Title: SPEW: Synthetic Populations and Ecosystems of the World,
Abstract: Agent-based models (ABMs) simulate interactions between autonomous agents in
constrained environments over time. ABMs are often used for modeling the spread
of infectious diseases. In order to simulate disease outbreaks or other
phenomena, ABMs rely on "synthetic ecosystems," or information about agents and
their environments that is representative of the real world. Previous
approaches for generating synthetic ecosystems have some limitations: they are
not open-source, cannot be adapted to new or updated input data sources, and do
not allow for alternative methods for sampling agent characteristics and
locations. We introduce a general framework for generating Synthetic
Populations and Ecosystems of the World (SPEW), implemented as an open-source R
package. SPEW allows researchers to choose from a variety of sampling methods
for agent characteristics and locations when generating synthetic ecosystems
for any geographic region. SPEW can produce synthetic ecosystems for any agent
(e.g. humans, mosquitoes, etc), provided that appropriate data is available. We
analyze the accuracy and computational efficiency of SPEW given different
sampling methods for agent characteristics and locations and provide a suite of
diagnostics to screen our synthetic ecosystems. SPEW has generated over five
billion human agents across approximately 100,000 geographic regions in about
70 countries, available online.