Performance of bovine genital campylobacteriosis diagnostic tests in bulls from Uruguay: a Bayesian latent class model approach.

The sensitivity (Se) and specificity (Sp) of three diagnostic tests for the detection of Campylobacter fetus venerealis (Cfv) using field samples were estimated using a Bayesian latent class model (BLCM), accounting for the absence of a gold standard. The tests included in this study were direct immunofluorescence antibody test (IFAT), polymerase chain reaction (PCR), and real-time PCR (RT-PCR). Twelve farms from two different populations were selected and bull prepuce samples were collected. The IFAT was performed according to the OIE Manual. The conventional PCR was performed as multiplex, targeting the gene nahE for C. fetus species identification and insertion element ISCfe1 for Cfv identification. The RT-PCR was performed as uniplex: one targeting the gene nahE for C. fetus and the other targeting the insertion ISCfe1 (ISC2) for Cfv. Results from the BLCM showed a median Se of 11.7% (Bayesian credibility interval (BCI): 1.93-29.79%), 53.7% (BCI: 23.1-95.0%), and 36.1% (BCI: 14.5-71.7%) for IFAT, PCR, and RT-PCR respectively. The Sp were 94.5% (BCI: 90.1-97.9%), 97.0% (BCI: 92.9-99.3%), and 98.4% (BCI: 95.3-99.7%) for IFAT, PCR, and RT-PCR respectively. The correlation between PCR and RT-PCR was positive and low in samples from both sampled population (0.63% vs 8.47%). These results suggest that diagnostic sensitivity of the studied tests is lower using field samples than using pure Cfv strains.

Capturing and analysing heterogeneity in residential greywater reuse preferences using a latent class model.

To legally permit greywater reuse as a management strategy, it is necessary to establish allowed uses, as well as guarantee legitimacy, safety and maintain public trust. Cities with previous experience in greywater reuse have reconfigured their regulations according to their own evidence with decentralized water reuse systems. This has allowed them to encourage or restrict certain indoor uses of treated greywater. However, cities starting to use these residential schemes lack the experience to reconfigure their water and sanitation regulation, and thus need "blindly" decide on the type of greywater uses to allow in order to achieve a balance between users' acceptability and avoiding public health problems. In this research, we analyse hypothetical situations of greywater reuse based on real evidence related to decentralized water systems. The main objective of this study is to evaluate the heterogeneity of individuals' preferences regarding residential greywater reuse for six intended indoor uses, using stated choice experiments and a latent class model. Hence, we obtain preliminary evidence about the direction that the regulation or pilot tests should take. We use the context of Santiago (Chile) as a reference, where although allowed, greywater reuse is not taking place widely. Our results show that survey respondents can be classified into four classes (enthusiasts, greywater sceptics, appearance conscious and water expenditure conscious), according to the preferences for the different types of indoor greywater reuse and the appearance of the treated greywater. From a policy perspective, our results show differences across classes as a function of socioeconomic characteristics and previous greywater reuse knowledge, as well as wider household characteristics, including the presence of sensitive individuals (under 15 and over 74 years old), number of residents, number of sanitary devices, and location and type of garden.

Bayesian estimation of diagnostic sensitivity and specificity of a qPCR and a bacteriological culture method for Piscirickettsia salmonis in farmed Atlantic salmon (Salmo salar L.) in Chile.

Early detection of piscirickettsiosis is an important purpose of government- and industry-based surveillance for the disease in Atlantic salmon farms in Chile. Real-time qPCRs are currently used for surveillance because bacterial isolation is inadequately sensitive or rapid enough for routine use. Since no perfect tests exist, we used Bayesian latent class models to estimate diagnostic sensitivity (DSe) and specificity (DSp) of qPCR and culture using separate two-test, single-population models for three farms (n = 148, 151, 44). Informative priors were used for DSp (culture (beta(999,1); qPCR (beta(98,2)), and flat priors (beta 1,1) for DSe and prevalence. Models were run for liver and kidney tissues combined and separately, based on the presence of selected gross-pathological signs. Across all models, qPCR DSe was 5- to 30-fold greater than for culture. Combined-tissue qPCR median DSe was highest in Farm 3 (sampled during P. salmonis outbreak (DSe = 97.6%)) versus Farm 1 (DSe = 85.6%) or Farm 2 (DSe = 83.5%), both sampled before clinical disease. Median DSe of qPCR was similar for liver and kidney, but higher when gross-pathological signs were evident at necropsy. High DSe and DSp and rapid turnaround-time indicate that the qPCR is fit for surveillance programmes and diagnosis during an outbreak. Targeted testing of salmon with gross-pathological signs can enhance DSe.

Farmers' Preferences for PES Contracts to Adopt Silvopastoral Systems in Southern Ecuador, Revealed Through a Choice Experiment.

This study investigates farmers' preferences to participate in payment contracts to adopt silvopastoral systems in Ecuador. A choice experiment was used to elicit preferences between different contract attributes, including differing payment amounts and land management requirements. The research was carried out in the buffer zone of Podocarpus National Park in Southern Ecuador, an area where most land is dedicated to cattle husbandry. A choice experiment was conducted to measure farmers' interest in different types of contracts. Based on existing incentive programs, contract choices varied with respect to the type of silvopastoral system, extra land-use requirements, payment levels and contract duration. In addition, contracts differed with regards to access by cattle to streams. Although the farmers did not show strong preferences for every contract attribute, the majority of farmers in the area showed interest in the proposed contracts. A latent class model identified three classes of respondents, based on their preferences for different contracts attributes or the "business as usual" option. The results suggest that farmland area, agricultural income, and landowners' perceptions of environmental problems provide a partial explanation for the heterogeneity observed in the choices for specific contracts. Participation might increase if contracts were targeted at specific groups of farmers, such as those identified through our latent class model. Offering flexible contracts with varying additional requirements within the same scheme, involving farmers from the start in payments for environmental services design, and combining payments for environmental services with integrated conservation and development projects may be a better way to convince more farmers to adopt silvopastoral systems.

A Bayesian approach to model the conditional correlation between several diagnostic tests and various replicated subjects measurements.

Two key aims of diagnostic research are to accurately and precisely estimate disease prevalence and test sensitivity and specificity. Latent class models have been proposed that consider the correlation between subject measures determined by different tests in order to diagnose diseases for which gold standard tests are not available. In some clinical studies, several measures of the same subject are made with the same test under the same conditions (replicated measurements), and thus, replicated measurements for each subject are not independent. In the present study, we propose an extension of the Bayesian latent class Gaussian random effects model to fit the data with binary outcomes for tests with replicated subject measures. We describe an application using data collected on hookworm infection carried out in the municipality of Presidente Figueiredo, Amazonas State, Brazil. In addition, the performance of the proposed model was compared with that of current models (the subject random effects model and the conditional (in)dependent model) through a simulation study. As expected, the proposed model presented better accuracy and precision in the estimations of prevalence, sensitivity and specificity. Copyright © 2017 John Wiley & Sons, Ltd.

Prevalence of tuberculosis infection in healthcare workers of the public hospital network in Medellín, Colombia: a Bayesian approach.

A latent tuberculosis infection (LTBI) prevalence survey was conducted using tuberculin skin test (TST) and Quantiferon test (QFT) in 1218 healthcare workers (HCWs) in Medellín, Colombia. In order to improve the prevalence estimates, a latent class model was built using a Bayesian approach with informative priors on the sensitivity and specificity of the TST. The proportion of concordant results (TST+,QFT+) was 41% and the discordant results contributed 27%. The marginal estimate of the prevalence P(LTBI+) was 62·1% [95% credible interval (CrI) 53·0-68·2]. The probability of LTBI+ given positive results for both tests was 99·6% (95% CrI 98·1-99·9). Sensitivity was 88·5 for TST and 74·3 for QFT, and specificity was 87·8 for TST and 97·6 for QFT. A high LTBI prevalence was found in HCWs with time-accumulated exposure in hospitals that lack control plans. In a context of intermediate tuberculosis (TB) incidence it is recommended to use only one test (either QFT or TST) in prevalence surveys or as pre-employment tests. Results will be useful to help implement TB infection control plans in hospitals where HCWs may be repeatedly exposed to unnoticed TB patients, and to inform the design of TB control policies.

Using a systematic approach to select flagship species for bird conservation.

Conservation marketing campaigns that focus on flagship species play a vital role in biological diversity conservation because they raise funds and change people's behavior. However, most flagship species are selected without considering the target audience of the campaign, which can hamper the campaign's effectiveness. To address this problem, we used a systematic and stakeholder-driven approach to select flagship species for a conservation campaign in the Serra do Urubu in northeastern Brazil. We based our techniques on environmental economic and marketing methods. We used choice experiments to examine the species attributes that drive preference and latent-class models to segment respondents into groups by preferences and socioeconomic characteristics. We used respondent preferences and information on bird species inhabiting the Serra do Urubu to calculate a flagship species suitability score. We also asked respondents to indicate their favorite species from a set list to enable comparison between methods. The species' traits that drove audience preference were geographic distribution, population size, visibility, attractiveness, and survival in captivity. However, the importance of these factors differed among groups and groups differed in their views on whether species with small populations and the ability to survive in captivity should be prioritized. The popularity rankings of species differed between approaches, a result that was probably related to the different ways in which the 2 methods measured preference. Our new approach is a transparent and evidence-based method that can be used to refine the way stakeholders are engaged in the design of conservation marketing campaigns.