University of California

About: University of California is a education organization based out in Oakland, California, United States. It is known for research contribution in the topics: Population & Layer (electronics). The organization has 55175 authors who have published 52933 publications receiving 1491169 citations. The organization is also known as: UC & University of California System.

Forecasting the global shortage of physicians: an economic- and needs-based approach

Abstract: OBJECTIVE: Global achievements in health may be limited by critical shortages of health-care workers. To help guide workforce policy, we estimate the future demand for, need for and supply of physicians, by WHO region, to determine where likely shortages will occur by 2015, the target date of the Millennium Development Goals. METHODS: Using World Bank and WHO data on physicians per capita from 1980 to 2001 for 158 countries, we employ two modelling approaches for estimating the future global requirement for physicians. A needs-based model determines the number of physicians per capita required to achieve 80% coverage of live births by a skilled health-care attendant. In contrast, our economic model identifies the number of physicians per capita that are likely to be demanded, given each country's economic growth. These estimates are compared to the future supply of physicians projected by extrapolating the historical rate of increase in physicians per capita for each country. FINDINGS: By 2015, the global supply of physicians appears to be in balance with projected economic demand. Because our measure of need reflects the minimum level of workforce density required to provide a basic health service that is met in all but the least developed countries, the needs-based estimates predict a global surplus of physicians. However, on a regional basis, both models predict shortages for many countries in the WHO African Region in 2015, with some countries experiencing a needs-based shortage, a demand-based shortage, or both. CONCLUSION: The type of policy intervention needed to alleviate projected shortages, such as increasing health-care training or adopting measures to discourage migration, depends on the type of shortage projected.

What is the Prevalence of Children with Special Health Care Needs? Toward an Understanding of Variations in Findings and Methods Across Three National Surveys

Abstract: Objectives To compare and consider sources of variation in the prevalence and characteristics of children with special health care needs (CSHCN) identified using the CSHCN Screener across the 2001 National Survey of Children with Special Health Care Needs (NS-CSHCN), the 2003 National Survey of Children’s Health (NSCH) and the 2001–2004 Medical Expenditures Panel Surveys (MEPS).

Synthetic analyses of phenotypic selection in natural populations: lessons, limitations and future directions

Abstract: There are now thousands of estimates of phenotypic selection in natural populations, resulting in multiple synthetic reviews of these data. Here we consider several major lessons and limitations emerging from these syntheses, and how they may guide future studies of selection in the wild. First, we review past analyses of the patterns of directional selection. We present new meta-analyses that confirm differences in the direction and magnitude of selection for different types of traits and fitness components. Second, we describe patterns of temporal and spatial variation in directional selection, and their implications for cumulative selection and directional evolution. Meta-analyses suggest that sampling error contributes importantly to observed temporal variation in selection, and indicate that evidence for frequent temporal changes in the direction of selection in natural populations is limited. Third, we review the apparent lack of evidence for widespread stabilizing selection, and discuss biological and methodological explanations for this pattern. Finally, we describe how sampling error, statistical biases, choice of traits, fitness measures and selection metrics, environmental covariance and other factors may limit the inferences we can draw from analyses of selection coefficients. Current standardized selection metrics based on simple parametric statistical models may be inadequate for understanding patterns of non-linear selection and complex fitness surfaces. We highlight three promising areas for expanding our understanding of selection in the wild: (1) field studies of stabilizing selection, selection on physiological and behavioral traits, and the ecological causes of selection; (2) new statistical models and methods that connect phenotypic variation to population demography and selection; and (3) availability of the underlying individual-level data sets from past and future selection studies, which will allow comprehensive modeling of selection and fitness variation within and across systems, rather than meta-analyses of standardized selection metrics.

Real-space quantum renormalization groups.

Abstract: Although originally thought to show great promise in solving quantum many-body problems on a lattice, numerical real-space renormalization-group techniques have had little success for such problems. We explore the nature of the difficulties involved by studying the applicaton of the method to the simple tight-binding model in one dimension. The standard approach fails dramatically for this model. We show that the key to successfully applying the renormalization-group technique lies in applying a variety of boundary conditions to a block in order to simulate the effect of neighboring blocks.