Surveillance for Shiga toxin--producing Escherichia coli, Michigan, 2001-2005.

A surveillance system used different detection methods to estimate prevalence of Shiga toxin-producing Escherichia coli during 2003-2005 and 2001-2002. More non-O157 serotypes were detected by enzyme immunoassay than by evaluation of non-sorbitol-fermenting E. coli isolates. We therefore recommend use of enzyme immunoassay and culture-based methods.

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Infection with Shiga toxin-producing Escherichia coli (STEC) is a frequent cause of gastrointestinal disease, particularly among children and elderly persons (1). Detection of O157 STEC by culture relies primarily on sorbitol MacConkey agar (SMAC) (2) because O157:H7 strains cannot rapidly ferment sorbitol (3). In contrast, using culture to detect sorbitol-fermenting O157 (4) and non-O157 serotypes is problematic because on SMAC these strains are indistinguishable from other E. coli. Consequently, whether the predominance of STEC O157 in disease reflects actual differences in pathogen prevalence or a bias associated with detection is unclear. We therefore sought to determine whether STEC prevalence, particularly of non-O157 serotypes, increased when enhanced detection methods were used.

The Study

The Michigan Department of Community Health implemented a sentinel surveillance system to evaluate blood-containing stool samples from 20 laboratories during April 2003-October 2005 and all stool samples from 2 hospitals during July 2004-October 2005. All suspect non-sorbitol-fermenting E. coli from the remaining laboratories were also examined.

The samples, transported in C&S transport medium (Medical Chemical Corporation, Torrance, CA, USA), were screened for Shiga toxin (Stx) by enzyme immunoassay (EIA) (Meridian BioScience, Cincinnati, OH, USA) after enrichment with gram-negative broth (Remel, Lenexa, KS, USA). EIA is sensitive and specific but cannot detect the Stx2e variant (5), and Pseudomonas aeruginosa can produce false-positive results (6). Samples were cultured on SMAC (Remel) and cefixime-tellurite SMAC (7), and samples from the 2 hospitals were tested for occult blood (Beckman Coulter, Fullerton, CA, USA) before EIA testing. Serotyping (Statens Serum Institute, Copenhagen, Denmark; BD Difco, Franklin Lakes, NJ, USA) and real-time PCR for stx1,2 genes (8) were performed on strains that had positive EIA results, suspect non-sorbitol-fermenting E. coli, and multiple colonies of sorbitol-fermenting (SF) strains that had positive EIA results. For some samples, the EIA result was negative but NSF stx-positive colonies were detected on SMAC, which indicated a false-negative EIA result. Epidemiologic data were obtained for STEC-positive patients.

During the 5 years studied, 438 STEC were isolated; 401 (92%) were O157. Prevalence over time did not differ ([chi square]= 4.14, degrees of freedom [df] = 4, p = 0.39). Similarly, overall prevalence of non-O157 serotypes during 2001-2002 and 2003-2005 did not differ ([chi square] = 0.83, df = 1, p = 0.36). Most (70%) STEC isolates were recovered between June and October from heavily populated areas (Figure). No SF O157 were recovered.

[FIGURE OMITTED]

In 2001 2002, a total of 664 suspect NSF E. coli isolates were evaluated; 179 (27%) were O157 and 2 (0.3%) were non-O157 serotypes (Table 1). After enhanced surveillance began in 2003, a total of 852 suspect isolates were tested; 177 (21%) were O157 and 3 (0.4%) were non-O157 serotypes (Table 1). The remaining STEC (n = 28, 2001-2002; n = 49, 2003-2005) were detected by EIA. For 5 samples, EIA yielded a false-negative result but STEC were recovered from SMAC. During 2003-2005, 7 of the 49 STEC came from screening all 2,426 samples from the 2 hospitals; 359 (15%) of these samples contained occult blood. Among the 7 detected, 5 contained occult blood and 6 were O157. The remaining 42 (10%) STEC were found by screening 423 suspect samples from other laboratories; 18 (4%) were non-O157 serotypes. More non-O157 serotypes were detected ([chi square] = 61.1, df = 1, p<0.00001) from 2003-2005 when EIA was used instead of the NSF E. coli isolate submission process. Among all 37 non-O157 serotypes isolated, O45:H2 (n = 10) and O26:H11 (n = 5) predominated.

Epidemiologic data were available for up to 389 (89%) STEC patients, depending on the variable assessed. Most patients (62%) were Caucasian; =50% were female. Disease occurred mostly in persons [less than or equal to] 10 (27%), 11-18 (19%), and 19-30 (17%) years of age. Although disease frequency was lower (9%) in persons >65 years of age, these persons were more likely to be hospitalized than were persons [less than or equal to] 18 years of age, as were persons with bloody diarrhea or hemolytic-uremic syndrome (HUS) (Table 2). Among the 12 patients with HUS, 2 were infected with non-O157 serotypes O103:H2 and O76:H7, and 7 of the 12 HUS-associated strains were stx2 only.

To adjust for factors associated with hospitalization, we fit a logistic regression model that included age and symptom variables in the model. The adjusted associations were similar to the crude associations. Hospitalization was more frequent for persons with bloody diarrhea (adjusted odds ratio [OR] 1.8, 95% confidence interval [CI] 1.04-3.08) and HUS (adjusted OR 16.0, 95% CI 2.00-127.47). Also, persons 19-64 (adjusted OR 1.6, 95% CI 1.05-2.59) and >65 (adjusted OR 6.6, 95% CI 2.57-17.15) years of age were hospitalized more frequently than persons [less than or equal to] 18 years of age.

Conclusions

Enhanced detection methods did not significantly increase the year-to-year recovery of STEC. Overall, the observed STEC prevalence decreased slightly over time, similar to the national trend of an overall 42% decrease in STEC O157 incidence during 1996-2004 (9). This reduction is likely attributable to numerous factors, including heightened consumer awareness (9) and improved screening protocols during food production (10).

Enhanced surveillance did, however, enhance detection of non-O157 serotypes; 4.3% of EIA-positive stools were non-O157 compared with 0.5% of suspect NSF E. coli. Additionally, among the STEC found, 34 (48%) were non-O157 and 37 (52%) were O157 when EIA was used on suspect stools, compared with only 3 (1.6%) non-O157 and 177 (98.3%) O157 among NSF E. coli. Despite enhanced surveillance, STEC prevalence is probably still underestimated, particularly for non-O157 serotypes, because not all ill persons seek medical care and not all laboratories submit suspect stools for evaluation. Nevertheless, in 5 years, our surveillance identified 66 (15%) cases that would have been undetected by conventional methods; 31 (47%) were non-O157. Among those patients for whom data were available, 27 (42%) of 64 were < 18 years of age, 22 (43%) of 51 were hospitalized, and 39 (76%) of 51 had bloody diarrhea. Although bloody stool and patient age are poor predictors of STEC infection (11), our analysis demonstrates that screening bloody stool samples improves detection of non-O157, and blood and older age are important predictors of more severe disease, which may be more costly if undetected.

Hospitalization of STEC patients with and without HUS costs an estimated US $30,307 and $4,061 per patient, respectively (12). Therefore, Michigan hospital costs associated with STEC infection likely exceeded $1,119,050 during 2001-2005, as 198 patients were hospitalized and 12 had HUS. Identification of each additional STEC case could have a substantial public health effect in that 1 case may lead to the recognition of an outbreak, which if detected early, could contribute to a cost savings as well as reduced STEC-associated illness. We estimated that the cost to detect each of the 66 additional cases using the EIA ($7 per test including labor) differed considerably when we evaluated screening of all stool samples ($2,426/per positive) versus suspect stool samples ($10/per positive).

No widely available test detects all STEC, and use of multiple methods is not cost-effective. Consequently, we recommend using EIA in conjunction with SMAC culture to recover isolates for molecular characterization and subsequent outbreak investigations. Although occult blood tests did not enhance the sensitivity of STEC recovery, patient data and accompanying epidemiologic information may help identify which samples to test, thereby preventing future outbreaks. Because such epidemiologic information is often not available to laboratory personnel, we suggest that clinical laboratories work with medical administrations to use EIAs as their standard of practice and to facilitate routine availability of such information. Until more sensitive and cost-effective STEC screening methods are available, facilities that cannot implement EIAs should forward stool samples that are suspect, as well as those with positive screening results, to public health laboratories. These laboratories can easily evaluate suspect stools for STEC by EIA or PCR followed by culture of all positive samples to recover the isolate for further characterization.

Use of trade names is for identification only and does not imply endorsement by the Public Health Service or by the U.S. Department of Health and Human Services.

Acknowledgments

We thank Francis Pouch Downes, Carrie Anglewicz, Barbara Evans, Kendra Anspaugh, Kelly Scott, Hao Trinh, Ben Hutton, Jon George, John Dyke, Kevin Rodeman, Jeff Massey, Steve Tharpe, Mary Grace Stobierski, Jim Collins, Michael Hass, Sally Bidol, Theresa Painter, James Wolcott, Eileen Matthews, Janet Green, Dave Aldrich, Carl Pierson, Duane Newton, Cora Manby, Richard Van Enk, Alan Petkus, Joan Baughman, Linda Hayka, Vito Damore, Cindy Miilu, Sharon Gauthier, John Kuehn, Marie Graham, Therese Carson, and Daniel Sundin.

The Emerging Infectious Diseases Research Fellowship Program, administered by the Association of Public Health Laboratories and funded by the US Centers for Disease Control and Prevention (CDC), supported S. Manning's appointment (2002-2004), and the CDC/Council of State and Territorial Epidemiologists Applied Epidemiology Fellowship Program supported R. Madera's appointment (2003-2005). This project was supported in part with federal funds for the Food and Waterborne Disease Integrated Research Network under National Institutes of Health research contract no. N01-AI-30058.

References

(1.) Thorpe CM. Shiga toxin-producing Escherichia coli infection. Clin Infect Dis. 2004;38:1298-303.

(2.) March SB, Ratnam S. Sorbitol-MacConkey medium for detection of Escherichia coli O157:H7 associated with hemorrhagic colitis. J Clin Microbiol. 1986;23:869-72.

(3.) Farmer JJ, Davis BR. H7 antiserum-sorbitol fermentation medium: a single tube screening medium for detecting Escherichia coli O157:H7 associated with hemorrhagic colitis. J Clin Microbiol. 1985;22:620-5.

(4.) Karch H, Bielaszewska M. Sorbitol-fermenting Shiga toxin-producing Escherichia coli O157:H(-) strains: epidemiology, phenotypic and molecular characteristics, and microbiological diagnosis. J Clin Microbiol. 2001;39:2043-9.

(5.) Allerberger F, Rossboth D, Dierich MP, Aleksic S, Schmidt H, Karch H. Prevalence and clinical manifestations of Shiga toxin-producing Escherichia coli infections in Austrian children. Eur J Clin Microbiol Infect Dis. 1996;15:545-50.

(6.) Beutin L, Zimmermann S, Gleier K. Pseudomonas aeruginosa can cause false-positive identification of verotoxin (Shiga-like toxin) production by a commercial enzyme immune assay system for the detection of Shiga-like toxins (SLTs). Infection. 1996;24:267-8.

(7.) Zadik PM, Chapman PA, Siddons CA. Use of tellurite for the selection of verocytotoxigenic Escherichia coli O157. J Med Microbiol. 1993;39:155-8.

(8.) Reischl U, Youssef MT, Kilwinski J, Lehn N, Zhang WL, Karch H, et al. Real-time fluorescence PCR assays for detection and characterization of Shiga toxin, intimin, and enterohemolysin genes from Shiga toxin-producing Escherichia coli. J Clin Microbiol. 2002;40:2555-65.

(9.) Centers for Disease Control and Prevention. Preliminary FoodNet data on the incidence of infection with pathogens transmitted commonly through food-10 sites, United States, 2004. MMWR Morb Mortal Wkly Rep. 2005;54:352-6.

(10.) Naugle AL, Holt KG, Levine P, Eckel R. Food safety and inspection service regulatory testing program for Escherichia coli O157:H7 in raw ground beef. J Food Prot. 2005;68:462-8.

(11.) Kehl KS, Havens P, Behnke CE, Acheson DW. Evaluation of the premier EHEC assay for detection of Shiga toxin-producing Escherichia coli. J Clin Microbiol. 1997;35:2051-4.

(12.) Frenzen PD, Drake A, Angulo FJ. Economic cost of illness due to Escherichia coli O157 infections in the United States. J Food Prot. 2005;68:2623-30.

Address for correspondence: James T. Rudrik, Michigan Department of Community Health, Bureau of Laboratories, 3350 North Martin Luther King Jr Blvd, Bldg 44, Rm 129, Lansing, MI 48909, USA; email: [e-mail]

Shannon D. Manning, * Robbie T. Madera, ([dagger]) William Schneider, ([dagger]) Stephen E. Dietrich, ([dagger]) Walid Khalife, ([double dagger]) William Brown, ([section]) Thomas S. Whittam, * Patricia Somsel, ([dagger]) and James T. Rudrik ([dagger])

* Michigan State University, East Lansing, Michigan, USA; ([dagger]) Michigan Department of Community Health, Lansing, Michigan, USA; ([double dagger]) Sparrow Health System, Lansing, Michigan, USA; and ([section]) Detroit Medical Center, Detroit, Michigan, USA

Dr Manning is a molecular and infectious disease epidemiologist. She studies the molecular epidemiology of pathogenic E. coli and group B Streptococcus at Michigan State University.

Table 1. Evaluation of shiga toxin-producing Escherichia
coli detection methods, Michigan, 2001-2005 *

                                                Routine STEC
                                                surveillance
                                             ([dagger]), no. (%)

Detection method                 Stool       2001        2002
                                samples

Culture and PCR [double          Total       327         337
dagger] for stx genes of         O157       85 (26)     94 (28)
suspect NSF E. coli            Non-O157     2 (0.6)      0 (0)

EIA of bloody or suspect         Total        N/A         N/A
samples                          O157         4           11
                               Non-O157       4           9

EIA of all samples               Total        N/A         N/A
                                 O157         N/A         N/A
                               Non-O157       N/A         N/A

                                    Enhanced STEC surveillance,
                                             no. (%)

Detection method                 2003        2004        2005

Culture and PCR [double           249         317         286
dagger] for stx genes of        63 (25)     58 (18)     56 (20)
suspect NSF E. coli              0 (0)       2 (0.6)     1 (0.3)

EIA of bloody or suspect          209         141         73
samples                         11 (5)       7 (5)       6 (8)
                                 4 (2)       7 (5)       7 (10)

EIA of all samples                N/A        1,405       1,021
                                  N/A        5 (0.4)     1 (0.1)
                                  N/A        1 (0.07)    0 (0)

* STEC, Shiga toxin-producing Escherichia coli; NSF,
non-sorbitol-fermenting; EIA, enzyme immunoassay.

([dagger]) In 2001 and 2002, EIA of bloody stools was performed
by 2 large clinical laboratories in Michigan and was not part of
the enhanced STEC surveillance system at the Michigan Department
of Community Health. Therefore, the total number of EIAs
performed is not known; the total number of EIA submitted as
positive for Stx is provided by serotype.

([double dagger]) PCR for stx1,2 genes was not initiated at the
Michigan Department of Community Health until 2002. Before 2002, a
DNA probe (Digene Signal Kit, Digene Diagnostic, Inc., Silver Spring,
MD, USA) was used to detect STEC.

Table 2. Association of characteristics with infection by Shiga
toxin-producing Escherichia coli among 389 of 438 patients for
whom data were available, Michigan, 2001-2005 * ([dagger])

                                       No. with          No. (%)
Characteristic                       characteristic    hospitalized

Demographics

  Age, y
   [less than or equal to]18              178             77 (43)
   19-64                                  178             94 (53)
   [greater than or equal to]65            32             26 (81)
  Sex
    Female                                204            105 (51)
    Male                                  185             92 (50)
Clinical symptoms
  Abdominal pain
    No                                     76             40 (53)
    Yes                                   304            151 (50)
  Body aches
    No                                    323            161 (50)
    Yes                                    57             30 (53)
  Chills
    No                                    313            155 (50)
    Yes                                    66             36 (55)
  Diarrhea
    No                                    154             82 (53)
    Yes                                   226            109 (48)
  Bloody diarrhea
    No                                     77             30 (39)
    Yes                                   303            161 (53)
  HUS
    No                                    368            180 (49)
    Yes                                    12             11 (92)
Bacterial serotype and genes
  O157                                    360            181 (50)
  Non-0157                                 29             16 (55)
  stx1                                     28             14 (50)
  stx2                                    121             54 (45)
  stx1,2                                  239            128 (54)

Characteristic                        OR (95% CI)

Demographics

  Age, y
   [less than or equal to]18              1.0
   19-64                            1.5 (0.95-2.28)
   [greater than or equal to]65     5.7 (2.09-16.27)
  Sex
    Female                                1.0
    Male                            0.9 (0.61-1.42)
Clinical symptoms
  Abdominal pain
    No                                    1.0
    Yes                             0.9 (0.54-1.47)
  Body aches
    No                                    1.0
    Yes                             1.1 (0.64-1.96)
  Chills
    No                                    1.0
    Yes                             1.2 (0.72-2.08)
  Diarrhea
    No                                    1.0
    Yes                             0.8 (0.54-1.23)
  Bloody diarrhea
    No                                    1.0
    Yes                             1.8 (1.10-2.96)
  HUS
    No                                    1.0
    Yes                             11.5 (1.47-89.90)
Bacterial serotype and genes
  O157                                    1.0
  Non-0157                          1.2 (0.57-2.60)
  stx1                                    1.0
  stx2                              0.8 (0.33-1.98)
  stx1,2                            1.2 (0.49-2.70)

* OR, odds ratio; CI, confidence interval; HUS, hemolytic-uremic
syndrome.

([dagger]) Some numbers do not add up to the total (n = 389) because
of missing values (never >2.6%).