RE-PLAN: An Extensible Software Architecture to Facilitate Disaster Response Planning

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.

Challenges of Designing and Implementing High Consequence Infectious Disease Response

“…The need to integrate data with complex mathematical and simulation models requires the development of computational tools that can present decision-makers with data driven and spatially-targeted intervention strategies. The REsponse PLan ANalyzer (RE-PLAN) 18 , 19 is a spatially-explicit framework that provides the computational infrastructure needed to develop such systems 20 21 It is designed to store, manage, and analyze large amounts of disparate data and execute computational models through a point-and-click interface.…”

Quantifying Access Disparities in Response Plans

“…The computational methods described above have been integrated into the RE-PLAN Framework which has been deployed for practical use at state and county offices [ 7 ]. Collaborations with practitioners have proven instrumental for understanding planning constraints, capabilities, and practices.…”

“…An emergency response decision support system to assist decision makers in evaluating and building emergency response plans, and selecting an appropriate one during an emergency event has been presented in [ 17 ]. RE-PLAN, a computational framework developed for regional public health departments to design and analyze response plans provides methods that assist in the optimal placement and design of PODs [ 7 ]. However data-driven tools and methods that enable the quantification of vulnerable populations in a response plan and facilitate the design of plans that provide uniform access to the concerned populations are yet to be developed.…”

“…A response plan is considered feasible only if available mitigation resources are sufficient to serve and are accessible to the target population within short, mandated time frames. A response plan generated using current methods [ 7 ] [ 8 ] may seem feasible when considering the spatial distribution of PODs within a given geographic region, overall population density, and estimated traffic demands. However, the plan may fail to serve particular vulnerable subpopulations, resulting in access disparities during a bio-emergency.…”

“…The large amount of data required for response plan design and analysis necessitates the application of computational tools to aid public health experts in preparing for bio-emergencies. To this end, the REPLAN Framework was designed to provide computational methods to facilitate the design, analysis and optimization of response plans for emergencies [ 10 ] [ 7 ]. The research into quantifying access disparities described in this article builds upon this framework enabling the quantification vulnerabilities in the context of specific response plans.…”