Prevalence of COVID-19-Related Social Disruptions and Effects on Psychosocial Health in a Mixed-Serostatus Cohort of Men and Women

Objectives:This study describes prevention behavior and psychosocial health among people living with HIV (PLHIV) and HIV-negative people during the early wave of the coronavirus disease 2019 (COVID-19) pandemic in the United States. We assessed differences by HIV status and associations between social disruption and psychosocial health.Design:A cross-sectional telephone/videoconference administered survey of 3411 PLHIV and HIV-negative participants in the Multicenter AIDS Cohort Study/WIHS Combined Cohort Study (MWCCS).Methods:An instrument combining new and validated measures was developed to assess COVID-19 prevention efforts, social disruptions (loss of employment, childcare, health insurance, and financial supports), experiences of abuse, and psychosocial health. Interviews were performed between April and June 2020. Associations between social disruptions and psychosocial health were explored using multivariable logistic regression, adjusting for sociodemographics and HIV status.Results:Almost all (97.4%) participants reported COVID-19 prevention behavior; 40.1% participants reported social disruptions, and 34.3% reported health care appointment disruption. Men living with HIV were more likely than HIV-negative men to experience social disruptions (40.6% vs. 32.9%; P < 0.01), whereas HIV-negative women were more likely than women with HIV to experience social disruptions (51.1% vs. 39.8%, P < 0.001). Participants who experienced ≥2 social disruptions had significantly higher odds of depression symptoms [aOR = 1.32; 95% confidence interval (CI): 1.12 to 1.56], anxiety (aOR = 1.63; 95% CI: 1.17 to 2.27), and social support dissatisfaction (aOR = 1.81; 95% CI: 1.26 to 2.60).Conclusions:This study builds on emerging literature demonstrating the psychosocial health impact related to the COVID-19 pandemic by providing context specific to PLHIV. The ongoing pandemic requires structural and social interventions to decrease social disruption and address psychosocial health needs among the most vulnerable populations

The 2024 Europe report of the Lancet Countdown on health and climate change: unprecedented warming demands unprecedented action

Record-breaking temperatures were recorded across the globe in 2023. Without climate action, adverse climate-related health impacts are expected to worsen worldwide, affecting billions of people. Temperatures in Europe are warming at twice the rate of the global average, threatening the health of populations across the continent and leading to unnecessary loss of life. The Lancet Countdown in Europe was established in 2021, to assess the health profile of climate change aiming to stimulate European social and political will to implement rapid health-responsive climate mitigation and adaptation actions. In 2022, the collaboration published its indicator report, tracking progress on health and climate change via 33 indicators and across five domains. This new report tracks 42 indicators highlighting the negative impacts of climate change on human health, the delayed climate action of European countries, and the missed opportunities to protect or improve health with health-responsive climate action. The methods behind indicators presented in the 2022 report have been improved, and nine new indicators have been added, covering leishmaniasis, ticks, food security, health-care emissions, production and consumption-based emissions, clean energy investment, and scientific, political, and media engagement with climate and health. Considering that negative climate-related health impacts and the responsibility for climate change are not equal at the regional and global levels, this report also endeavours to reflect on aspects of inequality and justice by highlighting at-risk groups within Europe and Europe's responsibility for the climate crisis

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

The rise of the consultants External advisers and public policy since 1979

Politics paper no. 4Available from British Library Document Supply Centre-DSC:9350.957(1996/28) / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

A physically based contributing area model for distributed flood forecasting in medium sizes catchments

SIGLEAvailable from British Library Document Supply Centre- DSC:D73946/87 / BLDSC - British Library Document Supply CentreGBUnited Kingdo