Severe acute respiratory syndrome coronavirus 2-mediated coronavirus disease (COVID-19) is an evolutionarily unprecedented natural experiment that causes major changes to the host immune system. We propose to develop a test that accurately predicts short- and long-term (within one-year) outcomes in hospitalized COVID-19 patients broadly reflecting US demographics who are at increased risk of adverse outcomes from COVID-19 using both clinical and molecular data. We will enroll patients from a hospitalized civilian population in one of the country's largest metropolitan areas and a representative National Veteran's population.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-mediated coronavirus disease (COVID-19) is an evolutionarily unprecedented natural experiment that causes major changes to the host immune system. Several high risk COVID-19 populations have been identified. Older adults, males, persons of color, and those with certain underlying health conditions (e.g., diabetes mellitus, obesity, etc.) are at higher risk for severe disease from COVID-19. While it is too soon to fully understand the impact of COVID-19 on overall health and well-being, there are already several reports of significant sequelae, which appear to correlate with disease severity. There is a clear and urgent need to develop prediction tests for adverse short- and long-term outcomes, especially for high-risk COVID-19 populations. We hypothesize that complementary multi-dimensional information gathered near the time of symptom onset can be used to predict new onset or worsening frailty, organ dysfunction and death within one year after COVID-19 onset. A single parameter provides limited information and is incapable of adequately characterizing the complex biological responses in symptomatic COVID-19 to predict outcome. Since they were designed for other illnesses, it is unlikely that existing clinical tools, such as respiratory, cardiovascular, and other organ function assessment scores, will precisely assess the long-term prognosis of this novel disease. Our extensive experience in biomarker development suggests that integrating molecular and clinical data increases prediction accuracy of long-term outcomes. We have chosen to test our hypothesis in a population reflecting US-demographics that is at increased risk of adverse outcomes from COVID-19. We will enroll patients, broadly reflecting US demographics, from a hospitalized civilian population in one of the country's largest metropolitan areas and a representative National Veteran's population. We anticipate that a prediction test that performs well in this hospitalized patient group will: help guide triaging and treatment decisions and, therefore, reduce morbidity and mortality rates, enhance patient quality of life, and improve healthcare cost-effectiveness. More accurate prognostic information will also assist clinicians in framing goals of care discussions in situations of likely futility and assist patients and families in this decision-making process. Finally, it will provide a logical means for allocating resources in short supply, such as ventilators or therapeutics with limited availability.

Inclusion Criteria:

• Symptomatic COVID-19 infection with hospital admission
• Age 18 and above
• Informed consent

Exclusion Criteria:

• Absence of symptomatic COVID-19 infection with hospital admission
• Age 17 or below
• No informed consent

Symptomatic COVID-19 infected civilians and symptomatic COVID-19 infected veterans

After our data is cleaned, quality checked, and analyzed, we will make the data available to the general research community. Data collected in this proposal will be submitted to the appropriate public databases (e.g. Gene Expression Omnibus), along with complete documentation to enable efficient use of the data by the general research community. Cumulative datasets will be submitted on a regular basis in a timely manner. All data made available for public use will be de-identified data, i.e., stripped of private, protected health information that could be used to deduce the identity of individual subjects, in compliance with the HIPPA Privacy Rule. The study will be registered in the database of Genotypes and Phenotypes and the following data and information will be shared through the Sequence Read Archive and Gene Expression Omnibus.

The data will be available following the completion of the study and will be available indefinitely.

COPA Study website to be determined