Monte-Carlo simulation is carried out using a large number of computations, using a computer, with random inputs. This method is particularly useful when it comes to “predicting” the outcome a complex eventuality. Typically, the Monte-Carlo simulation is useful when predicting the outcome of a large number inter-related factors that are “uncertain”. Predictivity using Monte-Carlo simulation is far more accurate where variables under consideration are many, uncertain and random.
For this particular reason, using Monte-Carlo simulation for this study is the best choice as there are many uncertain factors that need to be analyzed for computing a risk assessment. In this study, the first step begins with the production of meat and ends with health effects that meat can probably induce in consuming subjects. There is a large interplay of uncertain factors, and the entire food chain model proposed in the study has inherent variability across most levels. 2. What comment would you make about the source of data used for the concentration of E.
coli in cattle feces? Prevalence and concentration of E. Coli in cattle fecal matter was used to assess the level of contamination of the meat. The level of contamination of the meat is a pointer to the probable exposure that a consuming subject could possibly have, to E. Coli. Concentration of E. Coli in cattle fecal matter is directly related to factors like seasonality, geographical properties, and feeding practices. However, the data related to concentration of E. Coli in the cattle fecal matter was constructed without consideration for these factors.
Data used for concentration of E. Coli in fecal matter was obtained using enrichment methods. The results show a wide bipolar variation, from as low as undetectable E. Coli levels to as much as 5. 0 log10 CFU/g. The data for prevalence of E. Coli in cattle fecal matter was obtained from previously held studies. However, only data from those studies was used, that primarily aimed at detecting E. Coli prevalence rates in cattle fecal matter for beef that was supposedly slated for human consumption. 3. What comment would you make about the following:
• modeling the distribution of feces on carcass as Uniform? Slaughtering invariably causes the fecal matter to come in contact with the meat. Skinning a carcass will lead to contamination of exposed meat due to contact with the hide. Although, fecal matter is the main source of bacterial reservoir, the nature and number of agents that can directly or indirectly participate as contaminating agents is uncertain. However, the concentration of E. Coli in fecal matter is directly proportional to the extent of meat contamination.
The distribution of fecal matter on carcass surface is uneven. A dilution factor was used as a model simplification. • modeling fecal contamination only on the carcass surface? As a fact, E. Coli are present in the fecal matter but not inside red meat. Contamination of red meat, therefore, occurs only when fecal matter comes in contact with it. This will usually happen during slaughtering, and the following processes like packaging and trimming. For this reason fecal contamination has been modeled only on the carcass surface. 4.
Briefly (less than 500 words), discuss the practicalities and likely success of implementing each of the proposed hypothetical mitigation strategies in the paper. The author has proposed three hypothetical risk mitigation strategies for risk reduction. However, the strategies have been proposed to reduce risk as per mentioned figures, assuming that the strategy is being implemented and the desired goal is being achieved. For instance, the first strategy of regulating storage temperature control norms shows a reduced risk to over 80%.
Practically, this strategy can indeed cause a large risk reduction but a protocol will need to be developed that incorporates all the levels of the proposed beef-cold-chain, starting right from the farm to the retailer. Even with a concrete legislature to make sure this strategy works, it needs to be evaluated how far would this strategy prove to be practically enforceable. With definite legislature, a good compliance can be expected out of this strategy and apparently this strategy is far more practicable, and could prove successful.
Pre-slaughter screening proposes to reduce risk by over 46%. However, more variables like feeding practices, geographical locations, and seasonal variation (that affect E. Coli fecal load) need to considered, before a definite “control” level can be instated to rule out slaughters for animals that have more than a certain level of bacterial fecal concentration. The consumer information program, although with a risk reduction of 16%, is certainly a very important level wherein proper intervention can dramatically decrease E.
Coli related health morbidity. Even though anticipated risk reduction is only 16%, simple measures like adequate promotional tools, could significantly increase risk reduction through mass communication; the biggest limitation however, is that compliance in this case cannot be ascertained, nor enforceable. Keeping in mind the practical limitations of each of these strategies, a prudent approach would involve application of all the three strategies in conjunct, to ensure greater risk reduction.
A good reason for this approach is that due to the uncertain nature of all the factors involved in E. Coli contamination and delivery to consuming host, it appears quite difficult to determine the individual potency of each of these factors, and they would easily remain relative values. ‘Evaluation of MRSA Select, a new chromogenic medium for the detection of nasal carriage of methicillin-resistant Staphylococcus aureus’ 1. What is the ‘gold standard’ used to assess the sensitivity and specificity etc. of the different diagnostic tests?
The sensitivity and specificity of a particular diagnostic test needs to be estimated before the test under consideration can be employed for practical purposes, to ensure that the results obtained are accurate, and of consequence. A “gold standard”, hence, is an absolute, against which results from a particular diagnostic test are compared. The gold standard, also called as the standard frame of reference, is a perfect test for the given condition, and is 100% sensitive and specific as well. 2. Is the ‘gold standard’ the same for all of the tests? Within the context of this paper, the gold standard used is same for all the tests.
The gold standard used is identification of methicillin resistant S. Aureus, from nasal swabs of patients, confirmed for the mecA gene using PCR. 3. Can the tests be compared in this way? Yes, the tests can be compared this way. The same samples (n) were subjected to different growth mediums, to ascertain the presence of MRSA. All these media were specifically designed to promote the growth of MRSA. Hence, depending on the growths shown by these different media, results can be drawn and compared. 4. Are the authors’ conclusions valid? I think that the author’s conclusions are valid.
Although, PCR will remain the gold standard in ascertaining presence of MRSA, the application of this procedure, to remain practically enforceable, is quite limiting. For instance, considering the sheer number of samples that an urban community hospital has to handle on a daily basis, using PCR for all instances may not be feasible all the times. In this circumstance, using simple tissue culture techniques would definitely prove to be more desirable, especially with faster results and low costs; like using the MRSA Select that will give results within 24 hours with a sensitivity and specificity over 99%.
Moreover, simplicity of the test requires no complex skill set, especially compared with handling PCR techniques. References 1. Fishman, G. S. (1995). Monte Carlo: Concepts, Algorithms, and Applications. New York: Springer 2. Bell, B. P. , Goldoft, M. , Griffin, P. M. , Davis, M. S. , Gordon, D. C. , Tarr, P. I. , Bartleson, C. A. , Lewis, J. H. , Barret, T. J. , Wells, J. G. , Baron, R. , Kobayashi, J. , (1994). A multistate outbreak of Escherichia coli O157:H7-associated bloody diarrhea and hemolytic uremic syndrome from hamburgers: the Washington experience.
J. Am. Med. Assoc. 3. Vose, D. , (1996). Quantitative risk analysis: A guide to Monte Carlo simulation modelling. John Wiley and Sons, Chichester England. 4. USDA:APHIS:VS. , 1994a. E. coliO157:H7 issues and ramifications. Centers for Epidemiology and Animal Health, U. S. Department of Agriculture, Fort Collins, CO. 5. Gehlbach SH. (1993) Interpretation: sensitivity, specificity, and predictive value. In: Gehlbach SH, ed. Interpreting the medical literature. New York: McGraw-Hill 6. Apfalter P, Assadian O, Kalczyk A, et al. (2002) Performance of a new chromogenic
oxacillin resistance screen medium (Oxoid) in the detection and presumptive identification of methicillin-resistant Staphylococcus aureus. Diagn Microbiol Infect Dis;44:209–11. 7. Murakami K, Minamide W, Wada K, Nakamura E, Teraoka, H, Watanabe S. (1991) Identification of methicillin-resistant strains of staphylococci by polymerase chain reaction. J Clin Microbiol;29:2240–4. 8. Safdar N, Narans L, Gordon B, Maki DG. (2003) Comparison of culture screening methods for detection of nasal carriage of methicillin resistant Staphylococcus aureus: a prospective study comparing 32 methods. J Clin Microbiol;41:3163–6.
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