Research
GeoSeer, Geostatistical software for health and exposure analysis
Pierre Goovaerts, BioMedware, Inc., PI
This work is supported by an SBIR phase I grant from the National Cancer Institute (R43-CA105819).
Research Abstract
The overall objective of this project is to develop the first geostatistical software to offer tools that are specifically designed for the analysis of health data (e.g. cancer rates), providing: description of spatial patterns of disease and identification of scales of variability, spatial smoothing and filtering to detect regional patterns and hotspots, spatial interpolation and stochastic modeling of exposure data, and the investigation and visualization of scale-dependent relationships between exposure and health data.
Instructional materials will be developed to promote the use of this relatively new methodology among health scientists.
Phase I of the project will:
- Build on a firm foundation of completed simulation studies to further demonstrate and evaluate the ability of geostatistics to accurately map underlying local- and regional-scale risk patterns and to investigate scale-dependent relationships among diseases and environmental factors.
- Conduct a requirement analysis to identify the optimal geostatistical methods and functionalities to incorporate in the software.
- Develop and test algorithms and a software prototype to evaluate feasibility of the proposed approach.
Sample regional risk surface and
semivariogram for Cervix cancer 1950-1969
Publications
Goovaerts, P. and G.M. Jacquez. 2004. Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York. International Journal of Health Geographics, 3: 14.
Goovaerts, P. 2005. Simulation-based assessment of a geostatistical approach for estimation and mapping of the risk of cancer. In: Leuangthong O and Deutsch CV (eds) Geostatistics Banff 2004. Kluwer Academic Publishers, Dordrecht, The Netherlands, in press.
Goovaerts, P., Jacquez, G.M., and D.A. Greiling. 2005. Exploring scale-dependent correlations between cancer mortality rates using factorial kriging and population-weighted semivariograms. Geographical Analysis, 37, in press.
Goovaerts, P. and G.M. Jacquez. 2005. Detection of temporal changes in the spatial distribution of cancer rates using local Moran’s I and geostatistically simulated spatial neutral models. Journal of Geographical Systems 7: 137-159.
Goovaerts, P. 2005. Detection of spatial clusters and outliers in cancer rates using geostatistical filters and spatial neutral models. In: Soares A, Gomez-Hernandez J, and Froidevaux R (eds) geoENV V - Geostatistics for Environmental Applications. Kluwer Academic Publishers, Dordrecht, The Netherlands, in press.
Conference
BioMedware held a conference May 10, 2004 for planning and review of the GeoSeer project.