- Installing FRED
- Running FRED
- Output from FRED jobs
- Parameter Sweeps
- Automating Your FRED Workflow
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Note: This documentation refers to FRED Version 2. It does not apply to the version available on the FRED Web interface.
Documentation for the FRED Web version is coming soon.
FRED (A Framework for Reconstructing Epidemiological Dynamics) is an open source modeling system developed by the University of Pittsburgh Public Health Dynamics Laboratory in collaboration with the Pittsburgh Supercomputing Center and the School of Computer Science at Carnegie Mellon University.
FRED supports research on the dynamics of epidemics and the interacting effects of:
- disease characteristics,
- mitigation strategies, and
- personal health behavior.
The system uses agent-based modeling based on census-based synthetic populations that capture the demographic and geographic distributions of the population, as well as detailed household, school, and workplace social networks. Multiple circulating and evolving strains can be simulated. Mitigation strategies in the framework include vaccination, anti-viral drugs, and school closure policies. FRED supports models of health behavior change to facilitate the study of critical personal health behaviors such as vaccine acceptance, personal hygiene and spontaneous social distancing.
FRED is available through open source in the hopes of making large-scale agent-based epidemic models more useful to the policy-making community, the research community, and as a teaching tool for students in public health.
If you use FRED in your research, please use the following citation:
Grefenstette JJ, Brown ST, Rosenfeld R, Depasse J, Stone NT, Cooley PC, Wheaton WD, Fyshe A, Galloway DD, Sriram A, Guclu H, Abraham T, Burke DS. FRED (A Framework for Reconstructing Epidemic Dynamics): An open-source software system for modeling infectious diseases and control strategies using census-based populations. BMC Public Health, 2013 Oct;13(1), 940. doi: 10.1186/1471-2458-13-940. PubMed PMID: 24103508.
Support for this work is provided by the National Institute of General Medical Sciences under MIDAS grant 1U54GM088491-01 and by the Vaccine Modeling Initiative, funded by the Bill and Melinda Gates Foundation.