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Emergency Department (ED) crowding is defined as a situation wherein the demands of emergency services overcome the ability of a department to provide high-quality care within an appropriate time frame. There is a need for solutions, as the harms of crowding impact patients, staff, and healthcare spending. An overview of ED crowding was previously published by our group, which outlines these global issues. The problem of overcrowding in emergency departments has emerged as a global public health concern, and several healthcare agencies have addressed the issue and proposed possible solutions at each level of emergency care. There is no current literature summarizing the extensive research on interventions and solutions, thus there is a need for data synthesis to inform policymakers in this field. The aim of this overview was to summarize the interventions at each level of emergency care: input, throughput, and output. The methodology was supported by the current PRIOR statement for an overview of reviews. The study summarized twenty-seven full-text systematic reviews, which encompassed three hundred and eight primary studies. The results of the summary displayed a requirement for increasing studies in input and output interventions, as these showed the best outcomes with regard to ED crowding metrics. Moreover, the results displayed heterogeneous results at each level of ED care; these reflected that generally solutions have not been matched to specific problems facing regional centres. Thus, individual factors need to be considered when implementing solutions in Emergency Departments.

Effective states govern by some combination of enforcement and voluntary compliance. To contain the COVID-19 pandemic, a critical decision is the extent to which policy makers rely on voluntary as opposed to enforced compliance, and nations vary along this dimension. While enforcement may secure higher compliance, there is experimental and other evidence that it may also crowd out voluntary motivation. How does enforcement affect citizens’ support for anti–COVID-19 policies? A survey conducted with 4,799 respondents toward the end of the first lockdown in Germany suggests that a substantial share of the population will support measures more under voluntary than under enforced implementation. Negative responses to enforcement—termed control aversion—vary across the nature of the policy intervention (e.g., they are rare for masks and frequent for vaccination and a cell-phone tracing app). Control aversion is less common among those with greater trust in the government and the information it provides, and among those who were brought up under the coercive regime of East Germany. Taking account of the likely effectiveness of enforcement and the extent to which near-universal compliance is crucial, the differing degrees of opposition to enforcement across policies suggest that for some anti–COVID-19 policies an enforced mandate would be unwise, while for others it would be essential. Similar reasoning may also be relevant for policies to address future pandemics and other societal challenges like climate change.

[Display omitted] •Human crowding is positively and spatial crowding is negatively related to behavior.•While spatial crowding reduces control perceptions, human crowding has no such effect.•Human crowding improves store evaluation, whereas spatial crowding worsens it.•Effects of human and spatial crowding are enhanced or suppressed by various moderators.•A comprehensive model is more insightful as compared to individual crowding theories. While perceived crowding is an important construct in retailing literature, empirical findings on the consequences of this construct are mixed. This study uses meta-analytic techniques to combine the findings from 73 samples and more than 19,000 shoppers in order to both summarize and extend understanding of the consequences of human and spatial crowding in retail stores. It makes a threefold contribution. First, the examination of two distinct types of crowding – human crowding and spatial crowding – provides evidence that they have different impacts on customer satisfaction and behavioral responses. In general, spatial crowding has a negative impact on customer outcomes, whereas human crowding has positive effects. Second, a test of various theoretical perspectives on crowding demonstrates strong indirect effects of crowding through different mediators. While spatial crowding reduces shoppers’ perceived control, human crowding has no such effect. Spatial crowding contributes to a negative evaluation of the store, whereas human crowding leads to a positive store evaluation. Both crowding types are related to positive and negative emotions experienced by shoppers. Thus, complex relationships are uncovered through the study of mediated effects, particularly within a comprehensive framework that integrates constructs and relationships from various theories. Third, the study of the impacts of various moderators indicates that human and spatial crowding display different effects depending on the retailer’s offering (hedonic/utilitarian), retail type (store/agglomeration), employee support (high/low), customer type (new/existing), and the environment (cooperative/competitive). Study findings not only extend theory but also offer relevant implications for brick-and-mortar retail stores faced with the challenges of competing with new retail forms and the use of new technologies.

What is an effective vaccination policy to end the COVID-19 pandemic? We address this question in a model of the dynamics of policy effectiveness drawing upon the results of a large panel survey implemented in Germany during the first and second waves of the pandemic. We observe increased opposition to vaccinations were they to be legally required. In contrast, for voluntary vaccinations, there was higher and undiminished support. We find that public distrust undermines vaccine acceptance, and is associated with a belief that the vaccine is ineffective and, if enforced, compromises individual freedom. We model how the willingness to be vaccinated may vary over time in response to the fraction of the population already vaccinated and whether vaccination has occurred voluntarily or not. A negative effect of enforcement on vaccine acceptance (of the magnitude observed in our panel or even considerably smaller) could result in a large increase in the numbers that would have to be vaccinated unwillingly in order to reach a herd-immunity target. Costly errors may be avoided if policy makers understand that citizens’ preferences are not fixed but will be affected both by the crowding-out effect of enforcement and by conformism. Our findings have broad policy applicability beyond COVID-19 to cases in which voluntary citizen compliance is essential because state capacities are limited and because effectivenessmay depend on theways that the policies themselves alter citizens’ beliefs and preferences.

The coronavirus disease 2019 (COVID-19) pandemic is straining public health systems worldwide, and major non-pharmaceutical interventions have been implemented to slow its spread 1 – 4 . During the initial phase of the outbreak, dissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was primarily determined by human mobility from Wuhan, China 5 , 6 . Yet empirical evidence on the effect of key geographic factors on local epidemic transmission is lacking 7 . In this study, we analyzed highly resolved spatial variables in cities, together with case count data, to investigate the role of climate, urbanization and variation in interventions. We show that the degree to which cases of COVID-19 are compressed into a short period of time (peakedness of the epidemic) is strongly shaped by population aggregation and heterogeneity, such that epidemics in crowded cities are more spread over time, and crowded cities have larger total attack rates than less populated cities. Observed differences in the peakedness of epidemics are consistent with a meta-population model of COVID-19 that explicitly accounts for spatial hierarchies. We paired our estimates with globally comprehensive data on human mobility and predict that crowded cities worldwide could experience more prolonged epidemics. Analysis of spatial heterogeneity of crowding in China and Italy, together with COVID-19 case data, show that cities with higher crowding have longer epidemics and higher attack rates after the first epidemic wave.

In-vehicle crowding on public transportation is a serious problem that transportation planners must address. Recent studies have emphasized that in-vehicle crowding impacts travelers’ stress and health, while other studies have investigated how daily travel affects subjective well-being (SWB). Based on the findings of these studies, we provide useful insights into the value of a reduction in crowding in terms of SWB. The other factor we should consider is adaptation, as the effects of travel discomfort disappear after travelers become accustomed to them. In this paper, we analyzed the direct and stress-related indirect effects of dissatisfaction with in-vehicle crowding on life satisfaction, focusing on whether these effects differ by the length of time commuters have been using trains. Using a sample of 8296 train commuters in Tokyo, we found that (1) dissatisfaction with in-vehicle crowding directly lowers life satisfaction among some groups of short-term train commuters and (2) dissatisfaction with in-vehicle crowding indirectly lowers life satisfaction through stress and health, regardless of whether commuters have used trains for more or less than one year. These results revealed the importance of focusing on the stress-related indirect effects of dissatisfaction with crowding, while direct effects on SWB exist only among some commuters. Our results demonstrated the possibility of adaptation to direct effects.

In crowding, perception of an object deteriorates in the presence of nearby elements. Although crowding is a ubiquitous phenomenon, since elements are rarely seen in isolation, to date there exists no consensus on how to model it. Previous experiments showed that the global configuration of the entire stimulus must be taken into account. These findings rule out simple pooling or substitution models and favor models sensitive to global spatial aspects. In order to investigate how to incorporate global aspects into models, we tested a large number of models with a database of forty stimuli tailored for the global aspects of crowding. Our results show that incorporating grouping like components strongly improves model performance.

Metro crowding undermines passenger comfort, operational efficiency and network reliability. While prior research has examined station-level and system-wide crowding, little attention has been given to quantifying how individual stations contribute to link-level overcrowding. This study addresses this gap by introducing the Crowding Contribution Index (CCI), a metric that quantifies the extent to which destination stations drive overcapacity flows on preceding links. The CCI is computed via a structured framework integrating Automated Fare Collection (AFC) and GTFS link-network data. Applied to over 80 million trips across 237 Delhi Metro stations, 142 200 hourly CCI values reveal that 46.35% of station-hours exceed capacity, with highest contributions clustered in specific stations. A Type II Tobit model assesses built-environment (BE) variables, showing that POI and intersection densities increase contributions, while POI entropy reduces them, underscoring land-use diversity’s role. Random Forest and XGBoost models corroborate these findings, ranking BE variables as the strongest CCI predictors. These insights emphasise the need for integrated land-use and transport strategies. The CCI framework offers operators a scalable tool for real-time service adjustments, such as targeted short-turns and dynamic fleet deployment, and guides planners toward sustainable, integrated land-use planning, making it especially valuable for rapidly urbanising, data-constrained cities.

This study aimed to clarify the association between the crowding and clinical practice in the emergency department (ED). This 1-year retrospective cohort study conducted in two EDs in Taiwan included 70,222 adult non-trauma visits during the day shift between July 1, 2011, and June 30, 2012. The ED occupancy status, determined by the number of patients staying during their time of visit, was used to measure crowding, grouped into four quartiles, and analyzed in reference to the clinical practice. The clinical practices included decision-making time, patient length of stay, patient disposition, and use of laboratory examinations and computed tomography (CT). The four quartiles of occupancy statuses determined by the number of patients staying during their time of visit were <24, 24–39, 39–62, and >62. Comparing >62 and <24 ED occupancy statuses, the physicians' decision-making time and patients' length of stay increased by 0.3h and 1.1h, respectively. The percentage of patients discharged from the ED decreased by 15.5% as the ED observation, general ward, and intensive care unit admissions increased by 10.9%, 4%, and 0.7%, respectively. CT and laboratory examination slightly increased in the fourth quartile of ED occupancy. Overcrowding in the ED might increase physicians' decision-making time and patients' length of stay, and more patients could be admitted to observation units or an inpatient department. The use of CT and laboratory examinations would also increase. All of these could lead more patients to stay in the ED.

Pictograms are graphic symbols designed to function within limited space. They are characterized by overlapping elements within a frame, which can lead to visual crowding, where neighboring objects merge and become indistinguishable. While visual crowding has been extensively studied in reading and vision research, its impact on pictograms remains underexplored. This study aimed to measure the effect of spacing between two icons and between icons and an outline frame on icon recognition. Using Auckland Optotypes to construct fictive pictograms, we conducted an experiment within an object recognition experimental paradigm, involving 25 participants. Results showed significant interaction between the effects of icon-frame distance and the spacing between the two icons, with the most limiting factor for recognition being two icons overlapping or placed in close proximity to each other. Strategic spacing adjustments within framed pictograms can reduce the impact of crowding on recognition, particularly when icons are not overlapping