RAPID: Computational Methods for Quantifying Regional Ebola-Specific Resource Coverage

University Of North Texas, Denton TX

Investigators

Abstract

Federal, state, and local agencies must understand the availability of regional Ebola-specific resources to develop effective response plans. This research shall result in the development of methodologies to integrate data pertaining to available regional health infrastructure with population-specific information to identify capabilities and resources for mitigating a potential Ebola outbreak. The primary focus is the design and implementation of computational tools that facilitate the quantification of the availability and distribution of resources across regional healthcare infrastructure, specifically resources that pertain to the isolation and treatment of Ebola patients. This research will have broader impact by improving best practices for the allocation of limited health resources to mitigate the effects of emerging or reemerging infectious diseases, which may threaten the United States. The resulting computational framework may become an integral component of the national chemical, biological, radiological, or nuclear (CBRN) preparedness effort. Further, the proposed research will involve students, providing them an opportunity to conduct research in an interdisciplinary STEM project. The proposed computational methods will construct a hierarchy of regional healthcare facilities and their corresponding Ebola-specific capabilities. Geospatial partitioning algorithms, such as Voronoi tessellation and uniform partitioning (UPAS) shall form the basis for delineating service regions corresponding to available healthcare facilities, thereby quantifying the per capita resource availability. This will enable agencies to address existing resource constraints and develop strategies for the effective allocation of Ebola-specific resources to achieve adequate regional coverage. Resource constraints can be expected to affect mitigation efforts differently at different levels of outbreak magnitude. As the magnitude of the outbreak increases, adequate local and regional resources must be made available to reflect the increased demand. The proposed computational methods shall provide the necessary functionalities to estimate the required levels of resource availability for different levels of outbreak magnitude. The design and implementation of new methods to augment an existing planning framework (RE-PLAN) will extend its applicability to the geospatial allocation of health resources pertinent to Ebola mitigation.