Effectiveness of and Adherence to Triage Algorithms During Prehospital Response to Mass Casualty Incidents

Mass casualty incidents (MCIs) can rapidly exhaust available resources and demand the prioritization of medical response efforts and materials. Principles of triage (i.e., sorting) from the 18th century have evolved into a number of modern-day triage algorithms designed to systematically train responders managing these chaotic events. We reviewed reports and studies of MCIs to determine the use and efficacy of triage algorithms. Despite efforts to standardize MCI responses and improve the triage process, studies and recent experience demonstrate that these methods have limited accuracy and are infrequently used.

Quantitative risk assessment of typhoon storm surge for multi-risk sources

Typhoon storm surge (TSS) is a complex marine disaster affected by multi-risk sources. Quantitative risk assessment is an important prerequisite for identifying risk areas and designing risk reduction strategies. This paper aims to propose a rapid, accurate, and comprehensive quantitative risk assessment method for TSS under multi-risk sources, including disaster occurrence probability and severity. First, identify the primary risk sources according to the disaster-causing mechanism of TSS. Then, based on the official public data from 1989 to 2020, the dependence structure among multi-risk sources is constructed using Copulas to calculate the probability of each superposition scenario. Meanwhile, build visual scenario databases employing Geographical Information System (GIS) techniques. Subsequently, the extent and depth of inundation are translated into economic risk and population risk using GIS and depth-damage functions. Finally, taking the "Mangkhut" as a case study, the method's feasibility and accuracy are verified. The results show that the primary risk sources of TSS are storm tide, astronomical tide and coastal waves. The Gumbel Copula is optimal, with OLS (ordinary least squares) and D of 0.0186 and 0.1831, respectively. The probability assessment under different superposition scenarios indicates that the greatest threat of TSS in Guangzhou comes from the storm tide and the astronomical tide. As for the "Mangkhut" case study in Jiangmen City, the assesses occurrence probability is 0.0355%, the accuracy of economic risk assessment (except mariculture) is 95.28%, and the accuracy of population risk assessment is 98.60%. Residences and the disaster-bearing bodies in 0-3 m inundation depth are most severely affected by TSS disasters. Measures such as locating residential and important buildings away from the shoreline (at least 10 km) and ground (above 3 m), formulating disaster emergency plans, and developing the forecast and prevention of storm tides and astronomical tides will help ensure the safety of residents' life and property. This paper provides an efficient and accurate method, which is of great significance for disaster control, sustainable development, and decision-making.

The Need for a Preparedness Training Model on Disaster Risk Reduction Based on Culturally Sensitive Public Health Nursing (PHN)

The Indonesian Disaster Risk Index (IRBI) in 2018 found that 52.33% of districts or cities in Indonesia were at high risk of natural disasters and the others were at moderate risk. The World Risk Index places Indonesia at number 33 in the very high-risk category. The policy direction of the Implementation of Disaster Management in Indonesia in 2020-2024 is to increase disaster resilience toward sustainable prosperity for sustainable development.

PURPOSE

This study aims to identify the various needs for a culturally sensitive PHN-based disaster risk-reduction preparedness training model.

METHODS

This study used a descriptive qualitative research design. Data collection was done through in-depth interviews, Focus Group Discussions (FGDs), and expert panel stages in the Indonesian language. Samples involved in the research included 4 experts and 11 informants.

RESULTS

There were 10 themes generated from the results. The analysis results revealed that the level of knowledge, attitudes, and skills of the community is still low. Almost all of the people of Mekar Mukti Village stated that they had never received community-based disaster management training.

CONCLUSIONS

The study findings highlighted the importance of the Disaster Risk-Reduction Preparedness Model Based on Culturally Sensitive Public Health Nursing for the community.

An Interdisciplinary Approach to Quantify the Human Disaster Risk Perception and Its Influence on the Population at Risk: A Case Study of Longchi Town, China

Understanding disaster risk perception is vital for community-based disaster risk reduction (DRR). This study was set to investigate the correlations between disaster risk perception and the population at risk. To address this research question, the current study conducted an interdisciplinary approach: a household survey for measuring variables and constructed an Agent-based model for simulating the population at risk. Therefore, two correlations were defined, (1) between risk perception and willingness to evacuate, and (2) between willingness to evacuate and the population at risk. The willingness to evacuate was adopted as a mediator to determine the relationship between risk perception and the population at risk. The results show that the residents generally have a higher risk perception and willingness to evacuate because the study area frequently suffered from debris flow and flash floods. A positive correlation was found between risk perception and willingness to evacuate, and a negative correlation to the population at risk. However, a marginal effect was observed when raising public risk perception to reduce the number of the population at risk. This study provides an interdisciplinary approach to measuring disaster risk perception at the community level and helps policymakers select the most effective ways to reduce the population at risk.

Effectiveness of the virtual reality chemical disaster training program in emergency nurses: A quasi experimental study

BACKGROUND

In Taiwan, 50 % of the chemical disasters in the last decade were industrial accidents. The leakage of industrial toxic chemical substances may cause significant environmental pollution and harms. Taiwan's chemical disaster education and training mainly rely on simulation, which is labor-intensive, time-consuming, and costly. Tabletop drills are often used to as a substitute for simulations. However, tabletop drills lack a realistic presence. The 360° virtual reality (VR) transforms knowledge of disaster preparedness into audio-visual and other sensory experiences and allows participants to be physically immersed in an environment.

PURPOSE

This study examined effectiveness of a "360° VR chemical disaster training program" on disaster preparedness and self-efficacy in ER nurses.

METHOD

This study used convenience sampling and quasi-experimental design with two-group repeated measures. Seventy-seven ER nurses were recruited with the experimental group (n = 32) receiving chemical disaster training through 360° VR and the control group (n = 35) receiving training through tabletop drills. Data were collected before, one week after and three weeks after the intervention.

RESULT

Participants in the experimental group were significantly younger and less experienced in disaster management than those in the control group. There were no between-group differences in the participants' self-assessment of chemical disaster preparedness and self-efficacy before the intervention. The intervention group showed significantly higher self-assessment chemical disaster preparedness scores than the comparison group (p < .05) one week after the intervention. However, no significant differences were found three weeks after the intervention.

CONCLUSION

This study found that both 360° VR and tabletop drills improved preparedness and self-efficacy in chemical disasters among ER nurses. VR could be used for disaster preparedness training for nurses without prior disaster response experiences/ drills, whereas tabletop drills were more suitable for nurses with prior experiences. Both methods may effectively promote nurses' learning effectiveness and self-efficacy in chemical disaster preparedness.

Preparing for Pandemics and Other Health Threats: Societal Approaches to Protect and Improve Health

This Viewpoint discusses 3 areas in need of progress regarding societal approaches to pandemics and other health threats: a renaissance in public health; robustness of primary health care; and resilience of individuals and communities, with higher levels of trust in government and society.

Public Health Decision Making in the Case of the Use of a Nuclear Weapon

The current geopolitical situation and the war on Ukraine's territory generate questions about the possible use of a nuclear weapon and create the need to refresh emergency protective plans for the population. Ensuring the protection of public health is a national responsibility, but the problem is of international size and global scale. Radiological or nuclear disasters need suitable decision making at the right time, which determine large effective radiation protection activities to ensure public health is protected, reduce fatalities, radiation disease, and other effects. In this study, a simulation of a single nuclear weapon detonation with an explosion yield of 0.3 and 1 Mt was applied for a hypothetical location, to indicate the required decision making and the need to trigger protocols for the protection of the population. The simulated explosion was located in a city center, in a European country, for the estimation of the size of the effects of the explosion and its consequences for public health. Based on the simulation results and knowledge obtained from historical nuclear events, practical suggestions, discussion, a review of the recommendations was conducted, exacerbated by the time constraints of a public health emergency. Making science-based decisions should encompass clear procedures with specific activities triggered immediately based on confirmed information, acquired from active or/and passive warning systems and radiometric specific analysis provided by authorized laboratories. This study has the potential to support the preparedness of decision makers in the event of a disaster or crisis-related emergency for population health management and summarizes the strengths and weaknesses of the current ability to respond.

Factors Influencing Public Participation in Community Disaster Mitigation Activities: A Comparison of Model and Nonmodel Disaster Mitigation Communities

Public participation in community-organized disaster mitigation activities is important for improving disaster mitigation capacity. With data from 260 questionnaires, this study compared the current status of public participation in model disaster mitigation communities and nonmodel communities in a geological-disaster-prone area. Three community-organized disaster mitigation education activities were compared cross-sectionally. A binary logistic regression was used to analyze the effects of attitude, perceived behavioral control, disaster experience, and other key factors on the public's choice to participate in community disaster mitigation activities. The analysis results indicated that model communities had higher public participation in two efforts, evacuation drills and self-help skills training, and lower participation in activities that invited them to express their feedback than nonmodel communities. The influence of attitudinal factors on the decision to participate in disaster mitigation activities had a high similarity across community types. The public participation in model disaster mitigation communities is influenced by factors such as subjective norms and participation cognition; the behavior of people in nonmodel communities is influenced by factors such as previous experience with disasters, perceived behavioral control, risk perception, and participation cognition and has a greater potential for disaster mitigation community construction. This study provides practical evidence and theoretical support for strengthening the sustainable development of disaster mitigation community building.

Valuing Human Impact of Natural Disasters: A Review of Methods

This paper provides a comprehensive set of methodologies that have been used in the literature to give a monetary value to the human impact in a natural disaster setting. Four databases were searched for relevant published and gray literature documents with a set of inclusion and exclusion criteria. Twenty-seven studies that quantified the value of a statistical life in a disaster setting or discussed methodologies of estimating value of life were included. Analysis highlighted the complexity and variability of methods and estimations of values of statistical life. No single method to estimate the value of a statistical life is universally agreed upon, although stated preference methods seem to be the preferred approach. The value of one life varies significantly ranging from USD 143,000 to 15 million. While an overwhelming majority of studies concern high-income countries, most disaster casualties are observed in low- and middle-income countries. Data on the human impact of disasters are usually available in disasters databases. However, lost lives are not traditionally translated into monetary terms. Therefore, the full financial cost of disasters has rarely been evaluated. More research is needed to utilize the value of life estimates in order to guide policymakers in preparedness and mitigation policies.

Emergency Relief Chain for Natural Disaster Response Based on Government-Enterprise Coordination

Public health and effective risk response cannot be promoted without a coordinated emergency process during a natural disaster. One primary problem with the emergency relief chain is the homogeneous layout of rescue organizations and reserves. There is a need for government-enterprise coordination to enhance the systemic resilience and demand orientation. Therefore, a bi-level multi-phase emergency plan model involving procurement, prepositioning and allocation is proposed. The tradeoff of efficiency, economy and fairness is offered through the multi-objective cellular genetic algorithm (MOCGA). The flood emergency in Hunan Province, China is used as a case study. The impact of multi-objective and coordination mechanisms on the relief chain is discussed. The results show that there is a significant boundary condition for the coordinated location strategy of emergency facilities and that further government coordination over the transition phase can generate optimal relief benefits. Demand orientation is addressed by the proposed model and MOCGA, with the realization of the process coordination in multiple reserves, optimal layout, and transition allocation. The emergency relief chain based on government-enterprise coordination that adapts to the evolution of disasters can provide positive actions for integrated precaution and health security.

Factors Challenging the Spiritual Rehabilitation of Iranian Men Affected by Natural Disasters: A Qualitative Study

Spiritual health is one important dimension of human health. Natural disasters, however, can adversely affect human spiritual health. One of the undeniable requirements of disaster management is the spiritual rehabilitation of victims to help them recover to their pre-disaster health conditions. This study aimed to explore the factors challenging the spiritual rehabilitation of Iranian men suffering from natural disasters based on the experiences of key informants. The participants were 19 spiritual health experts in post-disaster spiritual rehabilitation. Participants were selected using a purposive sampling method until data saturation was reached. The data were collected through semi-structured interviews and analyzed using Granheim and Lundman (2004) content analysis method. The factors challenging men's spiritual rehabilitation were classified into 6 main categories and 16 subcategories. The extracted categories included (i) correcting victims' perspectives, (ii) describing God's characteristics, (iii) seeking help from God, (iv) strengthening spiritual beliefs, (v) psychological factors, and (vi) tranquility factors. Our findings identified the important factors challenging the spiritual rehabilitation of the men victimized by natural disasters, which needed to be considered by responsible organizations and health sectors. Particularly, the organizations in charge of disaster management should take necessary measures and plans during the post-disaster phase to restore people's spiritual health. Spiritual health, currently a neglected dimension of health, should be considered people's in parallel with physical, psychological, and social health dimensions. Our results can be helpful in developing action plans for delivering a comprehensive spiritual rehabilitation service, which would help to lead to the full rehabilitation of victims after natural disasters.

A Markov Decision Process Approach for Cost-Benefit Analysis of Infrastructure Resilience Upgrades

As climate change threatens to cause increasingly frequent and severe natural disasters, decisionmakers must consider costly investments to enhance the resilience of critical infrastructures. Evaluating these potential resilience improvements using traditional cost-benefit analysis (CBA) approaches is often problematic because disasters are stochastic and can destroy even hardened infrastructure, meaning that the lifetimes of investments are themselves uncertain. In this article, we develop a novel Markov decision process (MDP) model for CBA of infrastructure resilience upgrades that offer prevention (reduce the probability of a disaster) and/or protection (mitigate the cost of a disaster) benefits. Stochastic features of the model include disaster occurrences and whether or not a disaster terminates the effective life of an earlier resilience upgrade. From our MDP model, we derive analytical expressions for the decisionmaker's willingness to pay (WTP) to enhance infrastructure resilience, and conduct a comparative static analysis to investigate how the WTP varies with the fundamental parameters of the problem. Following this theoretical portion of the article, we demonstrate the applicability of our MDP framework to real-world decision making by applying it to two case studies of electric utility infrastructure hardening. The first case study considers elevating a flood-prone substation and the second assesses upgrading transmission structures to withstand high winds. Results from these two case studies show that assumptions about the value of lost load during power outages and the distribution of customer types significantly influence the WTP for the resilience upgrades and are material to the decisions of whether or not to implement them.

Preparing railway stakeholders against CBRNe threats through better cooperation with security practitioners

This paper presents partial results from the Horizon2020 PROACTIVE project, following a set of literature reviews and surveys conducted with first responder organisations and rail security experts. Qualitative and quantitative data from two surveys are being presented. The results provide an overview of the CBRNe (Chemical, Biological, Radiological, Nuclear and explosive) preparedness and response capabilities of railway stakeholders and how these relate to a wider context represented by CBRNe first responders. The results highlight a set of challenges as well as five core skills that railway staff need to develop or improve: 1) understand the specific characteristics of the CBRNe threat, 2) develop basic response measures, 3) cooperate with authorities and train with specialised first responders, 4) improve public awareness about this threat, and 5) optimise crisis communication. In line with these, project PROACTIVE will further help update rail crisis management plans with practical recommendations concerning the CBRNe threat.

Operationalizing Community Assessment Results to Enhance Preparedness for a Radiological Emergency

OBJECTIVE

A radiological emergency such as the detonation of a radiological dispersal device would have catastrophic health, environmental, and economic consequences. Community assessments can provide useful information about radiological and other emergency preparedness at the household level. Tools such as logic models can be applied to link data collected in a community assessment to planned activities and targeted outcomes. This study sought to answer how public health departments can use the results of a community assessment to improve preparedness for radiological and other types of emergencies and to present a sample logic model demonstrating how questions asked in a community assessment can be used to drive intended outcomes.

DESIGN

Surveys were fielded in 2019 to professionals with experience in radiological emergency preparedness, state and local health and emergency management, and journalism. Questions included the role of health departments in radiological emergency preparedness, the operationalization of results from a community assessment for preparedness, and information sharing in a radiological emergency. Descriptive statistics and a modified framework approach were used for open-ended questions.

RESULTS

Nearly three-fourths of state/local officials reported that it would be at least somewhat difficult (73%; 11 of 15 state/local officials) for a local health department to operationalize the results of a community health assessment for radiological emergency preparedness. Potential barriers included competing priorities, lack of funds, and limited staff. Resources such as pretested communication materials, tailored messaging, and technical tools and training can assist health departments and emergency management agencies in using the information collected from a community assessment.

CONCLUSIONS

To address implementation challenges in operationalizing the results of a community assessment, officials can use tools such as logic models to illustrate how the information gathered from a community health assessment will create an intended preparedness outcome and to advocate for funds for this type of assessment.

The timing of storm awareness in the Caribbean: the utility of climate information for improved disaster preparedness

Noting the frequency of tropical storm hazards and related disasters within the Caribbean, this paper initially highlights the relatively short average period of 'storm awareness timing' in the region, less than 24 hours, with variations in time and space. Next, it evaluates the results of a survey on communicating disaster risk by a range of participants at the 2016 Wet/Hurricane Season Caribbean Community Climate Outlook Forum in Dominica. Respondents commented that there may be a 'weekend effect' possibly hindering quick action and suggested that improved institutional support was needed to use climate information better. Analysis of these two datasets in tandem offers a unique understanding of whether the timing of events may contribute to limitations on responses by local authorities. Lastly, the paper ends with insights into how this research can assist regional authorities in enhancing and utilising climate information for disaster risk reduction, as well as by indicating where critical issues remain.

Critical decisions in hurricane evacuation bridge and roadway closures

The closure of bridges and roadways during hurricanes can represent an abrupt end to evacuations for the resi-dents of coastal barrier island. Despite the gravity of bridge and roadway closures during hurricane evacuations, their governing policies and practices in the United States are often opaque, poorly defined, or mired in confusion. The lack of clarity among bridge and roadway closure policy rationales and terminology, as well as their wide dissensus, may disrupt public compliance and participation in hurricane evacuations. This article argues for the application of critical decision methods (CDMs) analysis in hurricane evacuation bridge and roadways closures as a means of producing better, evidence-based policies and practices. Using CDM to study the decision-making of the experts responsible for the actual work of closing bridges and roadways in hurricane evacuations can help produce more detailed, evi-dence-based policies, more compelling communication about those policies, and greater public compliance in hurricane evacuations.

Disaster Response-A Global Concern: Are You Prepared to Care for Victims of Chemical, Biological, Radiological, and Nuclear Attacks?

The threat of bioterrorism is increasing in lethality and numbers of events globally. Weapons of mass destruction include devices of chemical, biological, radiological, and nuclear origin and are often selected by terrorists because they are capable of causing widespread destruction, harm, and panic. Emergency personnel are often first to recognize and report potential terrorist activities. It is essential that emergency personnel maintain a high index of suspicion for symptom patterns that correspond with effects of bioterrorism agents. Health care providers must have a solid understanding of personal protective equipment for specific categories of bioterrorism agents to protect themselves and others while providing care to victims in the emergency department. A clear understanding of disaster protocols, established communication systems, reporting requirements, and available resources to aid in patient management following a bioterrorism event is crucial for optimal, safe, quality care to be administered.

Multiobjective Emergency Resource Allocation under the Natural Disaster Chain with Path Planning

Public safety and health cannot be secured without the comprehensive recognition of characteristics and reliable emergency response schemes under the disaster chain. Distinct from emergency resource allocation that focuses primarily on a single disaster, dynamic response, periodic supply, and assisted decision-making are necessary. Therefore, we propose a multiobjective emergency resource allocation model considering uncertainty under the natural disaster chain. Resource allocation was creatively combined with path planning through the proposed multiobjective cellular genetic algorithm (MOCGA) and the improved A* algorithm with avoidance of unexpected road elements. Furthermore, timeliness, efficiency, and fairness in actual rescue were optimized by MOCGA. The visualization of emergency trips and intelligent avoidance of risk areas were achieved by the improved A* algorithm. The effects of logistics performance, coupling of disaster factors, and government regulation on emergency resource allocation were discussed based on different disaster chain scenarios. The results show that disruption in infrastructure support, cascading effect of disasters, and time urgency are additional environmental challenges. The proposed model and algorithm work in obtaining the optimal solution for potential regional coordination and resilient supply, with a 22.2% increase in the total supply rate. Cooperative allocation complemented by political regulation can be a positive action for successfully responding to disaster chains.

A Novel Digital Twin Architecture with Similarity-Based Hybrid Modeling for Supporting Dependable Disaster Management Systems

Disaster management systems require accurate disaster monitoring and prediction services to reduce damages caused by natural disasters. Digital twins of natural environments can provide the services for the systems with physics-based and data-driven disaster models. However, the digital twins might generate erroneous disaster prediction due to the impracticability of defining high-fidelity physics-based models for complex natural disaster behavior and the dependency of data-driven models on the training dataset. This causes disaster management systems to inappropriately use disaster response resources, including medical personnel, rescue equipment and relief supplies, to ensure that it may increase the damages from the natural disasters. This study proposes a digital twin architecture to provide accurate disaster prediction services with a similarity-based hybrid modeling scheme. The hybrid modeling scheme creates a hybrid disaster model that compensates for the errors of physics-based prediction results with a data-driven error correction model to enhance the prediction accuracy. The similarity-based hybrid modeling scheme reduces errors from the data dependency of the hybrid model by constructing a training dataset using similarity assessments between the target disaster and the historical disasters. Evaluations in wildfire scenarios show that the digital twin decreases prediction errors by approximately 50% compared with those of the existing schemes.

[Management of COVID-19 mass casualty incidents in nursing and retirement homes]

BACKGROUND

During the coronavirus disease 2019 (COVID-19) pandemic, outbreaks in inpatient care facilities, which grow into a large-scale emergency scenario, are frequently observed. A standardized procedure analogous to algorithms for mass casualty incidents (MCI) is lacking.

METHODS

Based on a case report and the literature, the authors present a management strategy for infectious MCI during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and distinguish it from traumatic MCI deployment tactics.

RESULTS

This management strategy can be divided into three phases, beginning with the acute emergency response including triage, stabilization of critical patients, and transport of patients requiring hospitalization. Phase 2 involves securing the facility's operational readiness, or housing residents elsewhere in case staff are infected or quarantined to a relevant degree. Phase 3 marks the return to regular operations.

DISCUSSION

Phase 1 is based on usual MCI principles, phase 2 on hospital crisis management. Avoiding evacuation of residents to relieve hospitals is an important operational objective. The lack of mission and training experience with such situations, the limited applicability of established triage algorithms, and the need to coordinate a large number of participants pose challenges.

CONCLUSION

This strategic model offers a practical, holistic approach to the management of infectious mass casualty scenarios in nursing facilities.

On the resilience of health systems: A methodological exploration across countries in the WHO African Region

The need for resilient health systems is recognized as important for the attainment of health outcomes, given the current shocks to health services. Resilience has been defined as the capacity to "prepare and effectively respond to crises; maintain core functions; and, informed by lessons learnt, reorganize if conditions require it". There is however a recognized dichotomy between its conceptualization in literature, and its application in practice. We propose two mutually reinforcing categories of resilience, representing resilience targeted at potentially known shocks, and the inherent health system resilience, needed to respond to unpredictable shock events. We determined capacities for each of these categories, and explored this methodological proposition by computing country-specific scores against each capacity, for the 47 Member States of the WHO African Region. We assessed face validity of the computed index, to ensure derived values were representative of the different elements of resilience, and were predictive of health outcomes, and computed bias-corrected non-parametric confidence intervals of the emergency preparedness and response (EPR) and inherent system resilience (ISR) sub-indices, as well as the overall resilience index, using 1000 bootstrap replicates. We also explored the internal consistency and scale reliability of the index, by calculating Cronbach alphas for the various proposed capacities and their corresponding attributes. We computed overall resilience to be 48.4 out of a possible 100 in the 47 assessed countries, with generally lower levels of ISR. For ISR, the capacities were weakest for transformation capacity, followed by mobilization of resources, awareness of own capacities, self-regulation and finally diversity of services respectively. This paper aims to contribute to the growing body of empirical evidence on health systems and service resilience, which is of great importance to the functionality and performance of health systems, particularly in the context of COVID-19. It provides a methodological reflection for monitoring health system resilience, revealing areas of improvement in the provision of essential health services during shock events, and builds a case for the need for mechanisms, at country level, that address both specific and non-specific shocks to the health system, ultimately for the attainment of improved health outcomes.

Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations

OBJECTIVE

To develop a new model to quantify information management dynamically and to identify factors that lead to information gaps.

BACKGROUND

Information management is a core task for emergency medical service (EMS) team leaders during the prehospital phase of a mass-casualty incident (MCI). Lessons learned from past MCIs indicate that poor information management can lead to increased mortality. Various instruments are used to evaluate information management during MCI training simulations, but the challenge of measuring and improving team leaders' abilities to manage information remains.

METHOD

The Dynamic Communication Quantification (DCQ) model was developed based on the knowledge representation typology. Using multi point-of-view synchronized video, the model quantifies and visualizes information management. It was applied to six MCI simulations between 2014 and 2019, to identify factors that led to information gaps, and compared with other evaluation methods.

RESULTS

Out of the three methods applied, only the DCQ model revealed two factors that led to information gaps: first, consolidation of numerous casualties from different areas, and second, tracking of casualty arrivals to the medical treatment area and departures from the MCI site.

CONCLUSION

The DCQ model allows information management to be objectively quantified. Thus, it reveals a new layer of knowledge, presenting information gaps during an MCI. Because the model is applicable to all MCI team leaders, it can make MCI simulations more effective.

APPLICATION

This DCQ model quantifies information management dynamically during MCI training simulations.

A comprehensive review of the articles published in the field of health in emergencies and disasters in Iran

Introduction

Iran is one of the most disaster-prone countries in the world. A research-based approach is essential to reduce the effects of disasters and provide effective responses. This study aims to review the articles published in the field of emergencies and disasters in Iran.

Methods

a combination of descriptive and qualitative content analysis using Hsieh and Shannon´s method was done. Since the first and most well-known specialized journal in the field of emergencies and disasters in Iran is the Health in emergencies and Disasters Quarterly (HDQ), all articles published in this journal were examined in terms of theme and scientometric indicators.

Results

regarding the type of research, 103 were quantitative (66.5%), 18 were qualitative (11.6%), and 4 (2.6%) were performed by mixed method. Most of the articles (n=116, 76.3%) were original research. The most frequently studied risk was traffic accidents (n=17, 10.96%) followed by earthquakes (n=10, 6.45%) and floods (n=8, 5.16%). In terms of theme and content, 103 published articles were related to one of the 4 main phases of the disaster risk management cycle where most of them were related to preparedness (n=48, 46.6%) followed by mitigation (n=26, 25.24%), response (n=20, 19.42%), and recovery (n=9, 8.47%) phases.

Conclusion

although there are studies related to the four phases of disaster risk management cycle in Iran, most of them are related to assessing preparedness followed by mitigation. In addition, qualitative and mixed studies could have more significant contribution to this field of research, accelerating this process requires the development of disaster research methodology training and researcher training programs as well as their organized and financial support.

Resetting international systems for pandemic preparedness and response

Sudhvir Singh and colleagues summarise the recommendations of the Independent Panel for Pandemic Preparedness and Response to try to prevent future pandemics