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Conveys that the reliance on information technologies may disenfranchise those students unable to secure access to computers and the knowledge needed to use them. Addresses the issues behind technological segregation and asserts the need to replace the personal computer (PC) with a network computer (NC). Technological segregation affects all disciplines, including the arts. (CMK)

Background: The COVID-19 pandemic has substantially impacted American Indian and Alaska Native (AI/AN) communities. Rates of infection, hospitalization, and mortality have been severe relative to non-Hispanic whites. While AI/AN communities have had some of the highest levels of COVID-19 vaccination, utilization rates remain suboptimal and there is a need to identify facilitators and barriers to testing and vaccination. Methods: We examined cross-sectional survey data from January to May 2021, among 619 AI/AN patients from five tribal health organizations (AK, CO, KS, NM, WA). Exposures include perceived stress, Kessler distress, PTSD screening, and AUDIT-C alcohol misuse screen. Poisson regression was used to estimate associations with prevalence of COVID-19 testing and vaccination. Results: Over three-quarters of participants were tested for COVID-19 and nearly half were vaccinated. Perceived stress and positive PTSD screening were associated with reduced vaccination prevalence, Prevalence Ratio (PR) 0.83 (0.73, 0.93) and PR 0.80 (0.66, 0.98), respectively. There was reduced prevalence of COVID-19 testing in subgroups with lower reported psychological resilience and PTSD, PR 0.78 (0.64, 0.95). Conclusions: Past-month perceived stress and positive PTSD screening are associated with reduced prevalence of COVID-19 vaccination in urban AI/AN people. Subgroups reporting limited resilience and PTSD symptoms had lower prevalence of COVID-19 testing. The complex relationship between mental health and COVID-19 testing and vaccination warrants further exploration to identify interventions to improve health among urban AI/AN people, a population with known disparities in both mental health and COVID-19 outcomes.

Background:. Nurtec, a versatile migraine medication, has gained popularity. However, the awareness of migraine surgery remains uncertain. Methods:. Following a descriptive approach, this cross-sectional study used Google Trends data as of December 1, 2023, to analyze internet search patterns. Approval from Vanderbilt University’s institutional review board and adherence to Strengthening the Reporting of Observational Studies in Epidemiology guidelines were confirmed. Monthly relative search volume (RSV) data for “migraine surgery,” “Nurtec,” and “Rimegepant” were collected from January 1, 2004, to November 11, 2023, within the United States. Statistical analysis involved determining mean monthly RSV values and percentage changes for critical periods. Results:. For “Nurtec,” a significant surge in RSV occurred from March 2020 to April 2020 (344%). Additional peaks were observed from June 2020 to July 2020 (66%), October 2020 to December 2020 (169%), May 2021 to June 2021 (33%), and May 2023 to June 2023 (14%). “Migraine surgery” exhibited a notable 400% increase in RSV, from March 2005 to May 2005. However, post-2006, RSV for “migraine surgery” consistently remained low without noticeable peaks. Conclusions:. The analysis of RSV trends for “Nurtec” and “migraine surgery” from 2004 to 2023 reveals the impact of pivotal events and marketing strategies on public interest. The distinct peaks in “Nurtec” RSV align with Food & Drug Administration approvals and marketing campaigns, highlighting the medication’s accessibility. Conversely, the consistently low RSV for “migraine surgery” indicates limited awareness, emphasizing the need for enhanced promotion and education regarding surgical interventions.

BackgroundThe lack of regular physical activity (PA) in individuals with spinal cord injury (SCI) in the United States is an ongoing health crisis. Regular PA and exercise-based interventions have been linked with improved outcomes and healthier lifestyles among those with SCI. Providing people with an accurate estimate of their everyday PA level can promote PA. Furthermore, PA tracking can be combined with mobile health technology such as smartphones and smartwatches to provide a just-in-time adaptive intervention (JITAI) for individuals with SCI as they go about everyday life. A JITAI can prompt an individual to set a PA goal or provide feedback about their PA levels. ObjectiveThe primary aim of this study is to investigate whether minutes of moderate-intensity PA among individuals with SCI can be increased by integrating a JITAI with a web-based PA intervention (WI) program. The WI program is a 14-week web-based PA program widely recommended for individuals with disabilities. A secondary aim is to investigate the benefit of a JITAI on proximal PA, defined as minutes of moderate-intensity PA within 120 minutes of a PA feedback prompt. MethodsIndividuals with SCI (N=196) will be randomized to a WI arm or a WI+JITAI arm. Within the WI+JITAI arm, a microrandomized trial will be used to randomize participants several times a day to different tailored feedback and PA recommendations. Participants will take part in the 24-week study from their home environment in the community. The study has three phases: (1) baseline, (2) WI program with or without JITAI, and (3) PA sustainability. Participants will provide survey-based information at the initial meeting and at the end of weeks 2, 8, 16, and 24. Participants will be asked to wear a smartwatch every day for ≥12 hours for the duration of the study. ResultsRecruitment and enrollment began in May 2023. Data analysis is expected to be completed within 6 months of finishing participant data collection. ConclusionsThe JITAI has the potential to achieve long-term PA performance by delivering tailored, just-in-time feedback based on the person’s actual PA behavior rather than a generic PA recommendation. New insights from this study may guide intervention designers to develop engaging PA interventions for individuals with disability. Trial RegistrationClinicalTrials.gov NCT05317832; https://clinicaltrials.gov/study/NCT05317832 International Registered Report Identifier (IRRID)DERR1-10.2196/57699

This study utilized a max-stable process (MSP) model with a dependence structure defined via a non-Euclidean distance metric, with the goal of modelling extreme flood data on a river network. The dataset was composed of mean daily discharge observations from 22 United States Geological Survey streamflow gaging stations for river basins in Missouri and Arkansas. The analysis included the application of the elastic-net penalty to automatically build spatially varying trend surfaces to model the marginal distributions. The dependence model accounted for the river distance between hydrologically connected gaging sites and the hydrologic distance, defined as the Euclidean distance between the centers of site’s associated drainage areas, for all stations. Modelling the marginal distributions and spatial dependence among the extremes are two key components for spatially modelling extremes. Among the 16 covariates evaluated for marginal fitting, 7 were selected to spatially model the generalized extreme value (GEV) location parameter (for each gaging station’s contributing drainage basin, its outlet elevation, centroid x coordinate, centroid elevation, area, average basin width, elevation range, and median land surface slope). The three covariates selected for the GEV scale parameter included the area, average basin width, and median land surface slope. The GEV shape parameter was assumed to be constant throughout the entire study area. Comparisons of estimates obtained from the spatial covariate model with their corresponding “at-site” estimates resulted in computed values of 0.95, 0.95, 0.94 and 0.85, 0.84, 0.90 for the coefficient of determination, Nash–Sutcliffe efficiency, and Kling–Gupta efficiency for the GEV location and scale parameters, respectively. Brown–Resnick MSP models were fit to independent multivariate events extracted from a set of common discharge data, transformed to unit Fréchet margins while considering different permutations of the non-Euclidean dependence model. Each of the fitted model’s log-likelihood values indicated improved fits when using hydrologic distance rather than Euclidean distance. They also demonstrated that accounting for flow-connected dependence and anisotropy further improved model fit. In this study, the results from both parts were illustrative; however, further research with larger datasets and more heterogeneous systems is recommended.

Many public health challenges are characterized by complexity that reflects the dynamic systems in which they occur. Such systems involve multiple interdependent factors, actors, and sectors that influence health, and are a primary driver of challenges of insufficient implementation, sustainment, and scale of evidence-based public health interventions. Implementation science frameworks have been developed to help embed evidence-based interventions in diverse settings and identify key factors that facilitate or hinder implementation. These frameworks are largely static in that they do not explain the nature and dynamics of interrelationships among the identified determinants, nor how those determinants might change over time. Furthermore, most implementation science frameworks are top-down, deterministic, and linear, leaving critical gaps in understanding of both how to intervene on determinants of successful implementation and how to scale evidence-based solutions. Design thinking and systems science offer methods for transforming this problem-oriented paradigm into one that is solution-oriented. This article describes these two approaches and how they can be integrated into implementation science strategies to promote implementation, sustainment, and scaling of public health innovation, ultimately resulting in transformative systems changes that improve population health.

IntroductionAfrican swine fever (ASF) is an important disease of pigs in sub-Saharan Africa and Uganda and is threatening the pig population and agricultural economy of other continents. ASF virus (ASFV) can be transmitted from wild suids to domestic pigs through soft ticks of the Ornithodoros species. The aim of this study was to understand the relationship between domestic pigs’ O. moubata tick exposure and ASFV status.MethodsPigs were sampled from six abattoirs in the Kampala metropolitan area of Uganda from May 2021 through June 2022. Blood, serum, and tissue samples were collected. Serum was tested for antibodies against the rtTSGP1 salivary antigens of O. moubata ticks using an indirect ELISA assay. Blood and tissue samples from pigs were tested to detect ASFV using qPCR. Probability of tick exposure was categorized based on sample-to-positive ratio cut-off points.ResultsOut of 1,328 serum samples tested, there were 828 (62.3%) samples with a negligible probability; 369 (27.8%) with a medium probability; 90 (6.8%) with a high probability, and 41 (3.1%) with a very high probability of exposure to the O. moubata salivary antigen. There was a statistically significant association between the pigs’ O. moubata exposure and ASFV status with a higher proportion of pigs having a very high probability of infection if they were ASFV positive by blood, tonsil, and lymph nodes.DiscussionThese results suggested that tick exposure was associated with ASFV transmission in Uganda. There were ASFV qPCR positive pigs that had no O. moubata exposure as well, which highlights that pig-to-pig and indirect contact transmission still play a significant role. This work highlights the need for further work in Uganda to investigate these transmission factors related to the O. moubata tick and ASFV transmission.

Abstract Background African swine fever virus (ASFV) infections in Africa cause hemorrhagic disease in domestic pigs and is maintained by a sylvatic cycle in warthogs. It is endemic in Uganda, leading to significant economic losses. Previous studies performed in rural areas and in Kampala had differing diagnostic results. The purpose of this study was to provide a robust spatial, temporal, and diagnostic summary of pigs slaughtered in the greater Kampala metropolitan area over the course of one year. This study characterized 1208 to 1323 serum, blood, and tissue samples collected from pigs at six abattoirs in the greater Kampala metropolitan area of Uganda monthly from May 2021 through June 2022. Validated and standardized serologic and molecular diagnostics were used. Results Only 0.15% of pigs had detectable antibodies against ASFV, suggesting low survival rates or pre-clinical diagnosis. Yet, 59.5% of pigs were positive for ASFV DNA. Blood had the lowest detection rate (15.3%) while tonsil and lymph nodes had the highest (38% and 37.5%, respectively), spleen samples (31.5%) were in between. Agreement between sample types was fair to moderate overall. A significant seasonality of ASFV infections emerged with infections found predominately in the dry seasons. Spatial assessments revealed that the greater Kampala metropolitan area abattoirs have a catchment area that overlaps with Uganda’s most pig dense regions. Conclusions Pigs at greater Kampala metropolitan area abattoirs can be sentinels for acute disease throughout the pig dense region of Uganda, particularly in the dry seasons. The high prevalence detected suggests that pigs are sold in response to local reports of ASFV infections (panic sales). Serological surveillance is not useful, as very few pigs seroconverted in this study prior to slaughter. In contrast, tissue samples of pigs can be used to detect disease using qPCR methods.

Abstract The eastern Mediterranean sapropels, paced by insolation, provide a unique archive of African monsoon strength over the Late Neogene. However, the longer-term climate of this region lacks characterization within the context of changes in ice volume, sea surface temperature gradients, and terrestrial ecosystems. Here, we examine C28 n-alkanoic acid leaf wax hydrogen and carbon isotopes in sapropels, sourced from northeast Africa, along with vegetation-corrected precipitation isotopes, derived from astronomically dated sediment cores from ODP 160 Sites 966 and 967 since 4.5 million years ago. Despite sampling only wet-phase sapropels for African monsoon variability, we find a larger range in hydrogen isotopes than previously published data across wet-dry precession cycles, indicating the importance of long-term modulation of Green Sahara phases throughout the Neogene. An influence of orbital properties on regional monsoonal hydroclimate is observed, controlling up to 50% of total hydrogen isotope variance, but large changes outside of these typical frequencies account for at least 50% of the total variance. This secular trend may track changes in ice volume, tropical sea surface temperature, sea surface temperature gradients, or even lower-frequency orbital cycles. Long-term hydroclimate and environmental shifts provide new contexts for milestone events in northeast African hominin dispersal and evolution.

Purpose: In acute respiratory distress syndrome (ARDS), dead space fraction has been independently associated with mortality. We hypothesized that early measurement of the difference between arterial and end-tidal CO2 (arterial-ET difference), a surrogate for dead space fraction, would predict mortality in mechanically ventilated patients with ARDS.Methods: We performed two separate exploratory analyses. We first used publicly available databases from the ALTA, EDEN, and OMEGA ARDS Network trials (N = 124) as a derivation cohort to test our hypothesis. We then performed a separate retrospective analysis of patients with ARDS using University of Chicago patients (N = 302) as a validation cohort.Results: The ARDS Network derivation cohort demonstrated arterial-ET difference, vasopressor requirement, age, and APACHE III to be associated with mortality by univariable analysis. By multivariable analysis, only the arterial-ET difference remained significant (P = 0.047). In a separate analysis, the modified Enghoff equation ((PaCO2-PETCO2)/PaCO2) was used in place of the arterial-ET difference and did not alter the results. The University of Chicago cohort found arterial-ET difference, age, ventilator mode, vasopressor requirement, and APACHE II to be associated with mortality in a univariate analysis. By multivariable analysis, the arterial-ET difference continued to be predictive of mortality (P = 0.031). In the validation cohort, substitution of the arterial-ET difference for the modified Enghoff equation showed similar results.Conclusion: Arterial to end-tidal CO2 (ETCO2) difference is an independent predictor of mortality in patients with ARDS. [ABSTRACT FROM AUTHOR]