Emergency Response Time Research Articles

Resilience assessment of an urban rail transit network: A case study of Chengdu subway

Existing studies seldom consider network structure and passenger travel demand jointly, and certain impractical assumptions are generally considered for assessing the resilience of an urban rail transit (URT) network. To address the abovementioned limitations, we have proposed a performance indicator called the demand–impedance (DI) indicator, in which demand and impedance are reflected by passenger trips and travel time. By considering effective travel paths (ETPs) and passengers’ path choice behavior, we have proposed a node centrality called effective path betweenness (EPB) by modifying the betweenness centrality (BC) to evaluate the importance of stations. The performance curve of a URT network during the attack and repair processes is depicted using the DI indicator, and a modified resilience metric is formulated by referring to the resilience triangle. The model application in the Chengdu subway network demonstrates that the correlation coefficient between the EPB and BC of stations is 0.901, which indicates that stations with a higher EPB are inclined to have a higher BC. The Chengdu subway network demonstrates a higher resilience under random disturbances than it does under malicious disturbances. Disturbance duration, passengers’ tolerance time, and rescue ability on the Chengdu subway network significantly affect its resilience. Several practical suggestions involving the management of disturbances, shortening the emergency response time, providing passenger services, and improving emergency rescue ability are provided for managing the Chengdu subway system under disturbances.

Research on Route Optimization of Hazardous Materials Transportation Considering Risk Equity

The consequences of a hazmat accident can be catastrophic due to the characteristics of hazardous materials. Different from the models, which are constructed from the perspective of “government-carrier”, this paper considers the three objectives of the risk, the cost, and the compensation cost from the “government-carrier-public” perspective, so as to construct a route optimization model of hazmat transportation considering risk equity. Moreover, considering that the difference in regional emergency response time will significantly affect the risk, this research incorporates the emergency response time into the transportation risk assessment function, and realizes risk equity by minimizing the total compensation cost based on the difference in regional emergency response time. To solve the proposed model, a multi-objective genetic algorithm based on linear weighting is designed. The results obtained from the case study verify the necessity of considering the risk equity in the route optimization model of hazardous materials transportation and prove that the established model and algorithm can find an optimal route that meets the expectations of the government, the carrier, and the public.

Site Selection of Fire Stations in Large Cities Based on Actual Spatiotemporal Demands: A Case Study of Nanjing City

The rapid expansion of cities brings in new challenges for the urban firefighting security, while the increasing fire frequency poses serious threats to the life, property, and safety of individuals living in cities. Firefighting in cities is a challenging task, and the optimal spatial arrangement of fire stations is critical to firefighting security. However, existing researches lack any consideration of the negative effects of the spatial randomness of fire outbreaks and delayed response time due to traffic jams upon the site selection. Based on the set cover location model integrated with the spatiotemporal big data, this paper combines the fire outbreak point with the traffic situation. The presented site selection strategy manages to ensure the arrival of the firefighting task force at random simulated fire outbreak points within the required time, under the constraints of the actual city planning and traffic situation. Taking Nanjing city as an example, this paper collects multi-source big data for the comprehensive analysis, including the full data of the fire outbreak history from June 2014 to June 2018, the traffic jam data based on the Amap, and the investigation data of the firefighting facilities in Nanjing. The regularity behind fire outbreaks is analyzed, the factors related to fire risks are identified, and the risk score is calculated. The previous fire outbreak points are put through the clustering analysis, the spatial distribution probability at points in each cluster is calculated according to the clustering score, and the random fire outbreak points are generated via the Monte Carlo simulation. Meanwhile, the objective emergency response time is set as five minutes. The average vehicle speed for each road in the urban area is calculated, and the actual traffic network model is built to compute the travel time from massive randomly-distributed simulated fire points. The problem is solved by making the travel time for all simulated demand points below five minutes. At last, the site selection result based on our model is adjusted and validated, according to the planned land use. The presented method incorporates the view of the spatiotemporal big data and provides a new idea and technical method for the modification and efficiency improvement of the fire station site selection model, contributing to a service cover ratio increase from 58% to 90%.

Epidemiological characteristics of road traffic injuries accepted by Shenzhen Emergency Center from 2010 to 2018

Objective To investigate the current situation of road traffic injuries (RTI) among the population in Shenzhen from 2010 to 2018, and to provide references and suggestions for improving road traffic safety related policies and traffic injures prevention in Shenzhen. Methods Retrospective analysis was performed on the RTI data accepted by the Emergency Comprehensive Information Query Platform of Shenzhen Emergency Center from 2010 to 2018, and statistics were made on the overall situation, population characteristics, time, regional distribution and severity of RTI in Shenzhen. Results From 2010 to 2018, there were 79 369 cases of RTI in Shenzhen, and the ratio of injuries to instant deaths was 79.66∶1. The incidence of RTI in Shenzhen Emergency Center was generally decreasing (χtrend2=8.200, P=0.004), and the on-site death rate was also showed a decreasing (χtrend2=4.604, P=0.032) trend. The incidence rate of male was 478.90 per 100 000, which was higher than that of female (223.92 per 100 000, χ2=92.823, P Conclusion According to the epidemiological characters from 2010 to 2018, the key points to preventing and controlling RTI would be: improving the road traffic management system; improving the traffic safety awareness of the key crowds; strengthening the roads regulation during the rush hours; deploying the emergency resources more rationally; shorting the emergency response time; improving the first aid system and service mode; and developing scientific precautionary measures.

The Impact of 2020 Low Traffic Neighbourhoods on Fire Service Emergency Response Times, in London, UK

Between March and September 2020, 72 ‘Low Traffic Neighbourhoods’ (LTNs) were implemented in London. We examined the impact on fire brigade emergency response times in October 2020-February 2021 (‘post’), as compared to the same months in the previous two years (‘pre’). We found no evidence that response times inside the LTNs or on boundary roads were affected (e.g. pre/post change for first engine: -14 seconds inside LTNs; -11 seconds in the rest of London; p=0.4 for difference). Fire crews reported more delays due to ‘traffic calming measures’ in LTNs, but this was entirely offset by a decrease in delays for other reasons, particularly ‘traffic’. This was true both in LTNs that predominately blocked motor traffic using physical barriers (e.g. planters) and in LTNs using camera enforcement. These findings add to evidence that LTNs do not adversely affect emergency response times.

THE FACTORS RELATED TO NURSE TIME RESPONSE TO COVID 19 SUSPECT PATIENTS IN HERMINA JATINEGARA HOSPITAL IGD

The response time or emergency response time is a combination of the response time when the patient arrives at the hospital door until he gets a response from the Emergency Room staff with the service time needed to finish the 5 minute emergency handling process, this study aims to determine the factors Related to the Response Time of Nurses in Suspected Covid 19 Patients in the Emergency Room at the Hermina Jatinegara Hospital. This study used a descriptive research design with a cross-sectional approach. The population in this study were all nurses who served in the emergency room of Hermina Jatinegara Hospital, amounting to 30 people, the sample was taken using a total sampling technique with a total sample of 30 respondents. Data collection using a questionnaire. The data analysis used was univariate and bivariate analysis in the form of chi-square test. Obtained univariate analysis showed that the level of emergency patients in the Emergency Room was more dominated by yellow category emergency patients, namely as many as 13 patients (43.3%), most of the emergency room nurses had the skills of skilled category nurses, namely 19 nurses (63.3%), Generally, the workload of IGD nurses in the light category was 20 nurses (66.7%), and the emergency response time was dominated by nurses whose response time category was good for patients with suspected Covid 19, namely 21 nurses (70.0%). The results of the bivariate analysis showed that there was a relationship between the skills of nurses and the response time of nurses in suspected Covid 19 patients (p value = 0.042), there was a relationship between workload and nurse response time in patients with suspected Covid 19 (p value = 0.030), and there was a relationship between level of emergency with nurse response time in patients with suspected Covid 19 (p value = 0.028). It is hoped that students before carrying out their practice in the emergency room of the hospital can first take part in the BTCLS training so that they can be more skilled in performing emergency care so that the response time of nurses can be better

Multirotor-assisted measurements of wind-induced drift of irregularly shaped objects in aquatic environments

Ocean hazardous spills and search and rescue incidents are becoming more prevalent as maritime activities increase across all sectors of society. However, emergency response time remains a factor due to the lack of information available to accurately forecast the location of small objects. Existing drifting characterization techniques are limited to objects whose drifting properties are not affected by on-board wind and surface current sensors. To address this challenge, we study the application of multirotor small unmanned aerial systems (sUAS), and embedded navigation technology, for on-demand wind velocity and surface flow measurements to characterize drifting properties of small objects. An off-the-shelf quadrotor sUAS was used to measure the speed and direction of the wind field at 10 m above surface level near a drifting object. We also leveraged sUAS-grade attitude and heading reference systems and GPS antennas to build water-proof tracking modules that recorded the position and orientation, as well of translational and rotational velocities, of objects drifting in water. The quadrotor and water-proof tracking modules were deployed during field experiments conducted in Claytor Lake, Virginia and the Atlantic Ocean south of Martha’s Vineyard, Massachusetts to characterize the leeway parameters of manikins that simulated a person in water. Leeway parameters were found to be an order of magnitude within previous estimates that were derived using conventional wind and surface current observations. We also determined that multirotor sUAS and water-proof tracking modules can provide accurate and high-resolution ambient information that is critical to understand how changes in orientation affect the downwind displacement and jibing characteristics of small objects floating in water. These findings support further development and application of multirotor sUAS technology for leeway characterization and understanding the effect of an object’s downwind-relative orientation on its drifting characteristics.

Analisis Sejarah, Dampak, Dan Penanggulangan Bencana Gempa Bumi Pada Saat Pandemi Covid-19 Di Sulawesi Barat

[Analysis of the History, Impact and Management of Earthquake Disaster during the Covid-19 Pandemic in West Sulawesi] Geographical, demographic, sociological, meteorological and climatological conditions of Indonesia make Indonesia in a disaster-prone area (natural, non-natural, and social). This condition can be used as a laboratory to produce disaster experts, knowledge and technology in Indonesia. Law 24/2007 as a framework for disaster management systems in Indonesia currently prioritizes the disaster mitigation paradigm so that a strong commitment and participation of all parties is needed to build and run this system properly. However, currently Indonesia is faced with multiple disasters that occurred during the Covid-19 pandemic. This is supported by data on the earthquake disaster in West Sulawesi on January 15, 2021 which occurred amid the potential for the spread of Covid-19 infection. The character of the risk in this problem is how to minimize the time for evacuation, emergency response and recovery of community conditions without neglecting the potential for transmission of Covid-19 infection. This study uses a descriptive quantitative approach with secondary data in the form of BNPB volunteer desks, BNPB current situation reports and population data and civil records. The data analysis technique uses quantitative methods through univariate analysis. The results showed that the history of disaster recorded that in West Sulawesi, there had been an M ? 6 RS earthquake in 1820, 1976, 1969, 1984 and 2021. The earthquake of January 15, 2021 occurred at 01.28.17 WIB with a magnitude of M 6.2 RS at depth of 10 km with the location: 2.98 LS, 118.94 BT (6 km northeast of Majene). The potential affected population in Majene Regency is 59,543 people, Mamasa Regency 62,007 people, Mamuju Regency 144,377 people, Polewali Mandar Regency 219,305 people. Quick response was shown by Indonesia through the Presidents direction to BNPB, Ministry of Social Affairs, Basarnas, TNI and Kapolri and their staff to take emergency response steps as soon as possible through Emergency Response Status No.001 / Darurat-SB / I / 2021 which is valid for 14 days (15-28 January 2021). The seventh main sectors in the emergency response are search and rescue, logistics or soup kitchens, shelters, mapping, clean water, sanitation and hygiene, communication and health.

ESPC_NASUnet: An End-to-End Super-Resolution Semantic Segmentation Network for Mapping Buildings From Remote Sensing Images

Higher resolution building mapping from lower resolution remote sensing images is in great demand due to the lack of higher resolution data access, especially in the context of disaster assessment. High resolution building layout map is crucial for emergency rescue after the disaster. The emergency response time would be reduced if detailed building footprints were delineated from more easily available low-resolution data. To achieve this goal, we propose a super-resolution semantic segmentation network called ESPC_NASUnet, which consists of a feature super-resolution module and a semantic segmentation module. To the best of authors’ knowledge, this is the first work to systematically explore a deep learning-based approach to generate semantic maps with higher spatial resolution from lower spatial resolution remote sensing images in an end-to-end fashion. The experimental results for two datasets suggest that the proposed network is the best among four different end-to-end architectures in terms of both pixel-level metrics and object-level metrics. In terms of pixel-level $F$ 1-score, the improvements are greater than 0.068 and 0.055. Regarding the object-level $F$ 1-score, the disparities between ESPC_NASUnet and other end-to-end methods are more than 0.083 and 0.161 in the two datasets, respectively. Compared with stage-wise methods, our end-to-end network is less impacted by low-resolution input images. Finally, the proposed network produces building semantic maps comparable to those generated by semantic segmentation networks trained with high-resolution images and the ground truth utilizing the two datasets.

Design and development of feasibility analysis software for live working

The work load of the traditional calculation method of safety distance check and circuit mechanics calculation is huge inefficiency, this paper presents a set of software of safety analysis and mechanics calculation for live working, the electrical and mechanical parameters of live working transmission lines are obtained, the feasibility of operation is analyzed, working tools are reasonably selected to improve the safety and efficiency of live working, it is of great significance to reduce the emergency response time, the electric safety distance check and the line mechanics calculation methods.

The importance of general practitioners in emergency and pre-hospital first aid

The purpose of this study is to determine the critical role and managerial impact of general practitioners in pre-hospital first aid and emergency work. The study subjects were 100 emergency patients treated in a hospital between May 2020 and November 2021. They were randomly assigned to an observation group and a control group, each having 50 cases. The control group followed a standard management protocol, but the observation group included emergency care. Management, compare the management effectiveness of the two patient groups. The observation group's arrival and rescue times were much shorter than those in the control group. Patient satisfaction was much greater in the observation group than in the control group. Conclusion: General practitioners have a broader range of medical expertise and are better equipped to give complete medical care to their patients. Emergency management can enhance general practitioners' productivity, further reduce emergency response time, prioritize patient treatment time, and raise the success rate of rescue. Additionally, patient satisfaction.

Improving fire department turnout times: training versus sanctions in a high public service motivation environment

Fire departments are comprised of individuals known to have high levels of public service motivation (PSM). One of the most important measures of fire personnel performance, turnout time, may be affected by managerial strategies. Turnout time measures the time elapsed from when the emergency dispatcher informs the fire unit of an emergency and when the unit leaves the fire station. In 2015, the El Paso Fire Department required fire personnel to participate in a training module focusing on the importance of emergency response and turnout time. At the conclusion of the training period, the department began enforcing a turnout time policy of 90 s, with units being required to submit paperwork concerning their response if they exceeded the 90 s requirement. We find that training and policy enforcement decrease turnout times in these high PSM employees, but policy enforcement with sanctions yields the largest decrease.

The Impact of Introducing a Low Traffic Neighbourhood on Fire Service Emergency Response Times, in Waltham Forest London

There is sometimes concern that low traffic neighbourhoods slow emergency vehicles. We test this using London Fire Brigade data (2012-2020) in Waltham Forest, where from 2015 low traffic neighbourhoods have been implemented. We find no evidence that response times were affected inside low traffic neighbourhoods, and some evidence that they improved slightly on boundary roads. However, while the proportion of delays was unchanged, the reasons given for delays initially showed some shift from ‘no specific delay cause identified’ to ‘traffic calming measures’. Our findings indicate that low traffic neighbourhoods do not adversely affect emergency response times, although while LTNs are novel this perception may exist among some crews.

Automatic collision notification availability and emergency response times following vehicle collision—an analysis of the 2017 crash investigation sampling system

Objective To determine whether occupants of collisions involving at least one vehicle with an available Automatic Collision Notification (ACN) system have quicker times from collision to 1) Emergency Medical Services (EMS) notification and 2) arrival to a medical center. Methods Using data from the 2017 Crash Investigation Sampling System, vehicles were categorized as whether ACN was available using data from the CISS's dataset of crash avoidance system availability (in which ACN is included though notably not a crash avoidance system). A Cox proportional hazards model—overall and stratified by urbanization—was used to compare the time from collision to both EMS notification and EMS arrival to a medical center. Results A total of 2,034 collisions (weight n: 2,775,512) involving 4235 occupants (weighted n: 4,987,669) were included. An estimated 259,021 (9.3%) and 546,223 occupants (11.0%) were in a collision in which one vehicle had ACN equipped. The median time to EMS notification was longer for collisions in which no involved vehicles had ACN available (median 4, IQR 2-9 minutes) than ACN-exposed collisions (median 2, IQR 1-5 minutes). There was a marginally significant higher hazard (i.e., instantaneous risk) of EMS notification for collisions with at least one vehicle having ACN available (HR 1.77, 95% CI 0.99-3.15). Likewise, there was a higher instantaneous risk of medical center arrival for occupants (HR 1.80, 95% CI 1.41-2.30) involved in collisions in which at least one vehicle had ACN available. ACN was associated with quicker EMS notification only in urban areas (HR 3.06, 95% CI 1.57-5.97) and associated with a greater reduction in time to medical facility in less urban areas (median 36 vs 45 minutes, HR 2.12, 95% CI 1.22-3.63). Conclusions This is the first study to directly compare EMS response-related times between collisions involving vehicles with and without ACN available. The current data corroborate prior literature reporting quicker EMS notification times among collisions involving ACN-equipped vehicles. This is the first study to find that ACN is also associated to quicker times to medical center arrival, particularly for collisions occurring in less urban areas. Future research examining whether these decreased times are associated with better clinical outcomes are needed in order to fully assess ACN's ability to prevent trauma-related mortality and morbidity.

Does driving using a Green Beacon reduce emergency response times in a rural setting?

Green Beacons are used by many doctors across the UK when responding to emergencies, particularly in rural areas. These are used to alert other road users to the doctor's urgent need to reach a destination, with the hope that members of the public will make provisions for the doctor to make progress unhindered. While such warning lights have been used for many years, there is a paucity of research into the safety and efficacy of their use. This pilot study aimed to explore whether the use of Green Beacons does lead to reduced response times in rural areas of Scotland, and recorded any accidents occurring during such emergency response journeys. A repeated measures design was devised to investigate this question. The response times and distances travelled for 10 consecutive emergency journeys undertaken by a rural primary care and prehospital doctor during the winter of 2019 using Green Beacons were recorded. The same journeys were then repeated, at a later date by the same driver, under normal driving conditions, with no Green Beacon use. Travel times were compared for both journey types. Travel times were on average 4 minutes shorter when responding using Green Beacons (range 0-13 minutes), with statistically significantly faster average speeds during the emergency response journeys. There was a trend towards higher average speed with longer journeys. No accidents occurred during either type of journey. The use of Green Beacons when responding to emergencies in rural Scotland appears to reduce journey times and appears safe in this exploratory work. This is in keeping with other researchers' work into the use of blue and red emergency vehicle lighting, and does not dissuade from continuation of current practice among doctors in the UK. Further research in this area would benefit from a larger dataset, and quantitative time-motion data from the vehicles involved.

Site Selection for Pre-Hospital Emergency Stations Based on the Actual Spatiotemporal Demand: A Case Study of Nanjing City, China

Rapid economic and social development has been accompanied by the occurrence of many major issues throughout the world. Specifically, there is an ever-increasing demand for emergent medical services among the public. In order to ensure timely responses to emergency demands, it is critical to reasonably configure the emergency stations. In general, emergency stations are mostly distributed according to the distribution of emergency demands and response time, which, however, fails to consider the negative impacts of randomly occurring emergency demands and traffic delays. In this study, first aid demands are combined with traffic states based on the spatiotemporal big data set covering model, which alleviates the negative impacts of randomly occurring first aid demands and traffic delay time on the planning of pre-hospital first aid stations. Moreover, the accuracy of the site selection model is improved, which meets the requirements that all randomly occurring simulated first aid demands can be approached within the target time under planning conditions and actual traffic constraints. Taking Nanjing City as an example, this study obtains multi-source big data, such as ambulance-carried GPS data from June 2018 to June 2019, Gaode Map-recorded traffic congestion data, and survey data of emergency rescue facilities. Basing on the processing and analysis of these data, it shows that first aid demands in Nanjing City are highly region-specific with high time delay. Various required factors are determined based on modeling and analysis, and the target time is agreed to be 8 min. The average vehicle speed on each road is calculated, accompanied by the establishment of an actual road network model. In this context, the transit time from the randomly distributed first aid stations to the hospital can be calculated, which are set to satisfy the model conditions so as to obtain the solution. Finally, such a solution is adjusted and verified according to the land-use situation. The results of this study, based on spatiotemporal big data, are expected to provide insights into improving the site selection model and enhancing efficiency while providing new technical methods.

A Smart Priority-Based Traffic Control System for Emergency Vehicles

Unwanted events on roads, such as incidents and increased traffic jams, can cause human lives and economic loss. For efficient incident management, it is essential to send Emergency Vehicles (EVs) to the incident place as quickly as possible. To reduce incidence clearance time, several approaches exist to provide a clear pathway to EVs mainly fitted with RFID sensors in the urban areas. However, they neither assign priority to the EVs based on the type and severity of an incident nor consider the effect on other on-road traffic. To address this issue, in this paper, we introduce an Emergency Vehicle Priority System (EVPS) by determining the priority level of an EV based on the type and the severity of an incident, and estimating the number of necessary signal interventions while considering the impact of those interventions on the traffic in the roads surrounding the EV's travel path. We present how EVPS determines the priority code and a new algorithm to estimate the number of green signal interventions to attain the quickest incident response while concomitantly reducing impact on others. A simulation model is developed in Simulation of Urban Mobility (SUMO) using the real traffic data of Melbourne, Australia, captured by various sensors. Results show that our system recommends appropriate number of intervention that can reduce emergency response time significantly.

Current status analysis of bystander cardiopulmonary resuscitation for out-of-hospital cardiac arrest in Qinhuangdao region based on Utstein model

To analyze the status quo of bystander cardiopulmonary resuscitation (BCPR) for out-of-hospital cardiac arrest (OHCA) in Qinhuangdao area and its influence on the prognosis of cardiopulmonary resuscitation (CPR). Based on the Utstein model CPR database of Qinhuangdao, data of 1 162 OHCA patients admitted to the Health Emergency Dispatch Center of Qinhuangdao City from January 2018 to January 2019 were collected, and they were divided into two groups according to whether BCPR was performed or not. The patients' demographic parameters (gender, age), precardiac arrest parameters (location of cardiac arrest), the parameters of the CPR (first aid response time before hospital, initial diagnosis of causes of cardiac arrest, initial cardiac rhythm) and the parameters of the CPR results [whether to achieve on-site restoration of spontaneous circulation (ROSC) and 30-day survival rate] were collected. Multivariate Logistic regression analysis was performed for the relationship between BCPR and on-site ROSC rate. The social characteristics of bystanders implementing BCPR, including gender, age, occupation, educational background, and acquisition method of CPR knowledge, were analyzed. Among the 1 162 OHCA patients, the patients witnessed by professional medical personnel in nursing homes, hospitals and other places and pre-hospital emergency personnel were excluded. 852 OHCA patients were enrolled, among which only 24 patients obtained BCPR (2.8%), and the remaining 828 patients did not obtain BCPR (97.2%). There were no statistically significant differences in gender, age, location of cardiac arrest, pre-hospital emergency response time, primary diagnosis of cardiac arrest causes and initial cardiac rhythm between the two groups. Compared with the non-BCPR group, the on-site ROSC rate and the 30-day survival rate of the BCPR group were significantly increased [on-site ROSC rate: 16.7% (4/24) vs. 5.2% (43/828), 30-day survival rate: 8.3% (2/24) vs. 1.3% (11/828), both P < 0.05]. Multivariate Logistic regression analysis showed that BCPR [odds ratio (OR) = 32.132, 95% confidence interval (95%CI) was 11.129-65.471], location of cardiac arrest (OR = 0.080, 95%CI was 1.212-3.125) and response time during pre-hospital emergency treatment (OR = 0.121, 95%CI was 0.174-0.816) were important factors for on-site ROSC of OHCA patients (all P < 0.01). A total of 30 bystanders participated in the implementation of OHCA patients' BCPR, excluding 2 bystanders of lost follow-up, 28 bystanders with effective return visit. The 28 bystanders of BCPR practitioners were mainly male (85.7%), the age was mainly 18-40 years old (57.1%), the occupation was mainly in the tourism service industry (21.5%), students (17.9%), soldiers (14.3%) and bus drivers (10.7%), and the education background was mainly junior college or above (85.7%), the methods of acquiring CPR knowledge mainly included APP and new media (42.9%) and lectures (21.4%). The BCPR implementation rate of OHCA in Qinhuangdao was only 2.8%. BCPR can improve the success rate of pre-hospital CPR and the 30-day survival rate of OHCA patients. Targeted selection of tourism service industry, students, military personnel and bus drivers as CPR training targets may obtain more significant social benefits.

Post-Earthquake Emergency Response Time to Locations of Fire Ignition

ABSTRACT This paper investigates fire department response time to locations of ignition after an earthquake and proposes a framework to identify vulnerable areas in a community by considering both the likelihood of ignition and potential delays in response of the fire department. Delays are calculated as a function of bridge damage and blocked roadways due to building debris. Uncertainty in bridge performance and debris accumulation are incorporated into the analysis. The framework is applied to a case study to demonstrate how the proposed work can be used to plan fire department resources, and minimize losses from postearthquake fires.

The effect of small versus large clog size on emergency response time: A randomized controlled trial.

To assess the effect on healthcare professional emergency response time and safety of small compared to large clog size. Randomized controlled trial. The intensive care unit of a single university medical centre in The Netherlands. Intensive care medicine professionals. Participants were randomized to wear European size 38 clogs (US male size 6½, US female size 7½) or European size 47 clogs (US male size 13½, US female size 14½) clogs and were required to run a 125m course from the coffee break room to the elevator providing access to the emergency department. The primary outcome was the time to complete the running course. Height, shoe size, self-described fitness, age and staff category were investigated as possible effect modifiers. Secondary endpoints were reported clog comfort and suspected unexpected clog-related adverse events (SUCRAEs). 50 participants were randomized (25 to European size 38 clogs and 25 to size 47 clogs). Mean age was 37years (SD 12) and 29 participants (58%) were female. The primary outcome was 4.4s (95% CI -7.1; -1.6) faster in the size 5 clogs group compared to the size 12 clogs group. This effect was not modified by any of the predefined participant characteristics. No differences were found in reported clog comfort or SUCRAEs. European size 38 clogs lead to faster emergency response times than size 47 clogs. NCT04406220.