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Using meta-analysis to underpin a risk assessment model for the estimation of prevalence of Salmonella spp. on pork joints produced in Irish slaughterhouses Ursula Gonzales-Barron 1 , Ilias Soumpasis 1 , Francis Butler 1 & Geraldine Duffy 2 1


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SLIDE 1

Using meta-analysis to underpin a risk assessment model for the estimation of prevalence of Salmonella spp. on pork joints produced in Irish slaughterhouses

Ursula Gonzales-Barron1, Ilias Soumpasis1, Francis Butler1 & Geraldine Duffy2

1UCD School of Agriculture, Food Sci. & Vet. Med. 2Ashtown Food Research Centre, Teagasc

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SLIDE 2

Introduction

 Foodborne

salmonellosis is a major public health issue and requires concerted efforts to control the pathogen in the food supply.

 Pork is one of the main sources for human

salmonellosis (5-30% of human cases).

 The primary source of Salmonella in the whole

pork production chain is the Salmonella- infected animal.

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SLIDE 3

...Introduction

 In the slaughter process, contamination of 30%

  • f

Salmonella-positive carcasses arises from cross-contamination of other infected pigs in the slaughterhouse.

 Numerous researchers have observed that there

is a strong association between the proportion

  • f

sub-clinically infected pigs entering the slaughter lines (carrying

  • r

excreting Salmonella) and the proportion of contaminated carcasses at the point of evisceration.

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SLIDE 4

Objective

 To estimate the prevalence of Salmonella on pig

carcasses and pork joints produced in Ireland using quantitative risk assessment techniques.

 To this effect, a stochastic relationship between

Salmonella prevalence in pigs’ caeca and Salmonella prevalence on eviscerated carcasses was built taking into account sensitivities.

 Validation

  • f

results: Parallel study

  • n

the incidence

  • f

Salmonella

  • n

pork

  • yster

cuts (n=720) produced in the boning halls

  • f

commercial pork abattoirs of Ireland.

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SLIDE 5

Methodology

Scalding Stunning, killing and bleeding Evisceration Final washing Chilling Splitting and trimming Jointing Prevalence in caecal contents Weighted regression Dehairing, singe, and polishing

Meta-analysis

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Proportion of slaughter pigs carrying Salmonella in caeca Proportion of resulting Salmonella- positive eviscerated carcasses r2 = 0.77

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SLIDE 6

Proportion

  • f

slaughter pigs carrying Salmonella entering the slaughter lines (x’)

  • x = sC / nC = positive caecal samples / total number of

samples

  • Correcting x for culture sensitivities (Se) of Salmonella 

x’

Source Proportion + caecal samples (x) Culture Culture Se Estimated protocol Se Corrected Prop+ caec samples (x’) Duggan (2008) Sorensen (2004) Kranker (2003) Quirke (2001) Davies (1999) Morgan (1987) Oosterom (1985) 87/193 216/1658 22/122 61/419 256/2205 71/149 35/145 28/151 44/220 PCR-MSRV NMKL NMKL RV+BGA DIASSALM RV+XLD TB+BGPRA 0.950 0.450 0.450 0.950 0.892 0.710 0.710 0.710 0.860 0.880 0.450 0.450 0.460 0.892 0.710 0.710 0.710 0.797 99/193 480/1658 31/122 133/419 287/2205 100/149 49/145 39/151 55/210

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SLIDE 7

…Proportion

  • f

slaughter pigs carrying Salmonella

  • Se values of culture protocols were relative to

faecal contents and NOT to caecal contents in pigs.

  •  x’ cannot be regarded as true prevalence.
  • Corrections

provided a reliable metric to equalise the studies minimising the level of between-study heterogeneity.

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SLIDE 8

Source Proportion + carcass (y) Relative Se Swab extent (cm2) Estimated protocol Se Corrected Prop+ carcass (y’) Duggan (2008) Sorensen (2004) Kranker (2003) Quirke (2001) Davies (1999) Morgan (1987) Oosterom (1985) 29/191 159/1665 6/117 42/419 155/2211 41/150 19/148 14/150 27/210 1 0.985 0.985 0.985 0.985 0.985 0.985 0.985 0.985 1000 1400 300 Entire 1000 1000 1000 1 0.985 0.550 0.985 0.985 0.985 0.985 0.985 0.985 29/191 161/1665 11/117 43/419 157/2211 42/150 19/148 14/150 27/210

  • y = sS / nS = positive carcass swabs / total number of carcass swabs.
  • Se of carcass swabs for every protocol could not be found in the literature.
  • Malorny et al. (2003): PCR method in relation to traditional culture methods for

pig carcass swabs (Se=0.985).

  • Reasonable to correct sS in terms of PCR.

Proportion of resulting Salmonella positive carcasses at the point of evisceration (x’)

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SLIDE 9

Adding weights to individual studies

  • (x’, y’) data pairs have been extracted from different studies

presenting different degrees of precision.

  • In meta-analysis, a common method of weighting individual

estimates is by their inverse variances.

Source Log-relative risk (log RR) se(RR) Weight (ωi) Duggan (2008) Sorensen (2004) Kranker (2003) Quirke (2001) Davies (1999) Morgan (1987) Oosterom (1985)

  • 1.217
  • 1.097
  • 0.994
  • 1.129
  • 0.606
  • 0.874
  • 0.968
  • 1.018
  • 0.712

0.184 0.084 0.326 0.161 0.094 0.143 0.244 0.289 0.214 29.27 141.03 9.39 38.45 111.75 48.94 16.83 11.94 21.88 Fixed effects meta-analysis for RR, U test =368 P<0.001

C C C C S S S S i

n s s n n s s n RR se

' ' ' ' 2

) (

2

1

i i

RR se

  • Effect size

parameter: RR

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SLIDE 10

Stochastic weighted linear regression

  • Non-parametric

Bootstrap technique added uncertainty to m, c, and s.

  • B

Bootstraps samples {(x’1, y’1)*, (x’2, y’2)*…, (x’9, y’9)*} are created, where each (x’i, y’i)* is a random sample with replacement from {(x’1, y’1), (x’2, y’2)…, (x’9, y’9)}.

  • For every Bootstrap sample, a weighted linear

regression was fitted to the data using ωi  mB, cB and sB were calculated.

  • 50 000 Bootstrap samples were taken.
  • Distributions were fitted for m, c and s.
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SLIDE 11
  • m  average 0.0193, standard deviation 0.0435
  • c  average 0.2909, standard deviation 0.1344
  • s  average 0.0502, standard deviation 0.0193
  • Having

defined an estimate

  • f

prevalence

  • f

Salmonella-carrier slaughter pigs (Pc), the Salmonella prevalence on eviscerated pig carcasses (Pev) is approximated as:

s c Pc m Normal Pev ,

…Stochastic weighted linear regression

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SLIDE 12

Effect of splitting and trimming

 Alban and Stark (2005)  Prev. increase of 16%  Davies et al. (1999)  Incidence increase in 50%

Pev Csp Psp 1 Effect of final rinsing

 Davies et al. (1999): Salmonella-positive results

from two abattoirs before final rinsing (15/75) and after final rinsing (9/79).

50 . , 16 . , Pert Csp

1 15 75 , 1 15 1 9 79 , 1 9 Beta Beta Rfr

Rfr Pev Pfr

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SLIDE 13

Effect of chilling

 A reduction effect of chilling

  • n

the recovery

  • f

Salmonella from pork carcasses has been

  • bserved

by many researchers.

 Thus,

data

  • n

Salmonella prevalence on pig carcasses before chilling and after chilling were taken from 9 published studies.

 Parametric

meta-analysis was conducted  Effect size measured was the “relative risk” of chilling.

Study 1 Study 2 Study 3 Study 4 Study 5 Study 6 Study 7 Study 8 Study 9 Fixed

  • 5
  • 4
  • 3
  • 2
  • 1

1 2

Log relative risk (log pT/pC)

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SLIDE 14

...Effect of chilling

RR for chilling = Probability

  • f

encountering Salmonella- positive carcasses after chilling relative to the probability of encountering Salmonella-positive carcasses before chilling.

The distribution of the reduction factor for the overall effect of the chilling operation (Rch) was therefore approximated by meta-analysis conducted on RR. 166 . , 868 . Normal

e Rch

X <= 0.303 2.5% X <= 0.581 97.5%

1 2 3 4 5 6 7

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Reduction in detected Salmonella prevalence due to chilling (Rch)

Probability density

Pfr Rch Pch

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SLIDE 15

Increase in contamination in boning halls

 Berends et al. (1998): AP=0.67 of inadequate disinfection

in cross contamination of pork with Salmonella spp. during the first 2 hours of production  when the risk factor prevails, it provokes about two thirds of the total cross- contamination during the first production hours.

 Based on survey of Salmonella presence in Irish boning

halls, the probability of inadequate cleaning and disinfection was defined as,

 According to Berends et al. (1998), disinfection takes place

1-4 times a day (Np=Discrete (1,2,3,4)).

 The probability that disinfection is poorly performed at least

  • nce a day (picd’) is

30 . , 20 . , Pert picd

Np icd

Pert p 30 . , 20 . , 1 1

'

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SLIDE 16

…Increase in contamination in boning halls

Contribution of inadequate cleaning and disinfection (Cicd) on a particular day with respect to the cross-contamination that

  • ccurs during the first two production hours is

With respect to all cross-contamination that occurs during a full working day

  • f

8 h., the contribution

  • f

inadequate cleaning and disinfection (Cicd’) is

Thus, the prevalence of Salmonella in pork joints (Pj), which is the final model output, was estimated as

' icd icd

p AP C

8 2

' icd icd

C C

'

1

icd

C Pch Pj

~(1-C’icd)% ~C’icd%

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SLIDE 17

Model validation using Irish data

The model’s ability to produce accurate estimates, and intrinsically the effectiveness of the modeling capabilities of meta-analysis, were appraised using Irish data for the input parameter of prevalence of Salmonella-carrier slaughter pigs (Pc).

Pc for Ireland was estimated in the following way:

Source x=sC/nC Culture Culture protocol Se x’=sC’/nC Duggan et al. 87/193 PCR-MSRV 0.880 107/193 Quirke et al. 61/419 RV+BGA 0.460 133/419 UCD study 85/471 TB+BGPRA 0.797 99/471 POOLED DATA 339/1098

Pc=Beta(339+1,1098-339+1)

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SLIDE 18

...Model validation using Irish data

  • The model’s output (Pj) was compared to the results of

an extensive survey of Salmonella incidence in pork joints produced in the boning halls of four representative Irish abattoirs.

  • This separate survey study of Salmonella prevalence and

counts on pork joints covered an aspect within the same research project, and it is explained in detail in Prendergast et al. (2008).

  • The risk assessment model was developed in Microsoft

Excel using the @Risk add-in (Industrial Edition 4.5.2, Palisade, NY), and run for 20 000 iterations using Latin Hypercube sampling. The weighted regression for 50 000 Bootstrap samples was performed in Matlab 7.1 (The Mathworks Inc, Natick, MA).

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SLIDE 19
  • Batches
  • f

Salmonella-positive slaughter pigs entering the abattoir impart a force

  • f

contamination during processing, that explains ~75- 80% of the total contaminated carcasses at the beginning of the clean line.

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Proportion of slaughter pigs carrying Salmonella in caeca

Proportion of resulting Salmonella- positive eviscerated carcasses

r2 = 0.77

  • The principal sources of microbial contamination during the processing
  • f pigs:
  • Contamination from carrier animals (sub-clinically infected)
  • Cross-contamination from equipment, machinery inadequately

disinfected from previous batches, staff practices.

Results and Discussion

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SLIDE 20
  • The pool of Irish surveys on Salmonella prevalence in caecal

contents of slaughter pigs (Pc) led to an estimate of 31.3% (95% CI: 28.6 – 34.1%) which is regarded to be a value close to the true prevalence.

Observed incidence (underestimated values)

  • Cross-sectional study at four pig abattoirs in Northern Ireland, 31.4%

(161/513) of slaughter pigs tested positive for Salmonella in caecal culture.

  • UK national survey  23% (578/2509) of the caecal samples were

Salmonella positive in 34 pig abattoirs.

  • France national survey  24.8% (256/1030) of caecal samples tested

positive for Salmonella in 18 pig abattoirs.

  • Denmark

and The Netherlands have reported significantly lower incidence of Salmonella-carrier slaughter pigs (8.0% and 8.5%)  severity of the application of national programmes for Salmonella control at farm level?

…Results and Discussion

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SLIDE 21
  • Prevalence
  • f

Salmonella

  • n

eviscerated pig carcasses in Ireland. Pev=11.9%, 95%CI: 0.7- 26.8% Observed incidence

  • Pearce

et al. (2004)  recovered 10% positive swabs after evisceration from an Irish abattoir.

  • In

the Spanish region

  • f

Catalonia (Creus, 2007), Salmonella incidence found on pig carcasses after evisceration was 11.1% (40/360, 95%CI of 8.1-14.9%) sampled in three large slaughterhouses.

0.0 0.2 0.4 0.6 0.8 1.0 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Prevalence of Salmonella on eviscerated pig carcasses Cumulative probability

…Results and Discussion

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SLIDE 22
  • After splitting and trimming, reduction in Salmonella levels may

be related to the removal of residual contamination during the spraying of the carcasses, performed in order to remove bone and blood clots.

  • Thus, Salmonella prevalence on finished carcasses (after final

rinsing and before chilling) was estimated to be Pfr=8.8%, 95%CI: 0.5-24.6% Observed incidence (underestimated values)

  • While figures cannot be directly comparable since they have not

been corrected for culture protocol sensitivities nor are methods fully harmonised among countries, according to the last EFSA report, the average Salmonella incidence on carcass swabs detected among European slaughterhouses in 2006-2007 was 8.3% (95% CI: 6.3-11.0%).

…Results and Discussion

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SLIDE 23

X <= 0.003 2.5% X <= 0.115 97.5% 5 10 15 20 0.00 0.04 0.08 0.12 0.16 0.20 0.24

Simulation's output Fitted distribution Validation results

Probability density Prevalence of Salmonella in pork joints produced in Ireland

Mean = 0.033 Mean = 0.040

Output distribution of Salmonella prevalence in pork cuts produced in Ireland

Irish survey: Sampling pork cuts in boning halls Mean: 3.33% (24/720) 95% CI: 2.02 - 4.64%

…Results and Discussion

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SLIDE 24

Distribution of Salmonella prevalence in pork joints in Ireland as an

  • utput
  • f

the regressional model in contrast to a previously-developed stage-by-stage model

Stage-by-stage model

  • No meta-analysis
  • No

stochastic weighted regression

  • Contamination

and decontamination factors were used for each stage from bleeding to jointing

5 10 15 20 25 30 35 0.00 0.05 0.10 0.15 0.20

Prevalence of Salmonella in pork joints produced in Ireland

Stage-by-stage model Validation results Regressional model

Probability density

Mean = 0.034 Mean = 0.040

…Results and Discussion

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SLIDE 25

 Key

parameters having more influence

  • n model’s output.

 Reaffirmation

that final rinsing and chilling are efficient at controlling carcass contamination  CCP

 Expected

that final rinsing with hot water would further decrease Salmonella prevalence

  • 0.382
  • 0.221

0.106

  • 0.030

0.019

  • 0.6
  • 0.4
  • 0.2

0.0 0.2 0.4 0.6

Rfr Rch Csp Np

Correlation Coefficients Variables

picd

…Results and Discussion

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SLIDE 26

Conclusions

 A risk assessment

model was built on the assumption that the occurrence of Salmonella- infected carcasses post-evisceration is proportional to the total contamination introduced by the carriers animals themselves entering the slaughter lines.

 The

model

  • utput

for the Salmonella prevalence on pork joints produced in boning halls was successfully validated with the results

  • f an extensive survey carried out in four large

Irish abattoirs.

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SLIDE 27

...Conclusions

 The

suitability

  • f

meta-analysis for integrating different findings and producing distributions for use in stochastic modelling was demonstrated.

 Final rinsing and chilling had strong impact on the

prevalence of Salmonella on pork joints.

 According

to this model, interim cleaning and disinfection in the boning halls has only a marginal effect on diminishing the amount of contaminated pork joints produced.  as long as contaminated carcasses are being processed, about 90% of the cross-contamination is unavoidable.

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SLIDE 28

Future Work

 This

model

  • nly

considers the contamination force inflicted by carriers animal. Future models should incorporate parameters for the cross-contamination from equipment, inadequate disinfection from previous batch, etc.

 Data gaps:

 Lack of research on presence of Salmonella on the

skin of pigs entering the abattoir;

 Insufficient experiments for modelling the scalding

process;

 Sensitivity values cannot be found for all culture

protocols.

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SLIDE 29

Acknowledgments

SafeFood, QPorkChains and the Irish Department of Agriculture, Fisheries and Food

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SLIDE 30

Thanks for your attention