Research Paper

A Quantitative Risk Assessment of Human Salmonellosis fromConsumption of Walnuts in the United States

SOFIA M. SANTILLANA FARAKOS,1* RÉGIS POUILLOT,1 GORDON R. DAVIDSON,1 RHOMA JOHNSON,1

INSOOK SON,1 NATHAN ANDERSON,2 AND JANE M. VAN DOREN1

1U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, Maryland 20740 (ORCID: http://orcid.org/0000-0002-6107-5212 [R.P.]); and 2U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, Bedford Park, Illinois 60501, USA

MS 18-233: Received 25 May 2018/Accepted 30 August 2018/Published Online 26 December 2018

ABSTRACT

We assessed the risk of human salmonellosis from consumption of shelled walnuts in the United States and the impact of 0-to 5-log reduction treatments for Salmonella during processing. We established a baseline model with Salmonella contaminationdata from 2010 to 2013 surveys of walnuts from California operations to estimate baseline prevalence and levels of Salmonelladuring preshelling storage and typical walnut processing stages, considered U.S. consumption data, and applied an adapted dose-response model from the Food and Agriculture Organization and the World Health Organization to evaluate risk of illness perserving and per year. Our baseline model predicted 1 case of salmonellosis per 100 million servings (95% confidence interval[CI], 1 case per 3 million to 1 case per 2 billion servings) of walnuts untreated during processing and uncooked by consumers,resulting in an estimated 6 cases of salmonellosis per year (95% CI, ,1 to 278 cases) in the United States. A minimum 3-logreduction treatment for Salmonella during processing of walnuts eaten alone or as an uncooked ingredient resulted in a meanrisk of ,1 case per year. We modeled the impact on risk per serving of three atypical situations in which the Salmonella levelswere increased by 0.5 to 1.5 log CFU per unit pretreatment during processing at the float tank or during preshelling storage orposttreatment during partitioning into consumer packages. No change in risk was associated with the small increase in levels ofSalmonella at the float tank, whereas an increase in risk was estimated for each of the other two atypical events. In a fourthscenario, we estimated the risk per serving associated with consumption of walnuts with Salmonella prevalence and levels froma 2014 to 2015 U.S. retail survey. Risk per serving estimates were two orders of magnitude larger than those of the baselinemodel without treatment. Further research is needed to determine whether this finding reflects variability in Salmonellacontamination across the supply or a rare event affecting a portion of the supply.

Key words: Low-moisture food; Recontamination; Retail; Salmonella; Shelled; Tree nuts

The United States is a leading exporter of Englishwalnuts (75% of world trade), with 99% of its production(686,000 short tons in 2016 (39)) in California (7). The U.S.harvest occurs once per year and begins with maturewalnuts being mechanically shaken to the ground, sweptinto trailers, and transported to the huller-dryer. At thehuller-dryer, walnuts are mechanically precleaned toremove sticks and leaves, passed through a float tank(which generally does not contain an antimicrobial agent) toremove rocks and other debris, passed through a mechanicalhuller where the hull (if still present) is removed, and thendried by forced heated air in bins to approximately 8%moisture. Following drying, walnuts are stored at 10 to158C for up to 1 year, sized, graded, and sold as inshell nutsor shelled and packaged as halves or pieces (16). Asreported by the California Walnut Board (7), in the 2015 to2016 and 2016 to 2017 marketing years approximately 42and 47%, respectively, of walnuts produced in California

were inshell walnuts, and the majority of these (.95%)were exported. The remaining 58 and 53%, respectively,were sold as kernels (~40% domestic and ~60% exported).These percentages as reported for 2015 and 2016 are similarto those reported for the 2011 to 2012 marketing year byBlessington et al. (5).

The presence of Salmonella on walnuts has led torecalls in 2010 (halves and pieces), 2012 (inshell), 2014(pieces), and 2015 (two separate recalls of chopped and ofhalves and pieces) (28). However, no human salmonellosisoutbreaks have been linked to walnuts (22). A multiyear(2010 to 2013) survey (3,838 samples) of Salmonellaprevalence and contamination levels on inshell walnutsduring preprocess storage revealed prevalences of ,0.11%(2010; 100-g samples; 95% confidence interval [CI], 0 to0.41%) and 0.14% (2011 to 2013; 375-g samples; 95% CI,0.054 to 0.35%), with contamination in positive samples of0.32 to 0.42 most probable number (MPN)/100 g (12). A2014 to 2015 survey of the prevalence and levels ofSalmonella on shelled walnuts at retail in the United States(658 samples) conducted by the U.S. Food and Drug

* Author for correspondence. Tel: 240-402-2816; Fax: 301-436-2633;E-mail: sofia.santillanafarakos@fda.hhs.gov.

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Journal of Food Protection, Vol. 82, No. 1, 2019, Pages 45–57doi:10.4315/0362-028X.JFP-18-233Published 2019 by the International Association for Food Protection

Not subject to US Copyright. This is an open access article

Administration (FDA) revealed a higher Salmonellaprevalence of 1.22% (375-g samples; 95% CI, 0.53 to2.40%) and contamination of ,0.30 to 0.36 MPN/100 g(43). In a subsequent 2015 to 2016 FDA retail survey in theUnited States, no Salmonella-positive samples were foundamong the 498 retail samples examined (19). Inshellwalnuts can become contaminated in the orchard throughapplication of foliar sprays mixed with contaminated wateror by animal intrusion, during harvest through direct contactwith contaminated soil, during handling at the huller-dryer,and during storage. Contaminants on the shell can furthertransfer to the kernel during cracking and shelling or duringfurther processing (5). The marketing order issued by theU.S. Department of Agriculture, Agricultural MarketingService (38) does not require handlers to subject theirwalnuts to a treatment process to reduce Salmonella. Theproportion of walnuts sold in the United States that havebeen treated by one or more processes is not known.Processes that may be used by walnut processors includepropylene oxide and steam treatments (23).

The objective of this study was to conduct aquantitative risk assessment of human salmonellosis arisingfrom the consumption of walnut kernels in the United Statesand to evaluate the impact of Salmonella reductiontreatments on that risk to inform risk managementdecisions. We used the 2010 to 2013 survey contaminationdata on inshell walnuts during preprocess storage publishedby Davidson et al. (12) as the starting point of thequantitative model and examined six levels of Salmonellareduction treatments: no treatment and reduction by 1, 2, 3,4, or 5 log CFU). We also estimated the impact on publichealth risks of atypical Salmonella recontamination eventsthat can occur during walnut processing, either pre- orposttreatment. We then evaluated risk estimates using theSalmonella contamination levels found in the 2014 to 2015retail samples from U.S. retail markets published by Zhanget al. (43) and compared these values to those obtained withthe baseline model. To our knowledge, this is the firstpublished quantitative microbiological risk assessment forSalmonella on walnuts.

MATERIALS AND METHODS

Overview of the exposure assessment model for Salmo-nella on walnuts. We assessed prevalence and levels ofSalmonella on walnuts starting from storage at the sheller up tothe point of consumption (Fig. 1). The assessment includes themajor steps in a production process for walnuts to be sold shelled.These steps include preshelling storage (at ~10 to 158C for ,1week to 14 months), shelling, potential Salmonella reductiontreatment, partitioning (into smaller units and consumer-sizepackages and bags), and postprocess storage (at ~20 to 248C for,1 to 9 weeks). A treatment to reduce Salmonella levels by 1, 2,3, 4, or 5 log CFU was included to evaluate the impact of atreatment on the risk of salmonellosis. Minor variations to thisproduction process scheme could exist, depending on theoperation. In the absence of more detailed information, weassumed that the minor variations for individual shellers would notsignificantly change the prevalence or levels of Salmonella onwalnut kernels and thus would not impact the estimated riskobtained in this assessment. Consumer home storage was notincluded in the exposure assessment model because consumer

storage practices at home were considered beyond the scope ofthis risk assessment (i.e., not part of risk mitigation for regulatorypurposes) (34–36). The exposure assessment model thus assumesthat walnuts are consumed after purchase with no further storage.However, if the consumer stored walnuts at room temperature (20to 258C) or in the refrigerator or freezer after purchase, Salmonellalevels would be maintained (refrigeration or freezing) or woulddecrease (ambient temperature), depending on the time-tempera-ture characteristics of storage (4). The model does considerwhether the product would be consumed as purchased or would beused in a product further cooked by the consumer (e.g., as aningredient in a cooked food).

Certain exposure assessment process steps are expected tochange the Salmonella prevalence and/or levels on inshell walnutsand/or walnut kernels (Fig. 1). For instance, a decrease inSalmonella (both prevalence and levels) is expected as a result ofdry storage at ambient temperature (~20 to 258C) (4, 5), hot airdrying (20), a Salmonella reduction step (e.g., propylene oxide gasor steam treatment), or cooking in the home. No change inSalmonella level is expected as a result of partitioning of walnutunits (Salmonella cells would be only redistributed). Salmonellalevels would not be expected to change postpurchase (in the home)when walnuts are consumed without further cooking. As inprevious FDA tree nut risk assessment models (34–36), this model

FIGURE 1. Walnut production steps (left) and expected change inSalmonella levels (right) as a result of the correspondingproduction step. Salmonella prevalence and levels of contamina-tion as reported by Davidson et al. (12) were used as initial levelsin baseline risk assessment model. Preshelling storage is the pointin production where the baseline model begins. Asterisks indicatepoints in production associated with alternative scenariosmodeling atypical events or other situations: *1, atypical situation1: cross-contamination with Salmonella at the float tank; *2,atypical situation 2: contamination with Salmonella duringpreshelling storage; *3, atypical situation 3: posttreatmentrecontamination with Salmonella before partitioning into lotsand bags; *4, retail risk assessment model with Salmonellaprevalence and levels of contamination at consumption asreported by Zhang et al. (43) from the 2014 to 2015 U.S. retailsurvey.

46 SANTILLANA FARAKOS ET AL. J. Food Prot., Vol. 82, No. 1

considers variability and uncertainty of parameters separately toaccurately estimate risk (14, 17, 27) and to provide a measure ofthe uncertainty of the estimated number of salmonellosis cases peryear. We also evaluated the probability of contamination andSalmonella levels separately for each step throughout theproduction process for better accuracy (10, 30). The modelincludes the survival parameters for Salmonella on tree nutsdeveloped previously by our research group (33), which includedquantified survival parameter variability and uncertainty.

Estimating prevalence and level of Salmonella on walnutsduring storage. We used data from the 2010, 2011, 2012, and2013 surveys published by Davidson et al. (12) in this assessment.These data are the only prevalence data at the processor known tobe available. The 3,838 inshell walnut samples were collectedfrom 15 walnut operations located throughout five walnut growingregions in California, which process approximately half the totalproduction volume harvested in the state. Samples were shipped toDFA of California (Safe Food Alliance, https://dfaofcalifornia.com/), stored at 48C, and subjected to microbiological analysiswithin 3 months of collection. Subsamples of 100 g in 2010 and375 g in 2011, 2012, and 2013 were analyzed for Salmonella byAOAC official method 2001.09 (mini VIDAS assay system) (1).Positive results were confirmed using standard culture methods,and Salmonella levels were determined using the FDA Bacteri-ological Analytical Manual (42). We determined a rarity index foreach MPN pattern as described in Blodgett (6). The rarity index isdefined as the probability of observing a given pattern for theMPN divided by the probability of observing the most probablepattern for that MPN. A pattern was defined as rare when the rarityindex was ,0.05 (6). None of the patterns as analyzed weredefined as rare, indicating a homogeneous distribution of thepathogen within the unit of product (i.e., the unit size in grams)and no error or issue in the protocol.

We fit the observed MPN patterns to a lognormal distributionof sample Salmonella levels (32) and estimated uncertainty aroundthe mean and standard deviation (SD) using a parametric bootstrapprocedure (13).

A unit was defined as an independent unit quantity of walnuts(inshell or kernels) in mass (measured in grams). For eachiteration of the simulation, one mean and SD of the Salmonellalevel per unit was sampled from a coupled mean-SD (μu, σu; tokeep the correlation structure) of the bootstrap samples torepresent uncertainty. The size of a unit at the sheller step of thewalnut production process was estimated to follow a triangulardistribution with a minimum of 1,000 kg, a mode of 11,350 kg,and a maximum of 11,350 kg (20). This unit size changes as aresult of partitioning posttreatment (see ‘‘Partitioning’’). Through-out the risk assessment model, the minimum level in Salmonella-positive units was 1 CFU, and all Salmonella levels are wholenumbers.

Estimates for the prevalence (probability of having at leastone Salmonella cell in the given food unit) and level ofcontamination (modeled as a discrete CFU per positive unit, i.e.,a unit containing .0 Salmonella cells) were tracked separatelythroughout the simulation. We assumed that the Salmonella cellswere Poisson distributed in a given unit (homogeneous distribu-tion). The initial prevalence was then defined as

P0 ¼ 1� exp �k3 sð Þwhere log(λ) ~ Normal(μu, σu) is the Salmonella level per gram inthe unit and s is the size of the unit (in grams)

Salmonella survival during storage. Storage of walnuts insilos occurs at 10 to 158C, and storage times (in weeks) vary. Wemodeled storage time as 5% of storage times follow a triangulardistribution (minimum¼ 0, mode¼ 2, maximum¼ 2 weeks), 90%of storage times follow a uniform distribution (minimum ¼ 2,maximum¼ 49 weeks), and 5% of occurrences follow a triangulardistribution (minimum ¼ 49, mode ¼ 49, maximum ¼ 73 weeks)(20). Storage of walnuts postprocessing (posttreatment and retail)was modeled to occur 80% of the time at ~238C and 20% of thetime at refrigeration temperatures, all for a period of 3 weeks (20).

Santillana Farakos et al. (33) developed a Weibull model thatconsiders variability and uncertainty separately to predict survival ofSalmonella on almonds, pecans, pistachios, and walnuts at ambientstorage temperature (21 to 248C). This model was developed usingsurvival data on both inshell and shelled walnuts collected at arelative humidity below 50% (4, 5). Frelka et al. (16) collectedSalmonella survival data at ~108C on inshell walnuts stored at~65% relative humidity (commercial operation) and obtained areduction rate of 0.33 log CFU per nut per month. When we fit aWeibull model to the ~108C survival data of Frelka et al. andcompared the results to the~238Cmodel of Santillana Farakos et al.(36), we found the time to the first log reduction was shorter at~108C than at 238C, which was unexpected. This results waspresumed to be due to the higher humidity in the experiments ofFrelka et al. at ~108C; survival of Salmonella in low-water-activityfoods increases with decreasing temperature and water activity (2,29, 37). The model of Santillana Farakos et al. (33) specific towalnuts obtained at 21 to 248C was used in this risk assessment forboth preshelling storage at ~10 to 158C and postprocess storage at238C. Comparing the results we obtained with the result we wouldhave obtained using the reduction rate of Frelka et al., no differencein the estimated risk per year was found.

We assumed that the decrease in Salmonella levels wasnegligible when the 3-week postprocess storage period occurred atrefrigeration temperature based on the reduction of 0.1 log CFUper nut per month at 48C reported by Blessington et al. (3, 5).

In the Weibull model, the survival rate depends on time;therefore, it is necessary to consider the survival curve at the startof survival. The probability that a Salmonella cell selected atrandom will survive from time t1 to time t2 (a specified storagetime) is defined as

Psurv ¼ 10�t2q�t1

q

dq

� �where δ is the time it takes to reduce the population by 1 log, ρ is aparameter that defines the shape of the curve, and t1 and t2 aretimes since the beginning of the survival step (t0). In the presentassessment, t0 is defined as the start of the storage step for walnutsat the silo. We used a binomial process restricted to positive valuesto evaluate the level of Salmonella in positive units at the end ofeach stage of the exposure assessment model:

N2 ;Binomial N1;Psurvð Þ; with N2 . 0

where N2 is the level of Salmonella in the contaminated unit at theend of survival (t2) and N1 is the level of Salmonella in thecontaminated unit at the beginning of survival (t1). The binomialmodel assumes that each Salmonella cell has an independentprobability of survival. The probability of contamination isaccordingly adjusted to

P2 ¼ P1 1� 1� Psurvð ÞN1

h iaccounting for units in which there are no Salmonella remaining,where Psurv and N1 are defined as above, P2 is the probability of

J. Food Prot., Vol. 82, No. 1 RISK ASSESSMENT OF SALMONELLA ON U.S. SHELLED WALNUTS 47

contamination at the end of survival (t2), and P1 is the probabilityof contamination at the beginning of survival (t1).

Shelling. After storage, inshell walnuts to be sold shelled arecracked to remove the shell. In the absence of available data onSalmonella transfer rates from shell to kernel, we assumed allSalmonella present inshell would transfer to the shelled product(worst case scenario). Thus, no change in prevalence and levels ofcontamination were modeled.

Salmonella reduction treatment. We modeled six reductiontreatment scenarios: no Salmonella reduction and reduction ofSalmonella levels by 1 to 5 log CFU. The treatment levels weredefined per unit of product being treated. Variability in treatmentreduction was not considered because data were unavailable. Theimpact of a specific treatment level on the risk of salmonellosiscan be derived from the results provided in this risk assessmentwhen the reduction value or range of values is known. For theSalmonella reduction treatment step, we assumed that eachSalmonella cell had an identical and independent probability ofinactivation. We used a binomial process restricted to positivevalues to evaluate the level of Salmonella at the end of this stage:

PsurvT ¼ 10�L

N2T ;Binomial N1T ;PsurvTð Þ; with N2T . 0

P2T ¼ P1T 1� 1� PsurvTð ÞN1T

h iwhere L is the log reduction (1, 2, 3, 4, or 5 log CFU), PsurvT is theprobability of survival at the Salmonella reduction treatment level,P2T is the probability of contamination posttreatment, P1T is theprobability of contamination pretreatment, N2T is the level ofSalmonella in the contaminated unit posttreatment, and N1T is thelevel of Salmonella in the contaminated unit pretreatment.

Partitioning. After the Salmonella reduction treatment andshelling, the units are redistributed into units of sizes from 45 to45,000 kg (20). The units are then further partitioned intoconsumer packages (shelled walnuts) from an 18-g snack pack to a224-g (~0.5 lb) or 454-g (~1 lb) bag. To evaluate the change inSalmonella levels per subunit as a result of partitioning, onesubunit (at random) is followed per iteration, and the probabilityof contamination and level of Salmonella for each step isestimated as follows:

N2 ;Binomial N1;S2S1

� �; with N2 . 0

P2 ¼ P1 1� 1� S2S1

� �N1" #

where N1, N2, P1, and P2 are defined as above and S1 and S2 referto the subunit sizes before and after partitioning, respectively.

Further partitioning at the consumer level is the ingesteddose, and that is a partition process from the size of the pack to theserving size (see ‘‘Consumption’’).

Cooking. Consumers can use walnuts as an ingredient incooked products (e.g., when baking cakes or cookies). Thesewalnuts are purchased as an uncooked ingredient (inshell orshelled) and are later cooked at home. No references were foundwith data specifically concerning Salmonella survival on walnutsduring baking. Lathrop et al. (26) collected survival data for

Salmonella in peanut butter during the baking of cookies. In thatstudy, commercial peanut butter was artificially inoculated with afive-serovar cocktail of Salmonella (serovars Tennessee, Tornow,Hartford, Agona, and Typhimurium). The inoculated peanut butterwas used to prepare peanut butter cookies using a standard recipe,and cookies were baked at 1778C for various times (10 to 15 min).A minimum of a 4.8-log decrease in Salmonella levels per cookie(25 g) were found after 10 min at 1778C (detection limit of 0.04CFU/g). Cookies baked for 15 min had no detectable Salmonella.Peanut butter, similar to walnuts, is a low-water-activity product.Although the composition of peanuts and peanut-related productsis different from that of walnuts, the main parameters influencingsurvival of Salmonella during heating of foods are temperatureand water activity, which are assumed to be similar for peanutsand walnuts. In the absence of available data and based on thesimilarity in product type and water activity, we assumed that theexpected log decrease in Salmonella levels during baking ofwalnuts approximates the minimum decrease that occurs duringbaking of peanut butter cookies. We used a fixed value of 5 logCFU for the reduction achieved during cooking for walnutsincluded as an ingredient in food products that undergo a cookingstep in the home.

Consumption. Consumption of walnut kernels in the U.S.population was estimated using data originating from What WeEat in America (WWEIA), the dietary survey portion of theNational Health and Nutrition Examination Survey (NHANES),for the 2003 to 2004, 2005 to 2006, 2007 to 2008, and 2009 to2010 cycles (9). Proportions of walnut ingredients in NHANES-WWEIA foods used in these analyses were based on ‘‘recipes’’developed for the U.S. Environmental Protection Agency's foodcommodity intake database (41). Empirical distributions repre-senting serving sizes among consumers (eaters) and weighted bythe NHANES-WWEIA dietary statistical sampling weights wereused for walnuts consumed as a core product uncooked, as aningredient uncooked, and as an ingredient cooked. We distin-guished between three independent types of walnut productsconsumed (where the cooking step, when present, is assumed tohappen in the home): (i) core walnut product (�80% of theproduct ingredients are walnuts) consumed uncooked, (ii) walnutas an ingredient (,80% of the product ingredients are walnuts)consumed uncooked, and (iii) walnut as an ingredient (,80% ofthe product ingredients are walnuts) consumed cooked (e.g., inbaked, fried, or boiled products). The cooking step in cookedwalnuts is cooking by the consumer and would not include, forinstance, walnuts sold as roasted. We estimated the number ofservings per year, assuming that data reported in the NHANES-WWEIA 24-h dietary recalls (two per survey respondent,conducted 3 to 10 days apart) are representative of consumptionover the whole year and estimating approximately 320 millionindividuals in the United States (40). The number of walnutservings per year in the United States was estimated givenNHANES-WWEIA data indicating that 1.51% of the populationreported consumption of uncooked walnuts as a core product,1.62% reported consuming uncooked walnuts as an ingredient,and 11.46% reported consuming cooked walnuts as an ingredient.

Modeling atypical situations in walnut handling. Atypicalsituations in the supply chain may change the risk of salmonellosisstemming from consumption of walnuts. Cross-contamination hasbeen identified as a mechanism for pathogenic bacterial contam-ination of low-water-activity foods (8, 29).

In this risk assessment, three atypical situations that couldlead to increases in risk per serving were evaluated. These atypical

48 SANTILLANA FARAKOS ET AL. J. Food Prot., Vol. 82, No. 1

situations included both pre- and posttreatment recontaminationevents and were modeled for walnuts consumed as a core product(i.e., consumed as bought or as an ingredient in a food that is atleast 80% walnuts) not cooked at home. These atypical situationswere not modeled for the entire U.S. walnut supply but asindividual events impacting a portion of the supply. The number ofsalmonellosis cases per year linked to each atypical situationwould be equal to the number of cases linked to one atypicalsituation multiplied by the number of such atypical situations inthat year. Although it is not possible to predict the number of casesper year for each atypical situation because it is not known howmany such events occur in a year, the risk estimates obtained forthose situations we modeled provide an estimate of theirsignificance compared with the baseline model scenario and ofthe impact the atypical situation could have on risk (changes inorder of magnitude). In a fourth scenario, we evaluated riskestimates using the Salmonella contamination levels found in the2014 to 2015 retail samples from U.S. retail markets (43). The stepin the process where the atypical situations (1, 2, and 3) aremodeled to occur and where the retail model starts (situation 4) aremarked with asterisks (*1, *2, *3, and *4) in Figure 1.

In the atypical situation 1, cross-contamination at the floattank, water at the float tank becomes contaminated fromcontaminated walnuts and cross-contaminates other walnuts thatpass through the float tank. We assumed that the prevalence ofSalmonella was the same as in the baseline exposure assessmentmodel but that levels were increased by a fixed amount of 0.5 to1.5 log CFU per contaminated lot. The float tank step occursbefore drying, whereas the contamination data we used in thebaseline model were based on the levels after drying. To estimateprevalence and levels of contamination of Salmonella on walnutsat the float tank, a back-calculation from the values determined inthe silo storage (baseline model) was done, taking into account theimpact of drying. Drying was modeled based on data published byFrelka et al. (16), who found that Salmonella populationsdecreased by 2.57 log CFU (deterministic value) after dryingunder typical commercial conditions (warm air of ,438C for ~12h). The extra contamination with Salmonella of 0.5 to 1.5 log CFU(uniform distribution) was added to the back-calculated levels atthe flotation tank. The drying step (using the same decline as thatused for the back-calculation) was modeled followed by thesubsequent steps in the baseline model: preshelling storage,shelling, Salmonella reduction treatment, partitioning, posttreat-ment storage, and consumption.

In atypical situation 2, additional contamination duringpreshelling storage, increased levels of Salmonella on walnutsduring preshelling storage (0.5 to 1.5 log CFU per contaminatedlot) were modeled to represent a pest infestation in storage silos.The same prevalence as the baseline exposure assessment modelwas assumed, but levels of contamination were increased. The restof the process follows with the same steps as the baseline exposureassessment model: shelling, Salmonella reduction treatment,partitioning, postprocess storage, and consumption.

In atypical situation 3, posttreatment contamination, in-creased levels of Salmonella in contaminated units posttreatmentbut before partitioning into lots and bags (0.5 to of 1.5 log CFUper contaminated lot) were modeled assuming the same initialprevalence as the baseline exposure assessment model. The rest ofthe process follows with the same steps as those of the baselineexposure assessment model: partitioning, postprocess storage, andconsumption.

In the retail risk assessment model, scenario 4, prevalenceand levels found in the 2014 to 2015 FDA survey published byZhang et al. (43) were assumed to be those at retail and thus at the

point of consumption (1.22% prevalence; 375-g samples; 95% CI,0.53 to 2.40%), and levels of contamination were ,0.30 to 0.36MPN/100 g. The assay used to analyze the 2014 to 2015 FDAsurvey samples is the same as that used to estimate initial levels ofcontamination in the baseline exposure assessment model (42).

Hazard characterization. The dose-response model used inthis risk assessment is equivalent to the β-Poisson dose-responsemodel with parameters α¼ 0.1324 (95% CI, 0.094 to 0.1817) andβ ¼ 51.45 (95% CI, 43.75 to 56.39) derived by the Food andAgriculture Organization of the United Nations and the WorldHealth Organization (FAO-WHO) (17) adapted to the number ofSalmonella cells, which in our model is an exact value (β-binomialdose-response model (18)). The risk estimates obtained whenusing the 2.5th and 97.5th percentile of the FAO-WHO Salmonelladose-response curve (15) resulted in mean estimated risks thatwere in the same order of magnitude as that when using the FAO-WHO expected values (15). As such, no uncertainty in the dose-response was considered.

Risk characterization. Risk estimates per serving resultfrom combining the FAO-WHO dose-response function (15) withthe results of the exposure assessment module (levels ofSalmonella per contaminated serving and prevalence of contam-inated servings). Risk per year was then calculated by multiplyingthe number of servings by the risk per serving. The risk wasassessed using a second-order Monte Carlo simulation (17). MonteCarlo simulations were developed in R using the mc2d package(31). The variability dimension was set to 10,001 replicates, andthe uncertainty was set to 501 replicates (i.e., 501 replicates toevaluate uncertainty, and within each uncertainty loop 10,001replicates to characterize variability in model parameters). Thefactors for which variability and uncertainty was considered werethe probability of contamination, the Salmonella contaminationlevels, the survival model parameters, pretreatment and posttreat-ment storage times, and consumption patterns.

Sensitivity analysis. Spearman's rho statistic was deter-mined, with risk per serving as the outcome variable and lookingat risk estimates arising from consumption of walnuts as a coreproduct uncooked at home for no treatment and a 4-log Salmonellareduction treatment level. Factors considered were those for whichvariability and uncertainty were estimated and included initialcontamination levels, the time it takes to reduce the Salmonellapopulation by 1 log CFU (δ), pretreatment and posttreatmentstorage times, and consumption patterns.

All statistical analyses were carried out using R 3.4.2 (R CoreTeam, Vienna, Austria). The R code is available on request by e-mail to FDAFoodSafetyRiskModel@fda.hhs.gov.

RESULTS AND DISCUSSION

Baseline probabilities of Salmonella contaminationand levels of contamination throughout steps in theexposure assessment stage. Examination of the estimatedmean probability of Salmonella contamination and Salmo-nella levels (for contaminated units) at the end of each stageof the exposure assessment model for no treatment and for1-, 2-, 3-, 4-, and 5-log Salmonella reduction treatmentsrevealed a decrease in both of these quantities throughoutthe exposure model (Table 1). Gradually increasingreduction treatments (from 1 to 5 log CFU) result ingradually decreasing levels of Salmonella per unit, with an

J. Food Prot., Vol. 82, No. 1 RISK ASSESSMENT OF SALMONELLA ON U.S. SHELLED WALNUTS 49

approximately 10-fold decrease for every additional logreduction (Fig. 2). Among the factors considered in thebaseline model, these results indicate that treatment has thelargest impact on the probability of Salmonella contamina-tion and on levels in contaminated units (Table 1 and Fig.2). Although the mean level is 1 CFU per contaminated unitfor all treatments at the partitioning-into-packages stage, thelevels are not necessarily independent of treatment andpartitioning does not necessarily result in a decrease inSalmonella levels. Rather, contamination levels are ex-pressed per contaminated unit, and the units are partitionedto such a degree that they contain the minimum Salmonellalevel to be considered positive, which is 1 CFU. The impactof the treatment is thus mostly reflected in the probability ofcontamination for a given unit (Table 1). The lowerprobability of contamination per unit after partitioning(Table 1) is a result of the increase in the number of unitsthat contain zero Salmonella cells (which results from theredistribution of Salmonella cells into a higher number ofunits of smaller unit size).

Consumption. The mean (6SD) intakes per serving(based on NHANES-WWEIA 2003 to 2010 data) are 20.6(616.6) g for walnuts consumed as a core productuncooked at home, 4.77 (65) g for walnuts consumed asan ingredient uncooked at home, and 1.52 (62.34) g forwalnuts consumed as an ingredient cooked at home.

Risk estimates per serving. The distribution of theestimated risk per serving of walnuts represents theprobability of acquiring human salmonellosis in the U.S.population due to the consumption of a walnut serving(Table 2 and Fig. 3). Table 2 contains six sets of statistics(one for each Salmonella treatment level: no treatment and1-, 2-, 3-, 4-, and 5-log reduction) on risk from consumingthree types of walnut products: walnuts consumed as a coreproduct uncooked at home, walnuts consumed as aningredient uncooked at home, and walnuts consumed asan ingredient cooked at home. In Figure 3, risk of humansalmonellosis per serving for consumption of walnuts givena 1-, 2-, 3-, 4-, and 5-log Salmonella reduction treatmentrelative to the risk per serving from consumption of walnutsas an ingredient cooked at home (i.e., having received anadditional 5-log Salmonella reduction treatment throughcooking) is shown. The highest risk is associated withwalnuts consumed as a core product uncooked at home(walnuts that receive no cooking step at home), followed bywalnuts consumed as an ingredient uncooked at home, andto a lesser extent walnuts cooked at home beforeconsumption (Table 2 and Fig. 3). As the treatmentefficiency increases from a 1- to 5-log reduction, the meanrisk of salmonellosis per serving in the U.S. populationdecreases for all three types of walnut products consumed(Table 2 and Fig. 3). Variability (columns in Table 2)represents heterogeneity in the risk per serving (notreducible by data collection), and uncertainty (rows inTable 2) represents lack of knowledge (which can bereduced by additional data collection). The consideredvariability and uncertainty is included in the probability ofTA

BLE1.

Proba

bility

ofSalmon

ella

contam

inationan

dcontam

inationlevelsforeach

stag

eof

theexpo

sure

assessmentmod

elforwalnu

tstreatedwithasimulated

0-,1-,2-,3-,4-,an

d5-log

Salmon

ella

redu

ctiontreatment

Exp

osureassessmentstage

Unitsize

(g)

Meanprob

abilityof

contam

inationafterredu

ctiontreatm

entof

a:

Meancontam

ination(CFU/unit)afterredu

ctiontreatm

entof

b:

0log

1log

2log

3log

4log

5log

0log

1log

2log

3log

4log

5log

Preshelling

storage

10,161

,226

0.32

20.71

Posttreatment

10,161

,226

0.06

80.01

90.00

420.00

072

0.00

0095

0.00

0009

71.81

1.06

11

11

Partition

into

units

4,71

5,83

60.04

50.01

20.00

240.00

039

0.00

0048

0.00

0004

91.37

11

11

1Partition

into

packages

224

3.75

E�0

53.81

E�0

63.78

E�0

73.74

E�0

83.76

E�0

93.82

E�1

01

11

11

1Postprocess

andretailstorage

224

1.84

E�0

51.83

E�0

61.81

E�0

71.79

E�0

81.85

E�0

91.86

E�1

01

11

11

1

aProbability

that

aun

itis

contam

inated

withSa

lmon

ella;acontam

inated

unitisdefinedas

having

atleast1CFU.

bSa

lmon

ella

levelin

each

contam

inated

unitat

theendof

each

expo

sure

assessmentstage(the

minim

umvalueis

1CFU).

50 SANTILLANA FARAKOS ET AL. J. Food Prot., Vol. 82, No. 1

contamination, the Salmonella contamination levels, thesurvival model parameters, and all process conditions thatare part of the exposure assessment model (e.g., times andtemperatures during storage). The impact of variability ismuch larger than the impact of the considered uncertainty.Variability in estimated risk (from the 2.5th to the 97.5thquantile of variability) spans over 5 log, whereas theuncertainty (from the 2.5th to the 97.5th quantile ofuncertainty) for a given statistic spans 2 to 3 log (Table2). The distributions, notably in the variability dimension,are skewed as can be inferred by the position of the mean,which is much closer to the 97.5% quantile of variabilitythan to the 2.5% quantile.

Mean risk estimates per contaminated serving amongthe contaminated servings eaten by individuals in the U.S.population correspond to one case of salmonellosis per 100million servings (95% CI, one case per 3 million to one caseper 2 billion servings) of walnuts consumed as a coreproduct uncooked at home with no Salmonella reductiontreatment applied. However, the 4- and 5-log Salmonellareduction treatments reduce the risk per serving for theseuncooked walnuts to one case of salmonellosis per 1 trillionservings (95% CI, one case per 50 billion to one case per 10trillion servings) and one case per 10 trillion servings (95%CI, one case per 100 billion to one case per 100 trillionservings), respectively. Walnuts consumed as an ingredientcooked at home have an average of ~2,000,000-fold lowerrisk per serving compared with walnuts consumed as a core

product uncooked at home. Differences in estimated risk forwalnuts consumed as a core product uncooked at homeversus as an ingredient cooked at home can be mainlyattributed to the additional Salmonella reduction step(cooking) when consuming cooked walnuts and, to a lesserdegree, to differences in serving size when walnuts areconsumed as an ingredient. Minimal differences inestimated risk for walnuts consumed as a core productuncooked at home versus as an ingredient uncooked athome (an average of fivefold lower when consumed as aningredient) can be attributed to differences in the walnutserving size when walnuts are consumed as an ingredient.

Risk estimates per year. As estimated from theNHANES-WWEIA data, 1.51% of the U.S. populationconsumed walnuts as a core product uncooked at home (7.93 108 servings per year), 1.62% consumed walnuts as aningredient uncooked at home (9.53 108 servings per year),and 11.46% consumed walnuts as an ingredient cooked athome (6.7 3 109 servings per year). The estimatedsalmonellosis occurrence in the United States (Table 3)for walnuts consumed as a core product uncooked at homewithout a Salmonella reduction treatment was 6 cases peryear (95% CI, ,1 to 278 cases). A 1- and 2-log Salmonellareduction treatment level reduces the mean risk for thesewalnuts to less than 1 case per year, with 95% CIs of ,1 to20 and ,1 to 2 cases per year, respectively. A minimum 3-log Salmonella reduction treatment for these walnuts results

FIGURE 3. Risk of human salmonellosisper serving for consumption of walnutsgiven a 1-, 2-, 3-, 4-, and 5-log Salmonellareduction treatment relative to the risk perserving from consumption of walnuts as aningredient cooked at home (i.e., havingreceived an additional 5-log reductiontreatment through cooking). In a corewalnut product, �80% of the ingredientsare walnuts; when walnuts are an ingredi-ent, ,80% of the product ingredients arewalnuts. Uncooked walnuts are not furthercooked at home; cooked walnuts receive acooking step at home (e.g., baking).

FIGURE 2. Salmonella levels (CFU perunit) in each exposure assessment stage forthe 0-, 1-, 2-, 3-, 4-, and 5-log Salmonellareduction treatments.

J. Food Prot., Vol. 82, No. 1 RISK ASSESSMENT OF SALMONELLA ON U.S. SHELLED WALNUTS 51

TABLE2.

Salmon

ellosisrisk

perservingforconsum

ptionof

walnu

tsin

theU.S.po

pulation

a

Treatment

(log

redu

ction)

Statistic

Walnu

tcore

uncook

edb

Walnu

tingredient

uncook

edc

Walnu

tingredient

cook

edd

Mean

SD

Quantiles

ofvariability

Mean

SD

Quantiles

ofvariability

Mean

SD

Quantiles

ofvariability

2.5%

97.5%

2.5%

97.5%

2.5%

97.5%

0Estim

ate

7.15

E�0

91.11E�0

71.62

E�1

31.26

E�0

81.44

E�0

92.32

E�0

83.13

E�1

42.60

E�0

92.86

E�1

54.31

E�1

42.39

E�2

04.86

E�1

595%

CI

5.50

E�1

04.69

E�0

98.38

E�2

56.70

E�1

71.35

E�1

01.05

E�0

91.66

E�2

51.41

E�1

71.08

E�1

62.66

E�1

51.12

E�3

11.85

E�2

33.15

E�0

72.86

E�0

51.65

E�1

08.58

E�0

85.54

E�0

84.72

E�0

63.29

E�1

11.73

E�0

87.79

E�1

47.33

E�1

22.07

E�1

73.67

E�1

41

Estim

ate

7.08

E�1

01.24

E�0

81.62

E�1

41.27

E�0

91.44

E�1

02.40

E�0

93.13

E�1

52.62

E�1

02.84

E�1

64.38

E�1

52.39

E�2

14.82

E� 1

695%

CI

5.02

E�1

14.66

E�1

08.38

E�2

66.70

E�1

81.49

E�1

11.09

E�1

01.66

E�2

61.41

E�1

81.10

E�1

72.39

E�1

61.12

E�3

21.85

E�2

42.29

E�0

82.05

E�0

61.66

E�1

18.42

E�0

95.52

E�0

94.65

E�0

73.31

E�1

21.73

E�0

97.07

E�1

56.80

E�1

32.08

E�1

83.61

E�1

52

Estim

ate

6.98

E�1

11.10

E�0

91.62

E�1

51.31

E�1

01.43

E�1

12.29

E�1

03.13

E�1

62.64

E�1

12.79

E�1

73.76

E�1

62.39

E�2

24.95

E�1

795%

CI

5.44

E�1

24.61

E�1

18.38

E�2

76.70

E�1

91.12

E�1

21.08

E�1

11.66

E�2

71.41

E�1

91.07

E�1

82.04

E�1

71.12

E�3

31.85

E�2

52.04

E�0

91.85

E�0

71.67

E�1

28.64

E�1

04.87

E�1

04.16

E�0

83.31

E�1

31.76

E�1

06.67

E�1

66.30

E�1

42.10

E�1

93.69

E�1

63

Estim

ate

7.09

E�1

21.08

E�1

01.62

E�1

61.31

E�1

11.42

E�1

22.14

E�1

13.13

E�1

72.65

E�1

22.84

E�1

84.38

E�1

72.39

E�2

34.95

E�1

895%

CI

5.52

E�1

34.61

E�1

28.38

E�2

86.70

E�2

01.25

E�1

31.06

E�1

21.66

E�2

81.41

E�2

01.14

E�1

92.60

E�1

81.12

E�3

41.85

E�2

62.45

E�1

02.22

E�0

81.67

E�1

38.75

E�1

14.80

E�1

14.01

E�0

93.31

E�1

41.77

E�1

16.78

E�1

76.50

E� 1

52.10

E�2

03.68

E�1

74

Estim

ate

7.05

E�1

31.07

E�1

11.62

E�1

71.31

E�1

21.44

E�1

32.40

E�1

23.13

E�1

82.65

E�1

32.84

E�1

94.34

E�1

82.39

E�2

44.95

E�1

995%

CI

7.66

E�1

44.61

E�1

38.38

E�2

96.70

E�2

11.34

E�1

41.06

E�1

31.66

E�2

91.41

E�2

11.13

E�2

02.61

E�1

91.12

E�3

51.85

E�2

72.21

E�1

11.99

E�0

91.67

E�1

48.76

E�1

25.20

E�1

24.68

E�1

03.31

E�1

51.77

E�1

26.84

E�1

86.38

E�1

62.10

E�2

13.69

E�1

85

Estim

ate

7.09

E�1

41.08

E�1

21.62

E�1

81.31

E�1

31.46

E�1

42.40

E�1

33.13

E�1

92.65

E�1

42.84

E�2

04.29

E�1

92.39

E�2

54.95

E�2

095%

CI

5.39

E�1

54.61

E�1

48.38

E�3

06.70

E�2

21.35

E�1

51.06

E�1

41.66

E�3

01.41

E�2

21.16

E�2

12.61

E�2

01.12

E�3

61.85

E�2

82.20

E�1

21.94

E�1

01.67

E�1

58.76

E�1

34.97

E�1

34.43

E�1

13.31

E�1

61.77

E�1

35.63

E�1

95.25

E�1

72.10

E�2

23.70

E�1

9

aColum

ns(e.g.,mean,SD,2.5%,and

97.5%)characterize

variability,androws(estim

ate,95%

CI)characterize

uncertaintyin

theestimates.95%

CIrepresentstherang

eof

values

inwhich

thereis

a95

%prob

abilityof

find

ingthetrue

value.

bWalnu

tsconsum

edas

acore

prod

uctun

cook

edat

home.

cWalnu

tsconsum

edas

aningredient

inaprod

uctun

cook

edat

home.

dWalnu

tsconsum

edas

aningredient

inaprod

uctcook

edat

home.

52 SANTILLANA FARAKOS ET AL. J. Food Prot., Vol. 82, No. 1

in a mean risk of ,1 case per year, including an upperuncertainty bound of the mean estimated cases of ,1. Forwalnuts consumed as an ingredient uncooked at home, aminimum 2-log Salmonella reduction treatment results in amean risk of ,1 case per year, with an upper uncertaintybound of the mean estimated cases of ,1. Cooking walnutssignificantly decreases the risk estimate, with the number ofcases per year estimated to be ,1 for all treatments whenwalnuts are cooked in the home.

Estimated risk from the modeled pre- and post-treatment atypical situations. For each of the threeatypical situations considered, the estimated risk ofsalmonellosis arising from consumption of walnuts as a

core product uncooked at home is compared with the riskfor the baseline model (with no atypical situation) in Figure4. The number of cases per year linked to each kind ofatypical situation would be equal to the number of caseslinked to the atypical situation multiplied by the number ofsuch atypical situations in that year (which is currentlyunknown).

For a pretreatment recontamination event at the floattank (with an increase in Salmonella by 0.5 to 1.5 log CFUin contaminated units predrying), no difference in risk wasfound compared with the baseline model (Fig. 4a). This isbecause drying is estimated to mitigate the risk. A ~3-logrecontamination would have to occur in this type of atypicalsituation to see a significant increase in risk estimatescompared with the baseline model. Because the atypicalsituation occurs prior to treatment, there is a significantdifference in risk estimate among reduction treatments, withthe risk decreasing as the reduction treatment level increasesfrom 1 to 5 log CFU.

When a pretreatment recontamination event occursduring preshelling storage (with an increase in levels ofSalmonella of 0.5 to 1.5 log CFU), a significant differencein risk estimates for the different reduction treatments ispredicted (Fig. 4b). The risk estimate for this atypical eventdecreases as the reduction treatment increases from 1 to 5log CFU. The risk estimates are an average of ~24 timeshigher mean risk per serving when compared with thebaseline for each treatment level (Fig. 4b). This increasedrisk is due to contamination that occurs after drying butbefore a Salmonella reduction treatment.

When contamination with Salmonella occurs posttreat-ment before partitioning into lots and packages with thesame increase in levels of Salmonella of 0.5 to 1.5 log CFUas assumed in the other two atypical situations, a significantincrease in risk is predicted. When no treatment is applied,the increase in mean risk per serving is predicted to be ~20times higher than the risk estimated for the baseline model

FIGURE 4. Risk per serving of walnutsconsumed as a core product uncooked athome assuming various Salmonella reduc-tion treatments (0- to 5-log reductions)relative to the risk per serving for thebaseline model given a 5-log Salmonellareduction treatment (7.1 3 10�14). (a)Atypical situation 1: cross-contaminationwith Salmonella at the float tank; (b)atypical situation 2: contamination withSalmonella during preshelling storage; (c)atypical situation 3: posttreatment recon-tamination with Salmonella before parti-tioning into lots and bags.

TABLE 3. Estimated number of salmonellosis cases per year fromconsumption of walnuts in the United States

Treatment(log reduction)

No. of salmonellosis cases

Walnut coreuncookeda

Walnut ingredientuncookedb

Walnut ingredientcookedc

Mean 95% CId Mean 95% CI Mean 95% CI

0 6 ,1–278 1 ,1–52 ,1 ,11 ,1 ,1–20 ,1 ,1–5 ,1 ,12 ,1 ,1–2 ,1 ,1 ,1 ,13 ,1 ,1 ,1 ,1 ,1 ,14 ,1 ,1 ,1 ,1 ,1 ,15 ,1 ,1 ,1 ,1 ,1 ,1

a Walnuts consumed as a core product uncooked at home (83 108

servings per year).b Walnuts consumed as an ingredient in a product uncooked athome (93 108 servings per year).

c Walnuts consumed as an ingredient in a product cooked at home(73 109 servings per year).

d 95% CI represents the range of values in which there is a 95%probability of finding the true value.

J. Food Prot., Vol. 82, No. 1 RISK ASSESSMENT OF SALMONELLA ON U.S. SHELLED WALNUTS 53

(without treatment). When a 5-log reduction treatment isapplied, the increase in risk estimated for this atypical eventis predicted to be ~2 3 106 times higher than that for thebaseline model. This difference is a result of the fact thatestimated mean risk of illness per serving for this atypicalevent is nearly independent of the log reduction treatmentlevel (Fig. 4c) because contamination takes place after thereduction treatment and is being compared with the baselinemodel assuming a 5-log reduction treatment.

These results indicate that generally, when a treatmentis in place, the contribution to the overall salmonellosis riskof atypical events that lead to pretreatment contamination ofwalnuts will be small compared with the contribution ofatypical events that lead to posttreatment contamination.When no Salmonella reduction treatment is applied, therelative risk is essentially the same whether recontaminationoccurs early or late in the process.

Sensitivity analysis results. The results of thesensitivity analysis indicate that the time it takes to reduceSalmonella by 1 log CFU has the greatest impact on meanrisk per serving estimates followed by pretreatment storagetime at any treatment level (Fig. 5). Longer storage timesresult in decreasing levels of mean estimated risk per serving(Salmonella tends to decrease at 20 to 258C), which is thereason for the negative Spearman rho values found for thesefactors (i.e., pretreatment and posttreatment storage). Initialcontamination levels and U.S. consumption patterns followin decreasing order of impact. Postprocess storage (includingretail storage time) has the lowest impact on risk estimates.

Estimated risk when using Salmonella contamina-tion data from the 2014 to 2015 retail survey. Data onprevalence and levels of Salmonella on tree nuts (includingwalnuts) at retail in the United States were collected from2014 to 2015 by a commercial testing laboratory undercontract with the FDA (43). Prepackaged shelled walnutsamples (617 conventional and 41 organic) were collectedfrom various types of retail markets (major chain, smallchain, discount store, drug store, etc.) and from variousregions throughout the continental United States. Roastednuts, nut butters, nut mixes, or nuts coated with seasonings,chocolate, or candy were excluded. A mean Salmonellaprevalence of 1.22% (95% CI, 0.53 to 2.40%) was found forshelled walnuts as a ready-to-eat product. When using the2014 to 2015 retail survey data, the risk estimate per servingfor walnuts consumed as a core product uncooked at homeleads to a risk estimate of one salmonellosis case per600,000 servings (95% CI, one case per 800,000 to one caseper 400,000 servings). This risk per serving estimate usingthe retail contamination data is approximately two orders ofmagnitude higher than that found for the baseline walnutrisk assessment model, which used contamination data atthe handler and assumed no Salmonella reduction treatment.It is not known whether the walnuts sampled at retail hadundergone a Salmonella reduction treatment because thisinformation is not provided on the package and treatmentcurrently is not required.

The difference in estimates can be traced to observedprevalence. The mean prevalence found for the 2014 to2015 samples at retail (1.22%, 8 of 658 total samples were

FIGURE 5. Spearman rho statistic for the baseline risk assessment model considering no Salmonella reduction treatment and a 4-logreduction treatment, with risk per serving from consumption of walnuts as a core product uncooked at home as the outcome variable.Delta1 is the time (weeks) it takes to reduce the Salmonella population by 1 log CFU per contaminated unit at 238C, PrePStorage is thepretreatment storage time (weeks), Cont is the initial Salmonella contamination, ConsCoreRaw is the serving size for walnuts consumedas a core product uncooked at home, and PostProcess is the posttreatment storage time (weeks).

54 SANTILLANA FARAKOS ET AL. J. Food Prot., Vol. 82, No. 1

positive for Salmonella) was approximately 10 times higherthan that found for the 2010 to 2013 inshell walnuts duringstorage at the handler (preshelling) (0.14%, 3 of 3,838samples were positive) (12). The observation of a higherprevalence at retail than at the handler is unexpectedbecause all typical walnut processing stages are expected toeither reduce the prevalence and levels of Salmonella orleave them unchanged (Fig. 1). We suggest that the higherprevalence observed in the 2014 to 2015 retail survey iseither a reflection of variability in Salmonella contaminationacross the supply or an atypical event affecting a portion ofthe supply. For example, raw walnuts at harvest from 2014to 2015 may have been significantly more contaminatedthan those sampled during the 2010 to 2013 survey. Inresearch on other tree nuts, Salmonella prevalence andlevels on these nuts (which are harvested once per year) canvary significantly among harvest years (11, 21, 34, 36).However, for this scenario to explain the 2014 to 2015prevalence estimate at retail, the prevalence and/or levels ofcontamination at harvest would have to have been orders ofmagnitude higher than the observations in the multiyear2010 to 2013 survey, taking into account the subsequentdecreases expected from drying (~2.6 log CFU) and frompre- and postprocess storage (~3 log CFU). A more likelyscenario is that there was Salmonella contamination duringprocessing in one or more facilities in 2014, most likelyposttreatment when a Salmonella reduction treatment wasapplied. This hypothesis is also consistent with preliminarydata from a follow-up survey conducted under contract withthe FDA during 2015 to 2016, in which no Salmonella-positive samples were found among 498 retail samplesexamined (19). Other scenarios or factors could explain theobserved contamination levels, but a thorough analysis isbeyond the scope of the present study.

Whether the relatively high prevalence of Salmonellaon walnuts during the 2014 to 2015 retail survey reflectsvariability in contamination among raw walnuts or atypicalsituations leading to contamination during processing, thesedata indicate that contaminated walnuts that pose a publichealth risk to U.S. consumers can reach the retail market.

Comparison with previous tree nut risk assessmentmodels. Previous risk assessments for Salmonella on treenuts include those for almonds (25, 36), pecans (35), andpistachios (24, 34). In these studies, the estimated mean riskof salmonellosis arising from U.S. consumption of almonds,pecans, or pistachios was less than one case per year when aminimum 4-log reduction treatment was applied to theentire U.S. supply. The current walnut risk assessmentresults predict that a minimum 3-log reduction treatmentwould result in a risk per year of ,1 case of salmonellosis,when the initial contamination levels of inshell walnutsduring storage at the handler are similar to those reported byDavidson et al. (12). This 10-fold difference in risk betweenwalnuts and the other tree nuts can mainly be attributed tothe lower prevalence of Salmonella on walnuts found at thehandler, which is on average 10 times lower than that foundfor almonds, pecans, and pistachios at the equivalent step intheir corresponding production processes.

In the FDA's previously published risk assessments(34–36), we also modeled examples of atypical situationsthat have the potential to lead to increased risk of illness,including simulation of two U.S. outbreak events, oneassociated with almonds in 2001 and one with pistachios in2016. Atypical events examined included higher initialcontamination levels at the pecan handler (35); growth ofSalmonella due to a delay in drying, leading to higherSalmonella levels prior to the simulated Salmonellareduction treatment in almonds and pistachios (34, 36);and Salmonella recontamination events pre- and postreduc-tion treatment for almonds, pecans, and pistachios (34–36).In all these simulated atypical events for almonds, pecans,and pistachios and in the current walnut risk assessment,risk per serving estimates increased as a result of theatypical situations. Although process control throughSalmonella reduction treatments is predicted to significantlyreduce the risk in the baseline models, our results indicatethat potential atypical situations that occur post- and insome cases pretreatment could lead to increased risk; suchsituations could explain the outbreak events that occurred inthe United States involving almonds and pistachios (34, 36).

The model and results of this assessment are limited toSalmonella, walnuts, and the United States. Data on theprobability of Salmonella contamination and on Salmonellalevels at harvest would allow development of models ofexposure from harvest to silo storage. Data on whetherSalmonella transfers through the shell to the kernel andduring shelling and the transfer rates associated with eachwould aid in estimating risk from consumption. Character-izing the time-temperature profiles for relevant cookingprocesses at the consumer level would provide a bettermeans of estimating the risk of salmonellosis fromconsumption of walnuts as an ingredient in products cookedat home. As data become available on the distribution of logreductions achieved from a targeted treatment and duringdrying, the effect of the variability in both the treatment andthe drying step could be quantified using the results of thisrisk assessment. If consumption of walnuts were to increase,a proportional increase in the number of salmonellosis caseswould occur, assuming all other factors remain the same.

The current risk assessment predicts that a minimum 3-log Salmonella reduction treatment would result in less thanone case of salmonellosis linked to the consumption ofwalnuts per year under typical conditions. However, therelatively high prevalence of Salmonella on walnutsobserved during the 2014 to 2015 retail survey suggeststhat contaminated walnuts that pose a health risk to U.S.consumers can reach the retail market, probably as a result ofone or more atypical events. Scenarios examining the impactof atypical events on the risk of illness indicate that processcontrol through preventive treatments can be insufficient,particularly when contamination takes place posttreatment.

ACKNOWLEDGMENTS

The authors thank Dr. Linda Harris for providing raw data andinformation and Jenny Scott for her careful review of the current andprevious versions of the manuscript.

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