wild boar and red deer to animal tuberculosis maintenance in multi-host communities

The contribution of wildlife species to pathogen maintenance in multi-host communities has seldom been quantified. To assess the relative contribution of the main wildlife hosts of animal tuberculosis (TB) to its maintenance, we estimated the basic reproduction number (R₀) of Mycobacterium tuberculosis complex in wild boar and red deer at 29 sites in the Iberian Peninsula. Host abundance and true TB prevalence were estimated for each species at each site by sampling from distributions incorporating the uncertainty in the proportion of the population harvested each year, sensitivity, and specificity of the diagnostic methods, while excretion of mycobacteria was estimated using site-occupancy models. The distributions of these parameters were then used to estimate, at each site, the R_{0,wild boar} (range 0.1 - 55.9, average 8.7, standard deviation 11.8), and the R_{0,red deer} (0.1 - 18.9, 2.2, 3.9). Animal TB is maintained in epidemiological scenarios ranging from any single species acting as a maintenance host (the wild boar in 18 sites and the red deer in 5), to facultative multi-host disease (6 sites). The prevalence of TB in the red deer is likely an important driver of the epidemiology in multi-host communities. The wild boar was the main maintenance host of TB in most of the study sites and could have an epidemiological role linking the wildlife multi-host community and livestock.

MULTI-STATE OCCUPANCY MODEL ESTIMATES PROBABILITY OF DETECTION OF AN AQUATIC PARASITE USING ENVIRONMENTAL DNA: PSEUDOLOMA NEUROPHILIA IN ZEBRAFISH AQUARIA

Detecting the presence of important parasites within a host and its environment is critical to understanding the dynamics that influence a pathogen's ability to persist, while accurate detection is also essential for the implementation of effective control strategies. Pseudoloma neurophilia is the most common pathogen reported in zebrafish (Danio rerio) research facilities. The only assays currently available for P. neurophilia are through lethal sampling, often requiring euthanasia of the entire population for accurate estimates of prevalence in small populations. We present a non-lethal screening method to detect P. neurophilia in tank water based on the detection of environmental DNA (eDNA) from this microsporidium, using a previously developed qPCR assay that was adapted to the digital PCR (dPCR) platform to complement current surveillance protocols. Using the generated dPCR data, a multi-state occupancy model was also implemented to predict the probability of detecting the microsporidium in tank water under different flow regimes and pathogen prevalence. The occupancy model revealed that samples collected in static conditions were more informative than samples collected from flow-through conditions, with a probability of detection at 80% and 47%, respectively. There was also a positive correlation between the frequency of detection in water and prevalence in fish based on qPCR.

Diagnostic sensitivity of porcine biological samples for detecting African swine fever virus infection after natural consumption in feed and liquid

African swine fever virus (ASFV) is a global threat to swine production and sustainable pork supply. Without a commercially available vaccine, prevention of ASFV entry and spread is reliant on biosecurity and early detection of infection. Although ASFV ingestion in swill or feed by naïve pigs is a likely route of initial introduction, controlled experimental studies rarely utilize natural consumption as the infection route. In the current study, we utilized biological samples collected from pigs 5 days after natural consumption of ASFV in feed and liquid to assess diagnostic sensitivity for early detection of virus infection. Biological samples (serum, spleen, lymph nodes, tonsils, and faeces) were assessed for the presence of ASFV using quantitative PCR and virus isolation. Statistical methods modelled the detection sensitivity of each sample type with each diagnostic assay in individual samples. Our results provide important information that can be incorporated into ASFV surveillance programs.

Host-multiparasite interactions in amphibians: a review

Parasites, including viruses, bacteria, fungi, protists, helminths, and arthropods, are ubiquitous in the animal kingdom. Consequently, hosts are frequently infected with more than one parasite species simultaneously. The assessment of such co-infections is of fundamental importance for disease ecology, but relevant studies involving non-domesticated animals have remained scarce. Many amphibians are in decline, and they generally have a highly diverse parasitic fauna. Here we review the literature reporting on field surveys, veterinary case studies, and laboratory experiments on co-infections in amphibians, and we summarize what is known about within-host interactions among parasites, which environmental and intrinsic factors influence the outcomes of these interactions, and what effects co-infections have on hosts. The available literature is piecemeal, and patterns are highly diverse, so that identifying general trends that would fit most host–multiparasite systems in amphibians is difficult. Several examples of additive, antagonistic, neutral, and synergistic effects among different parasites are known, but whether members of some higher taxa usually outcompete and override the effects of others remains unclear. The arrival order of different parasites and the time lag between exposures appear in many cases to fundamentally shape competition and disease progression. The first parasite to arrive can gain a marked reproductive advantage or induce cross-reaction immunity, but by disrupting the skin and associated defences (i.e., skin secretions, skin microbiome) and by immunosuppression, it can also pave the way for subsequent infections. Although there are exceptions, detrimental effects to the host are generally aggravated with increasing numbers of co-infecting parasite species. Finally, because amphibians are ectothermic animals, temperature appears to be the most critical environmental factor that affects co-infections, partly via its influence on amphibian immune function, partly due to its direct effect on the survival and growth of parasites. Besides their importance for our understanding of ecological patterns and processes, detailed knowledge about co-infections is also crucial for the design and implementation of effective wildlife disease management, so that studies concentrating on the identified gaps in our understanding represent rewarding research avenues.

A multi-state occupancy model to non-invasively monitor visible signs of wildlife health with camera traps that accounts for image quality

Camera traps are an increasingly popular tool to monitor wildlife distributions. However, traditional analytical approaches to camera trap data are difficult to apply to visible wildlife characteristics in single images, such as infection status. Several parasites produce visible signs of infection that could be sampled via camera traps. Sarcoptic mange Sarcoptes scabiei is an ideal disease to study using cameras because it results in visible hair loss and affects a broad host range. Here, we developed a multi-state occupancy model to estimate the occurrence of mange in coyotes Canis latrans across an urban gradient. This model incorporates a secondary detection function for apparent by-image infection status to provide detection-corrected estimates of mange occurrence. We analysed a multi-year camera trap dataset in Chicago, Illinois, United States, to test whether the apparent occurrence of sarcoptic mange in coyotes Canis latrans increases with urbanization or varies through time. We documented visible signs consistent with current or recovering mange infection and variables we hypothesized would improve mange detection: The proportion of the coyote in frame, image blur and whether the image was in colour. We were more likely to detect coyotes with mange in images that were less blurry, in colour, and if a greater proportion of the coyote was visible. Mangy coyote occupancy was significantly higher in urban developed areas with low housing density and higher canopy cover whereas coyote occupancy, mangy or otherwise, decreased with urbanization. By incorporating image quality into our by-image detection function, we provide a robust method to non-invasively survey visible aspects of wildlife health with camera traps. Apparently mangy coyotes were associated with low-density forested neighbourhoods, which may offer vegetated areas while containing sources of anthropogenic resources. This association may contribute to human-wildlife conflict and reinforces posited relationships between infection risk and habitat use. More generally, our model could provide detection-corrected occupancy estimates of visible characteristics that vary by image such as body condition or injuries.

Use of occupancy modelling to identify sample sizes and waterbodies with fish exceeding mercury consumption advisory thresholds

Identifying waterbodies where fish methylmercury concentrations are elevated is critical for development of consumption guidelines. However, mercury concentrations vary among waterbodies and fishes due to a suite of environmental conditions and detection of elevated mercury concentrations is imperfect, resulting in inaccurate consumption guidelines. Occupancy models may be a useful approach for addressing these issues but have not been used for these purposes. Our objectives were to use occupancy modeling to (1) estimate number of samples needed to detect mercury levels surpassing >0.30 mg/kg wet weight in fish at a waterbody (2) identify individual fish-level factors associated with detection probability, and (3) identify environmental-level factors linked to elevated mercury levels in fish at a waterbody. Mercury concentrations were estimated from >500 largemouth bass Micropterus salmoides and walleye Sander vitreus from 30 waterbodies throughout Iowa, USA to identify individuals with concentrations > or <0.30 mg/kg. Probability of detecting mercury concentrations >0.30 mg/kg varied between species and increased with fish length; consequently, more samples were needed to detect elevated mercury concentrations in small versus large fish. The probability of a waterbody having fish with elevated mercury levels increased with the percent grassland and declined with percent agriculture in the watershed, providing prioritization metrics for mercury surveillance programs. Our results demonstrate that occupancy models can be a valuable tool for mercury surveillance due to their ability to estimate necessary sample sizes and identify fish sizes and waterbodies with elevated mercury concentrations while accounting for imperfect detection probabilities.

Choice of molecular assay determines ranavirus detection probability and inferences about prevalence and occurrence

Ranaviruses are emerging pathogens that can cause morbidity, mortality and population declines in ectothermic hosts; however, there is no standardized approach to diagnostics. Here, we compared the inter-assay variation and intra-assay precision among 2 commonly used quantitative PCRs (qPCRs), a conventional and a nested PCR assay (used as a gold standard), using laboratory-propagated ranavirus (FV3 and CMTV) and field-collected samples. A qPCR assay ('Leung') detected viral DNA in dilutions 2 orders of magnitude lower than other assays regardless of the viral lineage of the cultured isolate (FV3/CMTV). The second qPCR ('Brunner') was slightly more sensitive than the conventional PCR ('Mao' assay). For field samples, the Leung qPCR detected all known positives, while the Mao assay PCR only detected 2.5% of the positive samples. Amplicon sequences from the 2 conventional PCRs were shown to be useful for inferring viral lineage. Inaccurate results will bias estimates of the distribution and prevalence of ranaviruses, and together these findings emphasize that molecular assays should be chosen carefully in the context of study aims.

How sure are you? A web-based application to confront imperfect detection of respiratory pathogens in bighorn sheep

The relationships between host-pathogen population dynamics in wildlife are poorly understood. An impediment to progress in understanding these relationships is imperfect detection of diagnostic tests used to detect pathogens. If ignored, imperfect detection precludes accurate assessment of pathogen presence and prevalence, foundational parameters for deciphering host-pathogen dynamics and disease etiology. Respiratory disease in bighorn sheep (Ovis canadensis) is a significant impediment to their conservation and restoration, and effective management requires a better understanding of the structure of the pathogen communities. Our primary objective was to develop an easy-to-use and accessible web-based Shiny application that estimates the probability (with associated uncertainty) that a respiratory pathogen is present in a herd and its prevalence given imperfect detection. Our application combines the best-available information on the probabilities of detection for various respiratory pathogen diagnostic protocols with a hierarchical Bayesian model of pathogen prevalence. We demonstrated this application using four examples of diagnostic tests from three herds of bighorn sheep in Montana. For instance, one population with no detections of Mycoplasma ovipneumoniae (PCR assay) still had an 6% probability of the pathogen being present in the herd. Similarly, the apparent prevalence (0.32) of M. ovipneumoniae in another herd was a substantial underestimate of estimated true prevalence (0.46: 95% CI = [0.25, 0.71]). The negative bias of naïve prevalence increased as the probability of detection of testing protocols worsened such that the apparent prevalence of Mannheimia haemolytica (culture assay) in a herd (0.24) was less than one third that of estimated true prevalence (0.78: 95% CI = [0.43, 0.99]). We found a small difference in the estimates of the probability that Mannheimia spp. (culture assay) was present in one herd between the binomial sampling approach (0.24) and the hypergeometric approach (0.22). Ignoring the implications of imperfect detection and sampling variation for assessing pathogen communities in bighorn sheep can result in spurious inference on pathogen presence and prevalence, and potentially poorly informed management decisions. Our Shiny application makes the rigorous assessment of pathogen presence, prevalence and uncertainty straightforward, and we suggest it should be incorporated into a new paradigm of disease monitoring.

On the True Number of COVID-19 Infections: Effect of Sensitivity, Specificity and Number of Tests on Prevalence Ratio Estimation

In this paper, a formula for estimating the prevalence ratio of a disease in a population that is tested with imperfect tests is given. The formula is in terms of the fraction of positive test results and test parameters, i.e., probability of true positives (sensitivity) and the probability of true negatives (specificity). The motivation of this work arises in the context of the COVID-19 pandemic in which estimating the number of infected individuals depends on the sensitivity and specificity of the tests. In this context, it is shown that approximating the prevalence ratio by the ratio between the number of positive tests and the total number of tested individuals leads to dramatically high estimation errors, and thus, unadapted public health policies. The relevance of estimating the prevalence ratio using the formula presented in this work is that precision increases with the number of tests. Two conclusions are drawn from this work. First, in order to ensure that a reliable estimation is achieved with a finite number of tests, testing campaigns must be implemented with tests for which the sum of the sensitivity and the specificity is sufficiently different than one. Second, the key parameter for reducing the estimation error is the number of tests. For a large number of tests, as long as the sum of the sensitivity and specificity is different than one, the exact values of these parameters have very little impact on the estimation error.

A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error

Stakeholder support is vital for achieving conservation success, yet there are few reliable mechanisms to monitor stakeholder attitudes toward conservation. Approaches used to assess attitudes rarely account for bias arising from reporting error, which can lead to falsely reporting a positive attitude toward conservation (false-positive error) or not reporting a positive attitude when the respondent has a positive attitude toward conservation (false-negative error). Borrowing from developments in applied conservation science, we used a Bayesian hierarchical model to quantify stakeholder attitudes as the probability of having a positive attitude toward wildlife notionally (or in abstract terms) and at localized scales while accounting for reporting error. We compared estimates from our model, Likert scores, and naïve estimates (i.e., proportion of respondents reporting a positive attitude in at least 1 question that was only susceptible to false-negative error) with true stakeholder attitudes through simulations. We then applied the model in a survey of tea estate staff on their attitudes toward Asian elephants (Elephas maximus) in the Kaziranga-Karbi Anglong landscape of northeast India. In simulations, Bayesian model estimates of stakeholder attitudes toward wildlife were less biased than naïve estimates or Likert scores. After accounting for reporting errors, we estimated the probability of having a positive attitude toward elephants notionally as 0.85 in the Kaziranga landscape, whereas the proportion of respondents who had positive attitudes toward elephants at a localized scale was 0.50. In comparison, without accounting for reporting errors, naïve estimates of proportions of respondents with positive attitudes toward elephants were 0.69 and 0.23 notionally and at local scales, respectively. False (positive and negative) reporting probabilities were consistently not 0 (0.22-0.68). Regular and reliable assessment of stakeholder attitudes-combined with inference on drivers of positive attitudes-can help assess the success of initiatives aimed at facilitating human behavioral change and inform conservation decision making.

Detection error influences both temporal seroprevalence predictions and risk factors associations in wildlife disease models

Understanding the prevalence of pathogens in invasive species is essential to guide efforts to prevent transmission to agricultural animals, wildlife, and humans. Pathogen prevalence can be difficult to estimate for wild species due to imperfect sampling and testing (pathogens may not be detected in infected individuals and erroneously detected in individuals that are not infected). The invasive wild pig (Sus scrofa, also referred to as wild boar and feral swine) is one of the most widespread hosts of domestic animal and human pathogens in North America.We developed hierarchical Bayesian models that account for imperfect detection to estimate the seroprevalence of five pathogens (porcine reproductive and respiratory syndrome virus, pseudorabies virus, Influenza A virus in swine, Hepatitis E virus, and Brucella spp.) in wild pigs in the United States using a dataset of over 50,000 samples across nine years. To assess the effect of incorporating detection error in models, we also evaluated models that ignored detection error. Both sets of models included effects of demographic parameters on seroprevalence. We compared our predictions of seroprevalence to 40 published studies, only one of which accounted for imperfect detection.We found a range of seroprevalence among the pathogens with a high seroprevalence of pseudorabies virus, indicating significant risk to livestock and wildlife. Demographics had mostly weak effects, indicating that other variables may have greater effects in predicting seroprevalence.Models that ignored detection error led to different predictions of seroprevalence as well as different inferences on the effects of demographic parameters.Our results highlight the importance of incorporating detection error in models of seroprevalence and demonstrate that ignoring such error may lead to erroneous conclusions about the risk associated with pathogen transmission. When using opportunistic sampling data to model seroprevalence and evaluate risk factors, detection error should be included.

How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure

Predicting infectious disease dynamics is a central challenge in disease ecology. Models that can assess which individuals are most at risk of being exposed to a pathogen not only provide valuable insights into disease transmission and dynamics but can also guide management interventions. Constructing such models for wild animal populations, however, is particularly challenging; often only serological data are available on a subset of individuals and nonlinear relationships between variables are common. Here we provide a guide to the latest advances in statistical machine learning to construct pathogen-risk models that automatically incorporate complex nonlinear relationships with minimal statistical assumptions from ecological data with missing data. Our approach compares multiple machine learning algorithms in a unified environment to find the model with the best predictive performance and uses game theory to better interpret results. We apply this framework on two major pathogens that infect African lions: canine distemper virus (CDV) and feline parvovirus. Our modelling approach provided enhanced predictive performance compared to more traditional approaches, as well as new insights into disease risks in a wild population. We were able to efficiently capture and visualize strong nonlinear patterns, as well as model complex interactions between variables in shaping exposure risk from CDV and feline parvovirus. For example, we found that lions were more likely to be exposed to CDV at a young age but only in low rainfall years. When combined with our data calibration approach, our framework helped us to answer questions about risk of pathogen exposure that are difficult to address with previous methods. Our framework not only has the potential to aid in predicting disease risk in animal populations, but also can be used to build robust predictive models suitable for other ecological applications such as modelling species distribution or diversity patterns.

Prevalence and diversity of avian blood parasites in a resident northern passerine

BACKGROUND

Climate-related changes are expected to influence the prevalence and distribution of vector-borne haemosporidian parasites at northern latitudes, although baseline information about resident birds is still lacking. In this study, we investigated prevalence and genetic diversity of Plasmodium, Haemoproteus, and Leucocytozoon parasites infecting the northwestern crow (Corvus caurinus), a non-migratory passerine with unique life-history characteristics. This species occupies both intertidal and forested habitats and is subject to high prevalence of avian keratin disorder (AKD), a disease that causes gross beak deformities. Investigation of avian blood parasites in northwestern crows at sites broadly distributed across coastal Alaska provided an opportunity to evaluate specific host factors related to parasite infection status and assess geographical patterns of prevalence.

RESULTS

We used molecular methods to screen for haemosporidian parasites in northwestern crows and estimated genus-specific parasite prevalence with occupancy modeling that accounts for imperfect detection of parasite infection. We observed considerable geographical and annual variation in prevalence of Plasmodium, Haemoproteus, and Leucocytozoon, but these patterns were not correlated with indices of local climatic conditions. Our models also did not provide support for relationships between the probability of parasite infection and body condition or the occurrence of co-infections with other parasite genera or clinical signs of AKD. In our phylogenetic analyses, we identified multiple lineages of each parasite genus, with Leucocytozoon showing greater diversity than Plasmodium or Haemoproteus.

CONCLUSIONS

Results from this study expand our knowledge about the prevalence and diversity of avian blood parasites in northern resident birds as well as corvids worldwide. We detected all three genera of avian haemosporidians in northwestern crows in Alaska, although only Leucocytozoon occurred at all sites in both years. Given the strong geographical and annual variation in parasite prevalence and apparent lack of correlation with climatic variables, it appears that there are other key factors responsible for driving transmission dynamics in this region. Thus, caution is warranted when using standard climatic or geographical attributes in a predictive framework. Our phylogenetic results demonstrate lower host specificity for some lineages of Leucocytozoon than is typically reported and provide insights about genetic diversity of local haemosporidian parasites in Alaska.

Developing noninvasive methodologies to assess koala population health through detecting Chlamydia from scats

Wildlife diseases are a recognized driver of global biodiversity loss, have substantial economic impacts, and are increasingly becoming a threat to human health. Disease surveillance is critical but remains difficult in the wild due to the substantial costs and potential biases associated with most disease detection methods. Noninvasive scat surveys have been proposed as a health monitoring methodology to overcome some of these limitations. Here, we use the known threat of Chlamydia disease to the iconic, yet vulnerable, koala Phascolarctos cinereus to compare three methods for Chlamydia detection in scats: multiplex quantitative PCR, next generation sequencing, and a detection dog specifically trained on scats from Chlamydia-infected koalas. All three methods demonstrated 100% specificity, while sensitivity was variable. Of particular interest is the variable sensitivity of these diagnostic tests to detect sick individuals (i.e., not only infection as confirmed by Chlamydia-positive swabs, but with observable clinical signs of the disease); for koalas with urogenital tract disease signs, sensitivity was 78% with quantitative PCR, 50% with next generation genotyping and 100% with the detection dog method. This may be due to molecular methods having to rely on high-quality DNA whereas the dog most likely detects volatile organic compounds. The most appropriate diagnostic test will vary with disease prevalence and the specific aims of disease surveillance. Acknowledging that detection dogs might not be easily accessible to all, the future development of affordable and portable "artificial noses" to detect diseases from scats in the field might enable cost-effective, rapid and large-scale disease surveillance.

Infection prevalence and ecotypes of Anaplasma phagocytophilum in moose Alces alces, red deer Cervus elaphus, roe deer Capreolus capreolus and Ixodes ricinus ticks from Norway

Background

The geographical expansion of the tick Ixodes ricinus in northern Europe is a serious concern for animal and human health. The pathogen Anaplasma phagocytophilum is transmitted by ticks and causes emergences of tick-borne fever (anaplasmosis) in livestock. The transmission dynamics of the different ecotypes of A. phagocytophilum in the ecosystems is only partly determined. Red deer and roe deer contribute to circulation of different ecotypes of A. phagocytophilum in continental Europe, while the role of moose for circulation of different ecotypes is not fully established but an important issue in northern Europe.

Methods

We determined infection prevalence and ecotypes of A. phagocytophilum in moose (n = 111), red deer (n = 141), roe deer (n = 28) and questing ticks (n = 9241) in Norway.

Results

As previously described, red deer was exclusively linked to circulation of ecotype I, while roe deer was exclusively linked to circulation of ecotype II. Surprisingly, we found 58% ecotype I (n = 19) and 42% of ecotype II (n = 14) in moose. Both ecotypes were found in questing ticks in areas with multiple cervid species present, while only ecotype I was found in ticks in a region with only red deer present. Hence, the geographical distribution of ecotypes in ticks followed the distribution of cervid species present in a given region and their link to ecotype I and II.

Conclusions

Moose probably function as reservoirs for both ecotype I and II, indicating that the ecotypes of A. phagocytophilum are not entirely host-specific and have overlapping niches. The disease hazard depends also on both host abundance and the number of immature ticks fed by each host. Our study provides novel insights in the northern distribution and expansion of tick-borne fever.

Disease-structured N-mixture models: A practical guide to model disease dynamics using count data

Obtaining inferences on disease dynamics (e.g., host population size, pathogen prevalence, transmission rate, host survival probability) typically requires marking and tracking individuals over time. While multistate mark-recapture models can produce high-quality inference, these techniques are difficult to employ at large spatial and long temporal scales or in small remnant host populations decimated by virulent pathogens, where low recapture rates may preclude the use of mark-recapture techniques. Recently developed N-mixture models offer a statistical framework for estimating wildlife disease dynamics from count data. N-mixture models are a type of state-space model in which observation error is attributed to failing to detect some individuals when they are present (i.e., false negatives). The analysis approach uses repeated surveys of sites over a period of population closure to estimate detection probability. We review the challenges of modeling disease dynamics and describe how N-mixture models can be used to estimate common metrics, including pathogen prevalence, transmission, and recovery rates while accounting for imperfect host and pathogen detection. We also offer a perspective on future research directions at the intersection of quantitative and disease ecology, including the estimation of false positives in pathogen presence, spatially explicit disease-structured N-mixture models, and the integration of other data types with count data to inform disease dynamics. Managers rely on accurate and precise estimates of disease dynamics to develop strategies to mitigate pathogen impacts on host populations. At a time when pathogens pose one of the greatest threats to biodiversity, statistical methods that lead to robust inferences on host populations are critically needed for rapid, rather than incremental, assessments of the impacts of emerging infectious diseases.

ESTIMATING OCCURRENCE, PREVALENCE, AND DETECTION OF AMPHIBIAN PATHOGENS: INSIGHTS FROM OCCUPANCY MODELS

Understanding the distribution of pathogens across landscapes and their prevalence within host populations is a common aim of wildlife managers. Despite the need for unbiased estimates of pathogen occurrence and prevalence for planning effective management interventions, many researchers fail to account for imperfect pathogen detection. Instead raw data are often reported, which may lead to ineffective, or even detrimental, management actions. We illustrate the utility of occupancy models for generating unbiased estimates of disease parameters by 1) providing a written tutorial describing how to fit these models in Program PRESENCE and 2) presenting a case study with the pathogen ranavirus. We analyzed ranavirus detection data from a wildlife refuge (Maryland, US) using occupancy modeling, which yields unbiased estimates of pathogen occurrence and prevalence. We found ranavirus prevalence was underestimated by up to 30% if imperfect pathogen detection was ignored. The unbiased estimate of ranavirus prevalence in larval wood frog (Lithobates sylvaticus; 0.73) populations was higher than in larval spotted salamander (Ambystoma maculatum; 0.56) populations. In addition, the odds of detecting ranavirus in tail samples were 6.7 times higher than detecting ranavirus in liver samples. Therefore, tail samples presented a nonlethal sampling method for ranavirus that may be able to detect early (nonsystemic) infections.

Eco-evolutionary rescue promotes host-pathogen coexistence

Emerging infectious pathogens are responsible for some of the most severe host mass mortality events in wild populations. Yet, effective pathogen control strategies are notoriously difficult to identify, in part because quantifying and forecasting pathogen spread and disease dynamics is challenging. Following an outbreak, hosts must cope with the presence of the pathogen, leading to host-pathogen coexistence or extirpation. Despite decades of research, little is known about host-pathogen coexistence post-outbreak when low host abundances and cryptic species make these interactions difficult to study. Using a novel disease-structured N-mixture model, we evaluate empirical support for three host-pathogen coexistence hypotheses (source-sink, eco-evolutionary rescue, and spatial variation in pathogen transmission) in a Neotropical amphibian community decimated by Batrachochytrium dendrobatidis (Bd) in 2004. During 2010-2014, we surveyed amphibians in Parque Nacional G. D. Omar Torríjos Herrera, Coclé Province, El Copé, Panama. We found that the primary driver of host-pathogen coexistence was eco-evolutionary rescue, as evidenced by similar amphibian survival and recruitment rates between infected and uninfected hosts. Average apparent monthly survival rates of uninfected and infected hosts were both close to 96%, and the expected number of uninfected and infected hosts recruited (via immigration/reproduction) was less than one host per disease state per 20-m site. The secondary driver of host-pathogen coexistence was spatial variation in pathogen transmission as we found that transmission was highest in areas of low abundance but there was no support for the source-sink hypothesis. Our results indicate that changes in the host community (i.e., through genetic or species composition) can reduce the impacts of emerging infectious disease post-outbreak. Our disease-structured N-mixture model represents a valuable advancement for conservation managers trying to understand underlying host-pathogen interactions and provides new opportunities to study disease dynamics in remnant host populations decimated by virulent pathogens.

SURVEY OF ARCTIC ALASKAN WILDLIFE FOR INFLUENZA A ANTIBODIES: LIMITED EVIDENCE FOR EXPOSURE OF MAMMALS

Influenza A viruses (IAVs) are maintained in wild waterbirds and have the potential to infect a broad range of species, including wild mammals. The Arctic Coastal Plain of Alaska supports a diverse suite of species, including waterfowl that are common hosts of IAVs. Mammals co-occur with geese and other migratory waterbirds during the summer breeding season, providing a plausible mechanism for interclass transmission of IAVs. To estimate IAV seroprevalence and identify the subtypes to which geese, loons, Arctic foxes ( Vulpes lagopus), caribou ( Rangifer tarandus), and polar bears ( Ursus maritimus) are potentially exposed, we used a blocking enzyme-linked immunosorbent assay (bELISA) and a hemagglutination inhibition (HI) assay to screen for antibodies to IAVs in samples collected during spring and summer of 2012-16. Apparent IAV seroprevalence using the bELISA was 50.3% in geese (range by species: 46-52.8%), 9% in loons (range by species: 3-20%), and 0.4% in Arctic foxes. We found no evidence for exposure to IAVs in polar bears or caribou by either assay. Among geese, we estimated detection probability from replicate bELISA analyses to be 0.92 and also found good concordance (>85%) between results from bELISA and HI assays, which identified antibodies reactive to H1, H6, and H9 subtype IAVs. In contrast, the HI assay detected antibodies in only one of seven loon samples that were positive by bELISA; that sample had low titers to both H4 and H5 IAV subtypes. Our results provide evidence that a relatively high proportion of waterbirds breeding on the Arctic Coastal Plain are exposed to IAVs, although it is unknown whether such exposure occurs locally or on staging or wintering grounds. In contrast, seroprevalence of IAVs in concomitant Arctic mammals is apparently low.

The slow dynamics of mycoplasma infections in a tortoise host reveal heterogeneity pertinent to pathogen transmission and monitoring

The epidemiology of infectious diseases depends on many characteristics of disease progression, as well as the consistency of these processes across hosts. Longitudinal studies of infection can thus inform disease monitoring and management, but can be challenging in wildlife, particularly for long-lived hosts and persistent infections. Numerous tortoise species of conservation concern can be infected by pathogenic mycoplasmas that cause a chronic upper respiratory tract disease (URTD). Yet, a lack of detailed data describing tortoise responses to mycoplasma infections obscures our understanding of URTDs role in host ecology. We therefore monitored Mycoplasma agassizii infections in 14 captive desert tortoises and characterised clinical signs of disease, infection intensity, pathogen shedding and antibody production for nearly 4 years after initial exposure to donor hosts. Persistent infections established in all exposed tortoises within 10 weeks, but hosts appeared to vary in resistance, which affected the patterns of pathogen shedding and apparent disease. Delays in host immune response and changes to clinical signs and infection intensity over time resulted in inconsistencies between diagnostic tools and changes in diagnostic accuracy throughout the study. We discuss the implications these results have for URTD epidemiology and past and future research assessing disease prevalence and dynamics in tortoise populations.

A multi-event capture-recapture analysis of Toxoplasma gondii seroconversion dynamics in farm cats

Background

Domestic cats play a key role in the epidemiology of the parasite Toxoplasma gondii by excreting environmentally-resistant oocysts that may infect humans and other warm-blooded animals. The dynamics of Toxoplasma gondii seroconversion, used as a proxy for primo-infection dynamics, was investigated in five cat populations living on farms.

Methods

Serological tests on blood samples from cats were performed every three months over a period of two years, for a total of 400 serological tests performed on 130 cats. Variations in seroconversion rates and associated factors were investigated using a multi-event capture-recapture modelling approach that explicitly accounted for uncertainties in cat age and serological status.

Results

Seroprevalence varied between farms, from 15 to 73%, suggesting differential exposure of cats to T. gondii. In farms with high exposure, cats could become infected before reaching the age of six months. Seroconversion rates varied from 0.42 to 0.96 seroconversions per cat per year and were higher in autumn and winter than in spring and summer.

Conclusion

Our results suggest inter-farm and seasonal variations in the risks of exposure to T. gondii oocysts for humans and livestock living on farms. The paper also discusses the role of young cats in the maintenance of environmental contamination by T. gondii oocysts on farms.

Electronic supplementary material

The online version of this article (10.1186/s13071-018-2834-4) contains supplementary material, which is available to authorized users.

The Certainty of Uncertainty: Potential Sources of Bias and Imprecision in Disease Ecology Studies

Wildlife diseases have important implications for wildlife and human health, the preservation of biodiversity and the resilience of ecosystems. However, understanding disease dynamics and the impacts of pathogens in wild populations is challenging because these complex systems can rarely, if ever, be observed without error. Uncertainty in disease ecology studies is commonly defined in terms of either heterogeneity in detectability (due to variation in the probability of encountering, capturing, or detecting individuals in their natural habitat) or uncertainty in disease state assignment (due to misclassification errors or incomplete information). In reality, however, uncertainty in disease ecology studies extends beyond these components of observation error and can arise from multiple varied processes, each of which can lead to bias and a lack of precision in parameter estimates. Here, we present an inventory of the sources of potential uncertainty in studies that attempt to quantify disease-relevant parameters from wild populations (e.g., prevalence, incidence, transmission rates, force of infection, risk of infection, persistence times, and disease-induced impacts). We show that uncertainty can arise via processes pertaining to aspects of the disease system, the study design, the methods used to study the system, and the state of knowledge of the system, and that uncertainties generated via one process can propagate through to others because of interactions between the numerous biological, methodological and environmental factors at play. We show that many of these sources of uncertainty may not be immediately apparent to researchers (for example, unidentified crypticity among vectors, hosts or pathogens, a mismatch between the temporal scale of sampling and disease dynamics, demographic or social misclassification), and thus have received comparatively little consideration in the literature to date. Finally, we discuss the type of bias or imprecision introduced by these varied sources of uncertainty and briefly present appropriate sampling and analytical methods to account for, or minimise, their influence on estimates of disease-relevant parameters. This review should assist researchers and practitioners to navigate the pitfalls of uncertainty in wildlife disease ecology studies.

Prior Precision, Prior Accuracy, and the Estimation of Disease Prevalence Using Imperfect Diagnostic Tests

Estimates of disease prevalence in any host population are complicated by uncertainty in the outcome of diagnostic tests on individuals. In the absence of gold standard diagnostics (tests that give neither false positives nor false negatives), Bayesian latent class inference can be applied to batteries of diagnostic tests, providing posterior estimates of the sensitivity and specificity of each test, alongside posterior estimates of disease prevalence. Here we explore the influence of precision and accuracy of prior information on the precision and accuracy of posterior estimates of these key parameters. Our simulations use three diagnostic tests, yielding eight possible diagnostic outcomes per individual. Seven degrees of freedom allow the estimation of seven parameters: sensitivity and specificity of each test, and disease prevalence. We show that prior precision begets posterior precision but only when priors are accurate. We also show that analyses without gold standard can use imprecise priors as long as they are initialised with accuracy. Imprecise priors risk the divergence of MCMC chains towards inaccurate posterior estimates, if inaccurate initial values are used. We note that inaccurate priors can yield inaccurate and imprecise inference. Bounded priors should certainly not be used unless their accuracy is well established. Inaccurate estimates of sensitivity or specificity can yield wildly inaccurate estimates of disease prevalence. Our analyses are motivated by studies of bovine tuberculosis in a wild badger population.

The Evolutionary Biology, Ecology and Epidemiology of Coccidia of Passerine Birds

Coccidia are intracellular parasites of the phylum Apicomplexa that cause a range of pathologies collectively termed coccidiosis. Species of coccidia of commercial importance have been well studied, with the effect of other species on passerine birds receiving increasing attention. In this chapter, we review the literature on coccidia in passerines, with a particular focus on wild populations. The taxonomy and life cycle of passerine coccidia are covered, as is their impact on the health of passerines, their epidemiology and their role in parasite-mediated natural and sexual selection. Coccidia can pose a significant threat to the health of wild passerine populations, and high rates of mortality have been observed in some studies. We examine some of the genetic factors that influence host resistance to coccidia and discuss how these parasites may be important in relation to sexually selected traits. General patterns are beginning to emerge with regard to the epidemiology of the parasites, and the influence of different aspects of the host's ecology on the prevalence and intensity of coccidia is being revealed. We examine these, as well exceptions, in addition to the phenomenon of diurnal oocyst shedding that can bias studies if not accounted for. Finally, we discuss potential future directions for research on coccidia in passerines and the importance of understanding parasite ecology in the management of threatened species.

Identification of spider-mite species and their endosymbionts using multiplex PCR

Spider mites of the genus Tetranychidae are severe crop pests. In the Mediterranean a few species coexist, but they are difficult to identify based on morphological characters. Additionally, spider mites often harbour several species of endosymbiotic bacteria, which may affect the biology of their hosts. Here, we propose novel, cost-effective, multiplex diagnostic methods allowing a quick identification of spider-mite species as well as of the endosymbionts they carry. First, we developed, and successfully multiplexed in a single PCR, primers to identify Tetranychus urticae, T. evansi and T. ludeni, some of the most common tetranychids found in southwest Europe. Moreover, we demonstrated that this method allows detecting multiple species in a single pool, even at low frequencies (up to 1/100), and can be used on entire mites without DNA extraction. Second, we developed another set of primers to detect spider-mite endosymbionts, namely Wolbachia, Cardinium and Rickettsia in a multiplex PCR, along with a generalist spider-mite primer to control for potential failure of DNA amplification in each PCR. Overall, our method represents a simple, cost-effective and reliable method to identify spider-mite species and their symbionts in natural field populations, as well as to detect contaminations in laboratory rearings. This method may easily be extended to other species.

Surveillance of vector-borne pathogens under imperfect detection: lessons from Chagas disease risk (mis)measurement

Vector-borne pathogens threaten human health worldwide. Despite their critical role in disease prevention, routine surveillance systems often rely on low-complexity pathogen detection tests of uncertain accuracy. In Chagas disease surveillance, optical microscopy (OM) is routinely used for detecting Trypanosoma cruzi in its vectors. Here, we use replicate T. cruzi detection data and hierarchical site-occupancy models to assess the reliability of OM-based T. cruzi surveillance while explicitly accounting for false-negative and false-positive results. We investigated 841 triatomines with OM slides (1194 fresh, 1192 Giemsa-stained) plus conventional (cPCR, 841 assays) and quantitative PCR (qPCR, 1682 assays). Detections were considered unambiguous only when parasitologists unmistakably identified T. cruzi in Giemsa-stained slides. qPCR was >99% sensitive and specific, whereas cPCR was ~100% specific but only ~55% sensitive. In routine surveillance, examination of a single OM slide per vector missed ~50–75% of infections and wrongly scored as infected ~7% of the bugs. qPCR-based and model-based infection frequency estimates were nearly three times higher, on average, than OM-based indices. We conclude that the risk of vector-borne Chagas disease may be substantially higher than routine surveillance data suggest. The hierarchical modelling approach we illustrate can help enhance vector-borne disease surveillance systems when pathogen detection is imperfect.

Assessment of Chronic Wasting Disease Prion Shedding in Deer Saliva with Occupancy Modeling

The detection of prions is difficult due to the peculiarity of the pathogen, which is a misfolded form of a normal protein. The specificity and sensitivity of detection methods are imperfect in complex samples, including in excreta. Here, we combined optimized prion amplification procedures with a statistical method that accounts for false-positive and false-negative errors to test deer saliva for chronic wasting disease (CWD) prions. This approach enabled us to discriminate the shedding of prions in saliva and the detection of prions in saliva-a distinction crucial to understanding the role of prion shedding in disease transmission and for diagnosis. We found that assay sensitivity and specificity were indeed imperfect, and we were able to draw several conclusions pertinent to CWD biology from our analyses: (i) the shedding of prions in saliva increases with time postinoculation, but is common throughout the preclinical phase of disease; (ii) the shedding propensity is influenced neither by sex nor by prion protein genotype at codon 96; and (iii) the source of prion-containing inoculum used to infect deer affects the likelihood of prion shedding in saliva; oral inoculation of deer with CWD-positive saliva resulted in 2.77 times the likelihood of prion shedding in saliva compared to that from inoculation with CWD-positive brain. These results are pertinent to horizontal CWD transmission in wild cervids. Moreover, the approach described is applicable to other diagnostic assays with imperfect detection.

Design- and model-based recommendations for detecting and quantifying an amphibian pathogen in environmental samples

Accurate pathogen detection is essential for developing management strategies to address emerging infectious diseases, an increasingly prominent threat to wildlife. Sampling for free‐living pathogens outside of their hosts has benefits for inference and study efficiency, but is still uncommon. We used a laboratory experiment to evaluate the influences of pathogen concentration, water type, and qPCR inhibitors on the detection and quantification of Batrachochytrium dendrobatidis (Bd) using water filtration. We compared results pre‐ and post‐inhibitor removal, and assessed inferential differences when single versus multiple samples were collected across space or time. We found that qPCR inhibition influenced both Bd detection and quantification in natural water samples, resulting in biased inferences about Bd occurrence and abundance. Biases in occurrence could be mitigated by collecting multiple samples in space or time, but biases in Bd quantification were persistent. Differences in Bd concentration resulted in variation in detection probability, indicating that occupancy modeling could be used to explore factors influencing heterogeneity in Bd abundance among samples, sites, or over time. Our work will influence the design of studies involving amphibian disease dynamics and studies utilizing environmental DNA (eDNA) to understand species distributions.

Higher risk of gastrointestinal parasite infection at lower elevation suggests possible constraints in the distributional niche of Alpine marmots

Alpine marmots Marmota marmota occupy a narrow altitudinal niche within high elevation alpine environments. For animals living at such high elevations where resources are limited, parasitism represents a potential major cost in life history. Using occupancy models, we tested if marmots living at higher elevation have a reduced risk of being infected with gastro-intestinal helminths, possibly compensating the lower availability of resources (shorter feeding season, longer snow cover and lower temperature) than marmots inhabiting lower elevations. Detection probability of eggs and oncospheres of two gastro-intestinal helminthic parasites, Ascaris laevis and Ctenotaenia marmotae, sampled in marmot feces, was used as a proxy of parasite abundance. As predicted, the models showed a negative relationship between elevation and parasite detectability (i.e. abundance) for both species, while there appeared to be a negative effect of solar radiance only for C. marmotae. Site-occupancy models are used here for the first time to model the constrains of gastrointestinal parasitism on a wild species and the relationship existing between endoparasites and environmental factors in a population of free-living animals. The results of this study suggest the future use of site-occupancy models as a viable tool to account for parasite imperfect detection in eco-parasitological studies, and give useful insights to further investigate the hypothesis of the contribution of parasite infection in constraining the altitudinal niche of Alpine marmots.

Modelling the range expansion of the Tiger mosquito in a Mediterranean Island accounting for imperfect detection

BACKGROUNDS

Aedes albopictus (Diptera; Culicidae) is a highly invasive mosquito species and a competent vector of several arboviral diseases that have spread rapidly throughout the world. Prevalence and patterns of dispersal of the mosquito are of central importance for an effective control of the species. We used site-occupancy models accounting for false negative detections to estimate the prevalence, the turnover, the movement pattern and the growth rate in the number of sites occupied by the mosquito in 17 localities throughout Mallorca Island.

RESULTS

Site-occupancy probability increased from 0.35 in the 2012, year of first reported observation of the species, to 0.89 in 2015. Despite a steady increase in mosquito presence, the extinction probability was generally high indicating a high turnover in the occupied sites. We considered two site-dependent covariates, namely the distance from the point of first observation and the estimated yearly occupancy rate in the neighborhood, as predicted by diffusion models. Results suggested that mosquito distribution during the first year was consistent with what predicted by simple diffusion models, but was not consistent with the diffusion model in subsequent years when it was similar to those expected from leapfrog dispersal events.

CONCLUSIONS

Assuming a single initial colonization event, the spread of Ae. albopictus in Mallorca followed two distinct phases, an early one consistent with diffusion movements and a second consistent with long distance, 'leapfrog', movements. The colonization of the island was fast, with ~90% of the sites estimated to be occupied 3 years after the colonization. The fast spread was likely to have occurred through vectors related to human mobility such as cars or other vehicles. Surveillance and management actions near the introduction point would only be effective during the early steps of the colonization.

Assessing respiratory pathogen communities in bighorn sheep populations: Sampling realities, challenges, and improvements

Respiratory disease has been a persistent problem for the recovery of bighorn sheep (Ovis canadensis), but has uncertain etiology. The disease has been attributed to several bacterial pathogens including Mycoplasma ovipneumoniae and Pasteurellaceae pathogens belonging to the Mannheimia, Bibersteinia, and Pasteurella genera. We estimated detection probability for these pathogens using protocols with diagnostic tests offered by a fee-for-service laboratory and not offered by a fee-for-service laboratory. We conducted 2861 diagnostic tests on swab samples collected from 476 bighorn sheep captured across Montana and Wyoming to gain inferences regarding detection probability, pathogen prevalence, and the power of different sampling methodologies to detect pathogens in bighorn sheep populations. Estimated detection probability using fee-for-service protocols was less than 0.50 for all Pasteurellaceae and 0.73 for Mycoplasma ovipneumoniae. Non-fee-for-service Pasteurellaceae protocols had higher detection probabilities, but no single protocol increased detection probability of all Pasteurellaceae pathogens to greater than 0.50. At least one protocol resulted in an estimated detection probability of 0.80 for each pathogen except Mannheimia haemolytica, for which the highest detection probability was 0.45. In general, the power to detect Pasteurellaceae pathogens at low prevalence in populations was low unless many animals were sampled or replicate samples were collected per animal. Imperfect detection also resulted in low precision when estimating prevalence for any pathogen. Low and variable detection probabilities for respiratory pathogens using live-sampling protocols may lead to inaccurate conclusions regarding pathogen community dynamics and causes of bighorn sheep respiratory disease epizootics. We recommend that agencies collect multiples samples per animal for Pasteurellaceae detection, and one sample for Mycoplasma ovipneumoniae detection from at least 30 individuals to reliably detect both Pasteurellaceae and Mycoplasma ovipneumoniae at the population-level. Availability of PCR diagnostic tests to wildlife management agencies would improve the ability to reliably detect Pasteurellaceae in bighorn sheep populations.

Prevalence and genetic diversity of blood parasite mixed infections in Spanish terrapins, Mauremys leprosa

Blood parasites such as haemogregarines and haemosporidians have been identified in almost all groups of vertebrates and may cause serious damages to their hosts. However, very little is known about biodiversity of these parasites and their effects on some groups of reptiles such as terrapins. Moreover, the information on virulence from blood parasites mixed infection is largely unknown in reptiles. With this aim, we investigated for the first time the prevalence and genetic diversity of blood parasites from one genus of haemoparasitic aplicomplexan (Hepatozoon) in two populations of Spanish terrapins (Mauremys leprosa), a semi-aquatic turtle from southwestern Europe with a vulnerable conservation status. We also examined the association between mixed blood parasite infection and indicators of health of terrapins (body condition, haematocrit values and immune response). Blood parasite infection with Hepatozoon spp was detected in 46·4% of 140 examined terrapins. The prevalence of blood parasites infection differed between populations. We found two different lineages of blood parasite, which have not been found in previous studies. Of the turtles with infection, 5·7% harboured mixed infection by the two lineages. There was no difference in body condition between uninfected, single-infected and mixed-infected turtles, but mixed-infected individuals had the lowest values of haematocrit, thus revealing the negative effects of blood parasite mixed infections. Immune response varied among terrapins with different infection status, where mixed infected individuals had higher immune response than uninfected or single-infected terrapins.

Estimating prevalence of avian haemosporidians in natural populations: a comparative study on screening protocols

Background

Birds harbour an astonishing diversity of haemosporidian parasites. Renewed interest in avian haemosporidians as a model system has placed a greater emphasis on the development of screening protocols to estimate parasite prevalence and diversity. Prevalence estimates are often based on the molecular or blood-smear microscopy techniques. However, variation in diagnostic sensitivity among screening methodologies represents a potential source of bias that may lead to erroneous inference in comparisons of prevalence across studies. Here, we analyzed a suite of blood samples for the presence of parasites using four diagnostic tools and compared method-specific estimates of detection probability to assess the relative performance of screening strategies.

Methods

We screened a total of 394 bird blood samples collected in India (n = 203) and Sweden (n = 191) for the combined presence of Plasmodium, Haemoproteus and Leucocytozoon with three PCR assays: (i) qPCR; (ii) restriction enzyme-based assay; and (iii) nested protocol. In addition, we examined blood smears for estimates of parasite intensity which was further screened using qPCR method to evaluate if parasite intensity shows a relationship with qPCR (Ct values). Furthermore, we used single infected samples from parasite intensities: low, medium, high, very high to establish the reproducibility in qPCR.

Results

For the combined data sets from India and Sweden, detection probability for submicroscopic and low intensity infections was highest for the qPCR method, followed by the nested protocol and the restriction enzyme-based assay. For high parasite intensities, the qPCR had high PCR reproducibility, with three out of three PCR replicates being positive and with consistent Ct values across all tenfold dilution series. For parasite intensities at very low and submicroscopic samples, the qPCR was reproducible in one out of the three replicates. The intensity of parasitemia estimated from smears showed inverse relationship with Ct values in both the Indian and Swedish data sets.

Conclusions

Our study highlights the importance of accounting for methodological issues to better estimate infection in parasitological studies and illustrates how a wider deployment of diagnostic tools combined with statistical approaches is needed for each study, in order to provide adequate insight into the most appropriate approach to avoid erroneous inferences.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-017-2066-z) contains supplementary material, which is available to authorized users.

Monitoring for the Management of Disease Risk in Animal Translocation Programmes

Monitoring is best viewed as a component of some larger programme focused on science or conservation. The value of monitoring is determined by the extent to which it informs the parent process. Animal translocation programmes are typically designed to augment or establish viable animal populations without changing the local community in any detrimental way. Such programmes seek to minimize disease risk to local wild animals, to translocated animals, and in some cases to humans. Disease monitoring can inform translocation decisions by (1) providing information for state-dependent decisions, (2) assessing progress towards programme objectives, and (3) permitting learning in order to make better decisions in the future. Here we discuss specific decisions that can be informed by both pre-release and post-release disease monitoring programmes. We specify state variables and vital rates needed to inform these decisions. We then discuss monitoring data and analytic methods that can be used to estimate these state variables and vital rates. Our discussion is necessarily general, but hopefully provides a basis for tailoring disease monitoring approaches to specific translocation programmes.

Multilevel Models for the Distribution of Hosts and Symbionts

Symbiont occurrence is influenced by host occurrence and vice versa, which leads to correlations in host-symbiont distributions at multiple levels. Interactions between co-infecting symbionts within host individuals can cause correlations in the abundance of two symbiont species across individual hosts. Similarly, interactions between symbiont transmission and host population dynamics can drive correlations between symbiont and host abundance across habitat patches. If ignored, these interactions can confound estimated responses of hosts and symbionts to other factors. Here, we present a general hierarchical modeling framework for distributions of hosts and symbionts, estimating correlations in host-symbiont distributions at the among-site, within-site, among-species, and among-individual levels. We present an empirical example from a multi-host multi-parasite system involving amphibians and their micro- and macroparasites. Amphibian hosts and their parasites were correlated at multiple levels of organization. Macroparasites often co-infected individual hosts, but rarely co-infected with the amphibian chytrid fungus. Such correlations may result from interactions among parasites and hosts, joint responses to environmental factors, or sampling bias. Joint host-symbiont models account for environmental constraints and species interactions while partitioning variance and dependence in abundance at multiple levels. This framework can be adapted to a wide variety of study systems and sampling designs.

Detection, prevalence, and transmission of avian hematozoa in waterfowl at the Arctic/sub-Arctic interface: co-infections, viral interactions, and sources of variation

BACKGROUND

The epidemiology of avian hematozoa at high latitudes is still not well understood, particularly in sub-Arctic and Arctic habitats, where information is limited regarding seasonality and range of transmission, co-infection dynamics with parasitic and viral agents, and possible fitness consequences of infection. Such information is important as climate warming may lead to northward expansion of hematozoa with unknown consequences to northern-breeding avian taxa, particularly populations that may be previously unexposed to blood parasites.

METHODS

We used molecular methods to screen blood samples and cloacal/oropharyngeal swabs collected from 1347 ducks of five species during May-August 2010, in interior Alaska, for the presence of hematozoa, Influenza A Virus (IAV), and IAV antibodies. Using models to account for imperfect detection of parasites, we estimated seasonal variation in prevalence of three parasite genera (Haemoproteus, Plasmodium, Leucocytozoon) and investigated how co-infection with parasites and viruses were related to the probability of infection.

RESULTS

We detected parasites from each hematozoan genus in adult and juvenile ducks of all species sampled. Seasonal patterns in detection and prevalence varied by parasite genus and species, age, and sex of duck hosts. The probabilities of infection for Haemoproteus and Leucocytozoon parasites were strongly positively correlated, but hematozoa infection was not correlated with IAV infection or serostatus. The probability of Haemoproteus infection was negatively related to body condition in juvenile ducks; relationships between Leucocytozoon infection and body condition varied among host species.

CONCLUSIONS

We present prevalence estimates for Haemoproteus, Leucocytozoon, and Plasmodium infections in waterfowl at the interface of the sub-Arctic and Arctic and provide evidence for local transmission of all three parasite genera. Variation in prevalence and molecular detection of hematozoa parasites in wild ducks is influenced by seasonal timing and a number of host traits. A positive correlation in co-infection of Leucocytozoon and Haemoproteus suggests that infection probability by parasites in one or both genera is enhanced by infection with the other, or that encounter rates of hosts and genus-specific vectors are correlated. Using size-adjusted mass as an index of host condition, we did not find evidence for strong deleterious consequences of hematozoa infection in wild ducks.