Geovisualization and Spatial Analysis of Cancer Data

  • Maceachren, Alan A.M. (PI)

Project: Research project

Project Details


DESCRIPTION (provided by applicant): The research proposed here will develop, implement, assess, and disseminate the next generation of cross-platform, visually-enabled geospatial analysis methods and tools to support cancer-related public health research and policy. The primary objective of the work is to develop a coordinated visual, statistical, and computational approach that extends current abilities to explore, identify, investigate, and explain spatial patterns of cancer incidence and mortality, and their relationships to population demographics and health policy. Of special note are new mechanisms to assess the potential for errors of omission and commission in that analysis The proposed methods and tools will facilitate the integration of epidemiological, demographic, and health-policy data, enabling researchers and analysts to take a holistic view of communities, their health with respect to cancer, and relationships to health policy (e.g. screening, accessibility). A series of proof-of-concept case studies will be used to demonstrate and assess the methods and tools developed and, at the same time, to address specific cancer research questions relevant to the Appalachia Cancer Network (ACN). Formal usability assessment methods will be applied throughout the human-centered process of software design, implementation, and deployment. The goal of these assessments will be to ensure that the methods and tools developed are both accessible to and useable by the cancer researchers and analysts whose work they are intended to support. We will take full advantage of outreach efforts within the ACN and the Center for Spatially Integrated Social Science (CSISS), to disseminate software developed and to provide training in its use to the cancer research and policy communities within Appalachia and beyond.
Effective start/end date4/1/023/31/04


Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.