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Infectious disease modeling and forecasting tools are crucial for outbreak management. However, variability exists in the capacity of state and local health departments to effectively utilize these tools, influenced by factors such as infrastructure, funding, staff capacity, and data access. This study aims to identify the current priorities, needs, and capacities of state and local public health departments regarding infectious disease modeling and forecasting tools. Key informant interviews were conducted with epidemiologists, informaticists, and leadership across state and local health departments from Montana, Utah, and Washington. Thematic coding and axial coding were used for thematic analysis. Three themes emerged: (1) models and tools must be adaptable based on the jurisdiction type (rural, urban, state); (2) building trust in models and tools is an important precursor to adoption; and (3) there are concerns about the availability and quality of data. This study highlights the need for adaptable modeling tools that are tailored to specific public health jurisdictions. Building trust in modeling and forecasting tools and addressing data quality issues are essential for successful tool implementation and adoption across diverse public health settings.

Dimethyl sulfide (DMS) is the major sulfur species emitted from the ocean. The gas-phase oxidation of DMS by hydroxyl radicals proceeds through the stable, soluble intermediate hydroperoxymethyl thioformate (HPMTF), eventually forming carbonyl sulfide (OCS) and sulfur dioxide (SO2). Recent work has shown that HPMTF is efficiently lost to marine boundary layer (MBL) clouds, thus arresting OCS and SO2 production and their contributions to new-particle formation and growth events. To date, no long-term field studies exist to assess the extent to which frequent cloud processing impacts the fate of HPMTF. Here, we present 6 weeks of measurements of the cloud fraction and the marine sulfur species methanethiol, DMS, and HPMTF made at the Atmospheric Radiation Measurement (ARM) research facility on Graciosa Island, Azores, Portugal. Using an observationally constrained chemical box model, we determine that cloud loss is the dominant sink of HPMTF in this region of the MBL during the study, accounting for 79 %–91 % of HPMTF loss on average. When accounting for HPMTF uptake to clouds, we calculate campaign average reductions in DMS-derived MBL SO2 and OCS of 52 %–60 % and 80 %–92 % for the study period. Using yearly measurements of the site- and satellite-measured 3D cloud fraction and DMS climatology, we infer that HPMTF cloud loss is the dominant sink of HPMTF in the eastern North Atlantic during all seasons and occurs on timescales faster than what is prescribed in global chemical transport models. Accurately resolving this rapid loss of HPMTF to clouds has important implications for constraining drivers of MBL new-particle formation.

To establish the position and duration-specific running demands of Australian Football (AF) competition for the prescription and monitoring of specific training drills. An observational time-motion analysis was performed on 40 professional AF players during 30 games throughout the 2014–15 competitive seasons. Player movements were collected and peak values were calculated for moving averages of between 1–10min in duration for relative distance (mmin−1), high-speed relative distance (HSmmin−1), average acceleration/deceleration (ms2) and metabolic power (Pmet). A mixed-model analysis was used to detect positional differences, and differences were described using a magnitude-based network. Relative distance was likely greater for midfielders (MID), and mobile forwards (MF) compared to tall backs (TB) across all moving average durations assessed, with MF peaking at 223±35mmin−1 for a 1-min window. High-speed relative distance was at least likely to be greater for MF compared to all other positions, across all moving average durations (ES=0.27–0.94). Acceleration/deceleration demands were similar across positions. The present study demonstrated that the peak running intensities of AF are well above previously reported peak intensities when considering the distance-based running requirements of match-play. Whilst the acceleration-based metric was unable to detect large differences between positions, it is important to note their contribution to the overall competition demands. This study presents a useful framework for the prescription and monitoring of drills specific to AF competition requirements.

Dimethyl sulfide (DMS) is the major sulfur species emitted from the ocean. The gas-phase oxidation of DMS by hydroxyl radicals proceeds through the stable, soluble intermediate hydroperoxymethyl thioformate (HPMTF), eventually forming carbonyl sulfide (OCS) and sulfur dioxide (SO.sub.2). Recent work has shown that HPMTF is efficiently lost to marine boundary layer (MBL) clouds, thus arresting OCS and SO.sub.2 production and their contributions to new-particle formation and growth events. To date, no long-term field studies exist to assess the extent to which frequent cloud processing impacts the fate of HPMTF. Here, we present 6 weeks of measurements of the cloud fraction and the marine sulfur species methanethiol, DMS, and HPMTF made at the Atmospheric Radiation Measurement (ARM) research facility on Graciosa Island, Azores, Portugal. Using an observationally constrained chemical box model, we determine that cloud loss is the dominant sink of HPMTF in this region of the MBL during the study, accounting for 79 %-91 % of HPMTF loss on average. When accounting for HPMTF uptake to clouds, we calculate campaign average reductions in DMS-derived MBL SO.sub.2 and OCS of 52 %-60 % and 80 %-92 % for the study period. Using yearly measurements of the site- and satellite-measured 3D cloud fraction and DMS climatology, we infer that HPMTF cloud loss is the dominant sink of HPMTF in the eastern North Atlantic during all seasons and occurs on timescales faster than what is prescribed in global chemical transport models. Accurately resolving this rapid loss of HPMTF to clouds has important implications for constraining drivers of MBL new-particle formation.

IntroductionExtracorporeal membrane oxygenation (ECMO) is a classic low-volume high-risk procedure that requires just in time and/or refresher training through animal or simulation modalities. This manuscript evaluated the performance of ECMO personnel trained with both modalities to determine which is better suited for ECMO skills training.MethodsParticipants (physicians, nurses and respiratory/medical technicians) completed a series of ECMO scenarios with synthetic tissue cannulation task trainer as well as a live tissue model. Objective performance quality was based on task completion using a validated ECMO skills assessment tool.ResultsThirty-eight individuals completed this study. Participants completed individual scenario tasks 3 min faster using the simulator (26 min vs 29 min; p=0.03). No differences were seen in percentage of individual tasks completed. In the group scenarios, participants completed a higher percentage of critical tasks using the simulator (97%) versus the animal model (91%; p=0.05), but no differences were seen in task completion times. Additionally, no differences were seen in either lab-based or participants’ prelab cognitive scores.ConclusionsRegardless of their self-assessment or experience, participants’ objective performances were similar among both animal and simulation labs. Task completion times were quicker with simulation model. The distinction between simulation versus animal model may be less important as both demonstrate benefit in development of and/or maintaining skill competency. In the era of questioning the need for and costs of live tissue training, expanding the role of simulation may achieve similar training goals.

The Short Form 36 (SF-36) questionnaire is the most widely accepted measure of quality of life (QOL); however, it is cumbersome to use and requires complicated analysis. The Cleveland Global Quality of Life (CGQL) is a simpler tool, which has been validated in patients with ulcerative colitis undergoing restorative proctocolectomy. This study validates CGQL in patients with Crohn’s disease and determines the correlation of QOL measurement systems with disease activity as measured by the Crohn’s Disease Activity Index (CDAI). All patients with Crohn’s disease presenting to this department between September 2001 and February 2002 were prospectively entered into a database, including demographic data, disease manifestations, Vienna classification, age at diagnosis, and duration of Crohn’s disease. SF-36, CGQL, and CDAI scores were entered concurrently. Cronbach’s α was used to assess the internal consistency among the components of the CGQL score. Correlation among various QOL measures was assessed with Spearman’s test. Relationships between QOL measures and various baseline factors were assessed by Wilcoxon rank sum test, Student’s t test, Kruskal–Wallis test, and Pearson’s test, depending on the type and distribution of data. Change from baseline in the CGQL was assessed with the Wilcoxon signed rank test. One hundred seventy-eight (178) patients were entered into the database, and 169 completed QOL and CDAI data. There was a significant correlation between SF-36 and CGQL. CGQL and SF-36 correlated similarly with CDAI. Neither patient age, gender, or smoking history were associated with CGQL. CGQL correlates with disease activity and is a simple measure of QOL in Crohn’s disease.

Practice and research with senior leaders can be rewarding but also challenging and risky for industrial and organizational (I-O) psychologists; the fact that much of the work with these populations is difficult to access elevates these concerns. In this article we summarize work presented by prominent researchers and practitioners at a symposium organized to share common practices and challenges associated with work at higher levels of organizational management. We review implications for research and practice with senior leaders by examining how assessments are applied at senior levels, how assessments and development practices can be linked, and the challenges associated with research and evaluation conducted with these leaders. Also, we offer suggestions for advancing research and practice at senior levels.

Background Children with respiratory tract infections are the single most frequent patient group to make use of primary care health care resources. The use of antibiotics remains highly prevalent in young children, but can lead to antimicrobial resistance as well as reinforcing the idea that parents should re-consult for similar symptoms. One of the main drivers of indiscriminate antimicrobial use is the lack of evidence for, and therefore uncertainty regarding, which children are at risk of poor outcome. This paper describes the protocol for the TARGET cohort study, which aims to derive and validate a clinical prediction rule to identify children presenting to primary care with respiratory tract infections who are at risk of hospitalisation. Methods/design The TARGET cohort study is a large, multicentre prospective observational study aiming to recruit 8,300 children aged ≥3 months and <16 years presenting to primary care with a cough and respiratory tract infection symptoms from 4 study centres (Bristol, London, Oxford and Southampton). Following informed consent, symptoms, signs and demographics will be measured. In around a quarter of children from the Bristol centre, a single sweep, dual bacterial-viral throat swab will be taken and parents asked to complete a symptom diary until the child is completely well or for 28 days, whichever is sooner. A review of medical notes including clinical history, re-consultation and hospitalisations will be undertaken. Multivariable logistic regression will be used to identify the independent clinical predictors of hospitalisation as well as the prognostic significance of upper respiratory tract microbes. The clinical prediction rule will be internally validated using various methods including bootstrapping. Discussion The clinical prediction rule for hospitalisation has the potential to help identify a small group of children for hospitalisation and a much larger group where hospitalisation is very unlikely and antibiotic prescribing would be less warranted. This study will also be the largest natural history study to date of children presenting to primary care with acute cough and respiratory tract infections, and will provide important information on symptom duration, re-consultations and the microbiology of the upper respiratory tract.

The Short Form 36 (SF-36) questionnaire is the most widely accepted measure of quality of life (QOL); however, it is cumbersome to use and requires complicated analysis. The Cleveland Global Quality of Life (CGQL) is a simpler tool, which has been validated in patients with ulcerative colitis undergoing restorative proctocolectomy. This study validates CGQL in patients with Crohn's disease and determines the correlation of QOL measurement systems with disease activity as measured by the Crohn's Disease Activity Index (CDAI). All patients with Crohn's disease presenting to this department between September 2001 and February 2002 were prospectively entered into a database, including demographic data, disease manifestations, Vienna classification, age at diagnosis, and duration of Crohn's disease. SF-36, CGQL, and CDAI scores were entered concurrently. Cronbach'S α was used to assess the internal consistency among the components of the CGQL score. Correlation among various QOL measures was assessed with Spearman'S test. Relationships between QOL measures and various baseline factors were assessed by Wilcoxon rank sum test, Student'S t test, Kruskal–Wallis test, and Pearson'S test, depending on the type and distribution of data. Change from baseline in the CGQL was assessed with the Wilcoxon signed rank test. One hundred seventy-eight (178) patients were entered into the database, and 169 completed QOL and CDAI data. There was a significant correlation between SF-36 and CGQL. CGQL and SF-36 correlated similarly with CDAI. Neither patient age, gender, or smoking history were associated with CGQL. CGQL correlates with disease activity and is a simple measure of QOL in Crohn's disease.