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2004 Health GIS Conference Proceedings Abstract
Estimating Infectious Disease Risk in the Absence of Incidence Data Author(s): D. Michael Thomas, Dynamics Technology, Inc.; Arthur Desch, Dynamics Technology, Inc; Holly Gaff, Dynamics Technology, Inc Estimating disease risk in developing countries may rely heavily on subjective analysis of data that can be incomplete and based on anecdotal reporting. GIS and remotely sensed data provide a more efficient and objective tool needed to support this analytical effort. For each disease of interest, a metric is defined and a relative risk scale value is assigned to physical parameters for a number of factors known to be associated with the disease, their potential for significant influence, and availability of data. A composite score combines relative risk scaled values to give the site specific risk. Detailed monthly maps are produced for a specific country or region and show the relative suitability of small land areas to support disease transmission. A color-coded disease "risk category" is assigned to each pixel. This method provides a useful first-order assessment of infectious disease risk when incidence data is lacking or of poor quality. Authors include: D. Michael Thomas, DO, MPH&TM, Arthur D. Desch, Holly D. Gaff, Ph.D., Suzanne K. Scheele, MS, Holly J. Butler, Ph.D.*, Mark Bramer, MS*,Richard K. Jordan, MS, Ph.D., Jonathan R. Davis, Ph.D., MS, Affiliations are from either Dynamics Technology, Inc. (Arlington, VA), or ESRI Professional Services Group (Vienna, VA). |
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