Development Plan of Facility Importance, Risk, and Damage Estimation Inventory Construction for Assisting Disaster Response Decision-Making

Purpose The purpose of this paper is to reveal the importance of the order of establishment of temporary logistics hubs (TLHs) when resources (mobile storage units used as TLHs) are limited and to present the development and implementation of a methodology that determines the order of establishment of TLHs to support post-disaster decision making. Design/methodology/approach It employed a decision support system that considers multiple decision makers and subjective attributes, while also addressing the impreciseness inherent in post-disaster decision making for ordering the establishment of TLHs. To do so, an optimization model was combined with a fuzzy multi-attribute group decision making approach. A numerical illustration was performed using data from the April 2015 Nepal Earthquake. Findings The results showed the location and order of establishment of TLHs, and demonstrated the impact of decision makers’ opinions on the overall ordering. Research limitations/implications The study does not discuss the uncertain nature of the location problem and the potential need for relocation of TLHs. Practical implications This methodology offers managerial insights for post-disaster decision making when resources are limited and their effective utilization is vital. The results highlight the importance of considering the opinions of multiple actors/decision makers to enable coordination and avoid complication between the growing numbers of humanitarian responders during disaster response. Originality/value This study introduces the concept of the order of establishment of TLHs and demonstrates its importance when resources are limited. It develops and implements a methodology determining the order of establishment of TLHs to support post-disaster decision making.

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(A226) Establishing a Framework for Synchronizing Critical Decision Making with Information Analysis during a Health/Medical Emergency

Prehospital and Disaster Medicine ◽

10.1017/s1049023x11002123 ◽

2011 ◽

Vol 26 (S1) ◽

pp. s61-s61 ◽

Cited By ~ 1

Author(s):

J. Paturas ◽

J. Pelazza ◽

R. Smith

Keyword(s):

Decision Making ◽

Emergency Preparedness ◽

Disaster Response ◽

The United States ◽

Medical Emergency ◽

Incident Management ◽

Local Health ◽

Information Analysis ◽

Incident Command ◽

State And Local

BackgroundThe Yale New Haven Center for Emergency Preparedness and Disaster Response (YNH-CEPDR) has worked in the United States with state and local health and medical organizations to evaluate critical decision making activities and to develop decision making tools and protocols to enhance decision making in a time sensitive environment. YNH-CEPDR has also worked with international organizations and US federal agencies to support situational awareness activities in simulated and real world events.ObjectivesDuring this session YNH-CEPDR will share the best practices from recent events such as the H1N1 response and the Haiti Earthquake. Participants will be engaged in discussions regarding overall framework for successful information collection, analysis and dissemination to support decision making based on these experiences. This session will also incorporate concepts provided by the US National Incident Management System (NIMS) and the Incident Command System (ICS), specifically through the development of Situational Reports (SitReps), Incident Action Plans (IAP) and Job Action Sheets as methods to implement the framework and concepts discussed. Participants will be led through a series of scenario-based discussions to allow application of critical decision making factors to their organization. At the conclusion of the session, participants will be able to identify next steps for enhancing the synchronization of critical decision making and information analysis within their organizations.

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Development Plan of Multi-Scenario for Efficient Complex-Disaster Response

Korean Journal of Hazardous Materials ◽

10.31333/kihm.2021.9.2.52 ◽

2021 ◽

Vol 9 (2) ◽

pp. 52-59

Author(s):

Hojin Jung ◽

Chonghwa Eun ◽

Il Moon

Keyword(s):

Disaster Response ◽

Development Plan

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Using Grid Technology for Maximizing Collaborative Emergency Response Decision Making

Grid Technology for Maximizing Collaborative Decision Management and Support ◽

10.4018/978-1-60566-364-7.ch013 ◽

2009 ◽

pp. 256-275 ◽

Cited By ~ 2

Author(s):

Eleana Asimakopoulou ◽

Chimay J. Anumba ◽

Bouchlaghem ◽

Bouchlaghem

Keyword(s):

Decision Making ◽

Emergency Response ◽

Data Grid ◽

Informed Decision ◽

Data Sources ◽

Grid Technology ◽

Distributed Data ◽

Grid Environment ◽

Design And Implementation ◽

Response Decision

Much work is under way within the Grid technology community on issues associated with the development of services to foster collaboration via the integration and exploitation of multiple autonomous, distributed data sources through a seamless and flexible virtualized interface. However, several obstacles arise in the design and implementation of such services. A notable obstacle, namely how clients within a data Grid environment can be kept automatically informed of the latest and relevant changes about data entered/committed in single or multiple autonomous distributed datasets is identified. The view is that keeping interested users informed of relevant changes occurring across their domain of interest will enlarge their decision-making space which in turn will increase the opportunities for a more informed decision to be encountered. With this in mind, the chapter goes on to describe in detail the model architecture and its implementation to keep interested users informed automatically about relevant up-to-date data.

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Modeling of emergency response decision-making process using stochastic Petri net: an e-service perspective

Information Technology and Management ◽

10.1007/s10799-012-0128-7 ◽

2012 ◽

Vol 13 (4) ◽

pp. 363-376 ◽

Cited By ~ 17

Author(s):

Siqing Shan ◽

Li Wang ◽

Ling Li

Keyword(s):

Decision Making ◽

Emergency Response ◽

Petri Net ◽

Decision Making Process ◽

Stochastic Petri Net ◽

Response Decision ◽

Service Perspective

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Flexible Data Input Layer Architecture (FDILA) for Quick-Response Decision Making Tools in Volatile Manufacturing Systems

2008 IEEE International Conference on Communications ◽

10.1109/icc.2008.1034 ◽

2008 ◽

Cited By ~ 3

Author(s):

S. Tavakoli ◽

A. Mousavi ◽

A. Komashie

Keyword(s):

Decision Making ◽

Manufacturing Systems ◽

Quick Response ◽

Data Input ◽

Input Layer ◽

Response Decision

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Outbreak response intervention models of vaccine-preventable diseases in humans and foot-and-mouth disease in livestock: a protocol for a systematic review

BMJ Open ◽

10.1136/bmjopen-2019-036172 ◽

2020 ◽

Vol 10 (10) ◽

pp. e036172

Author(s):

James M Azam ◽

Elisha B Are ◽

Xiaoxi Pang ◽

Matthew J Ferrari ◽

Juliet R C Pulliam

Keyword(s):

Systematic Review ◽

Decision Making ◽

Temporal Trends ◽

Foot And Mouth Disease ◽

Mouth Disease ◽

Outbreak Response ◽

Vaccine Preventable Diseases ◽

Foot And Mouth ◽

Response Decision ◽

The Impact

IntroductionOutbreaks of vaccine-preventable diseases continue to threaten public health, despite the proven effectiveness of vaccines. Interventions such as vaccination, social distancing and palliative care are usually implemented, either individually or in combination, to control these outbreaks. Mathematical models are often used to assess the impact of these interventions and for supporting outbreak response decision making. The objectives of this systematic review, which covers all human vaccine-preventable diseases, are to determine the relative impact of vaccination compared with other outbreak interventions, and to ascertain the temporal trends in the use of modelling in outbreak response decision making. We will also identify gaps and opportunities for future research through a comparison with the foot-and-mouth disease outbreak response modelling literature, which has good examples of the use of modelling to inform outbreak response intervention decision making.Methods and analysisWe searched on PubMed, Scopus, Web of Science, Google Scholar and some preprint servers from the start of indexing to 15 January 2020. Inclusion: modelling studies, published in English, that use a mechanistic approach to evaluate the impact of an outbreak intervention. Exclusion: reviews, and studies that do not describe or use mechanistic models or do not describe an outbreak. We will extract data from the included studies such as their objectives, model types and composition, and conclusions on the impact of the intervention. We will ascertain the impact of models on outbreak response decision making through visualisation of time trends in the use of the models. We will also present our results in narrative style.Ethics and disseminationThis systematic review will not require any ethics approval since it only involves scientific articles. The review will be disseminated in a peer-reviewed journal and at various conferences fitting its scope.PROSPERO registration numberCRD42020160803.

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