Environmental justice mapping tools are an important resource for helping identify communities at risk for environmental injustice and helping to guide decision making for policymakers, researchers, and communities. They typically include indicators related to environmental risks (e.g., air quality), socioeconomic factors (e.g., demographic data), and physical health (e.g., disease morbidity and mortality). Recent reviews have found that only two existing tools incorporate indicators related to infectious disease, despite the intrinsic relationship between environmental conditions and infectious disease transmission. This article provides a comprehensive framework for incorporating infectious disease indicators into environmental justice screening and mapping tools. The framework for indicator selection includes four key dimensions: relevance to environmental justice, data quality and availability, spatial-temporal characteristics, and practical utility for decision making. Indicators can be categorized into three types: direct disease measures (e.g., morbidity and mortality), vulnerability indicators (e.g., vaccination rates), and environmental risk factors (e.g., vector habitats). Some of the challenges to incorporating infectious disease indicators include temporal variability (e.g., seasonality) and the availability of spatially meaningful direct measures that align with other indicators. However, methodological approaches could overcome these challenges-for example, incorporating dynamic disease surveillance data using rolling averages for endemic diseases. Integrating infectious disease indicators into environmental justice mapping tools is a complex challenge but a vital step in advancing environmental health equity.

Through Epidemiology and Laboratory Capacity (ELC) cooperative agreements, the US Centers for Disease Control and Prevention (CDC) has funded three programs focused on enhancing foodborne illness outbreak detection and response at the state level-the Foodborne Diseases Centers for Outbreak Response Enhancement (FoodCORE), the Integrated Food Safety Centers of Excellence (Food Safety CoE), and OutbreakNet Enhanced (OBNE). Data from the CDC's Foodborne Disease Outbreak Surveillance System (FDOSS) were used to assess the effect of ELC-funded foodborne programs on single-state foodborne illness outbreak reporting from 2009 to 2022. Based on 2022 program status, participation in these programs was associated with higher rates of reporting compared to states not enrolled in any ELC programs. Average foodborne outbreak reporting rates per million population were 1.54 for states enrolled in No Programs, 2.40 for OBNE states, 3.75 for FoodCORE states, and 4.16 for Food Safety CoE states. For Salmonella, Shiga toxin-producing E. coli, and Listeria (SSL) outbreaks, average reporting rates per million population were 0.37 for states enrolled in No Programs, 0.46 for OBNE states, and 0.69 for FoodCORE and 0.67 for Food Safety CoE states. Overall ELC funding was associated with increased outbreak reporting rates. A one-dollar increase in average ELC funding was associated with an estimated 0.88 (95% CI 0.69, 1.07) unit increase in the single-state foodborne outbreak reporting rate and an estimated 0.14 (95% CI 0.09, 0.19) unit increase in the SSL outbreak reporting rate. Federal support for public health surveillance improves the detection and reporting of foodborne illness.

OBJECTIVES:The workplace is an important setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure and transmission. Using data from a large case-control study in Colorado during 2021 and 2022, we aimed to evaluate working outside the home and SARS-CoV-2 infection, the racial and ethnic distribution of workers in occupations associated with infection, and workplace face mask use. METHODS:Cases were Colorado adults with a positive SARS-CoV-2 test by reverse transcription-polymerase chain reaction (RT-PCR) reported to Colorado's COVID-19 surveillance system selected from surveillance data ≤12 days after their specimen collection date. Control participants were randomly selected adult Coloradans with a RT-PCR-confirmed negative SARS-CoV-2 test result reported to the same surveillance system. RESULTS:Working outside the home was associated with infection (odds ratio [OR] = 1.46, 95% confidence interval [CI]: 1.39-1.54). Among participants working outside the home, "Food Preparation and Serving Related" (aOR = 2.35, 95% CI: 1.80-3.06), "Transportation and Material Moving" (aOR = 2.09, 95% CI: 1.62-2.69), "Construction and Extraction" (aOR = 1.88, 95% CI: 1.36-2.59), "Protective Service" (aOR = 1.60, 95% CI: 1.15-2.24), and "Sales and Related" (aOR = 1.44, 95% CI: 1.22-1.69) were occupational categories most strongly associated with infection. American Indian/Alaskan Native, Black, and Hispanic/Latino participants were more likely than others to work in occupational categories with the highest odds of infection (p < 0.05). Cases were less likely than controls to report always wearing a mask (31.9% vs. 41.5%) and wearing a KN95/N95/KF94 mask (16.8% vs. 27.2%) at work. CONCLUSIONS:These findings emphasize the importance of occupation and workplace mask use in the COVID-19 pandemic and its disproportionate racial/ethnic impact on workers.

Objective: Food safety progress depends on the ability of public health agencies to detect and investigate foodborne disease outbreaks. The Integrated Food Safety Centers of Excellence identify and implement best practices and serve as resources for public health professionals who investigate enteric disease outbreaks. To target the needs of this diverse workforce, the Integrated Food Safety Centers of Excellence developed and assessed a professional tier framework and competencies. Methods: We described the characteristics of public health professionals who investigate enteric disease outbreaks in the epidemiology role in a conceptual tiered framework. We mapped core competencies to each tier and disseminated a survey to practitioners at local (June 2019) and state (August 2018) US public health agencies to evaluate the importance and frequency of each competency. Results: We developed 15 competencies on surveillance, outbreak detection, interview skills, investigation team, specimen testing, data analysis, hypothesis generation, study design, communication, enteric disease biology, control measures, legal authority, quality improvement, environmental health, and reporting to surveillance. The 286 survey respondents selected interview skills, surveillance, control measures, and hypothesis generation as the competencies most important to their work and most frequently performed. Conclusion: The Integrated Food Safety Centers of Excellence created the first published workforce framework and competencies for public health professionals who detect and investigate enteric disease outbreaks in the epidemiology role, in collaboration with local, state, and federal public health agencies and national organizations. These tools have been integrated into existing programs and can be used to develop training curricula, assess workforce competency over time, and identify priorities for continuing education and training.

Context: Routine case investigations are critical for enteric disease control and surveillance. Given limited resources and staffing, public health agencies are exploring more efficient case investigation methods. Objective: To identify and describe the advantages and disadvantages of using online surveys to supplement routine enteric disease case investigations. Design: We evaluated routine Campylobacter interview data collected via telephone vs online by interviewers with the Colorado Department of Public Health and Environment. Setting and Participation: Colorado laboratory-confirmed Campylobacter cases reported from September 1, 2020, through December 31, 2021. Main Outcome Measures: We calculated modality preference, response rates, and data quality (missing and unknown answers) and compared demographics (age, gender, and urban vs rural) by modality. Estimated staff time savings and investigation timeliness were compared. Results: Modality preference was split among the 966 contacted Campylobacter cases (46% telephone, 50% online, and 4% refusal). Among online respondents, 57% completed the survey for an overall 63% response rate. Females and those 18 to 44 years of age were most likely to select (55%, 60%) and complete (57%, 66%) the online survey, while those under 18 and over 65 years of age were least likely to select (47%, 45%) or complete (53%, 46%). Those who identified as non-Hispanic Black were most likely to select online (62%), whereas those who identified as mixed-race non-Hispanic and non-Hispanic White had the highest completion (78%, 60%). Modality preference was comparable by geography; however, rural residents had higher completion rates (61%). Data quality and completeness were comparable between modalities. Completing the 274 online surveys via telephone would have taken an estimated 78 hours of additional staff time. Conclusions: Online surveys can increase public health efficiency and capacity while maintaining data quality. However, use should be limited to high-burden, low-resource pathogens due to reduced response rates. Understanding implementation best practices and conducting regular evaluation are critical for optimization.

AIMS:Enteric pathogens with a livestock reservoir pose a unique risk to people in occupations with regular contact with animals. However, public health surveillance of occupational exposures is inadequate, with surveillance for occupation typically focusing on the risk of transmission and the need for worker exclusion, rather than workplace exposures. To improve surveillance for occupational zoonoses, the Colorado Integrated Food Safety Center of Excellence convened a group of subject matter experts who developed a set of variables on occupation, industry, and exposures, which were integrated into Colorado's surveillance system in 2017. We evaluated the quality and completeness of these new occupational fields for interviewed cases with laboratory-confirmed zoonotic infections and compared occupations to cases with a non-zoonotic infection (Shigella) and to employment data from the Bureau of Labor Statistics. METHODS AND RESULTS:From March 2017 through December 2019, 3668 domestically acquired, laboratory-confirmed sporadic infections of Campylobacter, Cryptosporidium, Shiga toxin-producing Escherichia coli, and non-typhoidal Salmonella among individuals ≥14 years of age were interviewed by public health. We found asking explicitly about occupational exposure risks and focusing on animal exposures, improved data quality and accuracy. Of the cases who stated that they were employed, 262 (13%) reported working in an occupation with regular animal exposure, and 254 (14%) reported an industry with regular animal exposure. Cases with an animal exposure occupation were more likely to be male and live in a rural or frontier county compared to other occupations. All occupations with regular animal contact were reported at a higher frequency than among Shigella cases or the general population. CONCLUSIONS:Public health efforts, both in occupational health and communicable disease sectors, should be made to improve surveillance for enteric zoonoses and identify opportunities for prevention strategies.

Foodborne disease burden estimates inform public health priorities and can help the public understand disease impact. This article provides new estimates of the cost of U.S. foodborne illness. Our research updated disease modeling underlying these cost estimates with a focus on enhancing chronic sequelae modeling and enhancing uncertainty modeling. Our cost estimates were based on U.S. Centers for Disease Control and Prevention estimates of the numbers of foodborne illnesses, hospitalizations, and deaths caused by 31 known foodborne pathogens and unspecified foodborne agents. We augmented these estimates of illnesses, hospitalizations, and deaths with more detailed modeling of health outcomes, including chronic sequelae. For health outcomes, we relied on U.S. data and research where possible, supplemented by the use of non-U.S. research where necessary and scientifically appropriate. Cost estimates were developed from large insurance or hospital charge databases, public data sources, and existing literature and were adjusted to 2023 dollars. We estimated the cost of foodborne illness in the United States circa 2023 to be $75 billion. Deaths accounted for 56% and chronic outcomes for 31% of the mean cost. The costliest pathogen was nontyphoidal Salmonella at $17.1 billion followed by Campylobacter at $11.3 billion. Toxoplasma ($5.7 billion) and Listeria ($4 billion) followed due primarily to deaths and chronic outcomes from pregnancy-associated cases. Per-case cost ranged from $196 for Bacillus cereus to $4.6 million for Vibrio vulnificus. Unspecified agents accounted for 38% of the total cost of foodborne illness, but these illnesses were generally mild (per-case cost $781). These cost estimates can help inform food safety priorities. Our pathogen-specific per-case cost estimates can also help inform benefit-cost analysis required for new federal food safety regulations.

Objectives: Although enteric disease case interviews are critical for control measures and education, not all case-patients are interviewed. We evaluated systematic differences between people with an enteric disease in Colorado who were and were not interviewed to identify ways to increase response rates and reduce biases in the surveillance data used to guide public health interventions. Methods: We obtained data from the Colorado Electronic Disease Reporting System from March 1, 2017, through December 31, 2019. Among case-patients not interviewed and interviewed, we used univariate analyses to describe sociodemographic characteristics, timing of contact attempts, and effect of additional funding. Results: As compared with case-patients who were interviewed, case-patients who were not interviewed were significantly more likely to be aged 18 to 39 years (35.7% vs 31.7%; P < .001); identify as male, Hispanic, or Black; be experiencing homelessness or hospitalization; reside in rural/frontier areas or an institution; or live in areas with lower levels of education, life expectancy, and income. Time to first contact attempt was longer for case-patients who were not interviewed than for those who were (mean days from specimen collection to first contact attempt, 9.8 vs 6.8; P < .001). Residing in a jurisdiction with additional funding for interviewing was associated with increased interview rates (87.7% vs 68.8%) and timeliness of public health report and first contact attempt (2.3 vs 4.4 days; P < .001). Conclusion: Findings can guide efforts to improve response rates in groups least likely to be interviewed, resulting in reduced biases in surveillance data, better disease mitigation, and increased efficiency in case investigations. Timeliness of case interviews and additional funding to conduct case investigations were factors in increasing response rates.

Background: Temperature and precipitation have previously been associated with Salmonella infections. The association between salmonellosis and precipitation might be explained by antecedent drought conditions; however, few studies have explored this effect. Methods: Using an ecological study design with public health surveillance, meteorological (total precipitation [inches], temperature [average degrees F], Palmer Drought Severity Index [PDSI, category]), and livestock data we explored the association between precipitation and Salmonella infections reported in 127/141 counties from 2009 to 2021 in the Southwest, US and determined how this association was modified by antecedent drought. To explore the acute effect of precipitation on Salmonella infections we used negative binomial generalized estimating equations adjusted for temperature with a 2-week lag resulting in Incidence Rate Ratios (IRR). Stratified analyses were used to explore the effect of antecedent drought and type of animal density on this association. Results: A one inch increase in precipitation was associated with a 2 % increase in Salmonella infections reported two weeks later (IRR: 1.02, 95 % CI: 1.00, 1.04) after adjusting for average temperature and PDSI. Precipitation following moderate (IRR: 1.22, 95 % CI: 1.17, 1.28) and severe drought (IRR: 1.16, 95 % CI: 1.10, 1.22) was associated with a significant increase in cases, whereas in the most extreme drought conditions, cases were significantly decreased (IRR: 0.89, 95 % CI: 0.85, 0.94). Overall, more precipitation (above a 30-year normal, the 95th and 99th percentiles) were associated with greater increases in cases, with the highest increase following moderate and severe drought. Counties with a higher density of chicken and beef cattle were significantly associated with increased cases regardless of drought status, whereas dairy cattle, and cattle including calves had mixed results. Discussion: Our study suggests precipitation following prior dry conditions is associated with an increase in salmonellosis in the Southwest, US. Public health is likely to see an increase in salmonellosis with extreme precipitation events, especially in counties with a high density of chicken and beef cattle.

OBJECTIVE:To assess the impact of the COVID-19 pandemic on the state-level enteric disease workforce and routine enteric disease surveillance and outbreak investigation activities in the western United States. DESIGN AND SETTING:Key informant interviews conducted using bidirectional video from March to April 2022. PARTICIPANTS:Enteric disease epidemiologists at state public health agencies in the western states served by the Colorado and Washington Integrated Food Safety Centers of Excellence. MAIN OUTCOMES:Key themes were identified using grounded theory. RESULTS:Nine themes were identified including excessive workload, shifts in local and state responsibilities, challenges with retention and hiring, importance of student teams, laboratory supplies shortages, changes to case and outbreak investigation priorities, transitioning back to enterics, adoption of new methods and technology, and current and future needs. CONCLUSIONS:The COVID-19 pandemic response had a substantial impact on state-level enteric disease activities in western states, with many staff members diverted from routine responsibilities and a de-prioritization of enteric disease work. There is a need for sustainable solutions to address staffing shortages, prioritize employee mental health, and effectively manage routine workloads when responding to emergencies.

BACKGROUND:Previous work has found climate change-induced weather variability is suspected to increase the transmission of enteric pathogens, including Campylobacter, a leading cause of bacterial gastroenteritis. While the relationship between extreme weather events and diarrheal diseases has been documented, the specific impact on Campylobacter infections remains underexplored. OBJECTIVE:To synthesize the peer-reviewed literature exploring the effect of weather variability on Campylobacter infections in humans. METHODS:The review included English language, peer-reviewed articles, published up to September 1, 2022 in PubMed, Embase, GEOBASE, Agriculture and Environmental Science Database, and CABI Global Health exploring the effect of an antecedent weather event on human enteric illness caused by Campylobacter (PROSPERO Protocol # 351884). We extracted study information including data sources, methods, summary measures, and effect sizes. Quality and weight of evidence reported was summarized and bias assessed for each article. RESULTS:After screening 278 articles, 47 articles (34 studies, 13 outbreak reports) were included in the evidence synthesis. Antecedent weather events included precipitation (n = 35), temperature (n = 30), relative humidity (n = 7), sunshine (n = 6), and El Niño and La Niña (n = 3). Reviewed studies demonstrated that increases in precipitation and temperature were correlated with Campylobacter infections under specific conditions, whereas low relative humidity and sunshine were negatively correlated. Articles estimating the effect of animal operations (n = 15) found presence and density of animal operations were significantly associated with infections. However, most of the included articles did not assess confounding by seasonality, presence of animal operations, or describe estimates of risk. DISCUSSION:This review explores what is known about the influence of weather events on Campylobacter and identifies previously underreported negative associations between low relative humidity and sunshine on Campylobacter infections. Future research should explore pathogen-specific estimates of risk, which can be used to influence public health strategies, improve source attribution and causal pathways, and project disease burden due to climate change.

BACKGROUND : Weather variability is associated with enteric infections in people through a complex interaction of human, animal, and environmental factors. Although Campylobacter infections have been previously associated with precipitation and temperature, the association between precipitation and drought on campylobacteriosis has not been studied. OBJECTIVE : Using data from Arizona, Colorado, New Mexico, and counties in Utah, this ecological study aimed to assess the association between precipitation and the incidence of campylobacteriosis by county from 2009 to 2021 and to determine how this association is modified by prior drought level and animal operations. METHODS : We merged 38,782 cases of campylobacteriosis reported in 127 counties with total precipitation (in inches), temperature (in average degrees Fahrenheit), Palmer Drought Severity Index (PDSI, category), and animal census data (presence, density per square mile) by week from 2009 to 2021. Negative binomial generalized estimating equations adjusted for temperature with a 3-wk lag were used to explore the association between precipitation on campylobacteriosis with resulting incidence rate ratios (IRRs). Stratified analyses explored the association with precipitation following antecedent drought, presence of farm operations, and animal density. RESULTS : A 1-in (25.4 mm) increase in precipitation was associated with a 3% increase in campylobacteriosis reported 3 wks later (IRR =1.03; 95% CI: 1.02, 1.04) after adjusting for average temperature and PDSI. Compared with normal conditions, there were significantly more cases when precipitation followed antecedent extremely wet (IRR =1.15; 95% CI: 1.04, 1.26), very wet (IRR =1.09; 95% CI: 1.01, 1.18), moderately wet (IRR =1.06; 95% CI: 1.01, 1.12), moderate drought (IRR =1.11; 95% CI: 1.07, 1.16), and severe drought (IRR =1.06; 95% CI: 1.02, 1.11) conditions, whereas there were significantly fewer cases (IRR = 0.89; 95% CI: 0.85, 0.94) for antecedent extreme drought. Compared to counties with no animal operations, counties with animal operations had significantly more cases following precipitation for every PDSI category except extreme drought. Counties with a higher density of beef cattle, goats for meat, chicken broilers, and chicken layers had significantly higher rates of campylobacteriosis following precipitation than those with no such operations, whereas those with dairy cattle and goats for milk, did not. DISCUSSION : In this majority arid and semiarid environment, precipitation following prior wet conditions and moderate and severe drought were significantly associated with increased rates of campylobacteriosis, and only in prior extreme drought did rates decrease. Where the precipitation fell made a difference; after precipitation, counties with farm operations had significantly more cases compared to counties without farm operations. Further work should assess individual-level risk factors within environmental exposure pathways for Campylobacter. .

BackgroundSequential mixed-mode surveys using both web-based surveys and telephone interviews are increasingly being used in observational studies and have been shown to have many benefits; however, the application of this survey design has not been evaluated in the context of epidemiological case-control studies. ObjectiveIn this paper, we discuss the challenges, benefits, and limitations of using a sequential mixed-mode survey design for a case-control study assessing risk factors during the COVID-19 pandemic. MethodsColorado adults testing positive for SARS-CoV-2 were randomly selected and matched to those with a negative SARS-CoV-2 test result from March to April 2021. Participants were first contacted by SMS text message to complete a self-administered web-based survey asking about community exposures and behaviors. Those who did not respond were contacted for a telephone interview. We evaluated the representativeness of survey participants to sample populations and compared sociodemographic characteristics, participant responses, and time and resource requirements by survey mode using descriptive statistics and logistic regression models. ResultsOf enrolled case and control participants, most were interviewed by telephone (308/537, 57.4% and 342/648, 52.8%, respectively), with overall enrollment more than doubling after interviewers called nonresponders. Participants identifying as female or White non-Hispanic, residing in urban areas, and not working outside the home were more likely to complete the web-based survey. Telephone participants were more likely than web-based participants to be aged 18-39 years or 60 years and older and reside in areas with lower levels of education, more linguistic isolation, lower income, and more people of color. While there were statistically significant sociodemographic differences noted between web-based and telephone case and control participants and their respective sample pools, participants were more similar to sample pools when web-based and telephone responses were combined. Web-based participants were less likely to report close contact with an individual with COVID-19 (odds ratio [OR] 0.70, 95% CI 0.53-0.94) but more likely to report community exposures, including visiting a grocery store or retail shop (OR 1.55, 95% CI 1.13-2.12), restaurant or cafe or coffee shop (OR 1.52, 95% CI 1.20-1.92), attending a gathering (OR 1.69, 95% CI 1.34-2.15), or sport or sporting event (OR 1.05, 95% CI 1.05-1.88). The web-based survey required an average of 0.03 (SD 0) person-hours per enrolled participant and US $920 in resources, whereas the telephone interview required an average of 5.11 person-hours per enrolled participant and US $70,000 in interviewer wages. ConclusionsWhile we still encountered control recruitment challenges noted in other observational studies, the sequential mixed-mode design was an efficient method for recruiting a more representative group of participants for a case-control study with limited impact on data quality and should be considered during public health emergencies when timely and accurate exposure information is needed to inform control measures.

Stool specimen collection during a foodborne or enteric illness outbreak investigation is essential for determining the outbreak etiology and for advancing the epidemiologic understanding of the pathogens and food vehicles causing illness. However, public health professionals face multifaceted barriers when trying to collect stool specimens from ill person during an outbreak investigation. The Colorado Integrated Food Safety Center of Excellence (Colorado IFS CoE) and the Arizona Department of Health Services surveyed local public health agencies (LPHAs) to identify barriers to collecting ≥2 clinical specimens in foodborne and enteric illness outbreaks. The most commonly selected patient-related barrier was that the patient did not think it is important to provide a stool sample because they are well by the time the LPHA follows-up (61%). The most frequently selected outbreak-related barrier was the LPHA did not learn about the outbreak until after symptoms had resolved (61%). Time/personnel not being available for stool collection was the most frequently chosen health department-related barrier (51%). Timing of the outbreak (e.g., on a weekend or holiday) was the most frequently selected transportation-related barrier (51%) to collecting ≥2 stool specimens. Many of the frequently cited barriers in this survey were similar to those previously reported, such as workforce capacity and patient privacy concerns, indicating that these barriers are ongoing. Reducing barriers to stool collection during outbreaks will require efforts led at the national and state levels, such as increased enteric illness program funding, educating public health staff on the importance of specimen collection during every enteric illness outbreak, and providing specimen collection resources to LPHA staff.

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.

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which causes coronavirus disease 2019 (COVID-19), is spread primarily through exposure to respiratory droplets from close contact with an infected person. To inform prevention measures, we conducted a case-control study among Colorado adults to assess the risk of SARS-CoV-2 infection from community exposures. Methods Cases were symptomatic Colorado adults (aged ≥18 years) with a positive SARS-CoV-2 test by reverse transcription-polymerase chain reaction (RT-PCR) reported to Colorado’s COVID-19 surveillance system. From March 16 to December 23, 2021, cases were randomly selected from surveillance data ≤12 days after their specimen collection date. Cases were matched on age, zip code (urban areas) or region (rural/frontier areas), and specimen collection date with controls randomly selected among persons with a reported negative SARS-CoV-2 test result. Data on close contact and community exposures were obtained from surveillance and a survey administered online. Results The most common exposure locations among all cases and controls were place of employment, social events, or gatherings and the most frequently reported exposure relationship was co-worker or friend. Cases were more likely than controls to work outside the home (adjusted odds ratio (aOR) 1.18, 95% confidence interval (CI): 1.09–1.28) in industries and occupations related to accommodation and food services, retail sales, and construction. Cases were also more likely than controls to report contact with a non-household member with confirmed or suspected COVID-19 (aOR 1.16, 95% CI: 1.06–1.27). Conclusions Understanding the settings and activities associated with a higher risk of SARS-CoV-2 infection is essential for informing prevention measures aimed at reducing the transmission of SARS-CoV-2 and other respiratory diseases. These findings emphasize the risk of community exposure to infected persons and the need for workplace precautions in preventing ongoing transmission.

Foodborne outbreaks reported to national surveillance systems represent a subset of all outbreaks in the United States; not all outbreaks are detected, investigated, and reported. We described the structural factors and outbreak characteristics of outbreaks reported during 2009-2018. We categorized states (plus DC) as high (highest quintile), middle (middle 3 quintiles), or low (lowest quintile) reporters on the basis of the number of reported outbreaks per 10 million population. Analysis revealed considerable variation across states in the number and types of foodborne outbreaks reported. High-reporting states reported 4 times more outbreaks than low reporters. Low reporters were more likely than high reporters to report larger outbreaks and less likely to implicate a setting or food vehicle; however, we did not observe a significant difference in the types of food vehicles identified. Per capita funding was strongly associated with increased reporting. Investments in public health programming have a measurable effect on outbreak reporting.

Background Sepsis causes a major health burden in the United States. To better understand the role of sepsis as a driver of the burden and cost of foodborne illness in the United States, we estimated the frequency and treatment cost of sepsis among US patients hospitalized with 31 pathogens commonly transmitted through food or with unspecified acute gastrointestinal illness (AGI). Methods Using data from the National Inpatient Sample from 2012 to 2015, we identified sepsis hospitalizations using 2 approaches-explicit ICD-9-CM codes for sepsis and a coding scheme developed by Angus that identifies sepsis using specific ICD-9-CM diagnosis codes indicating an infection plus organ failure. We examined differences in the frequency and the per-case cost of sepsis across pathogens and AGI and estimated total hospitalization costs using prior estimates of foodborne hospitalizations. Results Using Explicit Sepsis Codes, sepsis hospitalizations accounted for 4.6% of hospitalizations with a pathogen commonly transmitted through food or unspecified AGI listed as a diagnosis; this was 33.2% using Angus Sepsis Codes. The average per-case cost was $35 891 and $20 018, respectively. Applying the proportions of hospitalizations with sepsis from this study to prior estimates of the number foodborne hospitalizations, the total annual cost was $248 million annually using Explicit Sepsis Codes and $889 million using Angus Sepsis Codes. Conclusions Sepsis is a serious complication among patients hospitalized with a foodborne pathogen infection or AGI resulting in a large burden of illness. Hospitalizations that are diagnosed using explicit sepsis codes are more severe and costly, but likely underestimate the burden of foodborne sepsis. We examine differences in the frequency and per-case cost of sepsis across pathogens commonly transmitted through food. We integrate this with CDC foodborne disease incidence estimates to calculate the total cost of sepsis from 31 foodborne pathogens and foodborne AGI.

The rate of enteric infections reported to public health surveillance decreased during 2020 amid the coronavirus disease 2019 (COVID-19) pandemic. Changes in medical care-seeking behaviors may have impacted the diagnosis of enteric infections contributing to these declines. We examined trends in outpatient medical care-seeking behavior for acute gastroenteritis (AGE) in Colorado during 2020 compared with the that of previous 3 years using electronic health record data from the Colorado Health Observation Regional Data Service (CHORDS). Outpatient medical encounters for AGE were identified using diagnoses codes from the International Classification of Diseases 10th Revision and aggregated by year, quarter, age group, and encounter type. The rate of encounters was calculated by dividing the number of AGE encounters by the corresponding total number of encounters. There were 9064 AGE encounters in 2020 compared with an annual average of 18,784 from 2017 to 2019 (p < 0.01), representing a 52% decrease. The rate of AGE encounters declined after the first quarter of 2020 and remained significantly lower for the rest of the year. Moreover, previously observed trends, including seasonal patterns and the preponderance of pediatric encounters, were no longer evident. Telemedicine modalities accounted for 23% of all AGE encounters in 2020. AGE outpatient encounters in Colorado in 2020 were substantially lower than during the previous 3 years. Decreases remained stable over the second, third, and fourth quarters of 2020 (April-December) and were especially pronounced for children <18 years of age. Changes in medical care-seeking behavior likely contributed to declines in the number of enteric disease cases and outbreaks reported to public health. It is unclear to what extent people were ill with AGE and did not seek medical care because of concerns about the infection risk during a health care visit or to what extent there were reductions in certain exposures and opportunities for disease transmission resulting in less illness.