E. coli O157:H7 Characteristics, Pathogenicity, Spread and Control
A mathematical risk model for Escherichia coli O157:H7 in ready to eat vegetables Departamento de...
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Transcript of A mathematical risk model for Escherichia coli O157:H7 in ready to eat vegetables Departamento de...
A mathematical risk model for A mathematical risk model for Escherichia coli Escherichia coli O157:H7 in ready O157:H7 in ready
to eat vegetablesto eat vegetables
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Pérez Rodríguez, Fernando1; Todd, Ewen2
1. Food Science and Technology, University of Córdoba, Córdoba, Spain.2. Todd Ewen Consulting, Okemos, MI, USA.
Summary
• Framework• Scope and assumptions• Factors at factory• Food Distribution Chain• Simulation settings• Implenting model into an on-line object-
orientated software
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Completing the leafy green Picture
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
E. coli VTEC transmission via vegetable products is a serious concern :
Large outbreak in Germany associated with O104:H4 (Bielaszewska et al. 2011).
Unknown transmission routes and contamination sources.
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
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•Composting Methodology (CU)
•Internalization/Surface Contamination
Methodology (UGA and CU
•Cross-Contamination Methodology (MSU)
•Processing Water Detection Methodology (IIT)
•Long-wave X-ray Intervention Methodology (MSU)
•Sanitizing and Physical Interventions Methodology (IIT)
•Storage Studies Methodology (IIT)
Project Context and Goals
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
RISK ASSESSMENTRISK ASSESSMENT
Completing the leafy green Picture
Context & Scope– According to available data, E. coli O157:H7 is rarely able to survive in
soil.
– The model will evaluate the effect of different processing steps in ONE factory and subsequent stages during the Distribution Chain until the Consumer phase.
– As contamination by E. coli O157:H7 is sporadic event (Doyle & Eriksson, 2007), it is assumed that only one contaminated batch could came in the processing line
– The model will trace the changes in concentration and prevalence of the contaminated batch and batches cross contaminated during production.
– The model estimates the risk by E. coli O157:H7 associated with consumption of RTE leafy vegetables coming from ONE factory.
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
NO MODEL FOR PRIMARY PRODUCTINO MODEL FOR PRIMARY PRODUCTION
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Model OverviewE coli O157:H7 transmission and risk estimation associated with a contaminated batch
Factory ModelMain inputs and models included in the cross-contamination model
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Input Model Parameters Source
Survival on equipment *log(cfu)s=log(cfu)s-1-(ts/b)a a= 0.17; b=0.02unpublished data
Removal by washing Uniform (min,max) min=1 ; max=1.5 Han et al. (2000) ;Singh et al.
(2002ª);Reduction in water
by chlorine**log(cfu) f=µ· log(cfu)i+1 µ=-0.02 unpublished data
Reduction on produceby chlorine
Uniform (min,max) min=0.20; max=0.80
Singh et al. (2002b);Marks et al. (2009)
Reduction on produceby irradiation
log(cfu) f=-(1/D)· log(cfu)i
D =0.11 KGy Unpublished
Bacterial distribution in processed lettuce
Negative Binomial(∑binomial(C*S))
S= bagged sizedC= cfuf/g
Perez-Rodriguez et al. (2007)
*log(cfu)s: concentration on equipment at any time (ts); a and b are fitting parameters based on Weibull model; ts is the time that microorganisms are on equipment surfaces (h).
**µ is the reduction rate of Escherichia coli O157:H7 in chlorinated water; log(cfu) f: concentration on lettuce after treatment; log(cfu) i: concentration on lettuce before treatment
Extending a previous model
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
• An Exposure assessment models was developed (Pérez-Rodriguez et al., 2010) to describe cross contamination during processing of leafy grean at factory. Also, the impact of different control measures and decontamination steps on the contamination by E. coli O157:H7 on final product were assessed
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Non contaminated batches
SHREDDERSHREDDER
Tr_1(a) (%)Tr_1(a) (%) Tr_2(a) (%)Tr_2(a) (%) Tr_3(a) (%)Tr_3(a) (%)
Tr_1(b) (%)Tr_1(b) (%) Tr_2(b) (%)Tr_2(b) (%) Tr_3(b) (%)Tr_3(b) (%)
Concentration and Prevalence in bags
S1=0.01 cfu/g S2 = 1 cfu/gContaminated batch
Transfer type Distribution (%)
Tr_1 (a) Beta(0.12;0.19)
Tr_2(a) Beta (0.18;0.21)
Tr_3(c) Beta (0.20;0.22)
Tr_1(b)+Tr_2(b)+Tr_3(b) 10 Normal(-0.83; 0.15)
Simulated scenarios
Transfer: distributons
Packaging= Poisson D.
Lettuce Processing line Inputs
Output
Packaging
Number of batches processes: 22 ( ≈ 3 batches/h)Batch size = 1000 kgNumber of bags per batch: 10000Bag size: 100 g
FLUMEFLUME SHAKERSHAKER
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Transfer routes
Loop Bidirectional Interrelated
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
•Data for E. coli O157:H7 lettuce and also spinach
•Initial concentration on artificially-inoculated Lettuce entering processing line.
•Final concentration on cross contaminated Lettuce
•Contamination level on specific sampling zones in the equipment suface before uninoculated lettuce come in the processing line.
Experimental data
Factory model: Transfer
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Different experiment was developed in Pilot- Scale to generate data
ShredderConveyor
Flume tank
Shaker tableCentrifugal drier
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Factory model: Transfer
Factory model: transfer
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
ROUTE 1: Contaminated leafy green product to Equipment:
Using data from experiments with contaminated lettuce and spinach processed at pilot-scale plant and sampling different locations
ROUTE 2: Contaminated equipment to non-contaminated product
Similar experiments tracing contamination from a contaminated batch to non-contaminated through equipment and process water.
ROUTE 3: Distribution in bags of the contaminated pieces (trims) derived from the originally contaminated batch.
Experiments performed using two differentiated lettuces (Iceberg and Radicchio). From this, contamination contribution to each bag was quantified based on number of Radicchio pieces (originally contaminated batch)
Factory model: transferTransfer (at low level) Maximum Mininum Mean Ditribution
Spinach-Centrifuge 0.08 0.01 0.04 Beta
Spinach-Flume 0.24 0.00 0.06 Beta
Spinach-Shaker 0.12 0.00 0.06 Beta
Spinach-Water 52.65 0.00 10.78 Beta
Lettuce-Shredder 0.02 0.00 0.02 Log-Normal
Lettuce-Flume 0.02 0.00 0.01 Log-Normal
Lettuce-Shaker 0.02 0.00 0.01 Log-Normal
Lettuce-Conveyor 0.24 0.00 0.10 Log-Normal
Lettuce-Water 10.46 0.00 8.79 Beta
Equipment-Lettuce 18.83 9.90 15.33 Log-Normal
Transfer data expressed as porcentage (%)
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Factory model: transferBeta distribution describing transfer rates:
Contaminated spinachShaker
Beta (0.18045,0.21231)
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Storage and Consumption
CONSUMPTION: 25 g SERVING
Modeling E. coli O157:H7 Growth
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
MODEL by Koseki & Isobe (2000)
unpackaged –Lettuce: 5-25 C
Data in packaged spinach inoculated with non-virulent O157 strains (IIT ):
CO2/O2 and 5-15º COnly growth at 12 and 15º C
Bioscreen experiments (turbity) developed in vegetable juices (parsley, spinach, chard, etc.) inoculated with a cocktail NaR O157 strain
8-20 º C
Growth in LETTUCE: Koseki
& Isobe
Validation of Bioscreen for
SPINACH model using ITT´s data
Few suitable models in scientific literature:
Modeling E. coli O157:H7 Growth
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Growth in LETTUCE: Koseki
& Isobe
Validation of Bioscreen for
SPINACH model using ITT´s data
ALGORITHM TO DETERMINE GROWTH OR NO GROWTH:
BOUNDARY MODEL
NO GROWTH
GROWTHY/N
Salter et al. 2000
Although lag time was also modeled; predictions were realized assuming no lag.
Storage and consumption model
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
LEAVING FACTORY
ARRIVING WAREHOUSE
LEAVING WAREHOUSE
RETAIL
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TE
MP
ºC
TIME (H)
SPANISH DATA: CHILL CHAIN
Modeling retail temperature
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
in the botton (33%) in the middle (33%)in the top (33%)
Time-Temperature profiles in refrigerated cabinets at retail in the U.S. (Nunes et al., 2009)
Temperature Variability was added thorugh a Uniform distribution (shaded zones)
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0 10 20 30 40 50 60 70 80
Temperature(C)
Time (h)
Modeling Household temperature
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
5.0% 90.0% 5.0%
-0.40 9.42
-10-505101520
Temperature (ºC)
0.00
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Probability
TEMPERATURE were taken from ECOSURE study household refrigerated deli-salad items. Levels can be as high as 15 C.
TIME were modeled through a exponential distribution, and considering consumption after expiry date. Carrasco et al, 2008 determined that 9.9 % consumers use salad bags after expiry date.
This study also confirms that 46 % consumers use part of the salad bag keeping the rest in refrigeration for next use. No data about storage time once bags are opened.
Modeling Dose-response
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
• Various D-R models were simulated (Strachan et al., 2005; Teunis et al., 2008) :
– Beta-Poisson D-R Model (Strachan et al., 2005)P_ill =1-(1+(Dose/2.22) -0.057)
– Exponential D-R model (Strachan et al. 2005 )P_ill= 1-exp(-Dose*0.0011)
Simulation Parameters• Simulation:
– The model was simulated by applying “Latin Hypercube Sampling” technique implemented in the Software @Risk Palisade ©.
– The simulation consisted in 10 uncertainty realizations and 5,000 variability iterations.
– Simulation Seed used by RNG was fixed to 1 to make comparable results from different uncertainty realizations.
– Outputs:• prevalence and concentration of E. Coli O157:H7 at the end of the
processing line (bags).• Burden of illness: number of cases per batch.
– Results were plotted in graphs and statistics were calculated.
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Simulation Parameters
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Departamento de Bromatología y Tecnología de los Alimentos. Universidad de Córdoba
Grupo HIBRO
Thank you