Objectives Variation in the prevalence of eosinophilic gastrointestinal diseases in different geographical regions has not been extensively studied. The aim of the present study was to define the regional and national prevalence of eosinophilic gastrointestinal diseases, and differences in practice approaches. Patients and Methods We administered a survey electronically to members of the American College of Gastroenterology, the American Academy of Allergy, Asthma, and Immunology, and the North American Society Pediatric Gastroenterology, Hepatology, and Nutrition. Questions pertained to the number and proportion of patients seen with eosinophilic gastroenteritis or colitis and eosinophilic esophagitis (EoE), and methods used to diagnose and treat these conditions. Results A total of 1836 physicians responded from 10,874 requests (17% response). Extrapolating responses from our US sample, we estimated an overall prevalence of 52 and 28/100,000 for EoE and eosinophilic gastroenteritis or colitis. The patient burden of EoE is higher in urban (0.58) and suburban (0.44) compared with rural settings (0.36, P <0.0065), observations consistent with other allergic disorders. There was also increased prevalence in northeast region when calculated by prevalence per 100,000. There was considerable variability in criteria and initial treatment options used to diagnose EoE. Only one-third of respondents reported using diagnostic criteria proposed in a 2007 consensus document. Seventy-one and 35% of respondents reported treating some patients with EoE with a food elimination or elemental diet, respectively. Conclusions EoE is diagnosed more often in northeastern states and urban areas. There is considerable variability in diagnostic criteria and initial treatment approach supporting the need for additional clinical trials and consensus development.

BackgroundPediatric unintentional falls are the leading cause of injury-related emergency visits for children < 5 years old. The purpose of this study was to identify population characteristics, injury mechanisms, and injury severities and patterns among children < 5 years to better inform age-appropriate falls prevention strategies.MethodsThis retrospective database study used trauma registry data from the lead pediatric trauma system in Georgia. Data were analyzed for all patients < 5 years with an international classification of disease, 9th revision, clinical modification (ICD-9 CM) external cause of injury code (E-code) for unintentional falls between 1/1/2013 and 12/31/2015. Age (months) was compared across categories of demographic variables, injury mechanisms, and emergency department (ED) disposition using Kruskal-Wallis ANOVA and the Mann Whitney U test. The relationships between demographic variables, mechanism of injury (MOI), and Injury Severity Score (ISS) were evaluated using multinomial logistic regression.ResultsInclusion criteria were met by 1086 patients (median age = 28 months; 59.7% male; 53.8% White; 49.1% <  1 m fall height). Younger children, < 1-year-old, primarily fell from caregiver’s arms, bed, or furniture, while older children sustained more falls from furniture and playgrounds. Children who fell from playground equipment were older (median = 49 months, p < 0.01) than those who fell from the bed (median = 10 months), stairs (median = 18 months), or furniture (median = 19 months). Children < 1 year had the highest proportion of head injuries including skull fracture (63.1%) and intracranial hemorrhage (65.5%), 2-year-old children had the highest proportion of femur fractures (32.9%), and 4-year-old children had the highest proportion of humerus fractures (41.0%). Medicaid patients were younger (median = 24.5 months, p < 0.01) than private payer (median = 34 months). Black patients were younger (median = 20.5 months, p < 0.001) than White patients (median = 29 months). Results from multinomial logistic regression models suggest that as age increases, odds of a severe ISS (16–25) decreased (OR = 0.95, CI = 0.93–0.97).ConclusionsPediatric unintentional falls are a significant burden of injury for children < 5 years. Future work will use these risk and injury profiles to inform current safety recommendations and develop evidence-based interventions for parents/caregivers and pediatric providers.Electronic supplementary materialThe online version of this article (10.1186/s40621-018-0147-x) contains supplementary material, which is available to authorized users.

ObjectivesViolence is a major public health problem in the USA. In 2016, more than 1.6 million assault-related injuries were treated in US emergency departments (EDs). Unfortunately, information about the magnitude and patterns of violent incidents is often incomplete and underreported to law enforcement (LE). In an effort to identify more complete information on violence for the development of prevention programme, a cross-sectoral Cardiff Violence Prevention Programme (Cardiff Model) partnership was established at a large, urban ED with a level I trauma designation and local metropolitan LE agency in the Atlanta, Georgia metropolitan area. The Cardiff Model is a promising violence prevention approach that promotes combining injury data from hospitals and LE. The objective was to describe the Cardiff Model implementation and collaboration between hospital and LE partners.MethodsThe Cardiff Model was replicated in the USA. A process evaluation was conducted by reviewing project materials, nurse surveys and interviews and ED–LE records.ResultsCardiff Model replication centred around four activities: (1) collaboration between the hospital and LE to form a community safety partnership locally called the US Injury Prevention Partnership; (2) building hospital capacity for data collection; (3) data aggregation and analysis and (4) developing and implementing violence prevention interventions based on the data.ConclusionsThe Cardiff Model can be implemented in the USA for sustainable violent injury data surveillance and sharing. Key components include building a strong ED–LE partnership, communicating with each other and hospital staff, engaging in capacity building and sustainability planning.

Identifying geographic areas and time periods of increased violence is of considerable importance in prevention planning. This study compared the performance of multiple data sources to prospectively forecast areas of increased interpersonal violence. We used 2011-2014 data from a large metropolitan county on interpersonal violence (homicide, assault, rape and robbery) and forecasted violence at the level of census block-groups and over a one-month moving time window. Inputs to a Random Forest model included historical crime records from the police department, demographic data from the US Census Bureau, and administrative data on licensed businesses. Among 279 block groups, a model utilizing all data sources was found to prospectively improve the identification of the top 5% most violent block-group months (positive predictive value = 52.1%; negative predictive value = 97.5%; sensitivity = 43.4%; specificity = 98.2%). Predictive modelling with simple inputs can help communities more efficiently focus violence prevention resources geographically.

Role of the Funder/Sponsor: The funding organizations had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.