We have reviewed disaster management research papers published in major operations management, management science, operations research, supply chain management and transportation/logistics journals. In reviewing these studies, our objective is to assess and present the macro level “architectural blue print” of disaster management research with the hope that it will attract new researchers and motivate established researchers to contribute to this important field. The secondary objective is to bring this disaster research to the attention of disaster administrators so that disasters are managed more efficiently and more effectively. We have mapped the disaster management research on the following five attributes of a disaster: (1) Disaster Management Function (decision‐making process, prevention and mitigation, evacuation, humanitarian logistics, casualty management, and recovery and restoration), (2) Time of Disaster (before, during and after), (3) Type of Disaster (accidents, earthquakes, floods, hurricanes, landslides, terrorism and wildfires etc.), (4) Data Type (Field and Archival data, Real data and Hypothetical data), and (5) Data Analysis Technique (bidding models, decision analysis, expert systems, fuzzy system analysis, game theory, heuristics, mathematical programming, network flow models, queueing theory, simulation and statistical analysis). We have done cross tabulations of data among these five parameters to gain greater insights into disaster research. Recommendations for future research are provided.
Emergency services worldwide face increasing cost pressure that potentially limits their existing resources. In many countries, emergency services also face the issues of staff shortage–creating extra challenges and constraints, especially during crisis times such as the COVID-19 pandemic–as well as long distances to sparsely populated areas resulting in longer response times. To overcome these issues and potentially reduce consequences of daily (medical) emergencies, several countries, such as Sweden, Germany, and the Netherlands, have started initiatives using new types of human resources as well as equipment, which have not been part of the existing emergency systems before. These resources are employed in response to medical emergency cases if they can arrive earlier than emergency medical services (EMS). A good number of studies have investigated the use of these new types of resources in EMS systems, from medical, technical, and logistical perspectives as their study domains. Several review papers in the literature exist that focus on one or several of these new types of resources. However, to the best of our knowledge, no review paper that comprehensively considers all new types of resources in emergency medical response systems exists. We try to fill this gap by presenting a broad literature review of the studies focused on the different new types of resources, which are used prior to the arrival of EMS. Our objective is to present an application-based and methodological overview of these papers, to provide insights to this important field and to bring it to the attention of researchers as well as emergency managers and administrators.
Accurate forecast of the demand for emergency medical services (EMS) can help in providing quick and efficient medical treatment and transportation of out-of-hospital patients. The aim of this research was to develop a forecasting model and investigate which factors are relevant to include in such model. The primary data used in this study was information about ambulance calls in three Swedish counties during the years 2013 and 2014. This information was processed, assigned to spatial grid zones and complemented with population and zone characteristics. A Zero-Inflated Poisson (ZIP) regression approach was then used to select significant factors and develop the forecasting model. The model was compared to the forecasting model that is currently incorporated in the EMS information system used by the ambulance dispatchers. The results show that the proposed model performs better than the existing one.
Sufficient emergency resources are essential for emergency services to provide timely help to affected people and to minimize damage to public and private assets and the environment. Emergency services, however, face resource shortages and increasing demand over time. As a result, their response times increase, resulting in lower survival chances of affected people and more severe damage to properties and the environment. Thus, emergency services need to utilize and effectively manage all their available resources. These can be divided into traditional resources, such as ambulances, and new and emerging resources, such as volunteers. Models and methods developed using operations research (OR) methodologies can facilitate the management of these resources. However, despite a rich literature on OR-based models and methods focusing on traditional resources, the literature on new and emerging resources, and specifically volunteers, is scarce.The aim of this thesis is to develop models and methods for task assignment and dispatch of volunteers to daily medical emergencies. This also includes forecasting models for future emergencies. The developed models and methods consider volunteer programs in Sweden and the Netherlands, employing real historical data.The aim has been addressed through three studies, one main study and two substudies, the results of which are presented in the six included papers. The main study focuses on the development of models, methods, and strategies for task assignment and dispatch of volunteers to out-of-hospital cardiac arrest (OHCA) cases using OR.To evaluate the survival rates of these patients, the most important health outcome of a response process, survival functions have been used in the development of these models and strategies. The results of this study are presented in Papers Ⅱ-Ⅴ. The first sub-study investigates different types of new and emerging resources used in daily medical emergency response, and the results are presented as an overview of the literature in Paper Ⅰ. The second sub-study focuses on the forecast of medical emergency demand, and its outcomes are presented in Paper Ⅵ.The overall conclusion is that the use of OR-based models and methods can contribute to improved outcomes and increased survival probabilities compared to the strategies and techniques used in the existing systems. vi vii This PhD journey has been a roller coaster ride with many ups and downs. At times, the upward stretches were long and slow while the downward ones were deep, feeling as though they would never end. Despite all the challenges along the way, it was a very enjoyable experience, giving me the opportunity to learn many lessons and grow. It would not have been possible to finish this roller coaster ride and write this thesis alone; I have been lucky to have had many people with me throughout this time, cheering me on, helping me, and supporting me, to whom I am sincerely grateful.First and foremost, I would like to thank my supervisors, Tobias Andersson Granberg, Jan Lundgren, and Anna ...
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