Article ID Journal Published Year Pages File Type
8984988 Preventive Veterinary Medicine 2005 15 Pages PDF
Abstract
Samples from livestock or food items are often submitted to microbiological analysis to determine whether or not the group (herd, flock or consignment) is shedding or is contaminated with a bacterial pathogen. This process is known as 'herd testing' and has traditionally involved subjecting each sample to a test on an individual basis. Alternatively one or more pools can be formed by combining and mixing samples from individuals (animals or items) and then each pool is subjected to a test for the pathogen. I constructed a model to simulate herd-level sensitivity of the individual-sample approach (HSe) and the herd-level sensitivity of the pooled-sample approach (HPSe) of tests for detecting pathogen. The two approaches are compared by calculating the relative sensitivity (RelHSe = HPSe/HSe). An assumption is that microbiological procedures had 100% specificity. The new model accounts for the potential for HPSe and RelHSe to be reduced by the dilution of pathogen that occurs when contaminated samples are blended with pathogen-free samples. Key inputs include a probability distribution describing the concentration of the pathogen of interest in samples, characteristics of the pooled-test protocol, and a 'test-dose-response curve' that quantifies the relationship between concentration of pathogen in the pool and the probability of detecting the target organism. The model also compares the per-herd cost of the pooled-sample and individual-sample approaches to herd testing. When applied to the example of Salmonella spp. in cattle feces it was shown that a reduction in the assumed prevalence of shedding can cause a substantial fall in HPSe and RelHSe. However, these outputs are much less sensitive to changes in prevalence when the number of samples per pool is high, or when the number of pools per herd-test is high, or both. By manipulating the number of pools per herd and the number of samples per pool HPSe can be optimized to suit the range of values of true prevalence of shedding of Salmonella that are likely to be encountered in the field.
Related Topics
Life Sciences Agricultural and Biological Sciences Animal Science and Zoology
Authors
,