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Synthesized Population Databases: A US Geospatial Database for Agent-Based Models.

William D Wheaton¹, James C Cajka, Bernadette M Chasteen

¹senior research geographer and director of RTI International's Geospatial Science and Technology program.

Methods Report (RTI Press)

|May 28, 2010

Summary

This summary is machine-generated.

Researchers developed a synthesized human agent database for the US population in 2000, crucial for agent-based models simulating social systems and disease outbreaks.

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Area of Science:

Computational Social Science
Demographic Modeling
Epidemiological Simulation

Background:

Agent-based models (ABMs) are essential tools for simulating complex social systems and infectious disease outbreaks.
Accurate population data is critical for the validity and efficacy of ABMs.

Purpose of the Study:

To describe the methods used to create a synthesized, geospatially explicit human agent database for the US population in 2000.
To provide researchers with the necessary information to utilize this database for developing agent-based models.

Main Methods:

An iterative proportional fitting method was used and extended to generate the synthesized population database.
Methods were developed for creating synthesized households, assigning agents to schools and workplaces, and generating agents in group quarters.

Main Results:

A synthesized human agent database representing the US population in 2000 was generated.
The database includes agents assigned to households, schools, workplaces, and group quarters, enabling the simulation of daily activities and interactions.

Conclusions:

The described methods provide a robust framework for generating detailed synthetic population databases.
The synthesized agent database is available to researchers for use in agent-based modeling, facilitating studies on social dynamics and disease transmission.