A Prediction Tool to Identify the Causative Agent of Enteric Disease Outbreaks Using Outbreak Surveillance Data.

Information on the causative agent in an enteric disease outbreak can be used to generate hypotheses about the route of transmission and possible vehicles, to guide environmental assessments, and to target outbreak control measures. However, only about 40% of outbreaks reported in the United States include a confirmed etiology. The goal of this project was to identify clinical and demographic characteristics that can be used to predict the causative agent in an enteric disease outbreak and to use these data to develop an online tool for investigators to use during an outbreak when hypothesizing about the causative agent. Using data on enteric disease outbreaks from all transmission routes (animal contact, environmental contamination, foodborne, person-to-person, waterborne, unknown) reported to the U.S. Centers for Disease Control and Prevention, we developed random forest models to predict the etiology of an outbreak based on aggregated clinical and demographic characteristics at both the etiology category (i.e., bacteria, parasites, toxins, viruses) and individual etiology (Clostridium perfringens, Campylobacter, Cryptosporidium, norovirus, Salmonella, Shiga toxin-producing Escherichia coli, and Shigella) levels. The etiology category model had a kappa of 0.85 and an accuracy of 0.92, whereas the etiology-specific model had a kappa of 0.75 and an accuracy of 0.86. The highest sensitivities in the etiology category model were for bacteria and viruses; all categories had high specificities (>0.90). For the etiology-specific model, norovirus and Salmonella had the highest sensitivity and all etiologies had high specificities. When laboratory confirmation is unavailable, information on the clinical signs and symptoms reported by people associated with the outbreak, with other characteristics including case demographics and illness severity, can be used to predict the etiology or etiology category. An online publicly available tool was developed to assist investigators in their enteric disease outbreak investigations.

Foodborne illness outbreaks linked to unpasteurised milk and relationship to changes in state laws - United States, 1998-2018.

Consumption of unpasteurised milk in the United States has presented a public health challenge for decades because of the increased risk of pathogen transmission causing illness outbreaks. We analysed Foodborne Disease Outbreak Surveillance System data to characterise unpasteurised milk outbreaks. Using Poisson and negative binomial regression, we compared the number of outbreaks and outbreak-associated illnesses between jurisdictions grouped by legal status of unpasteurised milk sale based on a May 2019 survey of state laws. During 2013-2018, 75 outbreaks with 675 illnesses occurred that were linked to unpasteurised milk; of these, 325 illnesses (48%) were among people aged 0-19 years. Of 74 single-state outbreaks, 58 (78%) occurred in states where the sale of unpasteurised milk was expressly allowed. Compared with jurisdictions where retail sales were prohibited (n = 24), those where sales were expressly allowed (n = 27) were estimated to have 3.2 (95% CI 1.4-7.6) times greater number of outbreaks; of these, jurisdictions where sale was allowed in retail stores (n = 14) had 3.6 (95% CI 1.3-9.6) times greater number of outbreaks compared with those where sale was allowed on-farm only (n = 13). This study supports findings of previously published reports indicating that state laws resulting in increased availability of unpasteurised milk are associated with more outbreak-associated illnesses and outbreaks.

Using Outbreak Data for Hypothesis Generation: A Vehicle Prediction Tool for Disease Outbreaks Caused by Salmonella and Shiga Toxin-Producing Escherichia coli.

Hypothesis generation about potential food and other exposures is a critical step in an enteric disease outbreak investigation, helping to focus investigation efforts and use of limited resources. Historical outbreak data are an important source of information for hypothesis generation, providing data on common food- and animal-pathogen pairs and other epidemiological trends. We developed a model to predict vehicles for Shiga toxin-producing Escherichia coli and Salmonella outbreaks using demographic and outbreak characteristics from outbreaks in the Centers for Disease Control and Prevention's Foodborne Disease Outbreak Surveillance System (1998-2019) and Animal Contact Outbreak Surveillance System (2009-2019). We evaluated six algorithmic methods for prediction based on their ability to predict multiple class probabilities, selecting the random forest prediction model, which performed best with the lowest Brier score (0.0953) and highest accuracy (0.54). The model performed best for outbreaks transmitted by animal contact and foodborne outbreaks associated with eggs, meat, or vegetables. Expanding the criteria to include the two highest predicted vehicles, 83% of egg outbreaks were predicted correctly, followed by meat (82%), vegetables (74%), poultry (67%), and animal contact (62%). The model performed less well for fruit and poultry vehicles, and it did not predict any dairy outbreaks. The final model was translated into a free, publicly available online tool that can be used by investigators to provide data-driven hypotheses about outbreak vehicles as part of ongoing outbreak investigations. Investigators should use the tool for hypothesis generation along-side other sources, such as food-pathogen pairs, descriptive data, and case exposure assessments. The tool should be implemented in the context of individual outbreaks and with an awareness of its limitations, including the heterogeneity of outbreaks and the possibility of novel food vehicles.

Lessons Learned from a Decade of Investigations of Shiga Toxin-Producing Escherichia coli Outbreaks Linked to Leafy Greens, United States and Canada.

Shiga toxin-producing Escherichia coli (STEC) cause substantial and costly illnesses. Leafy greens are the second most common source of foodborne STEC O157 outbreaks. We examined STEC outbreaks linked to leafy greens during 2009-2018 in the United States and Canada. We identified 40 outbreaks, 1,212 illnesses, 77 cases of hemolytic uremic syndrome, and 8 deaths. More outbreaks were linked to romaine lettuce (54%) than to any other type of leafy green. More outbreaks occurred in the fall (45%) and spring (28%) than in other seasons. Barriers in epidemiologic and traceback investigations complicated identification of the ultimate outbreak source. Research on the seasonality of leafy green outbreaks and vulnerability to STEC contamination and bacterial survival dynamics by leafy green type are warranted. Improvements in traceability of leafy greens are also needed. Federal and state health partners, researchers, the leafy green industry, and retailers can work together on interventions to reduce STEC contamination.

Pediatric Botulism and Use of Equine Botulinum Antitoxin in Children: A Systematic Review.

Background: Botulism manifests with cranial nerve palsies and flaccid paralysis in children and adults. Botulism must be rapidly identified and treated; however, clinical presentation and treatment outcomes of noninfant botulism in children are not well described. Methods: We searched 12 databases for peer-reviewed and non-peer-reviewed reports with primary data on botulism in children (persons <18 years of age) or botulinum antitoxin administration to children. Reports underwent title and abstract screening and full text review. For each case, patient demographic, clinical, and outcome data were abstracted. Results: Of 7065 reports identified, 184 met inclusion criteria and described 360 pediatric botulism cases (79% confirmed, 21% probable) that occurred during 1929-2015 in 34 countries. Fifty-three percent were male; age ranged from 4 months to 17 years (median, 10 years). The most commonly reported signs and symptoms were dysphagia (53%), dysarthria (39%), and generalized weakness (37%). Inpatient length of stay ranged from 1 to 425 days (median, 24 days); 14% of cases required intensive care unit admission; 25% reported mechanical ventilation. Eighty-three (23%) children died. Median interval from illness onset to death was 1 day (range, 0-260 days). Among patients who received antitoxin (n = 193), 23 (12%) reported an adverse event, including rash, fever, serum sickness, and anaphylaxis. Relative risk of death among patients treated with antitoxin compared with patients not treated with antitoxin was 0.24 (95% confidence interval, .14-.40; P < .0001). Conclusions: Dysphagia and dysarthria were the most commonly reported cranial nerve symptoms in children with botulism; generalized weakness was described more than paralysis. Children who received antitoxin had better survival; serious adverse events were rare. Most deaths occurred early in the clinical course; therefore, botulism in children should be identified and treated rapidly.

Shiga Toxin-Producing Escherichia coli Outbreaks in the United States, 2010-2017.

Shiga toxin-producing Escherichia coli (STEC) cause illnesses ranging from mild diarrhea to ischemic colitis and hemolytic uremic syndrome (HUS); serogroup O157 is the most common cause. We describe the epidemiology and transmission routes for U.S. STEC outbreaks during 2010-2017. Health departments reported 466 STEC outbreaks affecting 4769 persons; 459 outbreaks had a serogroup identified (330 O157, 124 non-O157, 5 both). Among these, 361 (77%) had a known transmission route: 200 foodborne (44% of O157 outbreaks, 41% of non-O157 outbreaks), 87 person-to-person (16%, 24%), 49 animal contact (11%, 9%), 20 water (4%, 5%), and 5 environmental contamination (2%, 0%). The most common food category implicated was vegetable row crops. The distribution of O157 and non-O157 outbreaks varied by age, sex, and severity. A significantly higher percentage of STEC O157 than non-O157 outbreaks were transmitted by beef (p = 0.02). STEC O157 outbreaks also had significantly higher rates of hospitalization and HUS (p < 0.001).

Noninfectious Foodborne Exposures Reported to 2 National Reporting Systems, United States, 2000-2010.

OBJECTIVES: Foodborne disease is a pervasive problem caused by consuming food or drink contaminated by infectious or noninfectious agents. The 55 US poison centers receive telephone calls for advice on foodborne disease cases that may be related to a foodborne disease outbreak (FBDO). Our objective was to assess whether poison center call records uploaded to the National Poison Data System (NPDS) can be used for surveillance of noninfectious FBDOs in the United States. METHODS: We matched NPDS records on noninfectious FBDO agents in the United States with records in the Foodborne Disease Outbreak Surveillance System (FDOSS) for 2000-2010. We conducted multivariable logistic regression analysis comparing NPDS matched and unmatched records to assess features of NPDS records that may indicate a confirmed noninfectious FBDO. RESULTS: During 2000-2010, FDOSS recorded 491 noninfectious FBDOs of known etiology and NPDS recorded 8773 calls for noninfectious foodborne disease exposures. Of 8773 NPDS calls, 469 (5.3%) were matched to a noninfectious FBDO reported to FDOSS. Multivariable logistic regression indicated severity of medical outcome, whether the call was made by a health care professional, and etiology as significant predictors of NPDS records matching an FDOSS noninfectious FBDO. CONCLUSIONS: NPDS may complement existing surveillance systems and response activities by providing timely information about single cases of foodborne diseases or about a known or emerging FBDO. Prioritizing NPDS records by certain call features could help guide public health departments in the types of noninfectious foodborne records that most warrant public health follow-up.

Epidemiology of Foodborne Norovirus Outbreaks - United States, 2009-2015.

Noroviruses are the leading cause of acute gastroenteritis and foodborne disease in the United States (U.S.). About 1 in 5 reported norovirus outbreaks are spread through foodborne transmission, presenting opportunities for prevention. We describe the epidemiology of U.S. foodborne norovirus outbreaks reported to national surveillance systems, including differences between genotypes. Foodborne outbreaks that occurred during August 2009-July 2015 with norovirus reported as a single confirmed etiology to the National Outbreak Reporting System (NORS) were matched with outbreaks reported to CaliciNet, a U.S. laboratory norovirus outbreak surveillance network. We analyzed these matched outbreaks stratified by genotype for epidemiologic characteristics, including setting, size and duration, health outcomes of case-patients, implicated food, and outbreak contributing factors. Four hundred ninety-three confirmed foodborne norovirus outbreaks were reported in both NORS and CaliciNet. The most common norovirus genotypes reported were GII.4 (52%), GII.6 (9%), and GI.3 (8%). Compared to non-GII.4 outbreaks, GII.4 outbreaks had higher hospitalization rates (12.8 vs. 4.8 per 1,000 cases, P < 0.01). While contaminated foods were identified and reported in only 35% of outbreaks, molluscan shellfish (4% overall) were more often implicated in non-GII.4 outbreaks than in GII.4 outbreaks (7% vs. 1%, P = 0.04). Of the 240 outbreaks reporting at least one contributing factor, food workers were implicated as the source of contamination in 182 (76%), with no difference between GII.4 and non-GII.4 (73% vs 79%, P = 0.3). Foodborne norovirus outbreaks are frequently reported in the U.S., most of which are caused by GII.4 noroviruses. Viruses of this genotype are associated with higher rates of hospitalization; non-GII.4 noroviruses are more frequently associated with contaminated molluscan shellfish. These surveillance data highlight the diversity of noroviruses causing foodborne disease and can help guide appropriate food safety interventions, including worker hygiene, improved food handling and preparation, and further development of norovirus vaccines.