Respiratory viruses such as influenza and SARS-CoV-2 are responsible for pandemics, infect mil-lions of people, and cause tens of thousands of deaths each year in the United States, with a particularly high burden among elderly and immunocompromised patients. Clinicians currently have limited tools to identify which patients are at high risk of developing respiratory failure after infection or how long patients require isolation because they are contagious. Currently used di-agnostic PCR tests for respiratory viruses only provide a binary result of “positive” or “negative”, but do not provide quantitative information. The objective of this proposal is to assess the po-tential clinical utility of measuring quantitative viral load to i) predict complications from influ-enza infection and; ii) to identify patients who are likely to be contagious. Our central hypothesis is that viral load, as measured by a well-calibrated quantitative PCR assay, can help identify pa-tients infected with a respiratory virus who are at highest risk of developing respiratory failure, as well as those who harbor live virus that can be transmitted to others. The rationale for this work is that determining the relationship between viral load and outcome for hospitalized pa-tients with influenza infection will inform the clinical utility of developing this quantitative assay as a novel diagnostic tool. Furthermore, understanding how viral load predicts the presence of live virus would inform the potential for using this quantitative assay to guide decisions on dura-tion of isolation for infected patients. These contributions will be significant and innovative be-cause they will lead to further development of the assay as a novel diagnostic tool to guide clinical decision making for patients with respiratory viral infection, including the type of monitoring a patient requires, the potential role for antiviral therapies, and when a patient can be safely re-moved from respiratory isolation.