PROJECT SUMMARY/ABSTRACT Geographic and racial/ethnic disparities in cardiovascular diseases (CVD) – the leading cause of death in the U.S. – remain large. There is a gap in the available evidence on the burden of heart failure in particular and its role in health disparities more generally, especially at the local level. While the U.S. is rich in local health data, the data is poorly integrated. Disease models and population health simulation are an important way to integrate complex patterns of risk exposure and disease burden with other population trends including income, education, aging, migration, and health care access. Previous CVD forecasts and policy models have produced only single geography – primarily national – estimates, which cannot provide the evidence needed to address geographic disparities. The overarching goal of this project will be to expand the evidence base for prevention and treatment policies for heart failure in the U.S., reduce disparities, and expand publicly available datasets and software models to support the broader use of health metrics for cardiovascular research. For this work, we will adapt econometric, geospatial, and epidemiologic modelling methods by leveraging the large data and computational resources of the Global Burden of Disease Study. Aim 1 is the estimation of county-level heart failure burden, including prevalence, mortality, years of life lost prematurely and disability-adjusted life years from 2000 through the current year as well as projections through the year 2060, by age, sex, race, ethnicity, and ejection fraction for each U.S. state, including new data and methods to account for the impact of the COVID-19 pandemic. Aim 2 is a comprehensive and comparable assessment of the effect size of risk factors leading to heart failure using a causal inference framework and attributable fraction methods. Aim 3 is the adaptation of our existing 50-state health policy simulation (the U.S. Burden of Disease Health Policy Simulation) for use with heart failure in order to evaluate the real-world impact of interventions to prevent or reduce the burden of heart failure when delivered at scale. Our results are designed to guide local decision-makers considering a range of policy options to reduce the burden of heart failure.