Citation

O'Neill M, Mikler AR, Indrakanti S, Tiwari C, Jimenez T. IEEE Trans. Syst Man. Cybern. Syst. 2014; 44(12): 1569-1583.

Affiliation

Center for Computational Epidemiology and Response Analysis University of North Texas, Denton, TX USA.

Copyright

(Copyright © 2014, Institute of Electrical and Electronics Engineers)

DOI

10.1109/TSMC.2014.2332137

PMID

25419503

Abstract

Computational tools are needed to make data-driven disaster mitigation planning accessible to planners and policymakers without the need for programming or GIS expertise. To address this problem, we have created modules to facilitate quantitative analyses pertinent to a variety of different disaster scenarios. These modules, which comprise the REsponse PLan ANalyzer (RE-PLAN) framework, may be used to create tools for specific disaster scenarios that allow planners to harness large amounts of disparate data and execute computational models through a point-and-click interface. Bio-E, a user-friendly tool built using this framework, was designed to develop and analyze the feasibility of ad hoc clinics for treating populations following a biological emergency event. In this article, the design and implementation of the RE-PLAN framework are described, and the functionality of the modules used in the Bio-E biological emergency mitigation tool are demonstrated.

Language: en