scholarly journals Bayesian Estimation of the Prevalence and Test Characteristics (Sensitivity and Specificity) of Two Serological Tests (RB and SAT-EDTA) for the Diagnosis of Bovine Brucellosis in Small and Medium Cattle Holders in Ecuador

2021 ◽  
Vol 9 (9) ◽  
pp. 1815
Author(s):  
Valeria Paucar ◽  
Jorge Ron-Román ◽  
Washington Benítez-Ortiz ◽  
Maritza Celi ◽  
Dirk Berkvens ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Deviance Information Criterion ◽  
Coastal Region ◽  
Information Criterion ◽  
Herd Size ◽  
Screening Tests ◽  
Bovine Brucellosis ◽  
Serological Tests ◽  
Animal Blood ◽  
True Prevalence

In Ecuador, a national program for bovine brucellosis control has been in implementation since 2008. Given the costs, small- and medium-sized livestock holders are not completely committed to it. The objective of this study was to determine true prevalence (TP) of bovine brucellosis in small- and medium-sized herd populations, as well as the diagnostic sensitivity and specificity of the Rose Bengal (RB) test and the sero-agglutination test (SAT)-EDTA using a Bayesian approach. Between 2011 and 2016, 2733 cattle herds were visited, and 22,592 animal blood samples were taken in nineteen provinces on mainland Ecuador. Bayes-p and deviance information criterion (DIC) statistics were used to select models. Additionally, risk-factor analysis was used for herds according to their brucellosis test status. True prevalence (TP) in herds was estimated by pool testing. National seroprevalence of farms was 7.9% (95% CI: 6.79–9.03), and TP was 12.2% (95% CI: 7.8–17.9). Apparent prevalence (AP) in animals was 2.2% (95% CI: 1.82–2.67), and TP was 1.6% (95% CrI: 1.0–2.4). Similarly, the sensitivity of the RB was estimated at 64.6% (95% CrI: 42.6–85.3) and specificity at 98.9% (95% CrI: 98.6–99.0); for the SAT-EDTA test, sensitivity was 62.3% (95% CrI: 40.0–84.8) and 98.9% (95% CrI: 98.6–99.1) for specificity. Results of the two tests were highly correlated in infected and uninfected animals. Likewise, high spatial variation was observed, with the Coastal Region being the zone with the highest TP at 2.5%. (95% CrI: 1.3–3.8%) in individual animals and 28.2% (95% CI: 15.7–39.8) in herds. Risk factors include herd size, type of production (milk, beef, and mixed), abortions recorded, and vaccination. The results of this study serve to guide authorities to make decisions based on parallel testing at the beginning of a bovine brucellosis program for small livestock holders to increase sensitivity level of the screening tests in Ecuador.

scholarly journals Examination of sensitivity and specificity of some serological tests in diagnostics of bovine brucellosis

2008 ◽  
Vol 58 (5-6) ◽  
pp. 467-476 ◽  
Author(s):  
Matovic Kazimir ◽  
Asanin Ruzica ◽  
Radojicic Sonja ◽  
Lako B. ◽  
Zarkovic A.
Keyword(s):  
Sensitivity And Specificity ◽  
Bovine Brucellosis ◽  
Serological Tests

scholarly journals Latent class regression models for simultaneously estimating test accuracy, true prevalence and risk factors for Brucella abortus

2016 ◽  
Vol 144 (9) ◽  
pp. 1845-1856 ◽  
Author(s):  
A. CAMPE ◽  
D. ABERNETHY ◽  
F. MENZIES ◽  
M. GREINER
Keyword(s):  
Risk Factors ◽  
Brucella Abortus ◽  
Latent Class ◽  
Screening Tests ◽  
Test Accuracy ◽  
Serological Tests ◽  
Cross Sectional ◽  
Predictive Values ◽  
True Prevalence ◽  
Study Population

SUMMARYIn 2003/2004 a field trial was conducted in Northern Ireland to assess the diagnostic accuracy of six serological tests for bovine brucellosis caused by Brucella abortus. Whereas between-test comparisons have been used to calculate test performances so far, the present study used a latent class approach to estimate diagnostic test accuracy parameters in the absence of a gold standard for these six tests simultaneously and to estimate the true prevalence, while accounting for clustering in the study population and risk factors for true prevalence. Results obtained in this study with regard to prevalence, sensitivity and specificity were largely in accordance with previous findings. Screening tests (SAT and EDTA) appeared to be the most sensitive; however, at low prevalences the EDTA and CFT showed the highest positive predictive values of all investigated tests. The specificities and negative predictive values of all diagnostic tests were found to be very high. Differences of prevalence between three groups of the study population with different risk of exposure could be attributed to the mode of sampling indicating that a more risk-based sampling will result in a higher prevalence than a cross-sectional sampling mode. Age, dairy status and history of abortion were shown to influence the prediction of the latent true infection status.

scholarly journals Use of Bayesian Markov Chain Monte Carlo Methods to Model Kuwait Medical Genetic Center Data: An Application to Down Syndrome and Mental Retardation

Mathematics ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 248
Author(s):  
Reem Aljarallah ◽  
Samer A Kharroubi
Keyword(s):  
Monte Carlo ◽  
Down Syndrome ◽  
Mental Retardation ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Univariate Analysis ◽  
Deviance Information Criterion ◽  
Predictive Ability ◽  
Information Criterion ◽  
Medical Genetic

Logit, probit and complementary log-log models are the most widely used models when binary dependent variables are available. Conventionally, these models have been frequentists. This paper aims to demonstrate how such models can be implemented relatively quickly and easily from a Bayesian framework using Gibbs sampling Markov chain Monte Carlo simulation methods in WinBUGS. We focus on the modeling and prediction of Down syndrome (DS) and Mental retardation (MR) data from an observational study at Kuwait Medical Genetic Center over a 30-year time period between 1979 and 2009. Modeling algorithms were used in two distinct ways; firstly, using three different methods at the disease level, including logistic, probit and cloglog models, and, secondly, using bivariate logistic regression to study the association between the two diseases in question. The models are compared in terms of their predictive ability via R2, adjusted R2, root mean square error (RMSE) and Bayesian Deviance Information Criterion (DIC). In the univariate analysis, the logistic model performed best, with R2 (0.1145), adjusted R2 (0.114), RMSE (0.3074) and DIC (7435.98) for DS, and R2 (0.0626), adjusted R2 (0.0621), RMSE (0.4676) and DIC (23120) for MR. In the bivariate case, results revealed that 7 and 8 out of the 10 selected covariates were significantly associated with DS and MR respectively, whilst none were associated with the interaction between the two outcomes. Bayesian methods are more flexible in handling complex non-standard models as well as they allow model fit and complexity to be assessed straightforwardly for non-nested hierarchical models.

scholarly journals Sensitivity and specificity of the Bamberg Dementia Screening Test’s (BDST) full and short versions: brief screening instruments for geriatric patients that are suitable for infectious environments

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Wolfgang Trapp ◽  
Susanne Röder ◽  
Andreas Heid ◽  
Pia Billman ◽  
Susanne Daiber ◽  
...  
Keyword(s):  
Sensitivity And Specificity ◽  
Short Form ◽  
Neuropsychological Testing ◽  
Screening Tests ◽  
Fine Motor ◽  
Consecutive Series ◽  
Diagnostic Quality ◽  
Dementia Screening ◽  
Increased Risk ◽  
Diagnosis Of Dementia

Abstract Background Currently, many patients suffering from dementia do not have a diagnosis when admitted to geriatric hospitals. This is the case despite an increased risk of complications affecting the length of stay and outcome. Unfortunately, many dementia screening tests cannot be used on geriatric inpatients, who are often bedridden. Therefore, we aimed at evaluating the diagnostic accuracy of a small battery of bedside tasks that require minimal vision and fine motor skills in patients with suspected dementia. Methods In this prospective study, the Bamberg Dementia Screening Test (BDST) was administered to a consecutive series of 1295 patients referred for neuropsychological testing. The diagnosis of dementia was confirmed in 1159 and excluded in 136 patients. Sensitivity and specificity for the first subtest (ultra-short form), the first two subtests (short form), and the total score of the BDST were obtained via receiver operating characteristic curves and compared with the sensitivity and specificity values of the Mini-Mental Status Examination (MMSE). Results The overall diagnostic quality of the BDST was superior to the MMSE for mild Alzheimer’s dementia (sensitivity and specificity = .94 (95% CI .92 to .96) and .82 (95% CI .75 to .88) vs. .79 (95% CI .76 to .83) and .88 (95% CI .82 to .93)) as well as for other subtypes of mild dementia (sensitivity and specificity = .91 (95% CI .88 to .94) and .82 (95% CI .75 to .88) vs. .72 (95% CI .67 to .76) and .88 (95% CI .82 to .93)). Even the short form of the BDST was comparable to the MMSE regarding sensitivity and specificity. For moderate dementia, it was possible to identify dementia cases with sufficient and excellent diagnostic quality by using the ultra-short and the short form. Conclusions The BDST is able to detect dementia in geriatric hospital settings. If the adaptive algorithm is used, administration time can be reduced to less than 2 min in most cases. Because no test materials have to be exchanged, this test is particularly suitable for infectious environments where contact between the examiner and the person being tested should be minimized.

PSXV-9 Transgenerational epigenetic variance for production and reproduction traits in maternal-line pigs

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 258-259
Author(s):  
Jason R Graham ◽  
Jay S Johnson ◽  
Andre C Araujo ◽  
Jeremy T Howard ◽  
Luiz F Brito
Keyword(s):  
Additive Genetic Variance ◽  
Phenotypic Expression ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Pedigree Information ◽  
Relationship Matrix ◽  
Maternal Line ◽  
Genetic Heritability ◽  
Reproduction Traits ◽  
Search Approach

Abstract Modeling epigenetic factors impacting phenotypic expression of economically important traits has become a hot-topic in the field of animal breeding due to the variability in genetic expression caused by environmental stressors (e.g., heat stress). This variability may be due, in part, to in-utero epigenomic remodeling, which has been reported to be passed from parent to offspring. We aimed to estimate transgenerational epigenetic variance for various production and reproduction traits measured in a maternal-line pig population, using a Bayesian approach. The phenotypes for production [n = 10,862; i.e., weaning weight (WW), birth weight (BW) and ultrasound-backfat thickness (BF)] and reproduction [n = 5,235, i.e., number of piglets born alive (NBA) and total number of piglets born (TB)] traits from a purebred Landrace population were provided by Smithfield Premium Genetics (NC, USA). The pedigree information traced back to 10 generations. Single-trait genetic analyses were performed using mixed models that included additive genetic, common environmental, and epigenetic random effects. The Gibbs sampler algorithm based on Markov chain Monte Carlo was used to estimate the variance components. The epigenetic relationship matrix was constructed using a recursive parameter (λ) related to the transmissibility coefficient of epigenetic markers. A grid search approach was used to define the optimal λ value (λ values ranged from 0.1 to 0.5, with an interval of 0.1). The optimal λ value was determined based on the deviance information criterion, and it was used to estimate the additive and epigenetic variances. For instance, based on preliminary results, the optimal λ value estimated for TB was 0.3 with an additive genetic variance of 0.94 (0.19 PSD) and epigenetic variance of 0.67 (0.18 PSD). The additive genetic heritability was 0.076 (0.015 PSD) and the estimated epigenetic heritability was 0.053 (0.015 PSD). This preliminary result suggests that epigenetics contribute to the non-Mendelian variability in pigs.

scholarly journals Utilização da modelagem inteiramente bayesiana na detecção de padrões de variação de risco relativo de mortalidade infantil no Rio Grande do Sul, Brasil

2009 ◽  
Vol 25 (7) ◽  
pp. 1501-1510 ◽  
Author(s):  
Sérgio Kakuta Kato ◽  
Diego de Matos Vieira ◽  
Jandyra Maria Guimarães Fachel
Keyword(s):  
Deviance Information Criterion ◽  
Rio Grande ◽  
Information Criterion ◽  
Rio Grande Do Sul ◽  
Standardised Mortality Ratio ◽  
Mortality Ratio

Neste artigo são analisados os fatores possivelmente associados à mortalidade infantil nos 496 municípios do Rio Grande do Sul, Brasil, com base em dados acumuladas entre os anos de 2001 a 2004, obtidos pela análise de regressão utilizando modelagem inteiramente bayesiana como alternativa para superar a autocorrelação espacial e a instabilidade dos estimadores clássicos, como a taxa bruta e a SMR (Standardised Mortality Ratio). Foram comparadas diferentes especificações de componente espacial e covariáveis, provenientes dos blocos do Índice de Desenvolvimento Sócio-econômico da Fundação de Economia e Estatística (IDESE/FEE-2003). Verificou-se que o modelo que utiliza a estrutura espacial além da covariável educação apresenta melhor desempenho, quando comparado pelo critério DIC (Deviance Information Criterion). Comparando as estimativas das SMR com os riscos relativos obtidos pela modelagem inteiramente bayesiana, foi possível observar um ganho substancial na interpretação e na detecção de padrões de variação do risco de mortalidade infantil nos municípios do Rio Grande do Sul ao utilizar essa modelagem. A região da Serra Gaúcha destacou-se com baixo risco relativo e estimativas muito homogêneas.

Understanding historical summer flounder (Paralichthys dentatus) abundance patterns through the incorporation of oceanography-dependent vital rates in Bayesian hierarchical models

2019 ◽  
Vol 76 (8) ◽  
pp. 1275-1294 ◽  
Author(s):  
Cecilia A. O’Leary ◽  
Timothy J. Miller ◽  
James T. Thorson ◽  
Janet A. Nye
Keyword(s):  
Population Dynamics ◽  
Gulf Stream ◽  
Stock Assessment ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Natural Mortality ◽  
Vital Rates ◽  
Summer Flounder ◽  
Paralichthys Dentatus ◽  
Abundance Patterns

Climate can impact fish population dynamics through changes in productivity and shifts in distribution, and both responses have been observed for many fish species. However, few studies have incorporated climate into population dynamics or stock assessment models. This study aimed to uncover how past variations in population vital rates and fishing pressure account for observed abundance variation in summer flounder (Paralichthys dentatus). The influences of the Gulf Stream Index, an index of climate variability in the Northwest Atlantic, on abundance were explored through natural mortality and stock–recruitment relationships in age-structured hierarchical Bayesian models. Posterior predictive loss and deviance information criterion indicated that out of tested models, the best estimates of summer flounder abundances resulted from the climate-dependent natural mortality model that included log-quadratic responses to the Gulf Stream Index. This climate-linked population model demonstrates the role of climate responses in observed abundance patterns and emphasizes the complexities of environmental effects on populations beyond simple correlations. This approach highlights the importance of modeling the combined effect of fishing and climate simultaneously to understand population dynamics.

Sign in / Sign up

Export Citation Format

Share Document