Laboratory-based surveillance for enteric pathogens causing diarrhea is foundational for monitoring foodborne diseases in the United States. However, diarrheal illnesses are not always confirmed by laboratory testing, so estimates of the true number of illnesses must adjust for underdiagnosis, including underdiagnosis due to ill persons not seeking medical care or submitting a stool sample for laboratory testing. We assessed these factors among persons with an acute diarrheal illness who responded to the most recent Foodborne Diseases Active Surveillance Network (FoodNet) Population Survey (2018-2019). Multiple modes of administration (telephone, web-based) and multiple sampling frames were used to ask survey respondents in English or Spanish about diarrhea and other symptoms experienced in the 30 days before the interview and to ask if they had sought medical care or submitted a stool sample. Of 1018 respondents with an acute diarrheal illness, 22.0% had sought medical care and 4.7% submitted a stool sample. On multivariable analysis, older adults (aged 65 years and over), male respondents, and persons with a household income of ≥$40,000 per annum were significantly more likely to seek medical care, as were respondents reporting cough, fever, vomiting, recent international travel, or duration of diarrhea for ≥3 days. Older adults and persons with five or more loose stools in 24 h who sought medical care were significantly more likely to submit a stool sample. Ill respondents with a concurrent cough were less likely to submit a stool sample. Sociodemographic characteristics, symptoms, and international travel influence whether a patient with an acute diarrheal illness will seek care or submit a stool specimen. Accounting for these factors when analyzing surveillance data will likely produce more precise estimates of the true number of foodborne illnesses.

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.

This brief methods paper is being published concomitantly with "Preliminary Incidence and Trends of Infections Caused by Pathogens Transmitted Commonly Through Food- Foodborne Diseases Active Surveillance Network, 10 U.S. Sites, 2016-2021" in Morbidity and Mortality Weekly Reports (MMWR). That article describes the application of the new model described here to analyze trends and evaluate progress towards the prevention of infection from enteric pathogens in the United States. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

BACKGROUND: Case-control studies are commonly used to explore factors associated with enteric bacterial diseases. Control of confounding is challenging due to the large number of exposures of interest and the low frequencies of many of them. METHODS: We evaluated nearest-neighbors matching in a case-control study (originally 1:1 matched, published in 2004) of sporadic Campylobacter infections that included information on 433 exposures in 2,632 subjects during 1998-1999. We performed multiple imputation of missing data (m=100) and calculated Gower distances between cases and controls using all possible confounders for each exposure in each dataset. We matched each case with ≤20 controls within a data-determined distance. We calculated odds ratios and population attributable fractions (PAFs). RESULTS: Examination of pairwise correlation between exposures found very strong associations for 1,046 pairs of exposures. More than 100 exposures were associated with campylobacteriosis, including nearly all risk factors identified using the previously published approach that included only 16 exposures and some less studied, rare exposures such as consumption of chicken liver and raw clams. Consumption of chicken and non-poultry meat had the highest PAFs (62% and 59%, respectively). CONCLUSIONS: Nearest-neighbors matching appears to provide an improved ability to examine rare exposures and better control for numerous highly associated confounders.

We sought to determine which Salmonella serotypes cause illness related to the Thanksgiving holiday in the United States and to foods disproportionately eaten then (e.g., turkey). Using routine surveillance for 1998-2018 and a case-crossover design, we found serotype Reading to be most strongly associated with Thanksgiving.

Estimates of the overall human health impact of agents transmitted commonly through food complement surveillance and help guide food safety interventions and regulatory initiatives. The purpose of this scoping review was to summarize the methods and reporting practices used in studies that estimate the total number of illnesses caused by these agents. We identified and included 43 studies published from January 1, 1995, to December 31, 2019, by searching PubMed and screening selected articles for other relevant publications. Selected articles presented original estimates of the number of illnesses caused by ≥1 agent transmitted commonly through food. The number of agents (species or subspecies for pathogens) included in each study ranged from 1 to 31 (median: 4.5; mean: 9.2). Of the 40 agents assessed across the 43 studies, the most common agent was Salmonella (36; 84% of studies), followed by Campylobacter (33; 77%), Shiga toxin-producing Escherichia coli (25; 58%), and norovirus (20; 47%). Investigators used a variety of data sources and methods that could be grouped into four distinct estimation approaches-direct, surveillance data scaled-up, syndrome or population scaled-down, and inferred. Based on our review, we propose four recommendations to improve the interpretability, comparability, and reproducibility of studies that estimate the number of illnesses caused by agents transmitted commonly through food. These include providing an assessment of statistical and nonstatistical uncertainty, providing a ranking of estimates by agent, including uncertainties; describing the rationale used to select agents and data sources; and publishing raw data and models, along with clear, detailed methods. These recommendations could lead to better decision-making about food safety policies. Although these recommendations have been made in the context of illness estimation for agents transmitted commonly through food, they also apply to estimates of other health outcomes and conditions.

Treatment of Shiga toxin-producing Escherichia coli O157 (O157) diarrhea with antimicrobials might alter the risk of hemolytic uremic syndrome (HUS). However, full characterization of which antimicrobials might affect risk is lacking, particularly among adults. To inform clinical management, we conducted a case-control study of residents of the FoodNet surveillance areas with O157 diarrhea during a 4-year period to assess antimicrobial class-specific associations with HUS among persons with O157 diarrhea. We collected data from medical records and patient interviews. We measured associations between treatment with agents in specific antimicrobial classes during the first week of diarrhea and development of HUS, adjusting for age and illness severity. We enrolled 1308 patients; 102 (7.8%) developed confirmed HUS. Antimicrobial treatment varied by age: <5 years (12.6%), 5-14 (11.5%), 15-39 (45.4%), ≥40 (53.4%). Persons treated with a β-lactam had higher odds of developing HUS (OR 2.80, CI 1.14-6.89). None of the few persons treated with a macrolide developed HUS, but the protective association was not statistically significant. Exposure to "any antimicrobial" was not associated with increased odds of HUS. Our findings confirm the risk of β-lactams among children with O157 diarrhea and extends it to adults. We observed a high frequency of inappropriate antimicrobial treatment among adults. Our data suggest that antimicrobial classes differ in the magnitude of risk for persons with O157 diarrhea.

Salmonella is a major cause of foodborne illness in the United States, and antimicrobial-resistant strains pose a serious threat to public health. We used Bayesian hierarchical models of culture-confirmed infections during 2004-2016 from 2 Centers for Disease Control and Prevention surveillance systems to estimate changes in the national incidence of resistant nontyphoidal Salmonella infections. Extrapolating to the United States population and accounting for unreported infections, we estimated a 40% increase in the annual incidence of infections with clinically important resistance (resistance to ampicillin or ceftriaxone or nonsusceptibility to ciprofloxacin) during 2015-2016 (≈222,000 infections) compared with 2004-2008 (≈159,000 infections). Changes in the incidence of resistance varied by serotype. Serotypes I 4,[5],12:i:- and Enteritidis were responsible for two thirds of the increased incidence of clinically important resistance during 2015-2016. Ciprofloxacin-nonsusceptible infections accounted for more than half of the increase. These estimates can help in setting targets and priorities for prevention.

Foodborne illness source attribution is foundational to a risk-based food safety system. We describe a method for attributing US foodborne illnesses caused by nontyphoidal Salmonella enterica, Escherichia coli O157, Listeria monocytogenes, and Campylobacter to 17 food categories using statistical modeling of outbreak data. This method adjusts for epidemiologic factors associated with outbreak size, down-weights older outbreaks, and estimates credibility intervals. On the basis of 952 reported outbreaks and 32,802 illnesses during 1998-2012, we attribute 77% of foodborne Salmonella illnesses to 7 food categories (seeded vegetables, eggs, chicken, other produce, pork, beef, and fruits), 82% of E. coli O157 illnesses to beef and vegetable row crops, 81% of L. monocytogenes illnesses to fruits and dairy, and 74% of Campylobacter illnesses to dairy and chicken. However, because Campylobacter outbreaks probably overrepresent dairy as a source of nonoutbreak campylobacteriosis, we caution against using these Campylobacter attribution estimates without further adjustment.

Provision of safe drinking water in the United States is a great public health achievement. However, new waterborne disease challenges have emerged (e.g., aging infrastructure, chlorine-tolerant and biofilm-related pathogens, increased recreational water use). Comprehensive estimates of the health burden for all water exposure routes (ingestion, contact, inhalation) and sources (drinking, recreational, environmental) are needed. We estimated total illnesses, emergency department (ED) visits, hospitalizations, deaths, and direct healthcare costs for 17 waterborne infectious diseases. About 7.15 million waterborne illnesses occur annually (95% credible interval [CrI] 3.88 million-12.0 million), results in 601,000 ED visits (95% CrI 364,000-866,000), 118,000 hospitalizations (95% CrI 86,800-150,000), and 6,630 deaths (95% CrI 4,520-8,870) and incurring US $3.33 billion (95% CrI 1.37 billion-8.77 billion) in direct healthcare costs. Otitis externa and norovirus infection were the most common illnesses. Most hospitalizations and deaths were caused by biofilm-associated pathogens (nontuberculous mycobacteria, Pseudomonas, Legionella), costing US $2.39 billion annually.

Foodborne disease outbreak investigations identify foods responsible for illnesses. However, it is not known the degree to which foods implicated in outbreaks reflect the distribution of food consumption in the U.S. population or the risk associated with their consumption. To examine this, we compared the distribution of foods in 24 categories implicated in outbreaks to the distribution of foods consumed by the U.S. population. Beef, chicken, eggs, fish, herbs, mollusks, pork, sprouts, seeded vegetables, and turkey were implicated in outbreaks significantly more often than expected based on the frequency of their consumption in the general population, suggesting a higher risk of contamination or mishandling from foods in these categories than in others. In contrast, pasteurized dairy, fruits, grains-beans, oils and sugars, and root/underground vegetables were less frequently implicated in outbreaks than they were consumed in the general population, suggesting a lower risk for these food categories.

Most nontyphoidal Salmonella (NTS) illnesses in the United States are thought to be foodborne. However, transmission routes likely vary among the different serotypes. We developed a relative ranking of NTS serotypes according to the strength of their association with foodborne transmission. We used Laboratory-based Enteric Disease Surveillance data to estimate the proportion of infections for each Salmonella serotype reported from 1998 to 2015 and Foodborne Disease Outbreak Surveillance System data to calculate the proportion of foodborne outbreak-associated Salmonella illnesses caused by each serotype. We calculated the ratios of these proportions to create a foodborne relatedness (FBR) measure for each serotype. Of the top 20 serotypes, Saintpaul (2.14), Heidelberg (1.61), and Berta (1.48) had the highest FBR measures; Mississippi (0.01), Bareilly (0.13), and Paratyphi B variant L(+) tartrate(+) (0.20) had the lowest. The FBRs for the three most prevalent serotypes were 1.22 for Enteritidis, 0.77 for Typhimurium, and 1.16 for Newport. This method provides a quantitative approach to estimating the relative differences in the likelihood that an illness caused by a particular serotype was transmitted by food, which may aid in tailoring strategies to prevent Salmonella illnesses and guide future research into serotype-specific source attribution.

Although researchers have described numerous risk factors for salmonellosis and for infection with specific common serotypes, the drivers of Salmonella serotype diversity among human populations remain poorly understood. In this retrospective observational study, we partition records of serotyped non-typhoidal Salmonella isolates from human clinical specimens reported to CDC national surveillance by demographic, geographic and seasonal characteristics and adapt sample-based rarefaction methods from the field of community ecology to study how Salmonella serotype diversity varied within and among these populations in the USA during 1996-2016. We observed substantially higher serotype richness in children &lt;2 years old than in older children and adults and steadily increasing richness with age among older adults. Whereas seasonal and regional variation in serotype diversity was highest among infants and young children, variation by specimen source was highest in adults. Our findings suggest that the risk for infection from uncommon serotypes is associated with host and environmental factors, particularly among infants, young children and older adults. These populations may have a higher proportion of illness acquired through environmental transmission pathways than published source attribution models estimate.

Guillain Barre syndrome (GBS), which is triggered by autoantibodies produced in response to antigenic stimuli such as certain infections and vaccinations, is the most common cause of acute flaccid paralysis worldwide. Campylobacter, the most common bacterial enteric infection in the USA, is reported to be the most commonly diagnosed antecedent of GBS, yet little information is available about the risk of post-Campylobacter GBS. Data collected through active, population-based surveillance in the Emerging Infections Program during the 2009-2010 novel Influenza A (H1N1) vaccination campaign allowed us to compare confirmed and probable GBS cases to non-cases to determine whether antecedent Campylobacter infection (or a diarrhoeal illness consistent with campylobacteriosis) was more common among cases and to assess the risk of GBS following Campylobacter infection. We estimate that 8-12% of GBS cases in the USA are attributable to Campylobacter infection (or a diarrhoeal illness consistent with campylobacteriosis), with 434-650 cases of post-diarrhoeal GBS annually and about 49 cases of GBS per 100 000 Campylobacter infections. These results provide updated estimates for post-Campylobacter GBS incidence in the USA and highlight an important benefit of effective measures to prevent Campylobacter infections.

Analysing temporal patterns in foodborne illness is important to designing and implementing effective food safety measures. The reported incidence of illness due to Salmonella in the USA. Foodborne Diseases Active Surveillance Network (FoodNet) sites has exhibited no declining trend since 1996; however, there have been significant annual trends among principal Salmonella serotypes, which may exhibit complex seasonal patterns. Data from the original FoodNet sites and penalised cubic B-spline regression are used to estimate temporal patterns in the reported incidence of illness for the top three Salmonella serotypes during 1996-2014. Our results include 95% confidence bands around the estimated annual and monthly curves for each serotype. The results show that Salmonella serotype Typhimurium exhibits a statistically significant declining annual trend and seasonality (P < 0.001) marked by peaks in late summer and early winter. Serotype Enteritidis exhibits a significant annual trend with a higher incidence in later years and seasonality (P < 0.001) marked by a peak in late summer. Serotype Newport exhibits no significant annual trend with significant seasonality (P < 0.001) marked by a peak in late summer.

The National Antimicrobial Resistance Monitoring System (NARMS) at the Centers for Disease Control and Prevention tracks resistance among Salmonella infections. The annual number of Salmonella isolates of a particular serotype from states may be small, making direct estimation of resistance proportions unreliable. We developed a Bayesian hierarchical model to improve estimation by borrowing strength from relevant sampling units. We illustrate the models with different specifications of spatio-temporal interaction using 2004-2013 NARMS data for ceftriaxone-resistant Salmonella serotype Heidelberg. Our results show that Bayesian estimates of resistance proportions were smoother than observed values, and the difference between predicted and observed proportions was inversely related to the number of submitted isolates. The model with interaction allowed for tracking of annual changes in resistance proportions at the state level. We demonstrated that Bayesian hierarchical models provide a useful tool to examine spatio-temporal patterns of small sample size such as those found in NARMS.

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

OBJECTIVE: To identify modifiable risk factors contributing to Acanthamoeba keratitis (AK) infection. METHODS: A case-control investigation was conducted. Case patients were soft contact lens wearers with laboratory-confirmed AK. Control were soft contact lens wearers ≥12 years of age, with no history of AK. Case patients were recruited from 14 ophthalmology referral centers and a clinical laboratory. Control were matched on state of residence and type of primary eye care provider (ophthalmologist or optometrist). Participants were interviewed using a standardized questionnaire. Univariable and multivariable conditional logistic regression analyses were conducted. Matched odds ratios (mORs) were calculated. RESULTS: Participants included 88 case patients and 151 matched control. Case patients were more likely to be aged <25 years (unadjusted mOR 2.7, 95% confidence interval 1.3-5.5) or aged >53 years (mOR 2.5, 1.1-5.7), and more likely to be men (mOR 2.6, 1.4-4.8). Unadjusted analyses identified multiple risk factors: rinsing (mOR 6.3, 1.3-29.9) and storing lenses in tap water (mOR 3.9, 1.2-12.3), topping off solution in the lens case (mOR 4.0, 2.0-8.0), having worn lenses ≤5 years (mOR 2.4, 1.3-4.4), rinsing the case with tap water before storing lenses (mOR 2.1, 1.1-4.1), and using hydrogen peroxide (mOR 3.6, 1.1-11.7) versus multipurpose solution. Significant risk factors in multivariable modeling included age >53 years, male sex, topping off, and using saline solution. CONCLUSIONS: Numerous modifiable risk factors for AK were identified, mostly involving hygiene practices. To reduce the risk of AK, lens wearers should observe recommended lens care practices.

Salmonella infections are a major cause of illness in the United States. The antimicrobial agents used to treat severe infections include ceftriaxone, ciprofloxacin, and ampicillin. Antimicrobial drug resistance has been associated with adverse clinical outcomes. To estimate the incidence of resistant culture-confirmed nontyphoidal Salmonella infections, we used Bayesian hierarchical models of 2004-2012 data from the Centers for Disease Control and Prevention National Antimicrobial Resistance Monitoring System and Laboratory-based Enteric Disease Surveillance. We based 3 mutually exclusive resistance categories on susceptibility testing: ceftriaxone and ampicillin resistant, ciprofloxacin nonsusceptible but ceftriaxone susceptible, and ampicillin resistant but ceftriaxone and ciprofloxacin susceptible. We estimated the overall incidence of resistant infections as 1.07/100,000 person-years for ampicillin-only resistance, 0.51/100,000 person-years for ceftriaxone and ampicillin resistance, and 0.35/100,000 person-years for ciprofloxacin nonsusceptibility, or approximately 6,200 resistant culture-confirmed infections annually. These national estimates help define the magnitude of the resistance problem so that control measures can be appropriately targeted.

BACKGROUND: Ceftriaxone resistance in Salmonella is a serious public health threat. Ceftriaxone is commonly used to treat severe Salmonella infections, especially in children. Identifying the sources and drivers of ceftriaxone resistance among nontyphoidal Salmonella is crucial. MATERIALS AND METHODS: The National Antimicrobial Resistance Monitoring System (NARMS) tracks antimicrobial resistance in foodborne and other enteric bacteria from humans, retail meats, and food animals. We examined NARMS data reported during 1996-2013 to characterize ceftriaxone-resistant Salmonella infections in humans. We used Spearman rank correlation to examine the relationships between the annual percentage of ceftriaxone resistance among Salmonella isolates from humans with isolates from retail meats and food animals. RESULTS: A total of 978 (2.9%) of 34,100 nontyphoidal Salmonella isolates from humans were resistant to ceftriaxone. Many (40%) ceftriaxone-resistant isolates were from children younger than 18 years. Most ceftriaxone-resistant isolates were one of three serotypes: Newport (40%), Typhimurium (26%), or Heidelberg (12%). All were resistant to other antimicrobials, and resistance varied by serotype. We found statistically significant correlations in ceftriaxone resistance between human and ground beef Newport isolates (r = 0.83), between human and cattle Typhimurium isolates (r = 0.57), between human and chicken Heidelberg isolates (r = 0.65), and between human and turkey Heidelberg isolates (r = 0.67). CONCLUSIONS: Ceftriaxone resistance among Salmonella Newport, Typhimurium, and Heidelberg isolates from humans strongly correlates with ceftriaxone resistance in isolates from ground beef, cattle, and poultry, respectively. These findings support other lines of evidence that food animals are important reservoirs of ceftriaxone-resistant Salmonella that cause human illness in the United States.

INTRODUCTION: Salmonella causes an estimated 100,000 antimicrobial-resistant infections annually in the United States. Salmonella antimicrobial resistance may result in bacteremia and poor outcomes. We describe antimicrobial resistance among nontyphoidal Salmonella blood isolates using data from the National Antimicrobial Resistance Monitoring System. METHODS: Human nontyphoidal Salmonella isolates from 2003-2013 were classified as fully susceptible, resistant to ≥1 antimicrobial agent, or resistant to a first-line agent. Logistic regression was used to compare resistance patterns, serotypes, and patient characteristics for Salmonella isolated from blood vs. stool and to determine resistance trends over time. RESULTS: Approximately 20% of blood isolates had antimicrobial resistance. Bacteremia was associated with male sex, age ≥65 years, and specific serotypes. Blood isolates were more likely to be resistant to ≥1 agent for serotypes Enteritidis, Javiana, Panama, and Typhimurium. Blood isolates were most commonly resistant to tetracycline (19%), and more likely resistant to a first-line agent (OR, 1.81; 95% CI, 1.56-2.11) than stool isolates. Ceftriaxone resistance increased in blood isolates from 2003-2013 (OR, 1.12; 95% CI, 1.02-1.22). CONCLUSION: Resistance to first-line treatment agents in Salmonella bacteremia patients is a concern for public health and for informing clinical decisions. Judicious antimicrobial use is crucial to limit resistance.

We characterized the listeriosis incubation period (IP) among outbreak-associated cases using a simulation model to account for patients with multiple exposure dates. The median IP was 11 days; 90% of cases occurred within 28 days, and the IP varied by clinical manifestation.

Outbreak data have been used to estimate the proportion of illnesses attributable to different foods. Applying outbreak-based attribution estimates to nonoutbreak foodborne illnesses requires an assumption of similar exposure pathways for outbreak and sporadic illnesses. This assumption cannot be tested, but other comparisons can assess its veracity. Our study compares demographic, clinical, temporal, and geographic characteristics of outbreak and sporadic illnesses from Campylobacter, Escherichia coli O157, Listeria, and Salmonella bacteria ascertained by the Foodborne Diseases Active Surveillance Network (FoodNet). Differences among FoodNet sites in outbreak and sporadic illnesses might reflect differences in surveillance practices. For Campylobacter, Listeria, and Escherichia coli O157, outbreak and sporadic illnesses are similar for severity, sex, and age. For Salmonella, outbreak and sporadic illnesses are similar for severity and sex. Nevertheless, the percentage of outbreak illnesses in the youngest age category was lower. Therefore, we do not reject the assumption that outbreak and sporadic illnesses are similar.

The in vitro activity of the novel fungal Cyp51 inhibitor VT-1129 was evaluated against a large panel of C. neoformans and C. gattii isolates. VT-1129 demonstrated potent activity against both Cryptococcus species as demonstrated by low MIC50 and MIC90 values. Against C. gattii, the in vitro potency was maintained against all genotypes. In addition, significantly lower geometric mean MICs were observed for VT-1129 compared to fluconazole against C. neoformans, including isolates with reduced fluconazole susceptibility.

BACKGROUND: Despite control efforts, salmonellosis continues to cause an estimated 1.2 million infections in the United States (US) annually. We describe the incidence of salmonellosis in the US and introduce a novel approach to examine the epidemiologic similarities and differences of individual serotypes. METHODS: Cases of salmonellosis in humans reported to the laboratory-based National Salmonella Surveillance System during 1996-2011 from US states were included. Coefficients of variation were used to describe distribution of incidence rates of common Salmonella serotypes by geographic region, age group and sex of patient, and month of sample isolation. RESULTS: During 1996-2011, more than 600,000 Salmonella isolates from humans were reported, with an average annual incidence of 13.1 cases/100,000 persons. The annual reported rate of Salmonella infections did not decrease during the study period. The top five most commonly reported serotypes, Typhimurium, Enteritidis, Newport, Heidelberg, and Javiana, accounted for 62% of fully serotyped isolates. Coefficients of variation showed the most geographically concentrated serotypes were often clustered in Gulf Coast states and were also more frequently found to be increasing in incidence. Serotypes clustered in particular months, age groups, and sex were also identified and described. CONCLUSIONS: Although overall incidence rates of Salmonella did not change over time, trends and epidemiological factors differed remarkably by serotype. A better understanding of Salmonella, facilitated by this comprehensive description of overall trends and unique characteristics of individual serotypes, will assist in responding to this disease and in planning and implementing prevention activities.

Populations living in informal settlements with inadequate water and sanitation infrastructure are at risk of epidemic disease. In 2010, we conducted 398 household surveys in two informal settlements in Nairobi, Kenya with isolated cholera cases. We tested source and household water for free chlorine residual (FCR) and Escherichia coli in approximately 200 households. International guidelines are ≥0.5 mg/L FCR at source, ≥0.2 mg/L at household, and <1 E. coli/100 mL. In these two settlements, 82% and 38% of water sources met FCR guidelines; and 7% and 8% were contaminated with E. coli, respectively. In household stored water, 82% and 35% met FCR guidelines and 11% and 32% were contaminated with E. coli, respectively. Source water FCR ≥0.5 mg/L (p = 0.003) and reported purchase of a household water treatment product (p = 0.002) were associated with increases in likelihood that household stored water had ≥0.2 mg/L FCR, which was associated with a lower likelihood of E. coli contamination (p < 0.001). These results challenge the assumption that water quality in informal settlements is universally poor and the route of disease transmission, and highlight that providing centralized water with ≥0.5 mg/L FCR or (if not feasible) household water treatment technologies reduces the risk of waterborne cholera transmission in informal settlements.

BACKGROUND: A growing segment of the population-adults aged ≥65 years-is more susceptible than younger adults to certain enteric (including foodborne) infections and experience more severe disease. MATERIALS AND METHODS: Using data on laboratory-confirmed infections from the Foodborne Diseases Active Surveillance Network (FoodNet), we describe trends in the incidence of Campylobacter spp., Escherichia coli O157, Listeria monocytogenes, and nontyphoidal Salmonella infections in adults aged ≥65 years over time and by age group and sex. We used data from FoodNet and other sources to estimate the total number of illnesses, hospitalizations, and deaths in the United States caused by these infections each year using a statistical model to adjust for underdiagnosis (taking into account medical care-seeking, stool sample submission, laboratory practices, and test sensitivity). RESULTS: From 1996 to 2012, 4 pathogens caused 21,405 laboratory-confirmed infections among older adults residing in the FoodNet surveillance area; 49.3% were hospitalized, and 2.6% died. The average annual rate of infection was highest for Salmonella (12.8/100,000) and Campylobacter (12.1/100,000). Salmonella and Listeria led as causes of death. Among older adults, rates of laboratory-confirmed infection and the percentage of patients who were hospitalized and who died generally increased with age. A notable exception was the rate of Campylobacter infections, which decreased with increasing age. Adjusting for underdiagnosis, we estimated that these pathogens caused about 226,000 illnesses ( approximately 600/100,000) annually among U.S. adults aged ≥65 years, resulting in approximately 9700 hospitalizations and approximately 500 deaths. CONCLUSIONS: Campylobacter, E. coli O157, Listeria, and Salmonella are major contributors to illness in older adults, highlighting the value of effective and targeted intervention.

To design effective food safety programmes we need to estimate how many sporadic foodborne illnesses are caused by specific food sources based on case-control studies. Logistic regression has substantive limitations for analysing structured questionnaire data with numerous exposures and missing values. We adapted random forest to analyse data of a case-control study of Salmonella enterica serotype Enteritidis illness for source attribution. For estimation of summary population attributable fractions (PAFs) of exposures grouped into transmission routes, we devised a counterfactual estimator to predict reductions in illness associated with removing grouped exposures. For the purpose of comparison, we fitted the data using logistic regression models with stepwise forward and backward variable selection. Our results show that the forward and backward variable selection of logistic regression models were not consistent for parameter estimation, with different significant exposures identified. By contrast, the random forest model produced estimated PAFs of grouped exposures consistent in rank order with results obtained from outbreak data, with egg-related exposures having the highest estimated PAF (22.1%, 95% confidence interval 8.5-31.8). Random forest might be structurally more coherent and efficient than logistic regression models for attributing Salmonella illnesses to sources involving many causal pathways.

OBJECTIVE: To assess the clinical spectrum of postdiarrheal hemolytic uremic syndrome (D+HUS) hospitalizations and sought predictors of in-hospital death to help identify children at risk of poor outcomes. STUDY DESIGN: We assessed clinical variables collected through population-based surveillance of D+HUS in children <18 years old hospitalized in 10 states during 1997-2012 as predictors of in-hospital death by using tree modeling. RESULTS: We identified 770 cases. Of children with information available, 56.5% (430 of 761) required dialysis, 92.6% (698 of 754) required a transfusion, and 2.9% (22 of 770) died; few had a persistent dialysis requirement (52 [7.3%] of 716) at discharge. The tree model partitioned children into 5 groups on the basis of 3 predictors (highest leukocyte count and lowest hematocrit value during the 7 days before to 3 days after the diagnosis of hemolytic uremic syndrome, and presence of respiratory tract infection [RTI] within 3 weeks before diagnosis). Patients with greater leukocyte or hematocrit values or a recent RTI had a greater probability of in-hospital death. The largest group identified (n = 533) had none of these factors and had the lowest odds of death. Many children with RTI had recent antibiotic treatment for nondiarrheal indications. CONCLUSION: Most children with D+HUS have good hospitalization outcomes. Our findings support previous reports of increased leukocyte count and hematocrit as predictors of death. Recent RTI could be an additional predictor, or a marker of other factors such as antibiotic exposure, that may warrant further study.

We explored the overall impact of foodborne disease caused by seven leading foodborne pathogens in the United States using the disability adjusted life year (DALY). We defined health states for each pathogen (acute illness and sequelae) and estimated the average annual incidence of each health state using data from public health surveillance and previously published estimates from studies in the United States, Canada and Europe. These pathogens caused about 112 000 DALYs annually due to foodborne illnesses acquired in the United States. Non-typhoidal Salmonella (32 900) and Toxoplasma (32 700) caused the most DALYs, followed by Campylobacter (22 500), norovirus (9900), Listeria monocytogenes (8800), Clostridium perfringens (4000), and Escherichia coli O157 (1200). These estimates can be used to prioritize food safety interventions. Future estimates of the burden of foodborne disease in DALYs would be improved by addressing important data gaps and by the development and validation of US-specific disability weights for foodborne diseases.