RE-PLAN uses population data at the individual or household level to make it easy to:
- Determine the number of PODs needed for a region.
- Choose POD locations from a list of available facilities.
- Allocate SNS and personnel across chosen PODs to complete dispensing within time limits.
- Assign an equal population to each POD location.
- Minimize the distance the population must travel.
- Examine POD facilities without leaving the office by automatically linking to Google Earth’s 3D imagery.
- Analyze traffic resulting from plan activation.
- Identify vulnerable and at-risk populations to minimize access disparities including:
- Lack of access to transportation.
- Inability to communicate in English.
- Special needs related to age.
RE-PLAN was created at the Center for Computational Epidemiology and Response Analysis (CeCERA).
Support for the RE-PLAN project has been provided by the National Institutes of Health (1R01LM011647-01 and 1R15LM010804-01), the National Science Foundation (NSF 1514390), the Texas Department of State Health Services, and Tarrant County, TX.
- Indrakanti S, Mikler AR, O’Neill M, II, Tiwari C (2016) Quantifying Access Disparities in Response Plans. PLoS ONE 11(1): e0146350.
- Ramisetty-Mikler, S., Mikler, A. R., O’Neill, M., & Komatz, S. J. (2015). Conceptual Framework and Quantification of Population Vulnerability for Effective Emergency Response Planning. Journal of Emergency Management, 13(3), 227–238. http://doi.org/DOI:10.5055
- O’Neill II, M., Indrakanti, S., Schneider, T., & Mikler, A. R. (2014). RE-PLAN: An Extensible Software Architecture to Facilitate Disaster Response Planning. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 1569–1583.
- Jimenez, T., Mikler, A. R., & Tiwari, C. (2012). A Novel Space Partitioning Algorithm to Improve Current Practices in Facility Placement. IEEE Transactions on Systems, Man, and Cybernetics. Part A, Systems and Humans : A Publication of the IEEE Systems, Man, and Cybernetics Society, 42(5), 1194–1205. http://doi.org/10.1109/TSMCA.2012.2183360
- Jimenez, T., Tiwari, C., Mikler, A. R., & II, M. O. (2012). Maps, Rates, and Fuzzy Mountains: Generating Meaningful Risk Maps. In IEEE International Conference on Bioinformatics and Biomedicine. Philadelphia, PA.
- O’Neill II, M., Mikler, A. R., & Schneider, T. (2011). An Extensible Software Architecture to Facilitate Disaster Response Planning. In BIOCOMP’11. Las Vegas, NV.
- Schneider, T., & Mikler, A. R. (2010). RE-PLAN: A Computational Tool for Response Plan Analysis. International Journal of Functional Informatics and Personalised Medicine, 3(2), 103–121.
- Schneider, T., Mikler, A. R., & O’Neill II, M. (2009). Analyzing Response Feasibility for Bioemergencies. In Proceedings of the 2009 International Joint Conferences on System Biology, Bioinformatics and Intelligent Computing. Shanghai, China.
- Schneider, T., Mikler, A. R., & O’Neill II, M. (2009). Computational Tools for Evaluating Bioemergency Contingency Plans. In Proceedings of the 2009 International Conference on Disaster Management.
- Indrakanti, Saratchandra. Computational Methods for Vulnerability Analysis and Resource Allocation in Public Health Emergencies. Denton, Texas. UNT Digital Library. http://digital.library.unt.edu/ark:/67531/metadc804902/. Watch video of dissertation defense.
- O’Neill II, Martin Joseph. A Computational Methodology for Addressing Differentiated Access of Vulnerable Populations During Biological Emergencies. Denton, Texas. UNT Digital Library. http://digital.library.unt.edu/ark:/67531/metadc699851/. Watch video of dissertation defense.
- Schneider, Tamara. A Framework for Analyzing and Optimizing Regional Bio-Emergency Response Plans. Denton, Texas. UNT Digital Library. http://digital.library.unt.edu/ark:/67531/metadc33200/.