Geospatial Workforce Trends in the United States

International Journal of Applied Geospatial Research, Vol. 1, Issue 1, 2010

Lawrence Estaville

“Because of definitional problems regarding what is meant by the term “geospatial workforce,” specific reliable data are difficult to obtain about this increasingly important employment sector. This study reviews pertinent literature and U.S. Department of Labor datasets to corroborate the general sense that the geospatial workforce in the U.S. will continue robust expansion well into the next decade. However, because of this strong growth, an imbalance will remain in which demand outstrips supply, particularly in the more sophisticated modeling, design, and research positions, in the geospatial workforce.”

Common Errors in Disease Mapping

Geospatial Health, Volume 4, Number 2, May 2010, Pages 139-154

Ricardo Ocaña-Riola

“Many morbid-mortality atlases and small-area studies have been carried out over the last decade. However, the methods used to draw up such research, the interpretation of results and the conclusions published are often inaccurate. Often, the proliferation of this practice has led to inefficient decision-making, implementation of inappropriate health policies and negative impact on the advancement of scientific knowledge. This paper reviews the most frequent errors in the design, analysis and interpretation of small-area epidemiological studies and proposes a diagnostic evaluation test that should enable the scientific quality of published papers to be ascertained. Nine common mistakes in disease mapping methods are discussed. From this framework, and following the theory of diagnostic evaluation, a standardised test to evaluate the scientific quality of a small-area epidemiology study has been developed. Optimal quality is achieved with the maximum score (16 points), average with a score between 8 and 15 points, and low with a score of 7 or below. A systematic evaluation of scientific papers, together with an enhanced quality in future research, will contribute towards increased efficacy in epidemiological surveillance and in health planning based on the spatio-temporal analysis of ecological information.”