This goal of this project is to create a unique and comprehensive research repository of aging trajectory da- tasets, related resources, and analytic methods that can be used to answer new and important questions in aging and related sciences. Specifically, by harmonizing and merging multiple data sets this project will generate the data infrastructure needed to understand change over time in care settings, geriatric syndromes, physical functioning, and shared risk factors at multiple levels (patient, provider, community, healthcare system, and society) and across multiple domains (biological, behavioral, sociocultural, and physical/built environments) including chronic conditions and history of acute illness such as COVID-19, exposure to air pollution, neighborhood socioeconomic, and health care system factors (Aim 1). Analytic strategies will be developed for user- defined cohorts and their propensity score-matched controls, e.g., older adults who were living with chronic conditions including Alzheimer's disease and related dementias (ADRD), diabetes, heart failure, end-stage renal disease, metastatic cancer, and HIV. State-of-the-art analytic methods are used to identify patterns of aging trajectories (care setting, geriatric syndromes, physical functioning) experienced by older adults during the final years of life and their association with shared risk factors and distal outcomes (Aim 2). From the assem- bled trajectory file in Aim 1, cohorts are derived by aligning an originating index time such as age cutoff point and time at diagnosis (e.g., ADRD, stroke, chronic kidney disease). Both a model-based approach and ma- chine learning algorithms are then used to discover multilevel and potentially interactive predictors of trajecto- ries (e.g., rapid functional decline in independent living beneficiaries) and specific outcomes (e.g., respiratory ventilator usage among Medicare beneficiaries diagnosed with COVID-19) (Aim 3). The unique resources are then shared to disseminate resources including datasets, documentation, source code, and methodology (Aim 4). At the end of this project, the research infrastructure to investigate the relationship between shared risk factors and aging trajectories will be ready to use and replicate, giving investigators unprecedented ability to solve new challenges in aging science. This will allow researchers to understand the underlying processes and systems associated with reversible periods of disability across care settings, and interventions that may be used to support recovery of function and reduction of geriatric syndromes including cognitive decline, for the purpose of reducing burdensome care transitions, and maintenance of functional independence. This project will also create the resources and methods needed to evaluate the impact of innovations and interventions im- plemented at the patient, provider, community, healthcare system, and society/policy levels to improve care quality and outcomes for older adults.