In January 2020, Santa Clara County, California, USA, began identifying laboratory-confirmed coronavirus disease among residents. County staff conducted case and contact investigations focused on households and collected detailed case demographic, occupation, exposure, and outcome information. We describe the first 200 test-positive cases during January 31-March 20, 2020, to inform future case and contact investigations. Probable infection sources included community transmission (104 cases), known close contact with a confirmed case-patient (66 cases), and travel (30 cases). Disease patterns across race and ethnicity, occupational, and household factors suggested multiple infection risk factors. Disproportionately high percentages of case-patients from racial and ethnic subgroups worked outside the home (Hispanic [86%] and Filipino [100%]); household transmission was more common among persons from Vietnam (53%). Even with the few initial cases, detailed case and contact investigations of household contacts capturing occupational and disaggregated race and ethnicity data helped identify at-risk groups and focused solutions for disease control.

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: 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 < .01, all comparisons). 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.

By June 2020, Marshallese and Hispanic or Latino (Hispanic) persons in Benton and Washington counties of Arkansas had received a disproportionately high number of diagnoses of coronavirus disease 2019 (COVID-19). Despite representing approximately 19% of these counties' populations (1), Marshallese and Hispanic persons accounted for 64% of COVID-19 cases and 57% of COVID-19-associated deaths. Analyses of surveillance data, focus group discussions, and key-informant interviews were conducted to identify challenges and propose strategies for interrupting transmission of SARS-CoV-2, the virus that causes COVID-19. Challenges included limited native-language health messaging, high household occupancy, high employment rate in the poultry processing industry, mistrust of the medical system, and changing COVID-19 guidance. Reducing the COVID-19 incidence among communities that suffer disproportionately from COVID-19 requires strengthening the coordination of public health, health care, and community stakeholders to provide culturally and linguistically tailored public health education, community-based prevention activities, case management, care navigation, and service linkage.

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 eight 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 (CI) for predictors of invasive mechanical ventilation (IMV) and death. RESULTS: Compared with age <45 years, ages 65-74 years and ≥75 years were predictors of IMV (aOR 3.12, CI 1.47-6.60; aOR 2.79, CI 1.23-6.33) and the strongest predictors for death (aOR 12.92, CI 3.26-51.25; aOR 18.06, CI 4.43-73.63). Comorbidities associated with death (aORs from 2.4 to 3.8, p <0.05) included end-stage renal disease, coronary artery disease, and neurologic disorders, but not pulmonary disease, immunocompromise, or hypertension. Pre-hospital use vs. non-use of angiotensin receptor blockers (aOR 2.02, CI 1.03-3.96) and dihydropyridine calcium channel blockers (aOR 1.91, CI 1.03-3.55) were associated with death. 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.

The first reported U.S. case of coronavirus disease 2019 (COVID-19) was detected in January 2020 (1). As of June 15, 2020, approximately 2 million cases and 115,000 COVID-19-associated deaths have been reported in the United States.* Reports of U.S. patients hospitalized with SARS-CoV-2 infection (the virus that causes COVID-19) describe high proportions of older, male, and black persons (2-4). Similarly, when comparing hospitalized patients with catchment area populations or nonhospitalized COVID-19 patients, high proportions have underlying conditions, including diabetes mellitus, hypertension, obesity, cardiovascular disease, chronic kidney disease, or chronic respiratory disease (3,4). For this report, data were abstracted from the medical records of 220 hospitalized and 311 nonhospitalized patients aged >/=18 years with laboratory-confirmed COVID-19 from six acute care hospitals and associated outpatient clinics in metropolitan Atlanta, Georgia. Multivariable analyses were performed to identify patient characteristics associated with hospitalization. The following characteristics were independently associated with hospitalization: age >/=65 years (adjusted odds ratio [aOR] = 3.4), black race (aOR = 3.2), having diabetes mellitus (aOR = 3.1), lack of insurance (aOR = 2.8), male sex (aOR = 2.4), smoking (aOR = 2.3), and obesity (aOR = 1.9). Infection with SARS-CoV-2 can lead to severe outcomes, including death, and measures to protect persons from infection, such as staying at home, social distancing (5), and awareness and management of underlying conditions should be emphasized for those at highest risk for hospitalization with COVID-19. Measures that prevent the spread of infection to others, such as wearing cloth face coverings (6), should be used whenever possible to protect groups at high risk. Potential barriers to the ability to adhere to these measures need to be addressed.

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 <65 years, 50.5% were female, and 83.2% with known race/ethnicity were non-Hispanic black (black). Over a quarter of patients (26.2%) did not have conditions thought to put them at higher risk for severe disease, including being aged >/=65 years. The proportion of hospitalized patients who were black was higher than expected based on overall hospital admissions. In an adjusted time-to-event analysis, black patients were not more likely than were nonblack patients to receive invasive mechanical ventilation(dagger) (IMV) or to die during hospitalization (hazard ratio [HR] = 0.63; 95% confidence interval [CI] = 0.35-1.13). Given the overrepresentation of black patients within this hospitalized cohort, it is important for public health officials to ensure that prevention activities prioritize communities and racial/ethnic groups most affected by COVID-19. Clinicians and public officials should be aware that all adults, regardless of underlying conditions or age, are at risk for serious illness from COVID-19.