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Physical Vulnerability in Earthquake Risk Assessment  

Abdelghani Meslem and Dominik H. Lang

In the fields of earthquake engineering and seismic risk reduction the term “physical vulnerability” defines the component that translates the relationship between seismic shaking intensity, dynamic structural uake damage and loss assessment discipline in the early 1980s, which aimed at predicting the consequences of earthquake shaking for an individual building or a portfolio of buildings. In general, physical vulnerability has become one of the main key components used as model input data by agencies when developinresponse (physical damage), and cost of repair for a particular class of buildings or infrastructure facilities. The concept of physical vulnerability started with the development of the earthqg prevention and mitigation actions, code provisions, and guidelines. The same may apply to insurance and reinsurance industry in developing catastrophe models (also known as CAT models). Since the late 1990s, a blossoming of methodologies and procedures can be observed, which range from empirical to basic and more advanced analytical, implemented for modelling and measuring physical vulnerability. These methods use approaches that differ in terms of level of complexity, calculation efforts (in evaluating the seismic demand-to-structural response and damage analysis) and modelling assumptions adopted in the development process. At this stage, one of the challenges that is often encountered is that some of these assumptions may highly affect the reliability and accuracy of the resulted physical vulnerability models in a negative way, hence introducing important uncertainties in estimating and predicting the inherent risk (i.e., estimated damage and losses). Other challenges that are commonly encountered when developing physical vulnerability models are the paucity of exposure information and the lack of knowledge due to either technical or nontechnical problems, such as inventory data that would allow for accurate building stock modeling, or economic data that would allow for a better conversion from damage to monetary losses. Hence, these physical vulnerability models will carry different types of intrinsic uncertainties of both aleatory and epistemic character. To come up with appropriate predictions on expected damage and losses of an individual asset (e.g., a building) or a class of assets (e.g., a building typology class, a group of buildings), reliable physical vulnerability models have to be generated considering all these peculiarities and the associated intrinsic uncertainties at each stage of the development process.


Corruption and the Governance of Disaster Risk  

David Alexander

This article considers how corruption affects the management of disaster mitigation, relief, and recovery. Corruption is a very serious and pervasive issue that affects all countries and many operations related to disasters, yet it has not been studied to the degree that it merits. This is because it is difficult to define, hard to measure and difficult to separate from other issues, such as excessive political influence and economic mismanagement. Not all corruption is illegal, and not all of that which is against the law is vigorously pursued by law enforcement. In essence, corruption subverts public resources for private gain, to the damage of the body politic and people at large. It is often associated with political violence and authoritarianism and is a highly exploitative phenomenon. Corruption knows no boundaries of social class or economic status. It tends to be greatest where there are strong juxtapositions of extreme wealth and poverty. Corruption is intimately bound up with the armaments trade. The relationship between arms supply and humanitarian assistance and support for democracy is complex and difficult to decipher. So is the relationship between disasters and organized crime. In both cases, disasters are seen as opportunities for corruption and potentially massive gains, achieved amid the fear, suffering, and disruption of the aftermath. In humanitarian emergencies, black markets can thrive, which, although they support people by providing basic incomes, do nothing to reduce disaster risk. In counties in which the informal sector is very large, there are few, and perhaps insufficient, controls on corruption in business and economic affairs. Corruption is a major factor in weakening efforts to bring the problem of disasters under control. The solution is to reduce its impact by ensuring that transactions connected with disasters are transparent, ethically justifiable, and in line with what the affected population wants and needs. In this respect, the phenomenon is bound up with fundamental human rights. Denial or restriction of such rights can reduce a person’s access to information and freedom to act in favor of disaster reduction. Corruption can exacerbate such situations. Yet disasters often reveal the effects of corruption, for example, in the collapse of buildings that were not built to established safety codes.