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We compared the characteristics of hospitalized and nonhospitalized patients who had coronavirus disease in Atlanta, Georgia, USA. We found that risk for hospitalization increased with a patient's age and number of concurrent conditions. We also found a potential association between hospitalization and high hemoglobin A1c levels in persons with diabetes.

Background Coronavirus disease (COVID-19) can cause severe illness and death. Predictors of poor outcome collected on hospital admission may inform clinical and public health decisions. Methods We conducted a retrospective observational cohort investigation of 297 adults admitted to 8 academic and community hospitals in Georgia, United States, during March 2020. Using standardized medical record abstraction, we collected data on predictors including admission demographics, underlying medical conditions, outpatient antihypertensive medications, recorded symptoms, vital signs, radiographic findings, and laboratory values. We used random forest models to calculate adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for predictors of invasive mechanical ventilation (IMV) and death. Results Compared with age Conclusions After adjustment for patient and clinical characteristics, older age was the strongest predictor of death, exceeding comorbidities, abnormal vital signs, and laboratory test abnormalities. That coronary artery disease, but not chronic lung disease, was associated with death among hospitalized patients warrants further investigation, as do associations between certain antihypertensive medications and death.

SARS-CoV-2, the novel coronavirus that causes coronavirus disease 2019 (COVID-19), was first detected in the United States during January 2020 (1). Since then, >980,000 cases have been reported in the United States, including >55,000 associated deaths as of April 28, 2020 (2). Detailed data on demographic characteristics, underlying medical conditions, and clinical outcomes for persons hospitalized with COVID-19 are needed to inform prevention strategies and community-specific intervention messages. For this report, CDC, the Georgia Department of Public Health, and eight Georgia hospitals (seven in metropolitan Atlanta and one in southern Georgia) summarized medical record-abstracted data for hospitalized adult patients with laboratory-confirmed* COVID-19 who were admitted during March 2020. Among 305 hospitalized patients with COVID-19, 61.6% were aged

Background The relationships between socioeconomic status and domestically acquired salmonellosis and leading Salmonella serotypes are poorly understood. Methods We analyzed surveillance data from laboratory-confirmed cases of salmonellosis from 2010–2016 for all 10 Foodborne Disease Active Surveillance Network (FoodNet) sites, having a catchment population of 47.9 million. Case residential data were geocoded, linked to census tract poverty level, and then categorized into 4 groups according to census tract poverty level. After excluding those reporting international travel before illness onset, age-specific and age-adjusted salmonellosis incidence rates were calculated for each census tract poverty level, overall and for each of the 10 leading serotypes. Results Of 52 821geocodable Salmonella infections (>96%), 48 111 (91.1%) were domestically acquired. Higher age-adjusted incidence occurred with higher census tract poverty level (P < .001; relative risk for highest [≥20%] vs lowest [ Conclusion Children and older adults living in higher-poverty census tracts have had a higher incidence of domestically acquired salmonellosis. There is a need to understand socioeconomic status differences for risk factors for domestically acquired salmonellosis by age group and FoodNet site to help focus prevention efforts.

Background The epidemiological features and outcomes of hospitalized adults with coronavirus disease 2019 (COVID-19) have been described; however, the temporal progression and medical complications of disease among hospitalized patients require further study. Detailed descriptions of the natural history of COVID-19 among hospitalized patients are paramount to optimize health care resource utilization, and the detection of different clinical phenotypes may allow tailored clinical management strategies. Methods This was a retrospective cohort study of 305 adult patients hospitalized with COVID-19 in 8 academic and community hospitals. Patient characteristics included demographics, comorbidities, medication use, medical complications, intensive care utilization, and longitudinal vital sign and laboratory test values. We examined laboratory and vital sign trends by mortality status and length of stay. To identify clinical phenotypes, we calculated Gower’s dissimilarity matrix between each patient’s clinical characteristics and clustered similar patients using the partitioning around medoids algorithm. Results One phenotype of 6 identified was characterized by high mortality (49%), older age, male sex, elevated inflammatory markers, high prevalence of cardiovascular disease, and shock. Patients with this severe phenotype had significantly elevated peak C-reactive protein creatinine, D-dimer, and white blood cell count and lower minimum lymphocyte count compared with other phenotypes (P Conclusions Among a cohort of hospitalized adults, we identified a severe phenotype of COVID-19 based on the characteristics of its clinical course and poor prognosis. These findings need to be validated in other cohorts, as improved understanding of clinical phenotypes and risk factors for their development could help inform prognosis and tailored clinical management for COVID-19.

Background Shigella causes an estimated 500 000 enteric illnesses in the United States annually, but the association with socioeconomic factors is unclear. Methods We examined possible epidemiologic associations between shigellosis and poverty using 2004–2014 Foodborne Diseases Active Surveillance Network (FoodNet) data. Shigella cases (n = 21 246) were geocoded, linked to Census tract data from the American Community Survey, and categorized into 4 poverty and 4 crowding strata. For each stratum, we calculated incidence by sex, age, race/ethnicity, and FoodNet site. Using negative binomial regression, we estimated incidence rate ratios (IRRs) comparing the highest to lowest stratum. Results Annual FoodNet Shigella incidence per 100 000 population was higher among children Conclusions In the United States, Shigella infections are epidemiologically associated with poverty, and increased incidence rates are observed among young children, blacks, and Hispanics.

Shigella commonly causes gastroenteritis but rarely spreads to the blood. During 2002–2012, we identified 11,262 Shigella infections through population-based active surveillance in Georgia; 72 (0.64%) were isolated from blood. Bacteremia was associated with age >18 years, black race, and S. flexneri. More than half of patients with bacteremia were HIV-infected.

The increased availability and rapid adoption of culture-independent diagnostic tests (CIDTs) is moving clinical detection of bacterial enteric infections away from culture-based methods. These new tests do not yield isolates that are currently needed for further tests to distinguish among strains or subtypes of Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli, and other organisms. Public health surveillance relies on this detailed characterization of isolates to monitor trends and rapidly detect outbreaks; consequently, the increased use of CIDTs makes prevention and control of these infections more difficult. During 2012-2013, the Foodborne Diseases Active Surveillance Network (FoodNet*) identified a total of 38,666 culture-confirmed cases and positive CIDT reports of Campylobacter, Salmonella, Shigella, Shiga toxin-producing E. coli, Vibrio, and Yersinia. Among the 5,614 positive CIDT reports, 2,595 (46%) were not confirmed by culture. In addition, a 2014 survey of clinical laboratories serving the FoodNet surveillance area indicated that use of CIDTs by the laboratories varied by pathogen; only CIDT methods were used most often for detection of Campylobacter (10%) and STEC (19%). Maintaining surveillance of bacterial enteric infections in this period of transition will require enhanced surveillance methods and strategies for obtaining bacterial isolates.

Objectives. The objective of this study was to determine the role international travel plays in US Campylobacter epidemiology and antimicrobial resistance. Methods. In this study, epidemiological and antimicrobial resistance data, encompassing the years 2005 to 2011, from 10 sites participating in the Foodborne Diseases Active Surveillance Network were linked. The 10 sites are represented by 7 states that conducted surveillance on a statewide level, and 3 states which conducted county-level surveillance. Cases of Campylobacter among persons with history of international travel in the week prior to illness were compared with cases among individuals with no international travel. Results. Approximately 18% of Campylobacter infections were estimated to be associated with international travel, and 60% of international travel-associated infections had a quinolone-resistant Campylobacter isolate. Conclusions. We confirm that international travel plays a significant role in campylobacteriosis diagnosed in the United States. Recognizing this is important to both medical management decisions and understanding burden and attribution estimates of US campylobacteriosis and antibiotic-resistant campylobacteriosis.