Escherichia coli O157:H7 in Ground Beef Review of a Draft Risk Assessment (2002) / Chapter Skim
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2 Production Module
2 Production Module
Pages 27-40
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From page 27... ...
· Is fecal prevalence alone an adequate measure of output for the Production Module? · Are the prevalence estimates in cull cows (called "breeding cattle" 27
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From page 28... ...
and feedlot animals defensible? FECAL PREVALENCE AS THE SOLE OUTPUT OF THE PRODUCTION MODULE The arguments against using fecal prevalence alone for risk assessment are related to the wide range of concentrations of E
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From page 29... ...
Also, important sites for intervention, such as transport and confinement conditions or methods of hide removal, may be excluded from the draft risk assessment if fecal prevalence is the sole output of the Production Module. The exclusion of effects of preslaughter transport and lairage from the model may need re-examination in light of a report of increasing E
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From page 30... ...
For those reasons, the committee recommends that the final risk assessment acknowledge forthrightly that fecal prevalence is being used as a proxy variable and that some carcass contamination is derived from hides. DEFENSIBILITY OF PREVALENCE ESTIMATES FOR CULL COWS AND FEEDLOT ANIMALS Pooling data from disparate studies that had differing assay methods and sampling designs is difficult, and the draft risk assessment does a generally credible job.
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From page 31... ...
that those procedures were adhered to and that blanks were uniformly negative, it must be assumed that false positives probably occurred. In any case, it seems unreasonable to go to considerable lengths to address imperfect test sensitivity while failing to note the possibility of imperfect test specificity.
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From page 32... ...
The committee notes that there is a paucity of information on this topics and suggests that the risk assessment highlight the need for more research. Issues Related to Computation of Within-Herd Prevalence Data from Juvenile Cattle May Have Been Included Two of the within-herd prevalence estimates in Table 3-2 of the FSIS draft included juvenile animals (Besser et al., 1997; Hancock et al., 1994)
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From page 33... ...
The committee recommends that the FSIS draft risk assessment either compute within-herd prevalence estimates as the total positives divided by the total sampled (herd status notwithstanding) or use a denominator based on the estimated herd prevalence, such as that depicted in Figure 3-2 of the draft.
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From page 34... ...
Hence, the use of the within-herd prevalence in all adults may yield a biased estimate of prevalence of cull dairy cattle at the time of slaughter. The committee suggests that the risk assessment note as a possible weakness that prevalence estimates in cull cattle might be higher than those in all adult cattle.
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From page 35... ...
The committee recommends that the risk assessment use only data from independent feedlots to estimate herd prevalence in feedlots. Herd-Prevalence Estimates Erroneously Assume Homogeneous Prevalence over Time in Positive Herds Computation of the herd-level sensitivity (Equation 3.3 in the draft)
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From page 36... ...
The committee recommends that the risk assessment use an appropriate means of adjusting for herd sensitivity that incorporates effects of temporal clustering for breeding herds or base the estimate of herd prevalence only on studies in which breeding herds were sampled multiple times. For feedlots, the committee recommends that a 100% herd prevalence be used.
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From page 37... ...
If data from point-sampling studies (such as Garber et al., 1999; Hancock et al., 1994; Rice et al., 1997) are to be used in computing seasonal effect, the only reasonable way to treat them is as generally random surveys of the cattle population (ignoring herd, because herd status cannot be assessed accurately in such studies)
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From page 38... ...
(1997~. · Adjust all monthly prevalence estimates for imperfect test sensi· Either handle the data from multiple surveys as random surveys of the cattle population, thus using data on all cattle sampled in each month, or use only data from longitudinal studies to estimate seasonal adjustment factors.
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From page 39... ...
1997a. A longitudinal study of Escherichia cold 0157 in fourteen cattle herds.
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From page 40... ...
2000. Incidence of foodborne illnesses reported by the foodborne diseases active surveillance network (FoodNet)
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