PEOPLES: A Tool to Measure Community Resilience

Abstract

This paper provides a novel method to quantitatively assess the resilience of communities at various scales. The proposed method is based on the PEOPLES framework and it takes an indicator-based approach as an engine for its algorithm. PEOPLES is a framework for identifying the different resilience aspects of a community and for providing new ways through which the decision makers can take actions. The framework comprises seven dimensions, each of which is the collection of more specific components and indicators. Each indicator is accompanied with a measure allowing the analytical computation of the indicator's performance. The measures are presented in the form of continuous functions whose parameters can be analytically obtained. The output of the methodology is a performance function for each indicator and a resilience index for the whole community. A case study illustrating the application of the methodology is also provided in the paper.

VIGIRISKS platform, a web-tool for single and multi-hazard risk assessment

“…In addition, to classical risk-based approach, Resilience-Based Risk approach (Kammouh et al 2018a;Marasco et al 2022) are in development. For example, PEOPLES framework (Kammouh et al 2018b) is a hierarchical framework developed at the Multidisciplinary Center of Earthquake Engineering Research (MCEER), in which objective is to identify the resilience capabilities of communities at different scales (spatial and temporal) and to anticipate potential responses of a community to future hazard events. The PEOPLES framework has also been implemented as an online tool (http:// www.…”

Computational models of community resilience

“…Modeling community resilience by static models has attracted research in recent years. Kammouh et al, (2018a) proposed a framework using distribution/density, composition, and socio-economic indicators as input leading to an output of a resilience function showing the serviceability of the community for a given period following the disaster.…”

“…Risk analysis simulations to advance the execution and efficiency decision making before and after disastrous events (Salgado et al, 2016), fragility curves in quantifying structural damage after a natural disaster (Kammouh et al, 2018a), and the implementation of performance-based earthquake engineering frameworks to model the post-earthquake recovery of a community of residential houses (Burton et al, 2015) have all contributed into finding a solution for bettering our communities' resilience. Nejat et al (2019) used a spatial regression model to predict households' recovery decisions from data available of the aftermath of Hurricane Sandy.…”

Multi-system intervention optimization for interdependent infrastructure

“…Consequently, the diagonal terms of IM are I ii = 1 and I can be asymmetric as a result of the non-reciprocal interaction behavior between the objects. The values of the interaction coefficients can be obtained from expert judgment [40,41].…”