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Träfflista för sökning "WFRF:(Dowling Thomas) srt2:(2020-2023)"

Sökning: WFRF:(Dowling Thomas) > (2020-2023)

  • Resultat 1-4 av 4
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1.
  • Cable, Jennifer, et al. (författare)
  • Lessons from the pandemic : Responding to emerging zoonotic viral diseases-a Keystone Symposia report
  • 2022
  • Ingår i: Annals of the New York Academy of Sciences. - : Wiley. - 0077-8923 .- 1749-6632. ; 1518:1, s. 209-225
  • Tidskriftsartikel (refereegranskat)abstract
    • The COVID-19 pandemic caught the world largely unprepared, including scientific and policy communities. On April 10-13, 2022, researchers across academia, industry, government, and nonprofit organizations met at the Keystone symposium "Lessons from the Pandemic: Responding to Emerging Zoonotic Viral Diseases" to discuss the successes and challenges of the COVID-19 pandemic and what lessons can be applied moving forward. Speakers focused on experiences not only from the COVID-19 pandemic but also from outbreaks of other pathogens, including the Ebola virus, Lassa virus, and Nipah virus. A general consensus was that investments made during the COVID-19 pandemic in infrastructure, collaborations, laboratory and manufacturing capacity, diagnostics, clinical trial networks, and regulatory enhancements-notably, in low-to-middle income countries-must be maintained and strengthened to enable quick, concerted responses to future threats, especially to zoonotic pathogens.
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2.
  • Hagos, Desta Haileselassie, et al. (författare)
  • ExtremeEarth Meets Satellite Data From Space
  • 2021
  • Ingår i: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. - : Institute of Electrical and Electronics Engineers (IEEE). - 1939-1404 .- 2151-1535. ; 14, s. 9038-9063
  • Tidskriftsartikel (refereegranskat)abstract
    • Bringing together a number of cutting-edge technologies that range from storing extremely large volumes of data all the way to developing scalable machine learning and deep learning algorithms in a distributed manner and having them operate over the same infrastructure poses unprecedented challenges. One of these challenges is the integration of European Space Agency (ESA)'s Thematic Exploitation Platforms (TEPs) and data information access service platforms with a data platform, namely Hopsworks, which enables scalable data processing, machine learning, and deep learning on Copernicus data, and development of very large training datasets for deep learning architectures targeting the classification of Sentinel images. In this article, we present the software architecture of ExtremeEarth that aims at the development of scalable deep learning and geospatial analytics techniques for processing and analyzing petabytes of Copernicus data. The ExtremeEarth software infrastructure seamlessly integrates existing and novel software platforms and tools for storing, accessing, processing, analyzing, and visualizing large amounts of Copernicus data. New techniques in the areas of remote sensing and artificial intelligence with an emphasis on deep learning are developed. These techniques and corresponding software presented in this article are to be integrated with and used in two ESA TEPs, namely Polar and Food Security TEPs. Furthermore, we present the integration of Hopsworks with the Polar and Food Security use cases and the flow of events for the products offered through the TEPs.
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3.
  • Shangguan, Siyi, et al. (författare)
  • Health Impact and Cost-Effectiveness of Achieving the National Salt and Sugar Reduction Initiative Voluntary Sugar Reduction Targets in the United States : A Microsimulation Study.
  • 2021
  • Ingår i: Circulation. - : Wolters Kluwer. - 0009-7322 .- 1524-4539. ; 144:17, s. 1362-1376
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: High intake of added sugar is linked to weight gain and cardiometabolic risk. In 2018, the US National Salt and Sugar Reduction Initiative proposed government-supported voluntary national sugar reduction targets. This intervention's potential effects and cost-effectiveness are unclear.METHODS: A validated microsimulation model, CVD-PREDICT (Cardiovascular Disease Policy Model for Risk, Events, Detection, Interventions, Costs, and Trends), coded in C++, was used to estimate incremental changes in type 2 diabetes, cardiovascular disease (CVD), quality-adjusted life-years (QALYs), costs, and cost-effectiveness of the US National Salt and Sugar Reduction Initiative policy. The model was run at the individual level, incorporating the annual probability of each person's transition between health statuses on the basis of risk factors. The model incorporated national demographic and dietary data from the National Health and Nutrition Examination Survey across 3 cycles (2011 through 2016), added sugar-related diseases from meta-analyses, and policy costs and health-related costs from established sources. A simulated nationally representative US population was created and followed until age 100 years or death, with 2019 as the year of intervention start. Findings were evaluated over 10 years and a lifetime from health care and societal perspectives. Uncertainty was evaluated in a 1-way analysis by assuming 50% industry compliance and probabilistic sensitivity analyses through a second-order Monte Carlo approach. Model outputs included averted diabetes cases, CVD events and CVD deaths, QALYs gained, and formal health care cost savings, stratified by age, race, income, and education.RESULTS: Achieving the US National Salt and Sugar Reduction Initiative sugar reduction targets could prevent 2.48 million CVD events, 0.49 million CVD deaths, and 0.75 million diabetes cases; gain 6.67 million QALYs; and save $160.88 billion net costs from a societal perspective over a lifetime. The policy became cost-effective (<150 000/QALYs) at 6 years, highly cost-effective (<50 000/QALYs) at 7 years, and cost-saving at 9 years. Results were robust from a health care perspective, with lower (50%) industry compliance, and in probabilistic sensitivity analyses. The policy could also reduce disparities, with greatest estimated health gains per million adults among Black or Hispanic individuals, lower income, and less educated Americans.CONCLUSIONS: Implementing and achieving the US National Salt and Sugar Reduction Initiative sugar reformation targets could generate substantial health gains, equity gains, and cost savings.
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4.
  • Sinclair, Julia M A, et al. (författare)
  • Identifying the most important research, policy and practice questions for substance use, problematic alcohol use and behavioural addictions in autism (SABA-A) : A priority setting partnership
  • 2023
  • Ingår i: Comprehensive Psychiatry. - 0010-440X. ; 124, s. 1-7
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND: Autistic people are more likely to report problematic alcohol and other substance use when compared to the general population. Evidence suggests that up to one in three autistic adults may have an alcohol or other substance use disorder (AUD/SUD), although the evidence base for behavioural addictions is less clear. Autistic people may use substances or engage in potentially addictive behaviours as a means of coping with social anxiety, challenging life problems, or camouflaging in social contexts. Despite the prevalence and detrimental effects of AUD, SUD and behavioural addictions in community samples, literature focusing on the intersection between autism and these conditions is scarce, hindering health policy, research, and clinical practice.METHODS: We aimed to identify the top 10 priorities to build the evidence for research, policy, and clinical practice at this intersection. A priority-setting partnership was used to address this aim, comprising an international steering committee and stakeholders from various backgrounds, including people with declared lived experience of autism and/or addiction. First, an online survey was used to identify what people considered key questions about Substance use, alcohol use, or behavioural addictions in autistic people (SABA-A). These initial questions were reviewed and amended by stakeholders, and then classified and refined to form the final list of top priorities via an online consensus process.OUTCOMES: The top ten priorities were identified: three research, three policy, and four practice questions. Future research suggestions are discussed.
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