SPEW: Synthetic Populations and Ecosystems of the World. Issue 4 (2nd October 2018)

• Record Type: Journal Article
• Authors: Gallagher, Shannon; Richardson, Lee F.; Ventura, Samuel L.; Eddy, William F.
• Is Part Of: Journal of computational and graphical statistics. Volume 27:Issue 4(2018)
• Page Start: 773
• Page End: 784
• Publication Date: 2018-10-02
• Subjects: Agent-based models -- Disease modeling -- Iterative proportional fitting -- Parallel computing -- R -- Synthetic data; Mathematical statistics -- Data processing -- Periodicals; Mathematical statistics -- Graphic methods -- Periodicals; 519.50285
• DOI: 10.1080/10618600.2018.1442342
• Languages: English
• ISSNs: 1061-8600

Abstract

ABSTRACT: Agent-based models (ABMs) simulate interactions between autonomous agents in constrained environments over time and are often used for modeling the spread of infectious diseases. ABMs use information about agents and their environments as input, together referred to as a "synthetic ecosystem." Previous approaches for generating synthetic ecosystems have some limitations: they are not open-source, cannot be adapted to new or updated input data sources, or do not allow for alternative methods for sampling agent characteristics and locations. We introduce a general framework for generating synthetic ecosystems, called "Synthetic Populations and Ecosystems of the World" (SPEW). SPEW lets researchers choose from a variety of sampling methods for agent characteristics and locations and is implemented as an open-sourceR package. We analyze the accuracy and computational efficiency of SPEW, given different sampling methods for agent characteristics and locations, and provide a suite of statistical and graphical tools to screen our generated ecosystems. SPEW has generated over five billion human agents across approximately 100, 000 geographic regions in over 70 countries available online.