A Participatory Simulation Model for Studying Attitudes to Infection Risk

Citation

Maharaj S, Kleczkowski A & McCaldin T (2011) A Participatory Simulation Model for Studying Attitudes to Infection Risk. In: Proceedings of the Summer Computer Simulation Conference 2011 (SCSC 2011). Summer Computer Simulation Conference 2011 (SCSC 2011), The Hague, NL, 27.06.2011-30.06.2011. California: Society for Modeling and Simulation International Vista / ACM Digital Library, pp. 8-13.

Abstract
This paper describes work in progress in developing an agent based participatory simulation tool to be used in experiments to investigate human attitudes to the risk of being infected by disease. Previous work used agent-based simulation in NetLogo to explore how disease spread can be controlled by human behavioural changes such as social distancing (reducing the number of social contacts in response to the presence of disease in the neighbourhood). This work highlighted the importance of understanding attitudes to risk: how cautiously do real people behave when confronted with the threat of disease? To allow this question to be investigated, the original simulation was converted into a participatory simulation activity, in which a human experimental subject is able to control the actions of an agent in the simulation. To make the activity engaging for the participant and elicit realistic responses, a game-like front-end interface was created with Flash, and virtual economic incentives were provided so as to motivate the participant to seek out social contacts while attempting to avoid becoming infected. The tool is complete and is undergoing testing, in preparation for use in actual experiments. The paper discusses the background and motivation behind the work, the design and implementation of the experimental tool, and our plans for future development of the tool and for its use in carrying out experiments.

Keywords
participatory simulation; agent based simulation; NetLogo; human behaviour; SIR epidemic model; Computer programs Verification; Intelligent agents (Computer software)