University of California Los Angeles
BIOSTATISTICS & OTHER MATH SCI
Los Angeles · United States
NIH R01 · 2025
Bayesian Modeling and Inference for High-Dimensional Disease Mapping and Boundary Detection"
Project Summary/Abstract This application seeks to advance statistical methods within the Bayesian inferential paradigm for disease map- ping and spatial boundary analysis. Disease mapping is an epidemiological technique used to describe the geographic variation of disease and to generate etiological hypotheses about the possible causes for apparent differences in risk. The last decade has seen an explosion of interest in disease mapping, with recent method- ological developments in advanced spatial statistics and increasing availability of computerized Geographic In- formation Systems (GIS) technology. Spatial biostatisticians, data scientists and epidemiologists today routinely encounter…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.