You are presented with a paragraph from a COVID-19 literature. Classify the topics of this piece of text by choosing from the following categories:

- Epidemic Forecasting: The content relates to predictions about the spread of COVID-19.
- Treatment: The paragraph discusses therapeutic methods or medication for COVID-19.
- Prevention: The content covers measures to prevent the spread of COVID-19.
- Mechanism: The paragraph explains the biological mechanisms of the virus.
- Case Report: The content is a report of a COVID-19 case.
- Transmission: The paragraph discusses how COVID-19 is transmitted.
- Diagnosis: The content is about diagnosing COVID-19 in individuals.

Your classification should be provided as an element within a JSON array. The array should be formatted with topics enclosed in double quotes and separated by commas, following the JSON format, for example: ["Topic1", "Topic2", ...]. Include all applicable topics within the array. Your output should be a valid JSON array, and no additional text should be included in your response.

Article:

Objective: To measure the association of race, ethnicity, comorbidities, and insurance status with need for hospitalization of symptomatic emergency department patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Methods: This study is a cohort study of symptomatic patients presenting to a single emergency department (ED) with laboratory-confirmed SARS-CoV-2 infection from March 7-August 9, 2020. We collected patient-level information regarding demographics, insurance status, comorbidities, level of care, and mortality using a structured chart review. We compared characteristics of patients categorized by (1) home discharge, (2) general hospital ward admission, and (3) intensive care unit (ICU) admission or death within 30 days of the index visit. Univariate and multivariable logistic regression analyses were performed to report odds ratios (OR) and 95% confidence intervals (95% CI) between hospital admission versus ED discharge home and between ICU care versus general hospital ward admission. Results: In total, 994 patients who presented to the ED with symptoms were included in the analysis with 551 (55.4%) patients discharged home, 314 (31.6%) patients admitted to the general hospital ward, and 129 (13.0%) admitted to the ICU or dying. Patients requiring admission were more likely to be Black or to have public insurance (Medicaid and/or Medicare). Patients who were admitted to the ICU or dying were more likely aged >/= 65 years or male. In multivariable logistic regression, old age, public insurance, diabetes, hypertension, obesity, heart failure, and hyperlipidemia were independent predictors of hospital admission. When comparing those who needed ICU care versus general hospital ward admission in univariate logistic regression, patients with Medicaid (OR 2.4, 95% CI 1.2-4.6), Medicare (OR 4.2, 95% CI 2.1-8.4), Medicaid and Medicare (OR 4.3, 95% CI 2.4-7.7), history of chronic obstructive pulmonary disease (OR 2.2, 95% CI 1.2-4.2), hypertension (OR 1.7, 95% CI 1.1-2.7), and heart failure (OR 2.6, 95% CI 1.4-4.7) were more likely to be admitted into the ICU or die; Black (OR 1.1, 95% CI 0.4-2.9) and Hispanic/Latino (OR 1.0, 95% CI 0.6-1.8) patients were less likely to be admitted into the ICU; however, the associations were not statistically significant. In multivariable logistic regression, old age, male sex, public insurance, and heart failure were independent predictors of ICU care/death. Conclusion: Comorbidities and public insurance are predictors of more severe illness for patients with SARS-CoV-2. This study suggests that the disparities in severity seen in COVID-19 among Black patients may be attributable, in part, to low socioeconomic status and chronic health conditions.
["Diagnosis", "Treatment"]