Bayesian Disease Mapping: Opportunities, Challenges, and New Frontiers in an Information- and Data-Rich Era

• Activity Number: 389
• Type: Roundtables
• Date/Time: Tuesday, August 6, 2013 : 12:30 PM to 1:50 PM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Ying MacNab*+
• Companies: University of British Columbia
• Keywords: Bayesian disease mapping ; Spatial statistics ; Bayesian hierarchical models ; Spatial epidemiology ; Public health information and knowledge ; Funding for disease mapping and related research

Abstract

Early developments of Bayesian disease mapping (BDM) methods aimed at a systematic methodology for "pooling data" and intelligent smoothing. The efforts were focused primarily on hierarchical modeling and analysis of sparse and noisy spatial and spatiotemporal small area data and inference with respect to the underlying spatial risks variations and clustering. Disease mapping issues have presented challenging and exciting statistical problems, leading to fascinating research opportunities in the field of spatial statistics and beyond. Progressive developments in BDM also brought new dimensions and tools to population-based public health and health policy research. This roundtable will be a discussion on BDM in this exciting data-rich era; opportunities, challenges, and new frontiers in the development of disease-mapping methodologies; and related applications. Recent experiences in the development of health metrics (the disability adjusted life years or DALYs) and indices, linking disease with socioeconomic and environmental risk factors, and evaluation of health service delivery and outcomes, with information and examples on grant funding opportunities, will be discussed.