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. 2019 Jul 9;16(7):513–523. doi: 10.1089/fpd.2018.2592

Laboratory Review of Foodborne Disease Investigations in Washington State 2007–2017

Jennifer L Swoveland 1, Laurie K Stewart 2, Mary Kaye Eckmann 1, Raymond Gee 1, Krisandra J Allen 2, Calley M Vandegrift 1, Gina Olson 1, Mi-Gyeong Kang 1, Michael L Tran 1, Elizabeth Melius 2, Brian Hiatt 1, Romesh K Gautom 1, Ailyn C Perez-Osorio 1,✉
PMCID: PMC6653799  PMID: 30969140

Abstract

The Washington State Department of Health Public Health Laboratories (WAPHL) has tested 11,501 samples between 2007 and 2017 for a foodborne disease using a combination of identification, serotyping, and subtyping tools. During this period there were 8037 total clinical and environmental samples tested by pulsed-field gel electrophoresis (PFGE), including 512 foodborne disease clusters and 2176 PFGE patterns of Salmonella enterica subsp. enterica. There were 2446 Shiga toxin–producing Escherichia coli samples tested by PFGE, which included 158 foodborne disease clusters and 1174 PFGE patterns. There were 332 samples of Listeria monocytogenes tested by PFGE, including 35 foodborne disease clusters and 104 PFGE patterns. Sources linked to outbreaks included raw chicken, unpasteurized dairy products, various produce types, and undercooked beef among others. As next-generation sequencing (NGS) replaces PFGE, the impact of this transition is expected to be significant given the enhanced cluster detection power NGS brings. The measures presented here will be a reference baseline in future years.

Keywords: Washington State, PFGE, Salmonella, Listeria, foodborne illness and disease, PulseNet

Introduction

Approximately 3000 notifiable enteric foodborne illnesses are reported annually in Washington (WA) State, with 1–10 associated deaths (CDC, 2015a). The foodborne disease category is a leading cause of infectious illnesses in WA. Clinical laboratories in WA are required to submit specimens or isolates from patients diagnosed with listeriosis, salmonellosis, shigellosis, vibriosis, or infection with Shiga toxin Department of Health–producing Escherichia coli (STEC) to the Washington State Public Health Laboratories (WAPHL). Submissions are characterized to confirm the initial identification and some isolates are further serotyped and subtyped.

The PulseNet program is a national laboratory network that allows participating laboratories to link molecular characteristics of bacterial isolates from foodborne illness cases to detect outbreaks (Swaminathan et al., 2001). WAPHL was among the first four state PHLs to join the Centers for Disease Control and Prevention (CDC)-sponsored PulseNet program in 1996 (Stephenson, 1997; CDC, 2016b) and has continued its key role as the Western PulseNet Region Area Laboratory for >20 years. PulseNet relies on the use of standardized pulsed-field gel electrophoresis (PFGE) equipment, methodology, and analysis tools that link data across participating laboratories to detect clusters.

The primary source of infection with Listeria monocytogenes, STEC, Salmonella enterica, Campylobacter jejuni, Yersinia spp., Vibrio cholerae, or Vibrio parahaemolyticus is undercooked or adulterated food. Although listeriosis and STEC infections represent a small proportion of all foodborne illnesses, outcomes can be severe so each case is carefully investigated. Listeriosis occurs primarily in individuals with immunosuppression, pregnant women, neonates, and the elderly as invasive infection that can carry a mortality rate of at least 16% (Farber and Peterkin, 1991; Barton Behravesh et al., 2011; CDC, 2016a). STEC infections can also be severe because of the risk of developing hemolytic uremic syndrome that carries a high mortality rate particularly, for children younger than 4 years (Barton Behravesh et al., 2011). Along with listeriosis, salmonellosis causes the most deaths because of a foodborne disease in WA, despite a lower case fatality rate. This is because salmonellosis is among the most common bacterial foodborne infections, second only to campylobacteriosis (CDC, 2015b; Laufer et al., 2015).

The aim of this publication was to summarize the work that WAPHL has carried out over the past 11 years (2007–2017) in the area of foodborne disease investigations. The transition as next-generation sequencing (NGS) replaces PFGE is expected to have a significant impact given the enhanced cluster detection power because of the increase in resolution of NGS. In addition, the use of culture independent diagnostic testing (CIDT) and its impacts on the need for isolates are briefly addressed. The measures presented here will be a baseline for reference in future years. Although WAPHL has applied PFGE to organisms other than those already mentioned, this summary will focus on only these organisms and the work WAPHL has performed for WA residents.

Materials and Methods

Bacteria isolation, identification, and subtyping

STEC were isolated and identified using MacConkey with sorbitol (SMAC), tellurite, and cefixime (CT-SMAC), and Rainbow agar with novobiocin and tellurite. Specimens not already in Gram Negative (GN) broth were enriched by inoculating GN broth. All specimens were initially screened for functional Shiga toxin utilizing a lateral flow enzyme immunoassay (EIA) test (Meridian ImmunoCard STAT!® enterohemorrhagic E. coli [EHEC] or Alere SHIGA TOXIN QUIK CHEK™) which detects and differentiates Shiga toxin 1 and Shiga toxin 2 (Staples et al., 2017). Isolates were tested for Shiga toxin production and were confirmed biochemically. If the isolate was Shiga toxin positive and biochemically resembled E. coli, the isolate was serotyped using E. coli OK antisera or antibody-coated latex beads. Turnaround time for STEC isolation and confirmation was 4–7 business days. These isolates were routinely tested by PFGE.

Salmonella were isolated and identified using MacConkey (MAC), Hektoen Enteric (HE) agar, Salmonella-Snigella (SS) agar, and brilliant green agar. Stool were inoculated into selenite broth and tetrathionate broth as a selective enrichment for better recovery of Salmonella spp. Isolates resembling Salmonella were confirmed using biochemicals. From 2007 to 2012, Salmonella isolates were serotyped utilizing Salmonella antisera to determine O and H antigens. From 2012 to 2017, molecular techniques (Illumina xMAP Salmonella serotyping assay) were used to serotype Salmonella isolates, supplemented with Salmonella antisera (Dunbar et al., 2015). Turnaround time for Salmonella isolation and confirmation was 4–7 business days. All Salmonella isolates were routinely tested by PFGE.

Listeria from clinical specimens were identified using blood agar plates (BAP), brain–heart infusion (BHI) broth agar slant or a heart infusion agar (HIA) slant, and MAC to look for purity, hemolysis (BAP), and inhibited growth (MAC). A single colony was picked from the BAP to inoculate a set of biochemicals to confirm L. monocytogenes. If the results were not typical for L. monocytogenes, then hippurate and CAMP tests were performed to help with the identification. Turnaround time for Listeria identification was 3–5 business days. Listeria isolates were routinely tested by PFGE for subtyping and a BHI/HIA was referred to the CDC for further studies.

Listeria from food samples and environmental samples were isolated and identified using a modified Food and Drug Administration Bacteriological Analytical Manual procedure for detecting Listeria in food (FDA, 2017).

Media and test reagents for Salmonella, E. coli, and Listeria isolation and identification were purchased commercially with a few exceptions. Antisera were purchased from Difco, Denka Seiken, or SSI Diagnostica. Media and most biochemicals were purchased from Remel and Hardy Diagnostics. The antibody-coated latex beads were purchased from Pro-Lab for E. coli Non-O157 (E. coli Non-O157 Latex Test Reagent Kit) and from Remel for E. coli O157 (Remel RIM E. coli O157:H7 Latex test). Carbohydrate biochemicals and nutrient broths were made in-house at the WAPHL. All manufactured media were used following the manufacturer guidelines. All WAPHL in-house media use followed the Enterics and Special Bacteriology Reference Units laboratory procedure manuals and microbiology reference books (Holt, 1994; Weyant, 1996; MacFaddin, 2000; de la Maza, 2004; Garcia and Isenberg, 2010; Jorgensen, 2015).

PFGE subtyping

PFGE subtyping was carried out using PulseNet protocols for running and analyzing PFGE gels (Graves and Swaminathan, 2001; Ribot et al., 2001, 2006; Swaminathan et al., 2001; Parsons et al., 2007). Turnaround time for PFGE was 4 business days. PFGE patterns were compared with other patterns both in the WA database and in the national CDC PulseNet database using BioNumerics software. Any pattern matches were further assessed to determine if they should be considered a cluster and clusters were reported to an epidemiologist.

Cluster definition

For this publication a cluster identified by WAPHL is defined as two or more cases with matching PFGE patterns and similar illness onset date (within 60 d). Other supportive information for defining a cluster is similar geographic distribution or similar demographics, especially for a common PFGE pattern (Bender et al., 2001; Barrett et al., 2006; Tauxe, 2006). A foodborne disease outbreak is defined as two or more people with the same illness from a shared identified food or drink. Outbreaks vary in size and are classified depending on the spread of disease as local, multicounty, or multistate (CDC, 2015b). Ill people from the same household are not counted as a cluster.

Results

Between 2007 and 2017 WA received a total of 33,079 notifiable bacterial disease case reports for foodborne illnesses. During this period WAPHL received a total of 12,885 human enteric isolates of which 11,134 received PFGE characterization (Fig. 1). Of human enteric reports (confirmed, probable, and suspect cases), 51% were attributed to campylobacteriosis, 27% to salmonellosis, 9% to STEC, and 10% to other enteric illnesses including listeriosis, vibriosis, cholera, and shigellosis.

FIG. 1.

FIG. 1.

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Total number of case reports received, laboratory confirmed isolates, and subtyped isolates by PFGE stratified per pathogen. ∼Cases include confirmed, probable, and suspect. *Vibriosis cases. **Shigellosis cases. PFGE, pulsed-field gel electrophoresis.

There were 8759 salmonellosis and typhoid fever cases (confirmed, probable, and suspect) reported during the period and 7829 Salmonella isolates were subtyped at WAPHL (Table 1). Among the S. enterica subsp. enterica isolates tested, the most frequent serotypes identified, in order, were Enteritidis, Typhimurium, I 4,[5],12:i:-, Heidelberg, and Newport. Table 2 presents the most common serotypes reported in WA. Less common serotypes detected in WA are reported elsewhere (Washington State Department of Health). Serotypes Enteritidis and Typhimurium topped all serotypes for each year during 2007–2017, except for 2015 when a large outbreak of serotype I 4,5,12:i:- associated with roasted whole hogs occurred (Kawakami et al., 2016).

Table 1.

Foodborne Disease Clusters and Outbreaks in Washington 2007–2017

Criteria STEC (all serotypes) STEC (O157) Salmonella Enteriditis Salmonella Typhimurium Salmonella I 4,5,12:i:- Salmonella Newport Salmonella Heidelberg Salmonella Typhi All other Salmonella serotypes (non-Typhi) Listeria monocytogenes Shigella sonnei and Shigella flexneri Vibrio 11-Year totals
2007–2017
 No. of unique PFGE patterns 776 398 110 287 97 168 75   1439 104 313 6 3773
 No. of clusters 29 129 66 89 45 31 22 2 259 35 18 1 726
 No. of local clusters 12 54 15 30 8 4 6   55 8 13 0 205
 No. of multistate clusters 17 75 51 59 37 27 16   204 27 5 0 518
 Total WA food/environmental isolates pulsed 24 30 208 114 1 2 379
 Total WA clinical case isolates pulsed 1078 1314 1788 1086 619 392 444 131 3369 218 631 42 11,134
 Confirmed/suspect/probable cases 1152 1373 1842 1107 565 385 433 117 4310 249 1733 682 13,948
 Deaths 10 3 3 4 1 2   10 18 0 1 52
2007
 No. of local clusters 0 3 0 0 0 0 0   2 0 1 0  
 No. of multistate clusters 0 5 1 3 2 3 0   13 4 0 0  
 Confirmed/suspect/probable cases 13 119 120 121 45 58 39   375 25 159 25  
 Deaths 0 NA NA NA NA NA   NA 2 0 0  
 Total local and multistate clusters 0 8 1 3 2 3 0   15 4 1 0  
 Total WA clinical case isolates pulsed 12 126 112 127 48 56 36   332 16 133 0  
2008
 No. of local clusters 0 4 2 0 0 1 0   2 1 1 0  
 No. of multistate clusters 0 1 5 5 2 1 0   7 1 1 0  
 Confirmed/suspect/probable cases 24 151 199 133 15 39 31   429 29 116 29  
 Deaths 1 NA NA NA NA NA   NA 3 0 0  
 Total local and multistate clusters 0 5 7 5 2 2 0   9 2 2 0  
 Total WA clinical case isolates pulsed 12 144 197 129 22 37 31   304 22 96 0  
2009
 No. of local clusters 0 5 2 3 0 0 1   3 1 4 0  
 No. of multistate clusters 0 12 4 14 3 1 4   26 1 0 0  
 Confirmed/suspect/probable cases 32 159 147 148 17 29 63   416 24 153 48  
 Deaths 0 NA NA NA NA NA   NA 4 0 0  
 Total local and multistate clusters 0 17 6 17 3 1 5   29 2 4 0  
 Total WA clinical case isolates pulsed 28 156 146 157 26 29 72   318 25 125 0  
2010
 No. of local clusters 2 6 3 7 1 0 0   6 3 2 0  
 No. of multistate clusters 0 8 11 8 2 2 2   19 0 1 0  
 Confirmed/suspect/probable cases 77 110 173 127 10 50 52   368 24 112 59  
 Deaths 1 NA NA NA NA NA   NA 1 0 0  
 Total local and multistate clusters 2 14 14 15 3 2 2   25 3 3 0  
 Total WA clinical case isolates pulsed 78 103 166 133 18 50 53   234 20 102 0  
2011
 No. of local clusters 0 8 1 3 2 1 1   6 1 2 0  
 No. of multistate clusters 0 5 4 2 2 1 1   10 2 0 0  
 Confirmed/suspect/probable cases 88 104 137 88 16 20 27   301 24 153 45  
 Deaths 1 NA NA NA NA NA   NA 0 0 0  
 Total local and multistate clusters 0 13 5 5 4 2 2   16 3 2 0  
 Total WA clinical case isolates pulsed 80 98 132 82 15 27 29   271 17 91 26  
2012
 No. of local clusters 1 4 0 3 0 0 0   7 0 1 0  
 No. of multistate clusters 3 8 0 4 1 2 1   31 2 0 0  
 Confirmed/suspect/probable cases 100 118 151 93 19 39 87   453 26 133 67  
 Deaths 0 NA NA NA NA NA   NA 5 0 0  
 Total local and multistate clusters 4 12 0 7 1 2 1   38 2 1 0  
 Total WA clinical case isolates pulsed 94 111 150 87 27 36 87   350 20 23 0  
2013
 No. of local clusters 0 9 0 3 0 0 0   3 1 0 0  
 No. of multistate clusters 3 12 2 7 7 2 1   19 4 0 0  
 Confirmed/suspect/probable cases 137 165 148 98 38 21 35   330 21 122 90  
 Deaths 3 NA NA NA NA NA   NA 0 0 0  
 Total local and multistate clusters 3 21 2 10 7 2 1   22 5 0 0  
 Total WA clinical case isolates pulsed 130 157 146 94 38 21 34   305 25 13 0  
2014
 No. of local clusters 1 0 2 2 0 0 0   1 0 1 0  
 No. of multistate clusters 4 4 7 10 4 2 2   19 5 0 0  
 Confirmed/suspect/probable cases 159 103 217 67 67 21 31   336 24 157 92  
 Deaths 2 NA NA NA NA NA   NA 0 0 0  
 Total local and multistate clusters 5 4 9 12 4 2 2   20 5 1 0  
 Total WA clinical case isolates pulsed 153 94 206 60 70 22 31   291 20 8 0  
2015
 No. of local clusters 7 4 3 3 4 0 3   4 1 0 0  
 No. of multistate clusters 2 9 7 3 5 4 3   21 4 1 0  
 Confirmed/suspect/probable cases 181 157 208 74 224 31 36   461 21 152 68  
 Deaths 1 NA NA NA NA NA   NA 0 0 0  
 Total local and multistate clusters 9 13 10 6 9 4 6   25 5 1 0  
 Total WA clinical case isolates pulsed 165 149 198 69 234 35 38   350 21 8 0  
2016
 No. of local clusters 0 8 2 4 0 0 1   11 0 1 0  
 No. of multistate clusters 2 6 8 1 6 6 2   22 2 2 0  
 Confirmed/suspect/probable cases 154 97 195 79 70 16 18   376 14 191 63  
 Deaths 0 NA NA NA NA NA   NA 0 0 1  
 Total local and multistate clusters 2 14 10 5 6 6 3   33 2 3 0  
 Total WA clinical case isolates pulsed 153 91 188 74 71 18 18   239 16 27 0  
2017
 No. of local clusters 1 3 0 2 1 2 0   10 0 0 1 (vv)  
 No. of multistate clusters 3 5 2 2 3 3 0   17 2 0 0  
 Confirmed/suspect/probable cases 187 90 147 79 44 61 14   465 17 285 96  
 Deaths 1 NA NA NA NA NA   NA 3 0 0  
 Total local and multistate clusters 4 8 2 4 4 5 0   27 2 0 1  
 Total WA clinical case isolates pulsed 173 85 147 74 50 61 15   375 16 5 16  
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PFGE, pulsed-field gel electrophoresis; STEC, Shiga toxin–producing Escherichia coli; WA, Washington.

Table 2.

Predominant Salmonella Serovars Detected in Washington State During 2007–2017

Serotype 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 Total
Agona 13 25 9 15 18 9 9 6 11 4 7 126
Anatum 3 9 7 7 7 8 3 8 2 3 5 62
Bareilly 1 3 2 2 2 9 2 1 0 1 6 29
Berta 0 0 0 3 3 4 3 2 6 6 2 29
Braenderup 9 14 14 11 17 22 9 8 20 19 12 155
Brandenburg 4 1 0 5 8 4 11 2 5 11 3 54
Chester 2 3 1 10 0 1 2 2 1 2 3 27
Dublin 6 2 4 8 5 2 3 8 6 8 5 57
Enteritidis 120 199 147 173 137 151 148 217 208 195 147 1842
Hadar 7 9 15 6 12 13 6 8 14 3 7 100
Havana 2 1 2 3 1 1 1 3 6 0 1 21
Heidelberg 39 31 63 52 27 87 35 31 36 18 14 433
I 4,12:i:- 8 6 8 0 0 1 0 2 10 0 5 40
I 4,5,12:b:- 0 0 0 0 0 2 2 13 15 8 11 51
I 4,5,12:i:- 46 17 19 10 13 28 38 67 224 70 44 576
Infantis 10 11 15 18 11 22 13 19 18 24 28 189
Javiana 10 10 9 11 11 8 7 7 13 17 18 121
Kentucky 1 3 3 3 2 2 7 2 2 3 1 29
Litchfield 1 16 4 4 2 1 2 3 0 4 0 37
Mbandaka 7 6 5 10 6 6 6 4 5 4 4 63
Montevideo 32 34 44 29 13 19 13 17 12 14 16 243
Muenchen 12 6 12 12 7 8 16 16 10 22 20 141
Newport 58 39 29 50 20 39 21 21 31 16 61 385
Oranienburg 12 10 21 14 10 11 18 16 15 28 19 174
Panama 3 3 5 5 10 4 5 5 6 4 2 52
Paratyphi A 3 2 3 1 3 10 12 7 4 7 4 56
Paratyphi B 2 1 1 1 2 1 1 1 1 0 0 11
Paratyphi B var. L(+) tartrate(+) 17 19 18 14 11 8 14 5 8 10 28 152
Poona 5 19 2 9 1 11 7 6 26 4 5 95
Potsdam 1 1 6 0 2 0 0 1 1 0 0 12
Saintpaul 31 27 22 12 5 8 22 23 24 11 11 196
Sandiego 5 3 1 3 1 6 7 5 3 3 6 43
Senftenberg 29 20 6 7 3 3 1 2 2 3 5 81
Stanley 21 9 10 7 14 16 9 8 4 9 21 128
Thompson 11 9 19 16 9 17 16 23 17 24 18 179
Typhi 24 25 61 61 34 49 44 49 60 63 42 512
Typhimurium 121 133 148 127 88 93 98 67 74 79 79 1107
Virchow 1 4 5 3 4 41 4 2 1 3 8 76
Weltevreden 1 6 1 4 2 0 1 0 2 3 4 24
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Additional serotypes reported every year can be found in the annual WA communicable disease surveillance reports (Department of Health).

Source: Washington State Department of Health.

Within serotypes Enteritidis, Typhimurium, and I 4,5,12:i:- there were 110, 287, and 97 distinct PFGE patterns, respectively (Table 1). For all Salmonella serotypes there was an average of 45 Salmonella PFGE clusters per year (Table 1). Salmonella Enteritidis was responsible for multiple confirmed outbreaks linked to travel to Mexico, dining at local restaurants, or consuming poultry (Table 3). One outbreak linked to alfalfa sprouts and spicy sprouts sickened 25 people, 10 residing in WA. Three people were hospitalized and the investigation was closed on July 6, 2011, after the company voluntarily recalled the product (CDC, 2011). Salmonella Typhimurium outbreak vehicles included chicks, peanut butter, alfalfa sprouts, hedgehogs, a teaching laboratory exposure, and restaurants. An outbreak as a result of rotisserie chicken salad contaminated with Salmonella Typhimurium was identified in 2016.

Table 3.

Foods Associated with Clusters and Outbreaks in Washington 2007–2017

IFSACacategory Etiology Serotype(s) No. of WA cases No. of outbreaks
Beef Escherichia coli, Shiga toxin–producing O157:H7 9 2
Beef Salmonella enterica Senftenberg, Typhimurium, Braenderup 20 3
Chicken S. enterica Heidelberg, I 4,[5],12:i:- 104 5
Dairy E. coli, Shiga toxin–producing O157:H7; O121, O26:H11, O157:NM(H-) 18 5
Dairy Listeria monocytogenes   20 5
Dairy S. enterica Dublin 3 1
Eggs S. enterica Enteritidis, Typhimurium 69 2
Fish S. enterica Paratyphi B var. L(+) tartrate +, Weltevreden 1 1
Fruits L. monocytogenes   1 1
Fruits S. enterica I 4,[5],12:b:- var. L(+) tartrate +, Litchfield, Panama, Agona, Braenderup, Worthington, Enteritidis, Chailey, Infantis, Newport 116 10
Grains—beans E. coli, Shiga toxin–producing O121, O26:NM 6 2
Herbs S. enterica Wandsworth, Typhimurium 33 4
Nuts—seeds E. coli, Shiga toxin–producing O157:H7 2 1
Nuts—seeds S. enterica Typhimurium, Newport, Hartford, Oranienburg, Gaminara, Montevideo, Seftenberg 29 4
Oils—sugars S. enterica Virchow 1 1
Other S. enterica Heidelberg, I 4,[5],12:b:- var. L(+) tartrate +, Javiana, Okatie, Thompson, Weltevreden 16 1
Pork S. enterica Enteritidis, I 4,[5],12:i:-, Infantis 215 5
Seeded vegetables S. enterica Saintpaul, Newport, Paratyphi B, Poona 66 5
Sprouts E. coli, Shiga toxin–producing O26, O121 12 2
Sprouts S. enterica Typhimurium, Newport, Enteritidis, Muenchen, Cubana, Kentucky 34 4
Turkey S. enterica Subspecies IIIa, Hadar, I 4,[5],12:i:- 12 3
Vegetable row crops E. coli, Shiga toxin–producing O157:H7, O157:NM (H-), O26 28 9
Vegetable row crops S. enterica Typhimurium, Javiana, Enteritidis 30 3
Multiple E. coli, Shiga toxin–producing O157:H7, O121 79 6
Multiple L. monocytogenes   5 3
Multiple S. enterica IV 50:z4,z23:-, Typhimurium, Sandiego, I 4,[5],12:i:-, Enteritidis, Muenchen, Newport, Chester, Anatum, Heidelberg, Thompson, Paratyphi B var. L(+) tartrate + 279 18
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Food vehicles leading to recurrent outbreaks associated with other Salmonella serotypes included pot pie and pig roast linked to Salmonella I 4,[5],12:i:- (Kawakami et al., 2016) and frozen raw chicken linked to Salmonella Heidelberg (Green et al., 2018). Sources linked to multiple Salmonella serotypes included live chicks, pet reptiles, and multiple restaurants. Produce vehicles linked to salmonellosis outbreaks included mangoes, green onions, peppers, and pistachios. In 2015 there were two outbreaks resulting from exposure to peanut butter (Salmonella Newport) and spicy tuna rolls [Salmonella Paratyphi B L(+) Tartrate(+)]. One Salmonella Saintpaul outbreak in 43 U.S. states and Canada linked to jalapeno and serrano peppers, and possibly to raw tomatoes, affected 1442 people with 2 deaths (CDC, 2008b) (Table 3). In 2007 a WA outbreak involving 12 illnesses was linked to the use of an improperly cleaned food slicer contaminated with Salmonella Seftenberg. During the 2007–2017 period there were a total of 23 deaths associated with salmonellosis in WA.

The total number of confirmed, probable, and suspect cases as a result of STEC reported between 2007 and 2017 was 2525, of which 1373 cases were attributed to E. coli O157, 293 cases were attributed to E. coli O26, and 691 were attributed to other E. coli serotypes (not shown). Among E. coli O157 isolates there were 1398 PFGE patterns and 129 PFGE clusters (Table 1). Outbreaks were linked to consuming undercooked beef (2007, 2009), cookie dough (2009), or unpasteurized milk (Table 3); in addition, outbreaks occurred at day care centers, at petting zoos, or owing of contact with grazing animals. There were 10 STEC-related fatalities reported during this period (Table 1). For E. coli non-O157 there were 776 PFGE patterns and 29 PFGE clusters (Table 1), which included outbreaks because of raw sprouts and uncooked flour. In addition, lettuce, leafy greens, kale, and spinach were also found to be STEC vehicles (Table 3). Culture submissions for STEC testing decreased and stools and broths submitted to WAPHL for testing increased since 2012 (Fig. 2).

FIG. 2.

FIG. 2.

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Number of cultures and stools/broths received by WAPHL 2011–2017. WAPHL, Washington State Public Health Laboratories.

There were 249 confirmed, probable, and suspect L. monocytogenes cases reported between 2007 and 2017 including 18 deaths (case fatality rate of 7.5%). A total of 218 Listeria human and 114 nonhuman isolates were tested by PFGE with 104 PFGE patterns and 35 PFGE clusters observed during this period (Table 1). Outbreaks were associated with dairy products including raw milk, Mexican style soft cheeses, ice cream, and caramel apples (Table 3) as well as produce (lettuce, kale, cantaloupe, and onions).

Discussion

Salmonellosis has several characteristics that make control difficult (Ailes et al., 2008). It occurs naturally in cattle, poultry, and eggs and is not considered an adulterant in raw meat products; so producers can attempt but are not required to control it. Salmonella spp. can grow as biofilms on common surfaces used to process food, including stainless steel. Cross-contamination may be one of the main obstacles in reducing the prevalence of these bacteria in restaurants and other food-processing establishments as sources of recurrent outbreaks in WA (CDC, 2008a, 2013; Paz-Mendez et al., 2017; Green et al., 2018). Several reports have highlighted the potential for various serotypes of S. enterica to grow within the phyllosphere of several food-producing plants when exposure to this pathogen occurs through the soil or irrigation water (Barak et al., 2008; Gu et al., 2011; Zheng et al., 2013; Haendiges et al., 2018). These characteristics make Salmonella outbreaks linked to produce categories likely to occur in the future. Travel abroad is another well-recognized risk factor for salmonellosis (Ekdahl et al., 2005) as noted in this report. Contact with live poultry and amphibians was another common outbreak source in Washington that is well-recognized as a risk factor (Woodward et al., 1997; Behravesh et al., 2014; Basler et al., 2016; Bosch et al., 2016; Ribas and Poonlaphdecha, 2017).

Several large outbreaks in WA have been linked to Salmonella contamination of foods. An outbreak in 2014 linked to eating a raw beef “kitfo” dish sickened over 40 people. Starting in 2007, peanut butter was recognized as a new vehicle for salmonellosis (Sheth et al., 2011). WA reported 27 ill from 2 nut butter outbreaks since 2007. In 2015 there was the largest pork-associated salmonellosis outbreak in WA history (CDC, 2015a; Kawakami et al., 2016). This multiclonal Salmonella outbreak was linked to whole hogs from a slaughter facility and resulted in a large pork recall. Slaughter facilities in the past have been recognized as the most important source of Salmonella contamination for Salmonella-free hogs (Swanenburg et al., 2001a, 2001b).

STEC infections acquired through foods remain a significant source of death and severe complications in WA. Many of the STEC outbreaks (2007–2017) were associated with previously reported high-risk food vehicles particularly undercooked beef, raw sprouts, and unpasteurized milk (Erickson and Doyle, 2007; Neil et al., 2012; Luna-Gierke et al., 2014; Morton et al., 2017) in addition to flour, which has emerged as a risk factor for STEC infections in recent years (Morton et al., 2017). Animal exposures at petting zoos and state fairs are also a significant source of STEC infections. In 2015, WA reported an E. O157:H7 outbreak linked to attendance at a dairy education event. Environmental samples collected at the event site yielded PFGE patterns indistinguishable from the outbreak strain (Dunbar et al., 2015).

With the release of Shiga toxin EIA that allow clinical laboratories to better identify non-O157, there was a concomitant reduction in STEC culture submissions to WAPHL. In addition, with the emergence of polymerase chain reaction-based enteric testing, an increase in stool specimen submissions was noted (as opposed to isolate submissions). CIDT has impacted the workflow at WAPHL as specimen submissions have increased and isolate submissions have decreased. This trend is predicted to continue in future years. It will be important for the WAPHL to facilitate isolate recovery in future years as these new technologies expand and replace current testing workflows at clinical laboratories.

Listeriosis associated with ice cream, raw milk, and Mexican style soft cheeses was identified as a problem as early as 1985 and continues to this day (Linnan et al., 1988; Jackson et al., 2018). The ubiquity of L. monocytogenes in the environment and its potential to grow in biofilms mean that a previously unrecognized food vehicle could cause a foodborne outbreak (Ferreira et al., 2014). WA had two notable recurring listeriosis outbreaks from dairy products. Two patients hospitalized at the same facility in 2014–2015 and one a year later in 2016 developed listeriosis found to be linked to pasteurized ice cream served at the facility and produced by a local company (Rietberg et al., 2016). Pasteurized soft Mexican cheese produced by a local firm sickened several people in 2010 and again in 2015. Sushi and frozen vegetables have also been linked to listeriosis outbreaks in WA.

The implementation of policies or campaigns to encourage the use of specific interventions, in addition to the implementation of better identification tools (on-site rapid testing, whole-genome sequencing), may lead to the reduction in the incidence of enteric infections. There is strong evidence indicating that in areas of the country where these infections are investigated, such as FoodNet sites, there has been a reduction (by 30%) in illness incidence (Ailes et al., 2008). Better access to rapid test kits that can identify the presence of pathogens at food-processing facilities is also needed. Public health will, in the meantime, continue to rely on surveillance of notifiable conditions through the work of local health jurisdictions who conduct epidemiological and environment investigations. It is possible that the impact of the use of NGS tools may by overshadowed by the impact of CIDTs as fewer illnesses get characterized with an isolate culture that can then flow to get characterized by NGS. Nonetheless, NGS characterization offers unparalleled resolution in providing evidence to pathogen relatedness that will revolutionize the way foodborne disease investigations are conducted in the laboratory as PFGE is phased out.

To understand the impact of future laboratory testing as the use of NGS becomes more streamlined, it would be important for reference laboratories to track the amount of time it takes to detect clusters, number of outbreaks solved with food source identified, number of cases per cluster, and number of cases linked to a food source. In addition, there is work to be carried out to increase the proportion of stool samples submitted for laboratory testing for foodborne illnesses (Ailes et al., 2012) and in laboratory methodologies that ensure the recovery of an isolate. Characterization of isolates remains the key to a solved foodborne disease investigation (Hurd et al., 2012).

Limitations

Foodborne diseases attributed to botulism, norovirus, and yersiniosis were not evaluated. In addition, data for Campylobacter and Shigella are not complete as WAPHL did not test all the submitted isolates by PFGE. In WA the investigation of campylobacteriosis individual cases is considered optional (Washington State Department of Health, 2016).

Although the case counts were provided, most PHL data were missing vehicle source or cluster association data other than PFGE. All outbreaks and clusters reported herein were closed at the time of the writing of this article.

Acknowledgments

The authors thank the editing assistance of Bonnie Olsen and recognize all the work that several microbiologists have contributed to the Enterics, Food, Special Bacteriology Reference, and PFGE units of WAPHL. This work was supported in part by the Epidemiology and Laboratory Capacity grant sponsored by the CDC.

Disclosure Statement

No competing financial interests exist.

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