Duncan T. Wilson

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When attempting to determine how to respond optimally to a large-scale emergency, the ability to predict the consequences of certain courses of action <i>in silico</i> is of great utility. Agent-based simulations (ABSs) have become the de facto tool for this purpose; however, they may be used and implemented in a variety of ways. This article reviews(More)
(2015) 'Agent-based simulation of emergency response to plan the allocation of resources for a hypothetical two-site major incident.', Engineering applications of articial intelligence., 46 (Part B). pp. 336-345. The full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal(More)
Early phase trials of complex interventions currently focus on assessing the feasibility of a large randomised control trial and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, early assessment of efficacy is common for drug therapies,(More)
  • Duncan T Wilson, Rebecca EA Walwyn, Sarah R Brown, Julia Brown, Amanda J Farrin
  • 2015
To incorporate formal assessments of potential efficacy into feasibility and pilot studies of complex interventions, appropriate methods for sample size determination are required. In particular, the implications of clustered patient outcomes resulting from cluster randomisation or treatment provision must be addressed. In this paper we will show how(More)
Modeling the complex decision problems faced in the coordination of disaster response as a scheduling problem to be solved using an optimization algorithm has the potential to deliver efficient and effective support to decision makers. However, much of the utility of such a model lies in its ability to accurately predict the outcome of any proposed(More)
When designing a decision support program for use in coordinating the response to Mass Casualty Incidents, the modelling of the health of casualties presents a significant challenge. In this paper we propose one such health model, capable of acknowledging both the uncertain and dynamic nature of casualty health. Incorporating this into a larger optimisation(More)
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