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.

Nearest-Neighbors Matching for Case-Control Study Analyses: Better Risk Factor Identification From a Study of Sporadic Campylobacteriosis in the United States.

BACKGROUND: Case-control studies are commonly used to explore factors associated with enteric bacterial diseases. Control of confounding is challenging due to a 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 2632 subjects during 1998-1999. We performed multiple imputations 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 1046 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 nonpoultry meat had the highest PAFs (62% and 59%, respectively). CONCLUSIONS: Nearest-neighbors matching appear to provide an improved ability to examine rare exposures and better control for numerous highly associated confounders.

Salmonella Serotypes Associated with Illnesses after Thanksgiving Holiday, United States, 1998-2018.

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.

Risk of Hemolytic Uremic Syndrome Related to Treatment of Escherichia coli O157 Infection with Different Antimicrobial Classes.

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 ß-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 ß-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.

Estimating the Number of Illnesses Caused by Agents Transmitted Commonly Through Food: A Scoping Review.

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.

Increased Incidence of Antimicrobial-Resistant Nontyphoidal Salmonella Infections, United States, 2004-2016.

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.

Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States.

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.

Bayesian hierarchical model of ceftriaxone resistance proportions among Salmonella serotype Heidelberg infections.

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.

Risk Factors for Acanthamoeba Keratitis-A Multistate Case-Control Study, 2008-2011.

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.

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

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.

Ceftriaxone-Resistant Nontyphoidal Salmonella from Humans, Retail Meats, and Food Animals in the United States, 1996-2013.

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.

Estimated Incidence of Antimicrobial Drug-Resistant Nontyphoidal Salmonella Infections, United States, 2004-2012.

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 ≈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.

Assessment of the Incubation Period for Invasive Listeriosis.

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

Comparing Characteristics of Sporadic and Outbreak-Associated Foodborne Illnesses, United States, 2004-2011.

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.

Bacterial Enteric Infections Among Older Adults in the United States: Foodborne Diseases Active Surveillance Network, 1996-2012.

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 (≈600/100,000) annually among U.S. adults aged ≥65 years, resulting in ≈9700 hospitalizations and ≈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.

Postdiarrheal hemolytic uremic syndrome in United States children: clinical spectrum and predictors of in-hospital death.

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.

Improved health among people living with HIV/AIDS who received packages of proven preventive health interventions, Amhara, Ethiopia.

In 2009, basic care packages (BCP) containing health products were distributed to HIV-infected persons in Ethiopia who were clients of antiretroviral therapy clinics. To measure health impact, we enrolled clients from an intervention hospital and comparison hospital, and then conducted a baseline survey, and 7 bi-weekly home visits. We enrolled 405 intervention group clients and 344 comparison clients. Intervention clients were more likely than comparison clients to have detectable chlorine in stored water (40% vs. 1%, p<0.001), soap (51% vs. 36%, p<0.001), and a BCP water container (65% vs. 0%, p<0.001) at every home visit. Intervention clients were less likely than comparison clients to report illness (44% vs. 67%, p<0.001) or health facility visits for illness (74% vs. 95%, p<0.001), and had lower median illness scores (1.0 vs. 3.0, p<0.05). Participation in the BCP program appeared to improve reported health outcomes.

Recurrence of Helicobacter pylori infection in Bolivian children and adults after a population-based "screen and treat" strategy.

BACKGROUND: Strategies to prevent gastric cancer by decreasing Helicobacter pylori infections in high-prevalence, low-income countries could include a population-based "screen and treat" eradication program. METHODS: We tested residents of two rural villages for H. pylori infection using urea breath test (UBT), treated infected persons using directly observed therapy (DOT), retested for cure, and retested after 1 year later for H. pylori infection. FINDINGS: We tested 1,065 (92%) of 1153 residents from two villages in rural Bolivia. Baseline H. pylori prevalence was 80% (95% confidence interval [CI]: 78-84). Age-specific cure rates were similar (≥92%) after DOT. Among those cured, 12% (95% CI: 8-15) had recurrent infection. Age-specific annual H. pylori recurrence rates for combined villages were 20% (95% CI: 10-29) in persons <5 years, 20% (95% CI: 10-29) in 5-9 years, 8% (95% CI: 1-15) in 10-14 years, and 8% (95% CI: 4-12) in persons ≥15 years. Compared with the referent population, those ≥15 years, recurrent infections were significantly more likely in children <5 years (odds ratios [OR] 2.7, 95% CI: 1.2-5.8) and 5-9 years (OR 2.7, 95% CI: 1.4-5.1). INTERPRETATION: Children <10 years had high H. pylori recurrence rates following a population-based screen and treat program; this H. pylori eradication strategy may not be feasible in high-prevalence, low-income settings.

Dynamics of shigellosis epidemics: estimating individual-level transmission and reporting rates from national epidemiologic data sets.

Shigellosis, a diarrheal disease, is endemic worldwide and is responsible for approximately 15,000 laboratory-confirmed cases in the United States every year. However, patients with shigellosis often do not seek medical care. To estimate the burden of shigellosis, we extended time-series susceptible-infected-recovered models to infer epidemiologic parameters from underreported case data. We applied the time-series susceptible-infected-recovered-based inference schemes to analyze the largest surveillance data set of Shigella sonnei in the United States from 1967 to 2007 with county-level resolution. The dynamics of shigellosis transmission show strong annual and multiyear cycles, as well as seasonality. By using the schemes, we inferred individual-level parameters of shigellosis infection, including seasonal transmissibilities and basic reproductive number (R0). In addition, this study provides quantitative estimates of the reporting rate, suggesting that the shigellosis burden in the United States may be more than 10 times the number of laboratory-confirmed cases. Although the estimated reporting rate is generally under 20%, and R0 is generally under 1.5, there is a strong negative correlation between estimates of the reporting rate and R0. Such negative correlations are likely to pose identifiability problems in underreported diseases. We discuss complementary approaches that might further disentangle the true reporting rate and R0.

Attribution of foodborne illnesses, hospitalizations, and deaths to food commodities by using outbreak data, United States, 1998-2008.

Each year, >9 million foodborne illnesses are estimated to be caused by major pathogens acquired in the United States. Preventing these illnesses is challenging because resources are limited and linking individual illnesses to a particular food is rarely possible except during an outbreak. We developed a method of attributing illnesses to food commodities that uses data from outbreaks associated with both simple and complex foods. Using data from outbreak-associated illnesses for 1998-2008, we estimated annual US foodborne illnesses, hospitalizations, and deaths attributable to each of 17 food commodities. We attributed 46% of illnesses to produce and found that more deaths were attributed to poultry than to any other commodity. To the extent that these estimates reflect the commodities causing all foodborne illness, they indicate that efforts are particularly needed to prevent contamination of produce and poultry. Methods to incorporate data from other sources are needed to improve attribution estimates for some commodities and agents.