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

ABSTRACT: 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.

SUBMITTER: Paterson JT

PROVIDER: S-EPMC7478830 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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

Paterson J Terrill JT Butler Carson C Garrott Robert R Proffitt Kelly K

PloS one 20200908 9

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 the ...[more]

PMID: 32898140

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Project description:Respiratory disease caused by Mycoplasma ovipneumoniae and Pasteurellaceae poses a formidable challenge for bighorn sheep (Ovis canadensis) conservation. All-age epizootics can cause 10-90% mortality and are typically followed by multiple years of enzootic disease in lambs that hinders post-epizootic recovery of populations. The relative frequencies at which these epizootics are caused by the introduction of novel pathogens or expression of historic pathogens that have become resident in the populations is unknown. Our primary objectives were to determine how commonly the pathogens associated with respiratory disease are hosted by bighorn sheep populations and assess demographic characteristics of populations with respect to the presence of different pathogens. We sampled 22 bighorn sheep populations across Montana and Wyoming, USA for Mycoplasma ovipneumoniae and Pasteurellaceae and used data from management agencies to characterize the disease history and demographics of these populations. We tested for associations between lamb:ewe ratios and the presence of different respiratory pathogen species. All study populations hosted Pasteurellaceae and 17 (77%) hosted Mycoplasma ovipneumoniae. Average lamb:ewe ratios for individual populations where both Mycoplasma ovipneumoniae and Pasteurellaceae were detected ranged from 0.14 to 0.40. However, average lamb:ewe ratios were higher in populations where Mycoplasma ovipneumoniae was not detected (0.37, 95% CI: 0.27-0.51) than in populations where it was detected (0.25, 95% CI: 0.21-0.30). These findings suggest that respiratory pathogens are commonly hosted by bighorn sheep populations and often reduce recruitment rates; however ecological factors may interact with the pathogens to determine population-level effects. Elucidation of such factors could provide insights for management approaches that alleviate the effects of respiratory pathogens in bighorn sheep. Nevertheless, minimizing the introduction of novel pathogens from domestic sheep and goats remains imperative to bighorn sheep conservation.

Project description: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.

Project description:Managing water (e.g., catchments) to increase the abundance and distribution of game is popular in arid regions, especially throughout the southwest United States, where biologists often manage water year-round for desert bighorn sheep (Ovis canadensis nelsoni). Bighorn may visit water when predators (e.g., mountain lions [Puma concolor], coyotes [Canis latrans]) do not, suggesting that differences in species ecology or their surface water requirements influence visit timing. Alternatively, visits by desert bighorn sheep and predators may align. The former outcome identifies opportunities to improve water management by providing water when desert bighorn sheep visit most, which hypothetically may reduce predator presence, range expansion and predation, thereby supporting objectives to increase sheep abundances. Since advancing water management hinges on understanding the patterns of species visits, we identified when these three species and mule deer (Odocoileus hemionus) visited managed waters in three North American deserts (Chihuahuan, Sonoran, Mojave). We unraveled the ecological basis describing why visits occurred by associating species visits with four weather variables using multi-site, multi-species models within a Bayesian hierarchical framework (3.4 million images; 105 locations; 7/2009-12/2016). Desert bighorn sheep concentrated visits to water within 4-5 contiguous months. Mountain lions visited water essentially year-round within all deserts. Higher maximum temperature influenced visits to water, especially for desert bighorn sheep. Less long-term precipitation (prior 6-week total) raised visits for all species, and influenced mountain lion visits 3-20 times more than mule deer and 3-37 times more than sheep visits. Visits to water by prey were inconsistent predictors of visits to water by mountain lions. Our results suggest improvements to water management by aligning water provision with the patterns and ecological explanations of desert bighorn sheep visits. We exemplify a scientific approach to water management for enhancing stewardship of desert mammals, be it the southwest United States or arid regions elsewhere.

Dataset Information

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

Publications

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

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