[Show abstract][Hide abstract] ABSTRACT: We developed models and provide computer code to make carcass recovery data more useful to wildlife managers. With these tools, wildlife managers can understand the spatial, temporal (e.g., across time periods, seasons), and demographic patterns in mortality causes from carcass recovery datasets. From datasets of radio-collared and non-collared carcasses, managers can calculate the detection bias by mortality cause in a non-collared carcass dataset compared to a collared carcass dataset. As a first step, we provide a standard procedure to assign mortality causes to carcasses. We provide an example of these methods for radio-collared wolves (n ¼ 208) and non-collared wolves (n ¼ 668) found dead in Wisconsin (1979–2012). We analyzed differences in mortality cause relative to season, age and sex classes, wolf harvest zones, and recovery phase (1979–1995: initial recovery, 1996–2002: early growth, 2003–2012: late growth). Seasonally, illegal kills and natural deaths were proportionally higher in winter (Oct–Mar) than summer (Apr–Sep) for collared wolves, whereas vehicle strikes and legal kills were higher in summer than winter. Spatially, more illegally killed collared wolves occurred in eastern wolf harvest zones where wolves reestablished more slowly and in the central forest region where optimal habitat is isolated by agriculture. Natural mortalities of collared wolves (e.g., disease, intraspecific strife, or starvation) were highest in western wolf harvest zones where wolves established earlier and existed at higher densities. Calculating detection bias in the non-collared dataset revealed that more than half of the non-collared carcasses on the landscape are not found. The lowest detection probabilities for non-collared carcasses (0.113–0.176) occurred in winter for natural, illegal, and unknown mortality causes. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
[Show abstract][Hide abstract] ABSTRACT: Understanding the seasonal timing of disease transmission can lead to more effective control strategies, but the seasonality of transmission is often unknown for pathogens transmitted directly. We inserted vaginal implant transmitters (VITs) in 575 elk (Cervus elaphus canadensis) from 2006 to 2014 to assess when reproductive failures (i.e., abortions or still births) occur, which is the primary transmission route of Brucella abortus, the causative agent of brucellosis in the Greater Yellowstone Ecosystem. Using a survival analysis framework, we developed a Bayesian hierarchical model that simultaneously estimated the total baseline hazard of a reproductive event as well as its 2 mutually exclusive parts (abortions or live births). Approximately, 16% (95% CI = 0.10, 0.23) of the pregnant seropositive elk had reproductive failures, whereas 2% (95% CI = 0.01, 0.04) of the seronegative elk had probable abortions. Reproductive failures could have occurred as early as 13 February and as late as 10 July, peaking from March through May. Model results suggest that less than 5% of likely abortions occurred after 6 June each year and abortions were approximately 5 times more likely in March, April, or May compared to February or June. In western Wyoming, supplemental feeding of elk begins in December and ends during the peak of elk abortions and brucellosis transmission (i.e., Mar and Apr). Years with more snow may enhance elk-to-elk transmission on supplemental feeding areas because elk are artificially aggregated for the majority of the transmission season. Elk-to-cattle transmission will depend on the transmission period relative to the end of the supplemental feeding season, elk seroprevalence, population size, and the amount of commingling. Our statistical approach allowed us to estimate the probability density function of different event types over time, which may be applicable to other cause-specific survival analyses. It is often challenging to assess the cause of death, or in this case whether the reproductive event was an abortion or live birth. Accounting for uncertainty in the event type is an important future addition to our methodological approach. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.
[Show abstract][Hide abstract] ABSTRACT: Meadow voles (Microtus pennsylvanicus) are permissive to chronic wasting disease (CWD) infection, but their susceptibility to other transmissible spongiform encephalopathies (TSEs) is poorly characterized. In this initial study, we intracerebrally challenged 6 meadow voles with 2 isolates of sheep scrapie. Three meadow voles acquired a TSE after the scrapie challenge and an extended incubation period. The glycoform profile of proteinase K-resistant prion protein (PrPres) in scrapie-sick voles remained similar to the sheep inocula, but differed from that of voles clinically affected by CWD. Vacuolization patterns and disease-associated prion protein (PrPSc) deposition were generally similar in all scrapie-affected voles, except in the hippocampus, where PrPSc staining varied markedly among the animals. Our results demonstrate that meadow voles can acquire a TSE after intracerebral scrapie challenge and that this species could therefore prove useful for characterizing scrapie isolates.
Canadian journal of veterinary research = Revue canadienne de recherche vétérinaire 02/2015; 79(1):68. · 1.02 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Event-time or continuous-time statistical approaches have been applied throughout the biostatistical literature and have led to numerous scientific advances. However, these techniques have traditionally relied on knowing failure times. This has limited application of these analyses, particularly, within the ecological field where fates of marked animals may be unknown. To address these limitations, we developed an integrated approach within a Bayesian framework to estimate hazard rates in the face of unknown fates. We combine failure/survival times from individuals whose fates are known and times of which are interval-censored with information from those whose fates are unknown, and model the process of detecting animals with unknown fates. This provides the foundation for our integrated model and permits necessary parameter estimation. We provide the Bayesian model, its derivation, and use simulation techniques to investigate the properties and performance of our approach under several scenarios. Lastly, we apply our estimation technique using a piece-wise constant hazard function to investigate the effects of year, age, chick size and sex, sex of the tending adult, and nesting habitat on mortality hazard rates of the endangered mountain plover (Charadrius montanus) chicks. Traditional models were inappropriate for this analysis because fates of some individual chicks were unknown due to failed radio transmitters. Simulations revealed biases of posterior mean estimates were minimal (≤ 4.95%), and posterior distributions behaved as expected with RMSE of the estimates decreasing as sample sizes, detection probability, and survival increased. We determined mortality hazard rates for plover chicks were highest at <5 days old and were lower for chicks with larger birth weights and/or whose nest was within agricultural habitats. Based on its performance, our approach greatly expands the range of problems for which event-time analyses can be used by eliminating the need for having completely known fate data.
Ecology and Evolution 02/2015; 5(3). DOI:10.1002/ece3.1399 · 2.32 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: There are numerous situations in which it is important to determine whether a particular disease of interest is present in a free-ranging wildlife population. However adequate disease surveillance can be labor-intensive and expensive and thus there is substantial motivation to conduct it as efficiently as possible. Surveillance is often based on the assumption of a simple random sample, but this can almost always be improved upon if there is auxiliary information available about disease risk factors. We present a Bayesian approach to disease surveillance when auxiliary risk information is available which will usually allow for substantial improvements over simple random sampling. Others have employed risk weights in surveillance, but this can result in overly optimistic statements regarding freedom from disease due to not accounting for the uncertainty in the auxiliary information; our approach remedies this. We compare our Bayesian approach to a published example of risk weights applied to chronic wasting disease in deer in Colorado, and we also present calculations to examine when uncertainty in the auxiliary information has a serious impact on the risk weights approach. Our approach allows "apples-to-apples" comparisons of surveillance efficiencies between units where heterogeneous samples were collected.
PLoS ONE 03/2014; 9(3):e89843. DOI:10.1371/journal.pone.0089843 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This article describes a method for quantifying blood flow distribution among lung alveoli. Our method is based on analysis of trapping patterns of small diameter (4 μm) fluorescent latex particles infused into lung capillaries. Trapping patterns are imaged using confocal microscopy, and the images are analyzed statistically using SAS subroutines. The resulting plots provide a quantifiable way of assessing interalveolar perfusion distribution in a way that has not previously been possible. Methods for using this technique are described, and the SAS routines are included. This technique can be an important tool for learning how this critical vascular bed performs in health and disease.
[Show abstract][Hide abstract] ABSTRACT: Rapid antemortem tests to detect individuals with transmissible spongiform encephalopathies (TSE) would contribute to public health. We investigated a technique known as protein misfolding cyclic amplification (PMCA) to amplify abnormal prion protein (PrP(TSE)) from highly diluted variant Creutzfeldt-Jakob disease (vCJD)-infected human and macaque brain homogenates, seeking to improve the rapid detection of PrP(TSE) in tissues and blood. Macaque vCJD PrP(TSE) did not amplify using normal macaque brain homogenate as substrate (intraspecies PMCA). Next, we tested interspecies PMCA with normal brain homogenate of the southern red-backed vole (RBV), a close relative of the bank vole, seeded with macaque vCJD PrP(TSE). The RBV has a natural polymorphism at residue 170 of the PrP-encoding gene (N/N, S/S, and S/N). We investigated the effect of this polymorphism on amplification of human and macaque vCJD PrP(TSE). Meadow vole brain (170N/N PrP genotype) was also included in the panel of substrates tested. Both humans and macaques have the same 170S/S PrP genotype. Macaque PrP(TSE) was best amplified with RBV 170S/S brain, although 170N/N and 170S/N were also competent substrates, while meadow vole brain was a poor substrate. In contrast, human PrP(TSE) demonstrated a striking narrow selectivity for PMCA substrate and was successfully amplified only with RBV 170S/S brain. These observations suggest that macaque PrP(TSE) was more permissive than human PrP(TSE) in selecting the competent RBV substrate. RBV 170S/S brain was used to assess the sensitivity of PMCA with PrP(TSE) from brains of humans and macaques with vCJD. PrP(TSE) signals were reproducibly detected by Western blot in dilutions through 10(-12) of vCJD-infected 10% brain homogenates. This is the first report showing PrP(TSE) from vCJD-infected human and macaque brains efficiently amplified with RBV brain as the substrate. Based on our estimates, PMCA showed a sensitivity that might be sufficient to detect PrP(TSE) in vCJD-infected human and macaque blood.
PLoS ONE 10/2013; 8(10):e78710. DOI:10.1371/journal.pone.0078710 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Many ecological and epidemiological studies occur in systems with mobile individuals and heterogeneous landscapes. Using a simulation model, we show that the accuracy of inferring an underlying biological process from observational data depends on movement and spatial scale of the analysis. As an example, we focused on estimating the relationship between host density and pathogen transmission. Observational data can result in highly biased inference about the underlying process when individuals move among sampling areas. Even without sampling error, the effect of host density on disease transmission is underestimated by approximately 50 % when one in ten hosts move among sampling areas per lifetime. Aggregating data across larger regions causes minimal bias when host movement is low, and results in less biased inference when movement rates are high. However, increasing data aggregation reduces the observed spatial variation, which would lead to the misperception that a spatially targeted control effort may not be very effective. In addition, averaging over the local heterogeneity will result in underestimating the importance of spatial covariates. Minimizing the bias due to movement is not just about choosing the best spatial scale for analysis, but also about reducing the error associated with using the sampling location as a proxy for an individual’s spatial history. This error associated with the exposure covariate can be reduced by choosing sampling regions with less movement, including longitudinal information of individuals’ movements, or reducing the window of exposure by using repeated sampling or younger individuals.
[Show abstract][Hide abstract] ABSTRACT: Recent technological advances, such as proximity loggers, allow researchers to collect complete interaction histories, day and night, among sampled individuals over several months to years. Social network analyses are an obvious approach to analyzing interaction data because of their flexibility for fitting many different social structures as well as the ability to assess both direct contacts and indirect associations via intermediaries. For many network properties, however, it is not clear whether estimates based upon a sample of the network are reflective of the entire network. In wildlife applications, networks may be poorly sampled and boundary effects will be common. We present an alternative approach that utilizes a hierarchical modeling framework to assess the individual, dyadic, and environmental factors contributing to variation in interaction rates and allows us to estimate the underlying process variation in each. In a disease control context, this approach will allow managers to focus efforts on those types of individuals and environments that contribute the most towards super-spreading events. We account for the sampling distribution of proximity loggers and the non-independence of contacts among groups by only using contact data within a group during days when the group membership of proximity loggers was known. This allows us to separate the two mechanisms responsible for a pair not contacting one another: they were not in the same group or they were in the same group but did not come within the specified contact distance. We illustrate our approach with an example dataset of female elk from northwestern Wyoming and conclude with a number of important future research directions.
Methods in Ecology and Evolution 12/2012; 66(10):1437-1447. DOI:10.1007/s00265-012-1376-6 · 6.55 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Historically, avian influenza viruses have been isolated from cloacal swab specimens, but recent data suggest that the highly pathogenic avian influenza (HPAI) H5N1 virus can be better detected from respiratory tract specimens. To better understand how swab sample type affects the detection ability of low pathogenic avian influenza (LPAI) viruses we collected and tested four swab types: oropharyngeal swabs (OS), cloacal swabs (CS), the two swab types combined in the laboratory (LCS), and the two swab types combined in the field (FCS). A total of 1968 wild waterfowl were sampled by each of these four methods and tested for avian influenza virus using matrix gene reverse-transcription (RT)-PCR. The highest detection rate occurred with the FCS (4.3%) followed by the CS (4.0%). Although this difference did not achieve traditional statistical significance, Bayesian analysis indicated that FCS was superior to CS with an 82% probability. The detection rates for both the LCS (2.4%) and the OS (0.4%) were significantly different from the FCS. In addition, every swab type that was matrix RT-PCR positive was also tested for recovery of viable influenza virus. This protocol reduced the detection rate, but the ordering of swab types remained the same: 1.73% FCS, 1.42% CS, 0.81% LCS, and 0% OS. Our data suggest that the FCS performed at least as well as any other swab type for detecting LPAI viruses in the wild ducks tested. When considering recent studies showing that HPAI H5N1 can be better detected in the respiratory tract, the FCS is the most appropriate sample to collect for HPAI H5N1 surveillance while not compromising LPAI studies.
[Show abstract][Hide abstract] ABSTRACT: Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy (TSE) of cervids now detected in 19 states of the United States, three Canadian provinces, and South Korea. Whether noncervid species can be infected by CWD and thereby serve as reservoirs for the infection is not known. To investigate this issue, we previously used serial protein misfolding cyclic amplification (sPMCA) to demonstrate that CWD prions can amplify in brain homogenates from several species sympatric with cervids, including prairie voles (Microtus ochrogaster) and field mice (Peromyscus spp.). Here, we show that prairie voles are susceptible to mule deer CWD prions in vivo and that sPMCA amplification of CWD prions in vole brain enhances the infectivity of CWD for this species. Prairie voles inoculated with sPMCA products developed clinical signs of TSE disease approximately 300 days prior to, and more consistently than, those inoculated with CWD prions from deer brain. Moreover, the deposition patterns and biochemical properties of protease-resistant form of PrP (PrP(RES)) in the brains of affected voles differed from those in cervidized transgenic (CerPrP) mice infected with CWD. In addition, voles inoculated orally with sPMCA products developed clinical signs of TSE and were positive for PrP(RES) deposition, whereas those inoculated orally with deer-origin CWD prions did not. These results demonstrate that transspecies sPMCA of CWD prions can enhance the infectivity and adapt the host range of CWD prions and thereby may be useful to assess determinants of prion species barriers.
Journal of Virology 06/2011; 85(17):8528-37. DOI:10.1128/JVI.00809-11 · 4.44 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Chronic wasting disease (CWD) is a fatal disease of deer, elk, and moose transmitted through direct, animal-to-animal contact, and indirectly, via environmental contamination. Considerable attention has been paid to modeling direct transmission, but despite the fact that CWD prions can remain infectious in the environment for years, relatively little information exists about the potential effects of indirect transmission on CWD dynamics. In the present study, we use simulation models to demonstrate how indirect transmission and the duration of environmental prion persistence may affect epidemics of CWD and populations of North American deer. Existing data from Colorado, Wyoming, and Wisconsin's CWD epidemics were used to define plausible short-term outcomes and associated parameter spaces. Resulting long-term outcomes range from relatively low disease prevalence and limited host-population decline to host-population collapse and extinction. Our models suggest that disease prevalence and the severity of population decline is driven by the duration that prions remain infectious in the environment. Despite relatively low epidemic growth rates, the basic reproductive number, R(0), may be much larger than expected under the direct-transmission paradigm because the infectious period can vastly exceed the host's life span. High prion persistence is expected to lead to an increasing environmental pool of prions during the early phases (i.e. approximately during the first 50 years) of the epidemic. As a consequence, over this period of time, disease dynamics will become more heavily influenced by indirect transmission, which may explain some of the observed regional differences in age and sex-specific disease patterns. This suggests management interventions, such as culling or vaccination, will become increasingly less effective as CWD epidemics progress.
PLoS ONE 05/2011; 6(5):e19896. DOI:10.1371/journal.pone.0019896 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We monitored trends in urea nitrogen: creatinine (UN:C), cortisol:creatinine (Co:C), and allantoin:creatinine (A:C) ratios of snow-urine samples from 5 free-ranging female elk (Cervus elaphus) in Yellowstone National Park over a three-winter period to determine their potential as indices of nutrition or nutritional stress. UN:C ratios indicated that elk were nutritionally deprived during winter, but values did not vary significantly among winters despite interannual differences in winter severity inferred from snowpack measurements and declines in calf:cow ratios. The UN:C ratio appears to be an insensitive indicator of nutritional stress over a wide range of nutritional conditions. Co:C ratios demonstrated a significantly different linear trend during each winter, but we were unable to interpret these trends because they were not related to interannual differences in indices of nutritional stress. A:C ratios demonstrated a consistent, seasonal, parabolic pattern of nutrition, with lower values occurring in midwinter and higher values in December and April. There was also a significant year effect, with lower values occurring during the hardest winter and higher values during the mildest winter. Hence, trends in A:C ratios were sensitive, interpretable, and consistent with variations in winter severity and digestible energy intake, suggesting that this metabolite warrants further scrutiny.
Canadian Journal of Zoology 02/2011; 75(10):1687-1694. DOI:10.1139/z97-795 · 1.30 Impact Factor