This paper examines National Institutes of Health (NIH) pediatric research spending in absolute terms and relative to the doubling of the NIH overall budget between fiscal years 1998 and 2003. Pediatric spending increased by an average annual rate of 12.8 percent during the doubling period (almost on par with the NIH average annual growth rate of 14.7 percent). However, the proportion of the total NIH budget devoted to the pediatric portfolio declined from 12.3 to 11.3 percent. We offer recommendations for implementing existing commitments to strengthen the pediatric research portfolio and to protect the gains of the doubling period.
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http://dx.doi.org/10.1377/hlthaff.23.5.113 | DOI Listing |
J Bone Joint Surg Am
October 2024
Department of Orthopaedic Surgery, University of California Los Angeles, Los Angeles, California.
Background: Musculoskeletal diseases are a major contributor to global human disability, but research in this area of medicine contends with chronic underfunding in the United States, receiving <2% of the National Institutes of Health (NIH) budget. The Orthopaedic Research and Education Foundation (OREF) serves as a vital nongovernmental organization, providing essential support for orthopaedic research. This study investigated the translation of various OREF grants into successful extramural federal funding discerning the clinician demographics and OREF award characteristics associated with increased chances of securing federal grants.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
December 2024
Department of Biology, University of Oxford, Oxford OX1 3SZ, United Kingdom.
Tracking the spread of emerging pathogens is critical to the design of timely and effective public health responses. Policymakers face the challenge of allocating finite resources for testing and surveillance across locations, with the goal of maximizing the information obtained about the underlying trends in prevalence and incidence. We model this decision-making process as an iterative node classification problem on an undirected and unweighted graph, in which nodes represent locations and edges represent movement of infectious agents among them.
View Article and Find Full Text PDFIEEE Sens J
May 2024
Dept. of Electrical and Computer Engineering and the Dept. of Computer Science, University of California - Los Angeles, Los Angeles, CA 90095, USA.
Long-term and fine-grained maritime localization and sensing is challenging due to sporadic connectivity, constrained power budget, limited footprint, and hostile environment. In this paper, we present the design considerations and implementation of , a rugged ultra-low-footprint undersea sensor tag with on-device AI-driven localization, online communication, and energy-harvesting capabilities. uses on-chip (< 30 kB) neural networks to track underwater objects within 3 meters with ~6 minutes of GPS outage from 9DoF inertial sensor readings.
View Article and Find Full Text PDFFront Res Metr Anal
November 2024
Office of Graduate Education, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.
When the National Institutes of Health (NIH) budget doubled in the late 1990s, it led to a rise in the number of PhD-trained scientists and to increased NIH-funded programs to diversify the biomedical workforce. This trend has seen more PhD scientists take on leadership roles as program directors in academia. These program directors are often highly skilled in research design and data analysis, and they bring a scholarly approach to their administrative duties.
View Article and Find Full Text PDFSci Data
December 2024
Emory University, Rollins School of Public Health, Atlanta, GA, USA.
Many current gridded surface meteorological datasets are inadequate for quantifying near-surface spatiotemporal variability because they do not fully represent the impacts of land surface heterogeneity. Of note, explicit representation of the spatial structure and magnitude of local urban warming are usually lacking. Here we enhance the representation of spatial meteorological variability over urban areas in the conterminous United States (CONUS) by employing the High-Resolution Land Data Assimilation System (HRLDAS), which accounts for the fine-scale impacts of spatiotemporally varying land surfaces on weather.
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