About FRED

FRED (A Framework for Reconstructing Epidemiological Dynamics) is a modeling system that supports research on the dynamics of infectious disease epidemics and the interacting effects of mitigation strategies, viral evolution, and personal health behavior. FRED was designed as a flexible, modular, open source framework for epidemic modeling, rather than a model of a particular infectious disease. Key features of FRED include:

  • Highly modular, object-oriented software design to support rapid adaptation to a wide variety of infectious disease scenarios.
  • Realistic synthetic populations based on the US Census Bureau’s Public Use Microdata (PUMs) data and Census aggregated data. The synthetic populations used by FRED were developed by RTI International as part of the MIDAS project and are freely available.
  • Scalable and efficient simulation of large epidemics. FRED can run on a variety of computer platforms from laptops to supercomputers, depending on the size of the population being simulated. Simulations of an influenza epidemic like the H1N1 pandemic in a population of 1 million people takes less than 2 minutes on a laptop computer.
  • Flexible ways to specify agent health behavior and decision rules. Agents in FRED may exhibit a number of health-related behaviors involving individual health decisions, such as staying home when sick, accepting a vaccine or taking an anti-viral drug. The FRED platform is designed to accommodate a range of models of health behavior and supports a variety of strategies to determine an agent’s willingness to adopt a behavior.

Synthetic Population

FRED explicitly represents every individual in a specific geographic region. Each agent has a set of socio-demographic characteristics and daily behaviors that include age, sex, employment status, occupation, and household location and membership in a set of social contact networks. Each household, school, and workplace is mapped to a specific geographic location, reflecting the actual spatial distribution of the area and the distance travelled by individuals to work or to school. For regions within the United States, FRED uses the 2005-2009 U.S. Synthetic Population Database (Version 2) from RTI International:


The RTI Synthetic Population uses an iterative fitting method to generate an agent population from the US Census Bureau’s Public Use Microdata files (PUMs) and aggregated data from the 2005-2009 American Community Survey (ACS) 5-year sample. The synthetic population database contains geographically located synthetic households and household residents for the United States, as well as group quarters locations and residents, schools and assignments of students to schools, workplaces and assignments of workers to workplaces. Each household, group quarters, school and workplace is mapped to a specific geographic location, reflecting the actual spatial distribution of the area and the distance travelled by individuals to work or to school. Each agent has associated demographic information (e.g., age, sex), locations for social activities (household, and possibly school or workplace).

A FRED synthetic population is currently available for every county in the United States and for selected international populations. FRED can simulate any combination of counties in a single run, for example, an epidemic within a state or a Metropolitan Statistical Area (MSA).


FRED was named in tribute to Fred McFeely Rogers (1928-2003), a famous Pittsburgher best known for his television program Mister Rogers' Neighborhood (1968-2001). Mr. Rogers' theme song included the phrases:

It's a beautiful day in the neighborhood ... won't you be my neighbor?

His emphasis of the importance of neighborhoods seems like an appropriate reflection of the importance of social networks in the FRED simulation system.

How to cite FRED

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.

© 2012-2014 Public Health Dynamics Laboratory, University of Pittsburgh