From a Public Health Perspective
RE-PLAN was originally designed to be used by public health planners to build response plans for anthrax or smallpox events. Planners from public health agencies can start building response plans in RE-PLAN in many different ways - by importing existing plans, by starting from scratch, or through some hybrid of these two. RE-PLAN enables users to build plans by leveraging information such as dispensing throughput rate capabilities and the numbers of dispensing lanes an average POD would have to determine how many points of dispensing (PODs) would be required across a particular jurisdiction. If POD locations have not yet been determined, RE-PLAN helps users quickly and easily select from existing facility locations. For example, if there are 3,000 potential facility locations (e.g. schools, pharmacies, places of worship, etc.) across a particular jurisdiction, but that jurisdiction only needs 50 PODs, RE-PLAN can quickly help the planner choose 50 locations out of the 3,000. It performs this selection based on the geospatial distribution of the population across the jurisdiction. Planners can use RE-PLAN to analyze these PODs by calculating the number of dispensing lanes that would be required at each individual POD location and by assessing the feasibility of each individual POD facility towards hosting these numbers of dispensing lanes. Planners can manually fine-tune their plans through RE-PLAN's point-and-click interface and interactive maps.
Once these initial plans have been developed, the planner can use RE-PLAN to quantify the distribution of specific special, vulnerable, and at-risk populations across the set of PODs. RE-PLAN uses a needs-based vulnerability analysis approach to provide planners with information they can directly use to make resource distribution decisions. For example, RE-PLAN provides information regarding the specific languages spoken by non-English speaking populations. This information can be used by planners to distribute potentially scarce resources including language translators, literature, and signage for specific languages across their POD locations.
RE-PLAN has since been extended into a COVID-19 mass vaccination planning context. To learn more about how RE-PLAN can help build more effective, efficient, and equitable COVID-19 mass vaccination plans, please visit our COVID-19 RE-PLAN page.
The Anthrax version of RE-PLAN includes MCM distribution features. The novel approach to this logistical problem implemented into RE-PLAN was designed specifically to only ask planners (as input into the system) questions regarding RSS-to-POD delivery requirements that they can easily answer. Therefore, RE-PLAN does not ask questions regarding the number of delivery vehicles to be used or the starting RSS sites for each vehicle (in the case that multiple RSS sites are used). Rather, RE-PLAN was designed to provide planners with options to enable them to easily explore tradeoffs between the number of delivery vehicles used and the total time required to complete RSS-to-POD deliveries across the jurisdiction. The system then provides printable routing documents for each delivery vehicle that can be handed to vehicle drivers at the RSS. Further, RE-PLAN provides printable loading documents that can be used by RSS staff to ensure that pallets of MCMs are loaded appropriately onto delivery vehicles to minimize unloading time at each POD site.
From a Computational Perspecitve
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.
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- 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/.