This initiative is to support investigative and collaborative research focused on developing and evaluating simulation modeling and systems science (SMSS) to understand and address minority health and health disparities.
Big Data Science: Opportunities and Challenges to Address Minority Health and Health Disparities in the 21st Century
Using Google Street view cars and rooftop sensors, scientists are mapping pollution block by block in California. Now they think their tech is ready for primetime.
Educational Resource Discovery Index (ERuDIte), a database of 10,000+ data science educational resources from collective BD2K activities and from around the web.
The Future Americans Model (FAM) is an economic-demographic microsimulation that extends the Roybal Center’s Future Elderly Model (FEM) to the entire adult population in the United States.
As with its predecessor, the FAM involves three key components. The first component includes the transition models of health, education, family and work and earnings. The second component is an “initial conditions model” to feed the model new cohorts as younger groups enter the relevant ages of the model. To accomplish this, the FAM’s infrastructure generates new cohorts using information on demographic and health trends currently observed among younger cohorts. The outcomes of these cohorts are then projected using the transitional probabilities from the first step. The third and final component, the “policy outcomes module,” aggregates outcomes into health and cost measures such as taxes, medical care costs (by payer e.g. Medicare, Medicaid, out-of-pocket), QALYs, and life expectancies.
Very useful R package for parallel processing.
Source: CRAN – Package batch
Official website of Data science at NIH, harnessing Big Data to advance research in biomedical sciences coordinated by the NIH Scientific Data Council and the NIH Office of the Associate Director for Data Science (ADDS).