Using multiple scale spatio-temporal patterns for validating spatially explicit agent-based models

Authored by Jeon-Young Kang, Jared Aldstadt

Date Published: 2019

DOI: 10.1080/13658816.2018.1535121

Sponsors: United States National Institutes of Health (NIH)

Platforms: AnyLogic

Model Documentation: ODD

Model Code URLs: Model code not found

Abstract

Spatially explicit agent-based models (ABMs) have been widely utilized to simulate the dynamics of spatial processes that involve the interactions of individual agents. The assumptions embedded in the ABMs may be responsible for uncertainty in the model outcomes. To ensure the reliability of the outcomes in terms of their space-time patterns, model validation should be performed. In this article, we propose the use of multiple scale spatio-temporal patterns for validating spatially explicit ABMs. We evaluated several specifications of vector-borne disease transmission models by comparing space-time patterns of model outcomes to observations at multiple scales via the sum of root mean square error (RMSE) measurement. The results indicate that specifications of the spatial configurations of residential area and immunity status of individual humans are of importance to reproduce observed patterns of dengue outbreaks at multiple space-time scales. Our approach to using multiple scale spatio-temporal patterns can help not only to understand the dynamic associations between model specifications and model outcomes, but also to validate spatially explicit ABMs.

Tags

movement Pattern-oriented modelling Spatially explicit agent-based model systems Thailand transmission disease Culicidae Survival Aedes-aegypti diptera Pattern-oriented validation Space-time pattern Dengue virus Kamphaeng phet