Search

This study evaluates the epidemiology of nonfatal head injuries among children aged 1 to 4 years associated with consumer products and identifies the specific consumer products associated with these injuries. Data for children aged 1 to 4 years who presented to emergency departments (EDs) from 2015 to 2019 for a nonfatal head injury were extracted from the National Electronic Injury Surveillance System. An estimated 1 032 429 (95% confidence interval [CI]: 675 822-1 389 063) children presented to US EDs for head injuries, averaging 566 injuries daily. The average rate of head injury did not change over the 5-year study period (slope = −0.003; P =.852); it was highest among children aged 1 year (2.06 per 100 children aged 1 year), which was nearly 3 times that of children aged 4 years (rate ratio = 2.75; 95% CI: 2.73-2.77). Most injuries occurred at home (80.4%) and occurred from interacting with home furnishings (45.1%). This study underscores the need for increased head injury mitigation efforts among young children. [ABSTRACT FROM AUTHOR]

Background: Infectious disease computational modeling studies have been widely published during the coronavirus disease 2019 (COVID-19) pandemic, yet they have limited reproducibility. Developed through an iterative testing process with multiple reviewers, the Infectious Disease Modeling Reproducibility Checklist (IDMRC) enumerates the minimal elements necessary to support reproducible infectious disease computational modeling publications. The primary objective of this study was to assess the reliability of the IDMRC and to identify which reproducibility elements were unreported in a sample of COVID-19 computational modeling publications., Methods: Four reviewers used the IDMRC to assess 46 preprint and peer reviewed COVID-19 modeling studies published between March 13 th , 2020, and July 31 st , 2020. The inter-rater reliability was evaluated by mean percent agreement and Fleiss' kappa coefficients (κ). Papers were ranked based on the average number of reported reproducibility elements, and average proportion of papers that reported each checklist item were tabulated., Results: Questions related to the computational environment (mean κ = 0.90, range = 0.90-0.90), analytical software (mean κ = 0.74, range = 0.68-0.82), model description (mean κ = 0.71, range = 0.58-0.84), model implementation (mean κ = 0.68, range = 0.39-0.86), and experimental protocol (mean κ = 0.63, range = 0.58-0.69) had moderate or greater (κ > 0.41) inter-rater reliability. Questions related to data had the lowest values (mean κ = 0.37, range = 0.23-0.59). Reviewers ranked similar papers in the upper and lower quartiles based on the proportion of reproducibility elements each paper reported. While over 70% of the publications provided data used in their models, less than 30% provided the model implementation., Conclusions: The IDMRC is the first comprehensive, quality-assessed tool for guiding researchers in reporting reproducible infectious disease computational modeling studies. The inter-rater reliability assessment found that most scores were characterized by moderate or greater agreement. These results suggests that the IDMRC might be used to provide reliable assessments of the potential for reproducibility of published infectious disease modeling publications. Results of this evaluation identified opportunities for improvement to the model implementation and data questions that can further improve the reliability of the checklist.