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:

BACKGROUND: Several U.S. hospitals had surges in COVID-19 caseload, but their effect on COVID-19 survival rates remains unclear, especially independent of temporal changes in survival. OBJECTIVE: To determine the association between hospitals' severity-weighted COVID-19 caseload and COVID-19 mortality risk and identify effect modifiers of this relationship. DESIGN: Retrospective cohort study. (ClinicalTrials.gov: NCT04688372). SETTING: 558 U.S. hospitals in the Premier Healthcare Database. PARTICIPANTS: Adult COVID-19-coded inpatients admitted from March to August 2020 with discharge dispositions by October 2020. MEASUREMENTS: Each hospital-month was stratified by percentile rank on a surge index (a severity-weighted measure of COVID-19 caseload relative to pre-COVID-19 bed capacity). The effect of surge index on risk-adjusted odds ratio (aOR) of in-hospital mortality or discharge to hospice was calculated using hierarchical modeling; interaction by surge attributes was assessed. RESULTS: Of 144 116 inpatients with COVID-19 at 558 U.S. hospitals, 78 144 (54.2%) were admitted to hospitals in the top surge index decile. Overall, 25 344 (17.6%) died; crude COVID-19 mortality decreased over time across all surge index strata. However, compared with nonsurging (<50th surge index percentile) hospital-months, aORs in the 50th to 75th, 75th to 90th, 90th to 95th, 95th to 99th, and greater than 99th percentiles were 1.11 (95% CI, 1.01 to 1.23), 1.24 (CI, 1.12 to 1.38), 1.42 (CI, 1.27 to 1.60), 1.59 (CI, 1.41 to 1.80), and 2.00 (CI, 1.69 to 2.38), respectively. The surge index was associated with mortality across ward, intensive care unit, and intubated patients. The surge-mortality relationship was stronger in June to August than in March to May (slope difference, 0.10 [CI, 0.033 to 0.16]) despite greater corticosteroid use and more judicious intubation during later and higher-surging months. Nearly 1 in 4 COVID-19 deaths (5868 [CI, 3584 to 8171]; 23.2%) was potentially attributable to hospitals strained by surging caseload. LIMITATION: Residual confounding. CONCLUSION: Despite improvements in COVID-19 survival between March and August 2020, surges in hospital COVID-19 caseload remained detrimental to survival and potentially eroded benefits gained from emerging treatments. Bolstering preventive measures and supporting surging hospitals will save many lives. PRIMARY FUNDING SOURCE: Intramural Research Program of the National Institutes of Health Clinical Center, the National Institute of Allergy and Infectious Diseases, and the National Cancer Institute.
["Diagnosis", "Treatment", "Prevention"]