A tutorial in estimating the prevalence of disease in humans and animals in the absence of a gold standard diagnostic

Lewis, Fraser; Torgerson, Paul R.

doi:10.1186/1742-7622-9-9

Cited by 77 publications

(68 citation statements)

References 42 publications

(55 reference statements)

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“…For a detailed model description, see Lewis and Torgerson (2012). Diagnostic Se was defined as the probability that a test would correctly classify true positive samples; diagnostic Sp was defined as the probability that a test would correctly classify true negative samples.…”

Section: Bayesian Latent Class Analysismentioning

confidence: 99%

“…For BC, we used the categories "all pathogens" and "major pathogens" (Table 1) to account for the dependence of Se and Sp on defining a positive culture Reyher and Dohoo, 2011). We investigated 2 basic latent class models and used initial analyses with non-informative priors as β distributions (1,1) for all parameters of both models, as described by Lewis and Torgerson (2012). We set thresholds for SCC and MAA-ELISA at 100,000 cells/mL and at 1 µg/mL, respectively, for both models.…”

Section: Bayesian Latent Class Analysismentioning

confidence: 99%

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Test characteristics of milk amyloid A ELISA, somatic cell count, and bacteriological culture for detection of intramammary pathogens that cause subclinical mastitis

Jaeger

Virchow²,

Torgerson

et al. 2017

Journal of Dairy Science

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Bovine mastitis is an important disease in the dairy industry, causing economic losses as a result of withheld milk and treatment costs. Several studies have suggested milk amyloid A (MAA) as a promising biomarker in the diagnosis of mastitis. In the absence of a gold standard for diagnosis of subclinical mastitis, we estimated the diagnostic test accuracy of a commercial MAA-ELISA, somatic cell count (SCC), and bacteriological culture using Bayesian latent class modeling. We divided intramammary infections into 2 classes: those caused by major pathogens (e.g., Escherichia coli, Staphylococcus aureus, streptococci, and lacto-/enterococci) and those caused by all pathogens (major pathogens plus Corynebacterium bovis, coagulase-negative staphylococci, Bacillus spp., Streptomyces spp.). We applied the 3 diagnostic tests to all samples. Of 433 composite milk samples included in this study, 275 (63.5%) contained at least 1 colony of any bacterial species; of those, 56 contained major pathogens and 219 contained minor pathogens. The remaining 158 samples (36.5%) were sterile. We determined 2 different thresholds for the MAA-ELISA using Bayesian latent class modeling: 3.9 µg/mL to detect mastitis caused by major pathogens and 1.6 µg/mL to detect mastitis caused by all pathogens. The optimal SCC threshold for identification of subclinical mastitis was 150,000 cells/mL; this threshold led to higher specificity (Sp) than 100,000 cells/mL. Test accuracy for major-pathogen intramammary infections was as follows: SCC, sensitivity (Se) ABSTRACTBovine mastitis is an important disease in the dairy industry, causing economic losses as a result of withheld milk and treatment costs. Several studies have suggested milk amyloid A (MAA) as a promising biomarker in the diagnosis of mastitis. In the absence of a gold standard for diagnosis of subclinical mastitis, we estimated the diagnostic test accuracy of a commercial MAA-ELISA, somatic cell count (SCC), and bacteriological culture using Bayesian latent class modeling. We divided intramammary infections into 2 classes: those caused by major pathogens (e.g., Escherichia coli, Staphylococcus aureus, streptococci, and lacto-/enterococci) and those caused by all pathogens (major pathogens plus Corynebacterium bovis, coagulase-negative staphylococci, Bacillus spp., Streptomyces spp.). We applied the 3 diagnostic tests to all samples. Of 433 composite milk samples included in this study, 275 (63.5%) contained at least 1 colony of any bacterial species; of those, 56 contained major pathogens and 219 contained minor pathogens. The remaining 158 samples (36.5%) were sterile. We determined 2 different thresholds for the MAA-ELISA using Bayesian latent class modeling: 3.9 µg/mL to detect mastitis caused by major pathogens and 1.6 µg/mL to detect mastitis caused by all pathogens. The optimal SCC threshold for identification of subclinical mastitis was 150,000 cells/mL; this threshold led to higher specificity (Sp) than 100,000 cells/ mL.

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Section: Bayesian Latent Class Analysismentioning

confidence: 99%

Section: Bayesian Latent Class Analysismentioning

confidence: 99%

Test characteristics of milk amyloid A ELISA, somatic cell count, and bacteriological culture for detection of intramammary pathogens that cause subclinical mastitis

Jaeger

Virchow²,

Torgerson

et al. 2017

Journal of Dairy Science

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“…Assim, a estimativa precisa da prevalência é essencial tanto em saúde pública humana, quanto veterinária (Lewis & Torgerson 2012). O desempenho de um teste de diagnóstico é geralmente representado por duas medidas: a sensibilidade (SE) e a especificidade (SP), cada uma descrevendo a capacidade do teste, de modo a refletir o verdadeiro e desconhecido "estado da doença" (Speybroeck et al 2012).…”

Section: Introductionunclassified

“…Da mesma forma, a especificidade é a probabilidade de um teste de diagnóstico ser negativo, dado que a amostra a ser testada é certamente negativa (Lewis & Torgerson 2012). Infelizmente, SE e SP são raramente conhecidas exatamente e devem ser calculadas a partir de dados.…”

Section: Introductionunclassified

“…Os dois resultados de ensaio para um determinado animal são susceptíveis de ser correlacionados se ambos os ensaios medem um fenômeno biológico semelhante. Em particular, pode ser razoável assumir que os testes de diagnóstico utilizados serão dependentes quando eles compartilham uma base biológica semelhante (Branscum et al 2005, Lewis & Torgerson 2012. Na validação de múltiplos testes, a dependência condicional não deve ser ignorada quando os testes são de fato condicionalmente dependentes (Rahman et al 2013).…”

Section: Introductionunclassified

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Avaliação dos métodos de otoscopia e exame do swab parasitológico no diagnóstico da otocariose canina: uma abordagem bayesiana

et al. 2015

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Resumo Ácaros do gênero Otodectes são parasitos encontrados frequentemente no ouvido de cães e gatos, sendo reconhecidos como os principais causadores de otite externa nesses animais. Trezentos e vinte cães, oriundos do município de Cuiabá, Mato Grosso, foram examinados através da otoscopia e do exame do swab parasitológico, com o objetivo de avaliar, através da análise bayesiana para a estimativa da prevalência, sensibilidade e especificidade destes métodos no diagnóstico da infestação causada pelo ácaro utilizando-se de dados a priori informativos e não informativos. Cada animal foi considerado uma unidade experimental. Do total de cães examinados, 142 (44,37%) apresentaram-se positivos para otocariose. Em 100 animais (31,25%) a infestação foi diagnosticada pelos dois métodos, em 31 (9,69%) apenas pelo exame do swab parasitológico, em 11 (3,44%) apenas pela otoscopia e em 178 (55,62%) animais o resultado foi negativo por ambos os métodos. A sensibilidade da otoscopia, quando comparada ao exame do swab parasitológico, foi considerada menor, a especificidade dos testes, porém, não difere estatisticamente. O modelo, a priori informativo, demonstrou ser o mais plausível e reduziu consideravelmente o intervalo de credibilidade das estimativas dos parâmetros. Conclui-se que a análise bayesiana é efetiva na estimativa da prevalência e características dos testes diagnósticos.

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Estimating Neospora caninum prevalence in wildlife populations using Bayesian inference

Moreno-Torres

Wolfe

Saville

et al. 2016

Ecology and Evolution

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Prevalence of disease in wildlife populations, which is necessary for developing disease models and conducting epidemiologic analyses, is often understudied. Laboratory tests used to screen for diseases in wildlife populations often are validated only for domestic animals. Consequently, the use of these tests for wildlife populations may lead to inaccurate estimates of disease prevalence. We demonstrate the use of Bayesian latent class analysis (LCA) in determining the specificity and sensitivity of a competitive enzyme‐linked immunosorbent assay (cELISA; VMRD ®, Inc.) serologic test used to identify exposure to Neospora caninum (hereafter N. caninum) in three wildlife populations in southeastern Ohio, USA. True prevalence of N. caninum exposure in these populations was estimated to range from 0.1% to 3.1% in American bison (Bison bison), 51.0% to 53.8% in Père David's deer (Elaphurus davidianus), and 40.0% to 45.9% in white‐tailed deer (Odocoileus virginianus). The accuracy of the cELISA in American bison and Père David's deer was estimated to be close to the 96% sensitivity and 99% specificity reported by the manufacturer. Sensitivity in white‐tailed deer, however, ranged from 78.9% to 99.9%. Apparent prevalence of N. caninum from the test results is not equal to the true prevalence in white‐tailed deer and Père David's deer populations. Even when these species inhabit the same community, the true prevalence in the two deer populations differed from the true prevalence in the American bison population. Variances in prevalence for some species suggest differences in the epidemiology of N. caninum for these colocated populations. Bayesian LCA methods could be used as in this example to overcome some of the constraints on validating tests in wildlife species. The ability to accurately evaluate disease status and prevalence in a population improves our understanding of the epidemiology of multihost pathogen systems at the community level.

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A tutorial in estimating the prevalence of disease in humans and animals in the absence of a gold standard diagnostic

Cited by 77 publications

References 42 publications

Test characteristics of milk amyloid A ELISA, somatic cell count, and bacteriological culture for detection of intramammary pathogens that cause subclinical mastitis

Test characteristics of milk amyloid A ELISA, somatic cell count, and bacteriological culture for detection of intramammary pathogens that cause subclinical mastitis

Avaliação dos métodos de otoscopia e exame do swab parasitológico no diagnóstico da otocariose canina: uma abordagem bayesiana

Estimating Neospora caninum prevalence in wildlife populations using Bayesian inference

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