Synthesized population databases: A US geospatial database for agent-based models

Abstract

Agent-based models simulate large-scale social systems. They assign behaviors and activities to “agents” (individuals) within the population being modeled and then allow the agents to interact with the environment and each other in complex simulations. Agent-based models are frequently used to simulate infectious disease outbreaks, among other uses. RTI used and extended an iterative proportional fitting method to generate a synthesized, geospatially explicit, human agent database that represents the US population in the 50 states and the District of Columbia in the year 2000. Each agent is assigned to a household; other agents make up the household occupants. For this database, RTI developed the methods for generating synthesized households and personsassigning agents to schools and workplaces so that complex interactions among agents as they go about their daily activities can be taken into accountgenerating synthesized human agents who occupy group quarters (military bases, college dormitories, prisons, nursing homes).In this report, we describe both the methods used to generate the synthesized population database and the final data structure and data content of the database. This information will provide researchers with the information they need to use the database in developing agent-based models. Portions of the synthesized agent database are available to any user upon request. RTI will extract a portion (a county, region, or state) of the database for users who wish to use this database in their own agent-based models.

Agent-Based Models in Empirical Social Research

“…The most common method for generating individual-level data from incomplete tables on populations is table standardization using iterative proportional fitting (e.g., Agresti 2002: 345-6; Deming and Stephan 1940; Fienberg 1970; Ireland and Kullback 1968; Beckman, Baggerly, and McKay 1996). This approach was used in the NIH funded Models of Infectious Disease Agent Study (MIDAS) to generate an agent-based model with a population that included every household and individual in the U.S. population in 2000, as well as schools and workplaces generated to match counts at the Census block level area of geography (Wheaton et al 2009; Wheaton 2009). 13 The MIDAS micro- population data are available by request from RTI International.…”

The Role of Subway Travel in an Influenza Epidemic: A New York City Simulation

“…All persons are given disease status. 3 A total of 2,005,024 people are under 18 years of age, and 848,590 are over 65.…”

Virtual city: An individual-based digital environment for human mobility and interactive behavior

“…In this work, they utilize the population generator of TRANSIMS to generate micro-data records for all households, including household size, income, population, and vehicles available. 28 Besides the works based on or inherited from TRANSIMS, other researchers also make efforts to reconstruct virtual societies. Carley et al 2 design a city-scale, agent-based system BioWar, and individuals are characterized by heterogeneous population mixing, social networks, disease character, and diagnosis algorithms.…”