2 resultados para case-based reasoning (CBR)
em WestminsterResearch - UK
Resumo:
Climate change and continuous urbanization contribute to an increased urban vulnerability towards flooding. Only relying on traditional flood control measures is recognized as inadequate, since the damage can be catastrophic if flood controls fail. The idea of a flood-resilient city – one which can withstand or adapt to a flood event without being harmed in its functionality – seems promising. But what does resilience actually mean when it is applied to urban environments exposed to flood risk, and how can resilience be achieved? This paper presents a heuristic framework for assessing the flood resilience of cities, for scientists and policy-makers alike. It enriches the current literature on flood resilience by clarifying the meaning of its three key characteristics – robustness, adaptability and transformability – and identifying important components to implement resilience strategies. The resilience discussion moves a step forward, from predominantly defining resilience to generating insight into “doing” resilience in practice. The framework is illustrated with two case studies from Hamburg, showing that resilience, and particularly the underlying notions of adaptability and transformability, first and foremost require further capacity-building among public as well as private stakeholders. The case studies suggest that flood resilience is currently not enough motivation to move from traditional to more resilient flood protection schemes in practice; rather, it needs to be integrated into a bigger urban agenda.
Resumo:
Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals’ protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.