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Risk analysis is a crisis management tool that improves understanding of potential ramifications of risks that can lead to crisis situations and decision making about successfully reducing these risks. Relevant data and information for a specified analysis objective and scope are identified and systematized through synchronic analysis of the combined potential dynamic effects of underlying hazards, exposure, and vulnerability. Issues for consideration include the appropriate level of quantitative and qualitative data, of participation and aggregation, and of realized and anticipated loss of data.

Though it is sometimes considered a subcomponent of risk assessment and sometimes a separate component in the risk management process, the resulting systematized outputs enable risk evaluation to determine which risks are to be minimized through treatment measures and which residual risks will remain for risk transfer or crisis preparedness and response.

Risk analysis can also be conducted in areas currently in a crisis situation to help determine how to address risks faced in the crisis and from actions taken to resolve it. Although such corrective risk analyses can be especially relevant in conditions of protracted crisis from extensive risks, the following introduction focuses on prospective risk analyses for proactively understanding realized and unrealized consequences of changing intensive and extensive risks. Although it is based on approaches for disaster risk reduction for a geographical entity, the approach is applicable to analyses related to crises arising from vulnerability to all types of hazards for any type of organization.

Methodological Framework

Though steps and terminology in approaches lack uniformity, all risk analyses determine scope and objectives of analysis, technical characteristics of objective-relevant potential hazards, and expected effects from interaction of resulting hazard scenarios with objective-relevant exposure, vulnerability, and capacities of elements of the system being analyzed. Since outputs of risk analysis are inputs to risk evaluation, appropriate methodologies are determined according to the purposes of evaluation for the specific system scale under investigation and the complexity of information desired by decision makers. These objectives and scope can range from enabling evaluation by an individual of expected loss of one element of one process in one function for him/herself to doing so for all elements, processes, and functions of an organization, nation, or region or for comparison across systems or times. Overall assessment objectives and risk management objectives of decision makers must also be considered. Generally, from analyses focusing entirely on quantifying expected loss of physical elements at risk to holistic analyses of expected losses and improved practice for all environmental, physical, economic, and social elements at risk and the processes that combine them into resulting functions at risk, objectives and resultant methodologies are based on systematization of data regarding who or what is vulnerable to what hazards and exposure and with respect to what basis for evaluation.

Case Study 1: Central American Probabilistic Risk Assessment

Although the Central American Probabilistic Risk Assessment (CAPRA) methodology can provide different types of users with tools, capabilities, information, and data to evaluate disaster risk through probabilistic analysis, its main objective is providing probabilities and estimates of potential future risks at a national level. After statistical summarization of historical hazard intensities and frequencies into stochastic scenarios for locations across the country and estimation of exposure values of assets at risk, vulnerability curves quantify potential damage to each asset class according to hazard scenarios based on specified vulnerability functions. Economic losses from multiplication of this damage figure by the value at risk are calculated for each asset class at each location and are aggregated. Resulting measures such as loss exceedance curves, probable maximum loss estimates, and aggregated average annual loss can be used by decision makers to compare and aggregate expected losses from various hazards in current and future scenarios.

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