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2015-05-10T07:42:17Z

Importing a new version from external source

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2014-08-25T02:34:39Z

Importing a new version from external source

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==== Simulation modelling of longitudinal testing results ====
An alternative approach, using simulation modelling, has been used where no comparative test data was available, but results of repeated testing over time were available. In this example, the sensitivity of an ELISA for bovine Johneâ€™s disease was estimated from repeated herd-testing results over a 10-year period using a simulation model. Age-specific data from up to 7 annual tests in 542 dairy herds were used to estimate ELISA sensitivity at the first-round test. The total number of infected animals present at the first test was estimated from the number of reactors detected at that test, plus the estimated number of animals that failed to react at that test, but reacted (or would have reacted if they had not died or been previously culled) at a subsequent test, based on reactor rates at subsequent tests. Reactor rates were adjusted for an assumed ELISA specificity of 99.8% to ensure estimates were not biased by imperfect ELISA specificity ([#_ENREF_12 Jubb et al., 2004]). Age-specific estimates of ELISA sensitivity ranged from 1.2% in 2-year-old cattle to 30.8% in 10-year-old cattle, with an overall age-weighted average of 13.5%.

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	==== Simulation modelling of longitudinal testing results ====		==== Simulation modelling of longitudinal testing results ====
−	An alternative approach, using simulation modelling, has been used where no comparative test data was available, but results of repeated testing over time were available. In this example, the sensitivity of an ELISA for bovine ~~Johneâ€™s~~ disease was estimated from repeated herd-testing results over a 10-year period using a simulation model. Age-specific data from up to 7 annual tests in 542 dairy herds were used to estimate ELISA sensitivity at the first-round test. The total number of infected animals present at the first test was estimated from the number of reactors detected at that test, plus the estimated number of animals that failed to react at that test, but reacted (or would have reacted if they had not died or been previously culled) at a subsequent test, based on reactor rates at subsequent tests. Reactor rates were adjusted for an assumed ELISA specificity of 99.8% to ensure estimates were not biased by imperfect ELISA specificity ([#~~_ENREF_12~~ Jubb et al., 2004]). Age-specific estimates of ELISA sensitivity ranged from 1.2% in 2-year-old cattle to 30.8% in 10-year-old cattle, with an overall age-weighted average of 13.5%.	+	An alternative approach, using simulation modelling, has been used where no comparative test data was available, but results of repeated testing over time were available. In this example, the sensitivity of an ELISA for bovine Johne's disease was estimated from repeated herd-testing results over a 10-year period using a simulation model. Age-specific data from up to 7 annual tests in 542 dairy herds were used to estimate ELISA sensitivity at the first-round test. The total number of infected animals present at the first test was estimated from the number of reactors detected at that test, plus the estimated number of animals that failed to react at that test, but reacted (or would have reacted if they had not died or been previously culled) at a subsequent test, based on reactor rates at subsequent tests. Reactor rates were adjusted for an assumed ELISA specificity of 99.8% to ensure estimates were not biased by imperfect ELISA specificity ([#12 Jubb et al., 2004]). Age-specific estimates of ELISA sensitivity ranged from 1.2% in 2-year-old cattle to 30.8% in 10-year-old cattle, with an overall age-weighted average of 13.5%.

Translations:Advanced Field Epi:Manual 2 - Diagnostic Tests/237/en - Revision history

FuzzyBot: Importing a new version from external source

FuzzyBot: Importing a new version from external source