Disaster-related interventions are actions or responses undertaken during any phase of a disaster to change the current status of an affected community or a Societal System. Interventional disaster research aims to evaluate the results of such interventions in order to develop standards and best practices in Disaster Health that can be applied to disaster risk reduction. Considering interventions as production functions (transformation processes) structures the analyses and cataloguing of interventions/responses that are implemented prior to, during, or following a disaster or other emergency. Since currently it is not possible to do randomized, controlled studies of disasters, in order to validate the derived standards and best practices, the results of the studies must be compared and synthesized with results from other studies (ie, systematic reviews). Such reviews will be facilitated by the selected studies being structured using accepted frameworks. A logic model is a graphic representation of the transformation processes of a program [project] that shows the intended relationships between investments and results. Logic models are used to describe a program and its theory of change, and they provide a method for the analyzing and evaluating interventions. The Disaster Logic Model (DLM) is an adaptation of a logic model used for the evaluation of educational programs and provides the structure required for the analysis of disaster-related interventions. It incorporates a(n): definition of the current functional status of a community or Societal System, identification of needs, definition of goals, selection of objectives, implementation of the intervention(s), and evaluation of the effects, outcomes, costs, and impacts of the interventions. It is useful for determining the value of an intervention and it also provides the structure for analyzing the processes used in providing the intervention according to the Relief/Recovery and Risk-Reduction Frameworks.

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http://dx.doi.org/10.1017/S1049023X16000017DOI Listing

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