Seminars 1 and 2

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Operational Research (OR) has a strong legacy in EMA preparedness, beginning with the award-winning 1960s work for New York (Green & Kolesar 2004). To illustrate the breadth of well-known OR models on just evacuation, they include: Oak Ridge Evacuation Modeling System; Evacuation Traffic Information System; MassVAC. These analyse evacuation time, flow/congestion, destination percentages and shelter capacity - supporting decisions on evacuation destinations, optimal routes, regulating route flow rate, optimal evacuation rate (Chiu et al 2007), but mostly on self-evacuations. OR models also examine building evacuations (eg Cruz et al 2005) and on this Talebi & Smith’s (1985) queuing model analyses similar measures as above but also optimises staff allocation. Beyond evacuation, other OR models analyse: EMA responsiveness (Gendreau et al 2006); EMA sustained response (Albores & Shaw, 2008); mass vaccination clinics (Aaby et al 2004); mass casualties in hospitals (Ohbashi et al 1998); urban planning (Wolshon, 2007). However, preparedness requires multi-agency coordination and Jain & McLean (2003) and Brady (2003) offer models for analysing multi-agency response.
The preparedness of EMAs for major incidents is of course far advanced since it is the raison d’être for these organisations and OR has found a niche here. However, many issues remain worthy of further analyses, such as: how people move to access clean water sources during the recent floods in England; optimising the distribution of relief; using agent-base modelling to appreciate the effects of public response to an incident. The extent to which existing models/techniques can help here has not been fully explored nor has the requirement for new models and analytical techniques.
Given the depth of OR practice in this area, Seminar 1 will focus on drawing together and debating the latest knowledge and capability of (OR) models which have been applied to EMA preparedness and explore their flexibility in alternative contexts. Seminar 2 will build on this to: identify the limitations of current modelling provision; identify opportunities for further development of existing models; build stronger researcher/practitioner relations to support the development of theory in alignment with practice and vice versa.