Proximity-based modelling of cross-contamination through agent-based simulation: a feasibility study

Abstract

Proximity-based modelling methodology enables mathematical representation of a real system that is characterised by the existence of entities that come into physical contact. Healthcare systems can benefit from this methodology since physical proximity between entities (e.g., patients, clinical items like surgical equipment and blood units) can result in the spread of infectious diseases and cross-contamination. The existing analytical techniques, which are mainly based on differential equations, are unsuitable for representing the fine-grained, micro-world view of the entity interactions that we intend to model. We therefore extend Agent-Based Simulation (ABS) by enabling individual agents to be aware of the physical location of the other agents being modelled in a 3-Dimensional space -this is a perquisite for our proximitybased modelling methodology. To demonstrate the feasibility of our approach we experiment with a scenario wherein boxes of degradable clinical items, modelled as agents, are stored in close proximity. We use Cutting and Packing Optimisation (CPO) algorithms from literature to define the arrangement of these agents in the 3-D space and to make the individual agents "location-aware". An ABS model then simulates crosscontamination by modelling the spread of contaminants amongst the agents confined in the well-defined space. Our approach can be used to model analogous situations wherein physical proximity between entities in the underlying system is a necessary condition for entity interactions.

Widening requirements capture with soft methods: an investigation of hybrid M&S studies in health care

“…Chahal andEldabi, 2008, 2010;Zulkepli et al, 2012;Viana et al, 2014;Fakhimi et al, 2015;Mustafee et al, 2015). Specific techniques that have been applied include: the combined application of SD and DES (Viana et al, 2014;Zulkepli et al, 2012;Chahal, 2010;Chahal and Eldabi, 2008), models using ABS, SD and DES (Djanatliev and German, 2013;Viana et al, 2012), combined application of ABS and load plan construction heuristics (Mustafee et al, 2012), loosely coupled SD and agent-based models (Djanatliev et al, 2012) and application of integer programming with simulation (Lee et al, 2012). The majority of these papers focus on the model implementation phase of a simulation study.…”

Hybrid simulation studies and Hybrid Simulation systems: Definitions, challenges, and benefits

“…This is recognized by the panelist and indeed some of his M&S work has used techniques from OR, e.g., application of Cutting and Packing Optimization with ABM (Mustafee et al 2013) and Qualitative System Dynamics to informs DES studies (Powell and Mustafee 2014), as also from distributed systems, e.g., grid computing ( Mustafee and Taylor 2009) and PADS/HLA (Mustafee et al 2009;Mustafee et al 2015). It is recognized that there are pockets of interdisciplinary research clusters on M&S. However, it is also true that most journals, conferences, journal/conference quality rankings, special interest groups and arguably departmental structures continue to maintain their focus on specific subject areas (this does not however mean they do not offer a conduit for hybrid systems research), and the development of a hybrid M&S community could enable us to "look wider" and more horizontally and help facilitate a more integrated and inter-disciplinary approach to systems modelling.…”