Vibrio in seafood - FAO.org

More documents

Recommendations

Info

egions of the country the average percentage pathogenic was estimated to be 0.2% and the correspondingminimum and maximum of the distribution was 0.1% and 0.3%, respectively. Uncertainty with regard tothe shape parameter φ was not evaluated.The Monte Carlo simulation of the distribution of pathogenic V. parahaemolyticus present inoysters was performed as follows. For each region and season the mean and standard deviation of watertemperature distributions were sampled based on the bivariate normal distributions given in Table 2.4.Each random sample from these distributions represents a distribution of water temperature (i.e. fordifferent years). Given a water temperature distribution, the distribution of total V. parahaemolyticusnumbers in composites of 12 oysters at harvest was simulated by:• Sampling from the distribution of water temperature• Using the regression relationship to calculate a mean density corresponding to each sampled watertemperature• Perturbing the calculated means by a random normal deviate corresponding to the estimate ofpopulation variation of the numbers.The distribution of pathogenic V. parahaemolyticus numbers was derived from that of totalV. parahaemolyticus assuming a beta-binomial model for the extent of clustering of pathogenic relative tototal counts. Multiple simulations were run with different values of average percentage of isolatespathogenic in order to evaluate the uncertainty with regard to this parameter.2.2.5.4 Post harvestThe Post Harvest Module describes the effects of typical industry practices includingtransportation, handling and processing, as well as distribution, storage and retail on V. parahaemolyticusnumbers in oysters harvested from various locations and seasons. Factors considered as possibleinfluences on the numbers of pathogenic V. parahaemolyticus at consumption include:• Ambient air temperatures at time of harvest• Time from harvest until oysters are placed under refrigeration• Time it takes oysters to cool once under refrigeration• Length of refrigeration time until consumptionThe purpose of modelling the Post Harvest Module is to simulate the effects of typical industrypractices on the numbers of V. parahaemolyticus in oysters from harvest to consumption for variouslocations and seasons. The module can also be used to simulate the effect of intervention strategies. Theinputs to the module are the regional and seasonal distributions of total and pathogenicV. parahaemolyticus at harvest. The output of the module is a series of predicted distributions of the totaland pathogenic numbers at time of consumption. The final steps to be addressed in the exposureassessment are the storage and retail conditions of the product, storage after retail and finally preparationand consumption. Some of these factors are included at the end of the flowchart presented in Figure 2.8.Prior to consumption, temperature of storage is probably among the most critical factors to be considered.A diagrammatic representation of the parameters modelled in this section is presented in Figure 2.8. Thebaseline prediction is the distribution of numbers of V. parahaemolyticus (in 12 oyster composites),assuming current industry practices in the United States.The principal assumption used to develop the relationships between numbers at harvest and atconsumption is that the growth and survival of pathogenic V. parahaemolyticus is the same as totalV. parahaemolyticus. Although no definitive studies of the growth characteristics of pathogenic26
V. parahaemolyticus are available, preliminary data suggest that there is little difference between growthcharacteristics of pathogenic versus nonpathogenic strains (DePaola, 1999). Furthermore, observation ofthe growth of total V. parahaemolyticus in oysters is limited to only one temperature (26 o C). To bridgethis data gap a model of V. parahaemolyticus growth in broth developed by Miles et al. (1997) was used(see section 2.2.2.1). The predictions of this model have been adjusted to predict the growth rate inoysters, which is less than that of broth model systems possibly due to the influence of competingmicroflora.Vp/g at harvestTime to refrigerationAir temperatureVp/g at 1st refrigerationCooldown timeVp/g at cooldownStorage timeVp/g at consumptionFigure 2.8. Schematic depiction of the Post Harvest Module of the V. parahaemolyticus (Vp) riskassessment model.2.2.5.4.1 Growth of V. parahaemolyticus from harvest to first refrigerationThe extent of growth that occurs during the period of time from harvest until the time thatoysters are first placed under refrigeration is modelled by three factors:• Growth rate of V. parahaemolyticus as a function of temperature• Temperature of oyster meat following harvest• Length of time product is unrefrigerated2.2.5.4.2 Distribution of ambient air temperatureExamination of water and air temperatures obtained from the NOAA/NBDC database in theUnited States showed a strong correlation between water and air temperature. This correlation hasbeen incorporated into the risk simulation by modelling the distribution of the difference in waterversus air temperatures based on the normal distribution within any given region and season. Thesedistributions are then used to predict the air temperature that oysters would be subjected to dependingon the water temperature at the time of harvest.In the process of simulating the distribution of total and pathogenic V. parahaemolyticus atharvest by the Monte Carlo method, the water temperature associated with any given outcome is27
Page 1 and 2: Food and Agriculture Organization o
Page 3: 4.2.5 Simulation Results...........
Page 6 and 7: United States prior to 1997 illness
Page 8 and 9: 2 RISK ASSESSMENT OF VIBRIO PARAHAE
Page 10 and 11: The approach being taken is to use
Page 12 and 13: 2.2.2 Growth and survival character
Page 14 and 15: given average temperature and predi
Page 16 and 17: strains have been identified as a p
Page 18 and 19: 2001) and so this assumption may ha
Page 20 and 21: States. The study was undertaken on
Page 22 and 23: The estimated relationships between
Page 24 and 25: Clearly, in order to predict the di
Page 26 and 27: expected. Differences in these dist
Page 28 and 29: measurements were recorded for any
Page 32 and 33: etained. A corresponding air temper
Page 34 and 35: Frequency of duration of oysterharv
Page 36 and 37: 2.2.5.4.5 Die-off of V. parahaemoly
Page 38 and 39: V. parahaemolyticus cause illness -
Page 40 and 41: and four of those patients died. Pa
Page 42 and 43: Vomiting 52 17-79Headache 42 13-56F
Page 44 and 45: 2.3.3.2 Dose-response model2.3.3.2.
Page 46 and 47: While these assumptions are not rep
Page 48 and 49: Bean, N. H., Maloney, E. K., Potter
Page 50 and 51: Gjerde, E.P. and Bøe, B. 1981. Isp
Page 52 and 53: Levine, W. C., Griffin, P. M., and
Page 54 and 55: Abstract of the National Shellfishe
Page 56 and 57: 3.1.2 Prevalence in foodAlthough li
Page 58 and 59: The concentration of V. parahaemoly
Page 60 and 61: Figure 3.3. Schematic representatio
Page 62 and 63: 3.2.4 Preparation and consumption m
Page 64 and 65: • Frequency of consumption of raw
Page 66 and 67: Sarkar, B. L., G. B. Nair, et al..
Page 68 and 69: foodborne case has been associated
Page 70 and 71: (Cook and Ruple, 1992). However, th
Page 72 and 73: 4.2.4.1 HarvestLike V. parahaemolyt
Page 74 and 75: Although not incorporated in the pr
Page 76 and 77: increase in log of Vv density32.521
Page 78 and 79: Figure 4.6 shows typical distributi
Page 80 and 81:
1.5Probability Density0.7501 2 3 4
Page 82 and 83:
Table 4.6. Prevalence rates of V. v
Page 84 and 85:
4.3.3 Dose-response relationship4.3
Page 86 and 87:
Dec 15 0.76 0.61 1,841,000 1,025,00
Page 88 and 89:
• Does virulence vary by season,
Page 90 and 91:
ICMSF. 1996. Microorganisms in Food
Page 92 and 93:
Appendix.Analytica 2.0.5 Model Simu
Page 94 and 95:
The chance nodes representing varia
Page 96 and 97:
5.2.2.2 Death or inactivationV. cho
Page 98 and 99:
Table 5.3. Instances of fish implic
Page 100 and 101:
Shrimp harvested fromcoastal areas
Page 102 and 103:
O1 through poor quality water, and
Page 104 and 105:
5.3.1.2 Characteristics of the host
Page 106 and 107:
5.3.3.1.4 Probability of death give
Page 108 and 109:
Resampled Beta-Poisson dose-respons
Page 110 and 111:
De Paola, A. 1981. Vibrio cholerae
Page 112:
Reilly, L.A. and Hackney, C.R. 1985
show all

Vibrio in seafood - FAO.org

Create successful ePaper yourself

Delete template?

Save as template?