Silverman, E., Charles, F., Porteous, J., Wood, I. and Ells, L.J., 2017. Agent-Based Virtual Urban Environments for Population Health Applications. In: The 2nd International Workshop on Agent-based modelling of urban systems (ABMUS 2017), 8 - 9 May 2017, Sao Paulo, Brazil. (Unpublished)
Full text available as:
|
PDF
ABMUS_17.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 1MB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
Official URL: http://modelling-urban-systems.com/
Abstract
Agent-based computational models are gaining traction as a means for modelling the complexities of designing and implementing health interventions in our rapidly-changing society. When such models are integrated with an interactive virtual environment they o er a way to investigate complex conditions including social and environmental de- terminants, while also facilitating participation and interaction from re- search users and policy-makers. Here we present a prototype Agent-Based Virtual Environment which features an early-stage model of obesity in- tended to support planners and local authority members in the develop- ment of environments that encourage healthy diets and higher physical exertion. We illustrate the construction of the model and its intended role in raising awareness of the role of the built environment in prevent- ing obesity. We also describe future extensions and ways to extend this framework to other areas of concern in public health.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Group: | Faculty of Science & Technology |
ID Code: | 29132 |
Deposited By: | Symplectic RT2 |
Deposited On: | 08 Jun 2017 10:03 |
Last Modified: | 14 Mar 2022 14:04 |
Downloads
Downloads per month over past year
Repository Staff Only - |