Syndromic Gastrointestinal Panel Diagnostic Tests Have Changed our Understanding of the Epidemiology of Yersiniosis-Foodborne Diseases Active Surveillance Network, 2010-2021.

Background: In the US, yersinosis was understood to predominantly occur in winter and among Black or African American infants and Asian children. Increased use of culture-independent diagnostic tests (CIDTs) has led to marked increases in yersinosis diagnoses. Methods: We describe differences in the epidemiology of yersiniosis diagnosed by CIDT versus culture in 10 US sites, and identify determinants of health associated with diagnostic method. Results: Annual reported incidence increased from 0.3/100 000 in 2010 to 1.3/100 000 in 2021, particularly among adults ≥18 years, regardless of race and ethnicity, and during summer months. The proportion of CIDT-diagnosed infections increased from 3% in 2012 to 89% in 2021. An ill person's demographic characteristics and location of residence had a significant impact on their odds of being diagnosed by CIDT. Conclusions: Improved detection due to increased CIDT use has altered our understanding of yersinosis epidemiology, however differential access to CIDTs may still affect our understanding of yersinosis.

Real-Time Use of a Dynamic Model To Measure the Impact of Public Health Interventions on Measles Outbreak Size and Duration - Chicago, Illinois, 2024.

Measles is a highly infectious, vaccine-preventable disease that can cause severe illness, hospitalization, and death. A measles outbreak associated with a migrant shelter in Chicago occurred during February-April 2024, in which a total of 57 confirmed cases were identified, including 52 among shelter residents, three among staff members, and two among community members with a known link to the shelter. CDC simulated a measles outbreak among shelter residents using a dynamic disease model, updated in real time as additional cases were identified, to produce outbreak forecasts and assess the impact of public health interventions. As of April 8, the model forecasted a median final outbreak size of 58 cases (IQR = 56-60 cases); model fit and prediction range improved as more case data became available. Counterfactual analysis of different intervention scenarios demonstrated the importance of early deployment of public health interventions in Chicago, with a 69% chance of an outbreak of 100 or more cases had there been no mass vaccination or active case-finding compared with only a 1% chance when those interventions were deployed. This analysis highlights the value of using real-time, dynamic models to aid public health response, set expectations about outbreak size and duration, and quantify the impact of interventions. The model shows that prompt mass vaccination and active case-finding likely substantially reduced the chance of a large (100 or more cases) outbreak in Chicago.

Estimates of SARS-CoV-2 Hospitalization and Fatality Rates in the Prevaccination Period, United States.

Few precise estimates of hospitalization and fatality rates from COVID-19 exist for naive populations, especially within demographic subgroups. We estimated rates among persons with SARS-CoV-2 infection in the United States during May 1-December 1, 2020, before vaccines became available. Both rates generally increased with age; fatality rates were highest for persons >85 years of age (24%) and lowest for children 1-14 years of age (0.01%). Age-adjusted case hospitalization rates were highest for African American or Black, not Hispanic persons (14%), and case-fatality rates were highest for Asian or Pacific Islander, not Hispanic persons (4.4%). Eighteen percent of hospitalized patients and 44.2% of those admitted to an intensive care unit died. Male patients had higher hospitalization (6.2% vs. 5.2%) and fatality rates (1.9% vs. 1.5%) than female patients. These findings highlight the importance of collecting surveillance data to devise appropriate control measures for persons in underserved racial/ethnic groups and older adults.

The Increasing Burden of Emergency Department and Inpatient Consultations for "Papilledema".

BACKGROUND: Increasing incidence of idiopathic intracranial hypertension (IIH), overreported radiologic signs of intracranial hypertension, difficult access to outpatient neuro-ophthalmology services, poor insurance coverage, and medicolegal concerns have lowered the threshold for emergency department (ED) visits for "papilledema." Our objective was to examine referral patterns and outcomes of neuro-ophthalmology ED and inpatient consultations for concern for papilledema. METHODS: At one university-based quaternary care center, all adults referred for "papilledema" over one year underwent a standardized ED "papilledema protocol." We collected patient demographics, final diagnoses, and referral patterns. RESULTS: Over 1 year, 153 consecutive patients were referred for concern for papilledema. After papilledema protocol, 89 of 153 patients (58%) had bilateral optic disc edema, among whom 89% (79/89) had papilledema (intracranial hypertension). Of the 38 of 153 (25%) consultations for suspected disorder of intracranial pressure without previous fundus examination (Group 1), 74% (28/38) did not have optic disc edema, 21% (8/38) had papilledema, and 5% (2/38) had other causes of bilateral disc edema. Of the 89 of 153 (58%) consultations for presumed papilledema seen on fundus examination (Group 2), 58% (66/89) had confirmed papilledema, 17% (15/89) had pseudopapilledema, and 9% (8/89) had other causes of bilateral optic disc edema. Of the 26 of 153 (17%) patients with known IIH (Group 3), 5 had papilledema and 4 required urgent intervention. The most common diagnosis was IIH (58/79). Compared with IIH, patients with secondary causes of intracranial hypertension were older (P = 0.002), men (P < 0.001), not obese (P < 0.001), and more likely to have neurologic symptoms (P = 0.002). CONCLUSION: Inpatient and ED consultations for "papilledema" are increasing. Of the 153 ED and inpatient neuro-ophthalmology consultations seen for "papilledema" over 1 year, one-third of patients with optic disc edema of unknown cause before presentation to our ED had new vision- or life-threatening disease, supporting the need for prompt identification and evaluation of optic disc edema in the ED. In the face of limited access to neuro-ophthalmologists, this study supports the need for emergency department access to expert eye-care evaluation or ocular fundus camera for prompt identification of optic disc edema and standardized evaluation for neurologic emergencies.

Glaucoma as a cause of optic nerve abnormalities on magnetic resonance imaging.

BACKGROUND/OBJECTIVES: To report a series of patients with glaucoma and optic nerve abnormalities on magnetic resonance imaging (MRI) in at least one-eye, and to determine whether these findings correlate with the severity of glaucoma. PATIENTS AND METHODS: Retrospective study of all patients who underwent a brain/orbits MRI without and with contrast at our institution between 07/1/2019-6/30/2022. Patients with optic nerve T2-hyperintensity and/or MRI optic nerve atrophy in at least one-eye and a diagnosis of isolated glaucoma in at least one-eye were included. Demographic information, glaucoma clinical characteristics, glaucoma severity parameters, and MRI indication were collected. RESULTS: Fifty-six patients (112 eyes) (age 65 years-old [range 26-88]; 70% male) had isolated bilateral glaucoma with at least one-eye MRI optic nerve abnormality. The indication for MRI was atypical/asymmetric glaucoma in 91% of patients. Of the 112 eyes, 23 had optic nerve T2-hyperintensity alone; 33 had both optic nerve T2-hyperintensity and MRI optic nerve atrophy; 34 had MRI optic nerve atrophy alone; and 22 did not have abnormal optic nerve MRI-findings. None had optic nerve enhancement. A statistically significant association between optic nerve T2-hyperintensity or MRI optic nerve atrophy and glaucoma severity parameters was found. CONCLUSIONS: Glaucoma is a clinical diagnosis and MRI brain is usually not required, except in atypical or asymmetric cases. Optic nerve T2-hyperintensity and MRI optic nerve atrophy are nonspecific MRI-findings that can be found in severe glaucomatous optic nerves and should not systematically prompt investigations for another cause of optic neuropathy.

Optic Nerve MRI T2-Hyperintensity: A Nonspecific Marker of Optic Nerve Damage.

BACKGROUND: MRI abnormalities are common in optic neuropathies, especially on dedicated orbital imaging. In acute optic neuritis, optic nerve T2-hyperintensity associated with optic nerve contrast enhancement is the typical imaging finding. In chronic optic neuropathies, optic nerve T2-hyperintensity and atrophy are regularly seen. Isolated optic nerve T2-hyperintensity is often erroneously presumed to reflect optic neuritis, frequently prompting unnecessary investigations and neuro-ophthalmology consultations. Our goal was to determine the significance of optic nerve/chiasm T2-hyperintensity and/or atrophy on MRI. METHODS: Retrospective study of consecutive patients who underwent brain/orbital MRI with/without contrast at our institution between July 1, 2019, and June 6, 2022. Patients with optic nerve/chiasm T2-hyperintensity and/or atrophy were included. Medical records were reviewed to determine the etiology of the T2-hyperintensity and/or atrophy. RESULTS: Four hundred seventy-seven patients (698 eyes) were included [mean age 52 years (SD ±18 years); 57% women]. Of the 364 of 698 eyes with optic nerve/chiasm T2-hyperintensity without atrophy, the causes were compressive (104), inflammatory (103), multifactorial (49), glaucoma (21), normal (19), and other (68); of the 219 of 698 eyes with optic nerve/chiasm T2-hyperintensity and atrophy, the causes were compressive (57), multifactorial (40), inflammatory (38), glaucoma (33), normal (7), and other (44); of the 115 of 698 eyes with optic nerve/chiasm atrophy without T2-hyperintensity, the causes were glaucoma (34), multifactorial (21), inflammatory (13), compressive (11), normal (10), and other (26). Thirty-six eyes with optic nerve/chiasm T2-hyperintensity or atrophy did not have evidence of optic neuropathy or retinopathy on ophthalmologic examination, and 17 eyes had clinical evidence of severe retinopathy without primary optic neuropathy. CONCLUSIONS: Optic nerve T2-hyperintensity or atrophy can be found with any cause of optic neuropathy and with severe chronic retinopathy. These MRI findings should not automatically prompt optic neuritis diagnosis, workup, and treatment, and caution is advised regarding their use in the diagnostic criteria for multiple sclerosis. Cases of incidentally found MRI optic nerve T2-hyperintensity and/or atrophy without a known underlying optic neuropathy or severe retinopathy are rare. Such patients should receive an ophthalmologic examination before further investigations.

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.

Application of a Deep Learning System to Detect Papilledema on Nonmydriatic Ocular Fundus Photographs in an Emergency Department.

PURPOSE: The Fundus photography vs Ophthalmoscopy Trial Outcomes in the Emergency Department (FOTO-ED) studies showed that ED providers poorly recognized funduscopic findings in patients in the ED. We tested a modified version of the Brain and Optic Nerve Study Artificial Intelligence (BONSAI) deep learning system on nonmydriatic fundus photographs from the FOTO-ED studies to determine if the deep learning system could have improved the detection of papilledema had it been available to ED providers as a real-time diagnostic aid. DESIGN: Retrospective secondary analysis of a cohort of patients included in the FOTO-ED studies. METHODS: The testing data set included 1608 photographs obtained from 828 patients in the FOTO-ED studies. Photographs were reclassified according to the optic disc classification system used by the deep learning system ("normal optic discs," "papilledema," and "other optic disc abnormalities"). The system's performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 1-vs-rest strategy, with reference to expert neuro-ophthalmologists. RESULTS: The BONSAI deep learning system successfully distinguished normal from abnormal optic discs (AUC 0.92 [95% confidence interval {CI} 0.90-0.93]; sensitivity 75.6% [73.7%-77.5%] and specificity 89.6% [86.3%-92.8%]), and papilledema from normal and others (AUC 0.97 [0.95-0.99]; sensitivity 84.0% [75.0%-92.6%] and specificity 98.9% [98.5%-99.4%]). Six patients with missed papilledema in 1 eye were correctly identified by the deep learning system as having papilledema in the other eye. CONCLUSIONS: The BONSAI deep learning system was able to reliably identify papilledema and normal optic discs on nonmydriatic photographs obtained in the FOTO-ED studies. Our deep learning system has excellent potential as a diagnostic aid in EDs and non-ophthalmology clinics equipped with nonmydriatic fundus cameras. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

Clinical Outcomes of Patients With Nontyphoidal Salmonella Infections by Isolate Resistance-Foodborne Diseases Active Surveillance Network, 10 US Sites, 2004-2018.

BACKGROUND: Nontyphoidal Salmonella causes an estimated 1.35 million US infections annually. Antimicrobial-resistant strains are a serious public health threat. We examined the association between resistance and the clinical outcomes of hospitalization, length-of-stay ≥3 days, and death. METHODS: We linked epidemiologic data from the Foodborne Diseases Active Surveillance Network with antimicrobial resistance data from the National Antimicrobial Resistance Monitoring System (NARMS) for nontyphoidal Salmonella infections from 2004 to 2018. We defined any resistance as resistance to ≥1 antimicrobial and clinical resistance as resistance to ampicillin, azithromycin, ceftriaxone, ciprofloxacin, or trimethoprim-sulfamethoxazole (for the subset of isolates tested for all 5 agents). We compared outcomes before and after adjusting for age, state, race/ethnicity, international travel, outbreak association, and isolate serotype and source. RESULTS: Twenty percent of isolates (1105/5549) had any resistance, and 16% (469/2969) had clinical resistance. Persons whose isolates had any resistance were more likely to be hospitalized (31% vs 28%, P = .01) or have length-of-stay ≥3 days (20% vs 16%, P = .01). Deaths were rare but more common among those with any than no resistance (1.0% vs 0.4%, P = .01). Outcomes for patients whose isolates had clinical resistance did not differ significantly from those with no resistance. After adjustment, any resistance (adjusted odds ratio 1.23, 95% confidence interval 1.04-1.46) remained significantly associated with hospitalization. CONCLUSIONS: We observed a significant association between nontyphoidal Salmonella infections caused by resistant pathogens and likelihood of hospitalization. Clinical resistance was not associated with poorer outcomes, suggesting that factors other than treatment failure (eg, strain virulence, strain source, host factors) may be important.

Modelling counterfactual incidence during the transition towards culture-independent diagnostic testing.

BACKGROUND: Culture-independent diagnostic testing (CIDT) provides rapid results to clinicians and is quickly displacing traditional detection methods. Increased CIDT use and sensitivity likely result in higher case detection but might also obscure infection trends. Severe illness outcomes, such as hospitalization and death, are likely less affected by changes in testing practices and can be used as indicators of the expected case incidence trend had testing methods not changed. METHODS: Using US Foodborne Diseases Active Surveillance Network data during 1996-2019 and mixed effects quasi-Poisson regression, we estimated the expected yearly incidence for nine enteric pathogens. RESULTS: Removing the effect of CIDT use, CIDT panel testing and culture-confirmation of CIDT testing, the modelled incidence in all but three pathogens (Salmonella, Shigella, STEC O157) was significantly lower than the observed and the upward trend in Campylobacter was reversed from an observed 2.8% yearly increase to a modelled -2.8% yearly decrease (95% credible interval: -4.0, -1.4). CONCLUSIONS: Severe outcomes may be useful indicators in evaluating trends in surveillance systems that have undergone a marked change.

Predicting Food Sources of Listeria monocytogenes Based on Genomic Profiling Using Random Forest Model.

Listeria monocytogenes can cause severe foodborne illness, including miscarriage during pregnancy or death in newborn infants. When outbreaks of L. monocytogenes illness occur, it may be possible to determine the food source of the outbreak. However, most reported L. monocytogenes illnesses do not occur as part of a recognized outbreak and most of the time the food source of sporadic L. monocytogenes illness in people cannot be determined. In the United States, L. monocytogenes isolates from patients, foods, and environments are routinely sequenced and analyzed by whole genome multilocus sequence typing (wgMLST) for outbreak detection by PulseNet, the national molecular surveillance system for foodborne illnesses. We investigated whether machine learning approaches applied to wgMLST allele call data could assist in attribution analysis of food source of L. monocytogenes isolates. We compiled isolates with a known source from five food categories (dairy, fruit, meat, seafood, and vegetable) using the metadata of L. monocytogenes isolates in PulseNet, deduplicated closely genetically related isolates, and developed random forest models to predict the food sources of isolates. Prediction accuracy of the final model varied across the food categories; it was highest for meat (65%), followed by fruit (45%), vegetable (45%), dairy (44%), and seafood (37%); overall accuracy was 49%, compared with the naive prediction accuracy of 28%. Our results show that random forest can be used to capture genetically complex features of high-resolution wgMLST for attribution of isolates to their sources.

Neuro-ophthalmology Emergency Department and Inpatient Consultations at a Large Academic Referral Center.

PURPOSE: Prompt neuro-ophthalmology consultation prevents diagnostic errors and improves patient outcomes. The scarcity of neuro-ophthalmologists means that the increasing outpatient demand cannot be met, prompting many emergency department (ED) referrals by non-neuro-ophthalmologists. We describe our quaternary care institution's ED and inpatient neuro-ophthalmology consultation patterns and patient outcomes. DESIGN: Prospective observational study. PARTICIPANTS: Consecutive neuro-ophthalmology ED and inpatient consultation requests over 1 year. METHODS: We collected patient demographics, distance traveled, insurance status, referring provider details, consultation question, final diagnosis, complexity of consultation, time of consultation, and need for outpatient follow-up. MAIN OUTCOME MEASURES: Consultation patterns and diagnoses, complexity, and follow-up. RESULTS: Of 494 consecutive adult ED and inpatient neuro-ophthalmology consultations requested over 1 year, 241 of 494 consultations (49%) occurred at night or during weekends. Of ED consultations (322 of 494 [65%]), 127 of 322 consultations (39%) occurred during weekdays, 126 of 322 consultations (39%) occurred on weeknights, and 69 of 322 consultations (22%) occurred on weekends or holidays. Of 322 ED consultations, 225 of 322 consultations (70%) were patients who initially sought treatment in the ED with a neuro-ophthalmic chief symptom. Of the 196 patients sent to the ED by a health care professional, 148 patients (148/196 [76%]) were referred by eye care specialists (74 optometrists and 74 ophthalmologists). The most common ED referral questions were for papilledema (75 of 322 [23%]) and vision loss (72 of 322 [22%]). A total of 219 of 322 patients (68%) received a final active neuro-ophthalmic diagnosis, 222 of 322 patients (69%) were cases of high or very high complexity, and 143 of 322 patients (44%) required admission. Inpatient consultations (n = 172) were requested most frequently by hospitalists, including neurologists (71 of 172 [41%]) and oncologists (20 of 172 [12%]) for vision loss (43 of 172 [25%]) and eye movement disorders (36 of 172 [21%]) and by neurosurgeons (58 of 172 [33%]) for examination for mass or a preoperative evaluation (19 of 172 [11%]). An active neuro-ophthalmic diagnosis was confirmed in 67% of patients (116 of 172). Outpatient neuro-ophthalmology follow-up was required for 291 of 494 patients (59%). CONCLUSIONS: Neuro-ophthalmology consultations are critical to the diagnosis and management in the hospital setting. In the face of a critical shortage of neuro-ophthalmologists, this study highlights the need for technological and diagnostic aids for greater outpatient access. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Epidemiology and Antimicrobial Resistance of Campylobacter Infections in the United States, 2005-2018.

Background: Campylobacter is the most common cause of bacterial diarrhea in the United States; resistance to macrolides and fluoroquinolones limits treatment options. We examined the epidemiology of US Campylobacter infections and changes in resistance over time. Methods: The Foodborne Diseases Active Surveillance Network receives information on laboratory-confirmed Campylobacter cases from 10 US sites, and the National Antimicrobial Resistance Monitoring System receives a subset of isolates from these cases for antimicrobial susceptibility testing. We estimated trends in incidence of Campylobacter infection, adjusting for sex, age, and surveillance changes attributable to culture-independent diagnostic tests. We compared percentages of isolates resistant to erythromycin or ciprofloxacin during 2005-2016 with 2017-2018 and used multivariable logistic regression to examine the association of international travel with resistance. Results: Adjusted Campylobacter incidence remained stable or decreased for all groups analyzed since 2012. Among 2449 linked records in 2017-2018, the median patient age was 40.2 years (interquartile range, 21.6-57.8 years), 54.8% of patients were male, 17.2% were hospitalized, and 0.2% died. The percentage of resistant infections increased from 24.5% in 2005-2016 to 29.7% in 2017-2018 for ciprofloxacin (P < .001) and from 2.6% to 3.3% for erythromycin (P = .04). Persons with recent international travel had higher odds than nontravelers of having isolates resistant to ciprofloxacin (adjusted odds ratio [aOR] varied from 1.7 to 10.6 by race/ethnicity) and erythromycin (aOR = 1.7; 95% confidence interval, 1.3-2.1). Conclusions: Campylobacter incidence has remained stable or decreased, whereas resistance to antimicrobials recommended for treatment has increased. Recent international travel increased the risk of resistance.

A Bayesian Method for Exposure Prevalence Comparison During Foodborne Disease Outbreak Investigations.

CDC and health departments investigate foodborne disease outbreaks to identify a source. To generate and test hypotheses about vehicles, investigators typically compare exposure prevalence among case-patients with the general population using a one-sample binomial test. We propose a Bayesian alternative that also accounts for uncertainty in the estimate of exposure prevalence in the reference population. We compared exposure prevalence in a 2020 outbreak of Escherichia coli O157:H7 illnesses linked to leafy greens with 2018-2019 FoodNet Population Survey estimates. We ran prospective simulations using our Bayesian approach at three time points during the investigation. The posterior probability that leafy green consumption prevalence was higher than the general population prevalence increased as additional case-patients were interviewed. Probabilities were >0.70 for multiple leafy green items 2 weeks before the exact binomial p-value was statistically significant. A Bayesian approach to assessing exposure prevalence among cases could be superior to the one-sample binomial test typically used during foodborne outbreak investigations.

Preliminary Incidence and Trends of Infections Caused by Pathogens Transmitted Commonly Through Food - Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2022.

Each year, infections from major foodborne pathogens are responsible for an estimated 9.4 million illnesses, 56,000 hospitalizations, and 1,350 deaths in the United States (1). To evaluate progress toward prevention of enteric infections in the United States, the Foodborne Diseases Active Surveillance Network (FoodNet) conducts surveillance for laboratory-diagnosed infections caused by eight pathogens transmitted commonly through food at 10 U.S. sites. During 2020-2021, FoodNet detected decreases in many infections that were due to behavioral modifications, public health interventions, and changes in health care-seeking and testing practices during the COVID-19 pandemic. This report presents preliminary estimates of pathogen-specific annual incidences during 2022, compared with average annual incidences during 2016-2018, the reference period for the U.S. Department of Health and Human Services' Healthy People 2030 targets (2). Many pandemic interventions ended by 2022, resulting in a resumption of outbreaks, international travel, and other factors leading to enteric infections. During 2022, annual incidences of illnesses caused by the pathogens Campylobacter, Salmonella, Shigella, and Listeria were similar to average annual incidences during 2016-2018; however, incidences of Shiga toxin-producing Escherichia coli (STEC), Yersinia, Vibrio, and Cyclospora illnesses were higher. Increasing culture-independent diagnostic test (CIDT) usage likely contributed to increased detection by identifying infections that would have remained undetected before widespread CIDT usage. Reducing pathogen contamination during poultry slaughter and processing of leafy greens requires collaboration among food growers and processors, retail stores, restaurants, and regulators.

Risk Factors for Non-O157 Shiga Toxin-Producing Escherichia coli Infections, United States.

Shiga toxin-producing Escherichia coli (STEC) causes acute diarrheal illness. To determine risk factors for non-O157 STEC infection, we enrolled 939 patients and 2,464 healthy controls in a case-control study conducted in 10 US sites. The highest population-attributable fractions for domestically acquired infections were for eating lettuce (39%), tomatoes (21%), or at a fast-food restaurant (23%). Exposures with 10%-19% population attributable fractions included eating at a table service restaurant, eating watermelon, eating chicken, pork, beef, or iceberg lettuce prepared in a restaurant, eating exotic fruit, taking acid-reducing medication, and living or working on or visiting a farm. Significant exposures with high individual-level risk (odds ratio >10) among those >1 year of age who did not travel internationally were all from farm animal environments. To markedly decrease the number of STEC-related illnesses, prevention measures should focus on decreasing contamination of produce and improving the safety of foods prepared in restaurants.

Presumptive Idiopathic Intracranial Hypertension Based on Neuroimaging Findings: A Referral Pattern Study.

BACKGROUND: Radiologic findings of intracranial hypertension (RAD-IH) are common in idiopathic intracranial hypertension (IIH) patients. Paralleling the increasing rates of obesity, the burden of IIH is growing. Urgent neuro-ophthalmology consultations for possible IIH in patients with incidentally detected RAD-IH are increasing, with many patients receiving unnecessary lumbar punctures (LPs) and treatments. This retrospective observational study aimed to determine the prevalence of neuro-ophthalmology consultations for RAD-IH, rate of funduscopic examination by referring providers, prevalence of papilledema, outcomes after neuro-ophthalmic evaluation, and rates of misdiagnosis. METHODS: Records of 1,262 consecutive new patients seen in one neuro-ophthalmology clinic from January 2019 to January 2020 were reviewed. We identified patients who were: 1) referred with concern for IIH because of findings of RAD-IH; 2) referred for "papilledema"; 3) referred with a diagnosis of IIH; and 4) referred for spontaneous cranial cerebrospinal fluid (CSF) leaks. In addition to basic demographic profiles for all groups, detailed information was collected for patients referred solely for RAD-IH, including referral patterns, prior history of IIH, previous LPs, prior medical or surgical treatment(s), risk factors for increased intracranial pressure (ICP), presenting symptoms, radiologic features observed on neuroimaging, and final disposition. When available, the neuroimaging was reviewed by an expert neuroradiologist. RESULTS: Of 1,262 consecutive new patients, 66 (5%) were referred specifically for RAD-IH; most referrals came from neurologists (58%); 8/66 (12%) patients had papilledema; 16/66 (24%) patients had prior LP and 13/66 (20%) were already treated based on MRI findings; and 22/66 (33%) patients had ≤2 RAD-IH. Only 34/66 (52%) of patients referred for RAD-IH had prior funduscopic examinations. We confirmed papilledema in 26/82 (32%) patients referred for "papilledema." Only 29/83 (35%) patients referred with a diagnosis of IIH had active papilledema, and 3/16 (19%) patients with spontaneous CSF leaks had papilledema. In total, 247/1,262 (20%) new patients were referred to our clinic over 1 year with concern for IIH, among whom only 66 (27%) were confirmed to have active IIH with papilledema. CONCLUSIONS: One in 5 new patient referrals seen in our neuro-ophthalmology clinic were referred because of concern for increased ICP, but only 1/4 had active papilledema. Most patients referred for isolated RAD-IH do not have papilledema, many having undergone unnecessary LPs and treatments. The burden of these "rule-out IIH" consultations is overwhelming and will only continue to increase with the concurrent rise of obesity and IIH, straining the already limited neuro-ophthalmologic resources available in the US.

Power Law for Estimating Underdetection of Foodborne Disease Outbreaks, United States.

We fit a power law distribution to US foodborne disease outbreaks to assess underdetection and underreporting. We predicted that 788 fewer than expected small outbreaks were identified annually during 1998-2017 and 365 fewer during 2018-2019, after whole-genome sequencing was implemented. Power law can help assess effectiveness of public health interventions.

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.

Preliminary Incidence and Trends of Infections Caused by Pathogens Transmitted Commonly Through Food - Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2016-2021.

To evaluate progress toward prevention of enteric infections in the United States, the Foodborne Diseases Active Surveillance Network (FoodNet) conducts active population-based surveillance for laboratory-diagnosed infections caused by Campylobacter, Cyclospora, Listeria, Salmonella, Shiga toxin-producing Escherichia coli (STEC), Shigella, Vibrio, and Yersinia at 10 U.S. sites. This report summarizes preliminary 2021 data and describes changes in annual incidence compared with the average annual incidence for 2016-2018, the reference period for the U.S. Department of Health and Human Services' (HHS) Healthy People 2030 goals for some pathogens (1). During 2021, the incidence of infections caused by Salmonella decreased, incidence of infections caused by Cyclospora, Yersinia, and Vibrio increased, and incidence of infections caused by other pathogens did not change. As in 2020, behavioral modifications and public health interventions implemented to control the COVID-19 pandemic might have decreased transmission of enteric infections (2). Other factors (e.g., increased use of telemedicine and continued increase in use of culture-independent diagnostic tests [CIDTs]) might have altered their detection or reporting (2). Much work remains to achieve HHS Healthy People 2030 goals, particularly for Salmonella infections, which are frequently attributed to poultry products and produce, and Campylobacter infections, which are frequently attributed to chicken products (3).