A study on deep learning model based on global-local structure for crowd flow prediction.

Crowd flow prediction has been studied for a variety of purposes, ranging from the private sector such as location selection of stores according to the characteristics of commercial districts and customer-tailored marketing to the public sector for social infrastructure design such as transportation networks. Its importance is even greater in light of the spread of contagious diseases such as COVID-19. In many cases, crowd flow can be divided into subgroups by common characteristics such as gender, age, location type, etc. If we use such hierarchical structure of the data effectively, we can improve prediction accuracy of crowd flow for subgroups. But the existing prediction models do not consider such hierarchical structure of the data. In this study, we propose a deep learning model based on global-local structure of the crowd flow data, which utilizes the overall(global) and subdivided by the types of sites(local) crowd flow data simultaneously to predict the crowd flow of each subgroup. The experiment result shows that the proposed model improves the prediction accuracy of each sub-divided subgroup by 5.2% (Table 5 Cat #9)-45.95% (Table 11 Cat #5), depending on the data set. This result comes from the comparison with the related works under the same condition that use target category data to predict each subgroup. In addition, when we refine the global data composition by considering the correlation between subgroups and excluding low correlated subgroups, the prediction accuracy is further improved by 5.6-48.65%.

Health mediation does not reduce the readmission rate of frequent users of emergency departments living in precarious conditions: what lessons can be learned from this randomised controlled trial?

BACKGROUND: Severe overcrowding of emergency departments (EDs) affects the quality of healthcare. One factor of overcrowding is precariousness, but it has rarely been considered a key factor in designing interventions to improve ED care. Health mediation (HM) aims to facilitate access to rights, prevention, and care for the most vulnerable persons and to raise awareness among healthcare providers about obstacles in accessing healthcare. The primary aim was to determine whether HM intervention for frequent users of EDs (FUED) living in precarious conditions could reduce the readmission rate at 90 days. METHODS: Between February 2019 and May 2022, we enrolled and interviewed 726 FUED in four EDs of southeastern France in this randomised controlled trial. The HM intervention started in the ED and lasted 90 days. In addition to the primary endpoint (first readmission at 90 days), secondary endpoints (readmission at 30 and 180 days, number of hospitalisations at 30, 90, 180 days, admissions for the same reasons as the first admission) were also studied. The outcomes were measured in the ED information systems. Statistical methods included an intention-to-treat analysis and a per-protocol analysis. Comparisons were adjusted for gender, age, ED, and health mediator. RESULTS: 46% of patients reported attending the ED because they felt their life was in danger, and 42% had been referred to the ED by the emergency medical dispatch centre or their GP; 40% of patients were considered to be in a serious condition by ED physicians. The proportion of patients who were readmitted at 90 days was high but did not differ between the control and the HM intervention groups (31.7% vs. 36.3%, p = 0.23). There was no significant difference in any of the secondary outcome measures between the control and HM intervention groups. Per-protocol analysis also showed no significant difference for the primary and secondary endpoints. CONCLUSIONS: This randomised controlled trial did not show that our health mediation intervention was effective in reducing the use of emergency services by FUED living in precarious conditions. Some limitations are discussed: the duration of the intervention (90 days), the long-term effects (> 6 months), the involvement of the ED staff. TRIAL REGISTRATION: Registered on clinicaltrials.gov as NCT03660215 on 4th September 2018.

Safety-in-Numbers for route choice of bicycle trips: A choice experiment approach for commuters.

Safety-in-Numbers (SiN) implies that the risk of collision per road user is less when there are more road users. Although the available literature has confirmed the existence of SiN as an objective measure of safety, the effect on perceived safety, especially in the context of bicycle riders, has received much less attention. This study investigates the SiN effect on the perceived safety of bicycle riders that influences route choice behavior. A stated preference survey was performed in the South Delhi district of Delhi. The effect of attributes like posted speed limit, the volume of motorized traffic, bicycle infrastructure, and bicycle traffic/ crowding on route choice behavior was investigated. A binary logit model was developed to quantify the effect of these attributes on route choice. The results indicate that, in general, riders prefer routes with more bicycle traffic, hence validating SiN. But the effect does not always hold. For some riders, in the presence of dedicated bicycle infrastructure, when the perceived safety is higher, the presence of more bicycle traffic acts as crowding and demotivates riders to choose that route. The study also reveals that riders prefer routes with a low volume of motorized traffic and dedicated bicycle infrastructure. The outcomes suggest that a policy that encourages infrastructural development to provide lateral separation will encourage more people, hence increasing bicycle mode share as well as the perceived safety of riders.

Robust spatial self-organization in crowds of asynchronous pedestrians.

Human crowds display various self-organized collective behaviours, such as the spontaneous formation of unidirectional lanes in bidirectional pedestrian flows. In addition, parts of pedestrians' footsteps are known to be spontaneously synchronized in one-dimensional, single-file crowds. However, footstep synchronization in crowds with more freedom of movement remains unclear. We conducted experiments on bidirectional pedestrian flows (24 pedestrians in each group) and examined the relationship between collective footsteps and self-organized lane formation. Unlike in previous studies, pedestrians did not spontaneously synchronize their footsteps unless following external auditory cues. Moreover, footstep synchronization generated by external cues disturbed the flexibility of pedestrians' lateral movements and increased the structural instability of spatial organization. These results imply that, without external cues, pedestrians marching out of step with each other can efficiently self-organize into robust structures. Understanding how asynchronous individuals contribute to ordered collective behaviour might bring innovative perspectives to research fields concerned with self-organizing systems.

Glastonbury Festival: Medical Care at the World's Largest Greenfield Music Festival.

INTRODUCTION: Music festivals have become an increasingly popular form of mass-gathering event, drawing an increasing number of attendees across the world each year. While festivals exist to provide guests with an enjoyable experience, there have been instances of serious illness, injury, and in some cases death. Large crowds, prolonged exposure to loud music, and high rates of drug and alcohol consumption can pose a dangerous environment for guests as well as those looking after them. METHODS: A retrospective review of electronic patient records (EPRs) at the 2022 Glastonbury Festival was undertaken. All patients who attended medical services on-site during the festival and immediately after were included. Patient demographics, diagnosis, treatment received, and discharge destination were obtained and analyzed. RESULTS: A total of 2,828 patients received on-site medical care. The patient presentation rate (PPR) was 13.47 and the transport-to-hospital rate (TTHR) was 0.30 per 1,000 guests. The most common diagnoses were joint injuries, gastrointestinal conditions, and blisters. Only 164 patients (5.48%) were diagnosed as being intoxicated. Overall, 552 patients (19.52%) were prescribed a medication to take away and 268 (9.48%) had a dressing for a minor wound. One patient (0.04%) underwent a general anesthetic and no patients required cardiopulmonary resuscitation. Most patients were discharged back to the festival site (2,563; 90.66%). DISCUSSION: Minor conditions were responsible for many presentations and most patients only required mild or non-invasive interventions, after which they could be safely discharged back to the festival. Older adults were diagnosed with a different frequency of conditions compared to the overall study population, something not reported previously. Intoxicated patients only accounted for a very small amount of the medical workload.

Diagnosing an overcrowded emergency department from its Electronic Health Records.

Emergency department overcrowding is a complex problem that persists globally. Data of visits constitute an opportunity to understand its dynamics. However, the gap between the collected information and the real-life clinical processes, and the lack of a whole-system perspective, still constitute a relevant limitation. An analytical pipeline was developed to analyse one-year of production data following the patients that came from the ED (n = 49,938) at Uppsala University Hospital (Uppsala, Sweden) by involving clinical experts in all the steps of the analysis. The key internal issues to the ED were the high volume of generic or non-specific diagnoses from non-urgent visits, and the delayed decision regarding hospital admission caused by several imaging assessments and lack of hospital beds. Furthermore, the external pressure of high frequent re-visits of geriatric, psychiatric, and patients with unspecified diagnoses dramatically contributed to the overcrowding. Our work demonstrates that through analysis of production data of the ED patient flow and participation of clinical experts in the pipeline, it was possible to identify systemic issues and directions for solutions. A critical factor was to take a whole systems perspective, as it opened the scope to the boundary effects of inflow and outflow in the whole healthcare system.

The behavioural costs of overcrowding for gregarious cave-dwelling bats.

Bats are known for their gregarious social behaviour, often congregating in caves and underground habitats, where they play a pivotal role in providing various ecosystem services. Studying bat behaviour remains an underexplored aspect of bat ecology and conservation despite its ecological importance. We explored the costs and impacts of overcrowding on bat social behaviour. This study examined variations in bat behavioural patterns between two distinct groups, aggregated and non-aggregated male Rousettus amplexicaudatus, within the Monfort Bat Cave Sanctuary on Mindanao Island, Philippines. We found significant variations in the incident frequencies of various bat behavioural activities, particularly aggression and movement, between these two groups. The increase in aggregation was closely related to negative social behaviour among bats. In contrast, sexual behaviour was significantly related to the positive behaviour of individual bats and was headed in less crowded areas. The disparities in bat behaviour with an apparent decline in bat social behaviour because of overcrowding, with more aggressive behaviours emerging, align with the 'behavioural sink' hypothesis. Our study underscores the importance of considering habitat quality and resource availability in the management and conservation of bat colonies, as these factors can reduce the occurrence of aggressive and negative social behaviours in colonies with high population density by providing alternative habitats.

Quantitative Metrics in Mass-Gathering Studies: A Comprehensive Systematic Review.

INTRODUCTION: Mass gatherings are events where many people come together at a specific location for a specific purpose, such as concerts, sports events, or religious gatherings, within a certain period of time. In mass-gathering studies, many rates and ratios are used to assess the demand for medical resources. Understanding such metrics is crucial for effective planning and intervention efforts. Therefore, this systematic review aims to investigate the usage of rates and ratios reported in mass-gathering studies. METHODS: In this systematic review, the PRISMA guidelines were followed. Articles published through December 2023 were searched on Web of Science, Scopus, Cochrane, and PubMed using the specified keywords. Subsequently, articles were screened based on titles, abstracts, and full texts to determine their eligibility for inclusion in the study. Finally, the articles that were related to the study's aim were evaluated. RESULTS: Out of 745 articles screened, 55 were deemed relevant for inclusion in the study. These included 45 original research articles, three special reports, three case presentations, two brief reports, one short paper, and one field report. A total of 15 metrics were identified, which were subsequently classified into three categories: assessment of population density, assessment of in-event health services, and assessment of out-of-event health services. CONCLUSION: The findings of this study revealed notable inconsistencies in the reporting of rates and ratios in mass-gathering studies. To address these inconsistencies and to standardize the information reported in mass-gathering studies, a Metrics and Essential Ratios for Gathering Events (MERGE) table was proposed. Future research should promote consistency in terminology and adopt standardized methods for presenting rates and ratios. This would not only enhance comparability but would also contribute to a more nuanced understanding of the dynamics associated with mass gatherings.

Free-for-all: Does crowding impact outcomes because hospital emergency departments do not prioritise effectively?

Unexpected peaks in volumes of attendances at hospital emergency departments (EDs) have been found to affect waiting times, intensity of care and outcomes. We ask whether these effects of ED crowding on patients are caused by poor clinical prioritisation or a quality-quantity trade-off generated by a binding capacity constraint. We study the effects of crowding created by lower-severity patients on the outcomes of approximately 13 million higher-severity patients attending the 140 public EDs in England between April 2016 and March 2017. Our identification approach relies on high-dimensional fixed effects to account for planned capacity. Unexpected demand from low-severity patients has very limited effects on the care provided to higher-severity patients throughout their entire pathway in ED. Detrimental effects of crowding caused by low-severity patients materialise only at very high levels of unexpected demand, suggesting that binding resource constraints impact patient care only when demand greatly exceeds the ED's expectations. These effects are smaller than those caused by crowding induced by higher-severity patients, suggesting an efficient prioritisation of incoming patients in EDs.

Crowding under scotopic and photopic vision in albino and normal-sighted participants.

Crowding is a phenomenon in which the ability to recognize an object in a clutter deteriorates. It is, therefore, a fundamental aspect of object recognition and crucial in deciphering resolution. For visually impaired individuals, deficiency in crowding has a tremendous effect on vision and may reflect and predict the amount of deterioration in vision. It is well established that albinos suffer much more from crowding than normally sighted individuals under daylight luminance conditions. However, to our knowledge, this study is the first to investigate crowding in albino participants under low light conditions. In this study, we explored the crowding effect in a group of albino participants (n = 9) and a control group of normally sighted participants (n = 9). Crowding was conducted under daylight (photopic vision) and low light (scotopic vision). We measured the visual acuity threshold under crowding in three-letter spacing (0.5, 1, and 1.5) and compared it to a single target. Results indicate that albino participants experienced stronger crowding than the control under the photopic condition, while crowding under the scotopic condition was apparent in the albino but abolished for the control group. These findings highlight the importance of considering luminance when discussing the visually impaired population in general. In particular, it suggests that crowding in albinism is based on a peripheral-like mechanism and may indicate a cessation in visual development.

Early warning on safety risk of highly aggregated tourist crowds based on VGGT-Count network model.

In the era of mass tourism, more and more people are attracted by internet-famous site. With people's demand for travel surged, tourists are getting together in one scenic spot with doubling numbers, which easily leads to high concentration of tourists with uncontrollable security risks. It needs to be highly valued by the tourism department. Monitoring and issuing warnings for crowd density in scenic areas with Highly Aggregated Tourist Crowds (HATCs) is an urgent challenge that needs to be addressed. In this paper, Highly Aggregated Tourist Crowds is taken as the research objective, and a VGGT-Count network model is proposed to forecast the density of HATCs. The experimental outcomes demonstrated a substantial improvement in counting accuracy for the ShanghaiTech B and UCF-QNRF datasets. Furthermore, the model allows for real-time monitoring of tourist attractions, enabling advanced prediction of high concentrations in scenic areas. This timely information can alert relevant authorities to implement preventive measures such as crowd control and flow regulation, thereby minimizing safety hazards.

Interorganizational Knowledge Transfer in Mass Gatherings: Exploring the Health and Safety Stakeholders' Perceptions Participating in the Athens Marathon.

INTRODUCTION: Mass gatherings (MGs) usually represent significant challenges for the public health and safety sector of the host cities. Organizing a safe and successful mass event highly depends on the effective collaboration among different public and private organizations. It is necessary to establish successful coordination to ensure that all the key stakeholders understand their respective roles and responsibilities. The inconsistency between the variety of participating agencies because of their different culture can result in delays in decision making. Interorganizational knowledge transfer can improve the success of the event; however, knowledge transfer among professionals and agencies in MGs is not well-documented. OBJECTIVE: This study used the 2018 Athens Marathon as the empirical setting to examine how interorganizational knowledge transfer was perceived among the multiple public health and safety professionals during the planning stage of the event. METHODS: Data comprised 18 semi-structured, in-depth interviews with key informants, direct observations of meetings, and documentary analysis. Open coding and thematic analysis were used to analyze the data. RESULTS: Findings indicated that sharing the acquired knowledge was a necessary and challenging step to create an enabling collaborative environment among interacting organizations. Experiential learning was identified as a significant factor, which helped promote joint understanding and partnership work. Informal interpersonal exchanges and formal knowledge transfer activities facilitated knowledge sharing across organizational boundaries, helping to break down silos. CONCLUSION: Interorganizational knowledge transfer is a necessary step to achieve joint understanding and create an environment where interaction among agencies can be more effective. The study findings can be beneficial for organizers of marathons and other mass sporting events to support valuable interorganizational collaboration and conduct a safe event.

The nature of anchor-biased estimates and its application to the wisdom of crowds.

We propose a method to achieve better wisdom of crowds by utilizing anchoring effects. In this method, people are first asked to make a comparative judgment such as "Is the number of new COVID-19 infections one month later more or less than 10 (or 200,000)?" As in this example, two sufficiently different anchors (e.g., "10" or "200,000") are set in the comparative judgment. After this comparative judgment, people are asked to make their own estimates. These estimates are then aggregated. We hypothesized that the aggregated estimates using this method would be more accurate than those without anchor presentation. To examine the effectiveness of the proposed method, we conducted three studies: a computer simulation and two behavioral experiments (numerical estimation of perceptual stimuli and estimation of new COVID-19 infections by physicians). Through computer simulations, we could identify situations in which the proposed method is effective. Although the proposed method is not always effective (e.g., when a group can make fairly accurate estimations), on average, the proposed method is more likely to achieve better wisdom of crowds. In particular, when a group cannot make accurate estimations (i.e., shows biases such as overestimation or underestimation), the proposed method can achieve better wisdom of crowds. The results of the behavioral experiments were consistent with the computer simulation findings. The proposed method achieved better wisdom of crowds. We discuss new insights into anchoring effects and methods for inducing diverse opinions from group members.

Boarding in the emergency department: challenges and mitigation strategies.

PURPOSE OF REVIEW: Herein, we conducted a review of the literature to better understand the issue of prolonged emergency department (ED) boarding by providing an overview of the current evidence on the available causes, consequences, and mitigation strategies. RECENT FINDINGS: Severely ill patients awaiting transfer to intensive care units (ICU) imposes additional burdens on the emergency care team from both a clinical and management perspective. The reasons for prolonged ED boarding are multifactorial. ED boarding compromises patients' safety and outcomes, and is associated with increased team burnout and dissatisfaction. Mitigation strategies include the optimization of patients' flow, the establishment of resuscitative care units, deployment of mobile critical care teams, and improvements in training. Staffing adjustments, changes in hospital operations, and quality improvement initiatives are required to improve this situation, while active bed management and implementation of capacity command centers may also help. SUMMARY: Considering the characteristics of healthcare systems, such as funding mechanisms, organizational structures, delivery models, access and quality of care, the challenge of ED boarding of critically ill patients requires a nuanced and adaptable approach. Solutions are complex but must involve the entirety of the hospital system, emergency department, staff adjustment, and education.

An Effective Methodology for Scoring to Assist Emergency Physicians in Identifying Overcrowding in an Academic Emergency Department in Thailand.

BACKGROUND: Emergency Department (ED) overcrowding is a global concern, with tools like NEDOCS, READI, and Work Score used as predictors. These tools aid healthcare professionals in identifying overcrowding and preventing negative patient outcomes. However, there's no agreed-upon method to define ED overcrowding. Most studies on this topic are U.S.-based, limiting their applicability in EDs without waiting rooms or ambulance diversion roles. Additionally, the intricate calculations required for these scores, with multiple variables, make them impractical for use in developing nations. OBJECTIVE: This study sought to examine the relationship between prevalent ED overcrowding scores such as EDWIN, occupancy rate, and Work Score, and a modified version of EDWIN newly introduced by the authors, in comparison to the real-time perspectives of emergency physicians. Additionally, the study explored the links between these overcrowding scores and adverse events related to ED code activations as secondary outcomes. METHOD: The method described in the provided text is a correlational study. The study aims to examine the relationship between various Emergency Department (ED) overcrowding scores and the real-time perceptions of emergency physicians in every two-hour period. Additionally, it seeks to explore the associations between these scores and adverse events related to ED code activations. RESULTS: The study analyzed 459 periods, with 5.2% having Likert scores of 5-6. EDOR had the highest correlation coefficient (0.69, p < 0.001) and an AUC of 0.864. Only EDOR significantly correlated with adverse events (p = 0.033). CONCLUSION: EDOR shows the most robust link with 'emergency physicians' views on overcrowding. Additionally, elevated EDOR scores correlate with a rise in adverse events. Emergency physicians' perceptionof overcrowding could hint at possible adverse events. Notably, all overcrowding scores have high negative predictive values, efficiently negating the likelihood of adverse incidents.

The 4 S's of Disaster Management Framework: A Case Study of the 2022 Pediatric Tripledemic Response in a Community Hospital.

Most children in the United States present to community hospitals for emergency department (ED) care. Those who are acutely ill and require critical care are stabilized and transferred to a tertiary pediatric hospital with intensive care capabilities. During the fall of 2022 "tripledemic," with a marked increase in viral burden, there was a nationwide surge in pediatric ED patient volume. This caused ED crowding and decreased availability of pediatric hospital intensive care beds across the United States. As a result, there was an inability to transfer patients who were critically ill out, and the need for prolonged management increased at the community hospital level. We describe the experience of a Massachusetts community ED during this surge, including the large influx in pediatric patients, the increase in those requiring critical care, and the total number of critical care hours as compared with the same time period (September to December) in 2021. To combat these challenges, the pediatric ED leadership applied a disaster management framework based on the 4 S's of space, staff, stuff, and structure. We worked collaboratively with general emergency medicine leadership, nursing, respiratory therapy, pharmacy, local clinicians, our regional health care coalition, and emergency medical services (EMS) to create and implement the pediatric surge strategy. Here, we present the disaster framework strategy, the interventions employed, and the barriers and facilitators for implementation in our community hospital setting, which could be applied to other community hospital facing similar challenges.

Data-driven mathematical simulation analysis of emergency evacuation time in smart station's operations management.

This research establishes an emergency evacuation time model specifically designed for subway stations with complex structures. The model takes into account multiple factors, including passenger flow rate, subway facility parameters, and crowd density, to accurately assess evacuation times. It considers the impact of horizontal walking distance, flow rate, subway train size, and stair parameters on the overall evacuation process. By identifying bottleneck points such as gates, car doors, and stairs, the model facilitates the evaluation of evacuation capacity and the formulation of effective evacuation plans, particularly in multiline subway transfer stations. The good consistency is achieved between the calculated evacuation time and simulated results using the Pathfinder software (with the relative error of 5.4%). To address urban traffic congestion and enhance subway station safety, the study recommends implemented measures for emergency diversion and passenger flow control. Additionally, the research presents characteristic mathematical models for various evacuation routes by considering the structural and temporal characteristics of metro systems. These models provide valuable guidance for conducting large-scale passenger evacuation simulations in complex environments. Future research can further enhance the model by incorporating psychological factors, evacuation signage, and strategies for vulnerable populations. Overall, this study contributes to a better understanding of evacuation dynamics and provides practical insights to improve safety and efficiency in subway systems.