No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Measuring Community Disaster Resilience Over Time
Abstract
Natural disaster impacts can be mitigated by building community resilience and this recognition has elevated the importance of demonstrating the return on resilience investment. Subsequently, there is a demand for resilience measurement tools. The Baseline Resilience Indicator for Communities (BRIC), is an index based on variables representing resilience attributes identified in the literature. BRIC is representative of indices designed for national assessments, applies to multiple natural disasters at the county level in the US, and its application in national assessments has been demonstrated. This analysis tests the BRIC index in two longitudinal case studies by examining the variables that constitute the index. Specific variables used in the BRIC index are explored through the examination of the suitability of each variable for use in longitudinal studies at the county level and the variable’s skill in capturing known events and activities expected to have an impact on resilience. Detailed examination of each variable in the context of the community profile provides insights to improve formulations of variables. New variables are proposed to better capture community characteristics and actions that enhance resilience.
... It is also worth noting that a conceptualization of community capacity emphasizes two main aspects: the appropriation of structural assets (capitals or resources) and the community's agency (Matarrita-Cascante et al., 2017) to cope with and adapt to challenges. In other words, community capacity is strengthened by obtaining a particular set of assets as a static condition; at the same time, it requires a community's will, actions, and social interactions to mobilize such assets, rendering it a dynamic process (Matarrita-Cascante et al., 2017; see also McConkey & Larson, 2022;Mendis-Millard & Reed, 2007;Norris et al., 2008;Ntonis et al., 2019). Community agency, as a critical portion of community resilience, refers to 'the ability of a community to cultivate relationships between and within local people and organizations in order for them to unite, engage, and adapt to changing conditions while participating in decision-making and implementation of strategies' (Matarrita-Cascante et al., 2017, p. 116). ...
... Resilience as the capacity of the community to respond to and recover post-event (Cutter et al., 2008) differs from social vulnerabilities as the pre-event conditions of the community. Community resilience changes over time: it can increase, with investment in capacity and the development of community capital, or it can decline, with reductions in community resources (McConkey & Larson, 2022). 'Agency facilitation' is thus considered crucial in enhancing sustainability (Adhikari & Goldey, 2010) -especially in mediating the aspects of social capital and inducing it. ...
Community disaster resilience has become a key concept in the field of climate change and development, but it often remains a third party's terms (e.g. donors' or researchers') rather than being understood from local perspectives. In an attempt to understand it in local terms, and to exercise localism in seeking the next steps of a climate change adaptation project, this study used focal group interviews organized in a manner of local workshops in Battambang, Cambodia. Villagers were encouraged to speak about what they had (strengths and assets) and saw opportunities (although many were expected to come externally). Addressing threats, they pointed out some broader issues, such as market failure and structural power issues, such as crop pricing, which were never prioritized in the initial project, partly because of limited local participation in agenda setting. The strength of this research is its action-oriented data collection technique, which produced and shared findings that are meaningful to the community for possible interventions. The findings point to a holistic approach of (climate-driven disaster-) resilient development, which requires addressing governance and market issues. By engaging community members, we also hope these exercises have contributed to increasing their sense of ownership or to 'agency facilitation'. ARTICLE HISTORY
... The index is rooted in the Disaster Resilience of Place model, which states that the inherent conditions of a community, including its resilience, vary from place to place and impact how a community or region recovers from a hazard event (Cutter et al., 2008). BRIC has been critically evaluated (Camacho et al., 2023;McConkey & Larson, 2022) and adapted to new study areas (Javadpoor et al., 2021;Pazhuhan et al., 2023;Singh-Peterson et al., 2014). In addition, BRIC has been assessed over time (Cutter & Derakhshan, 2020), downscaled for the Gulf Coast region (Derakhshan et al., 2022), and is currently used in the NRI (Zuzak et al., 2023). ...
Community resilience measurement to natural hazards is becoming increasingly relevant due to the growth of federal programs and local and state resilience offices in the United States. This study introduces a methodology to co‐produce an actionable resilience metric to measure locally relevant and modifiable indicators of community resilience for the state of South Carolina. The “actionable” metrics, based on the Baseline Resilience Indicators for Communities (BRIC) index, are calculated at the county and tract scale and then compared to “conventional” versions of BRIC. Actionable BRICs perform better in reliability testing than conventional BRICs. Correlations across the two scales of BRIC construction show a stronger relationship between the actionable BRICs than conventional, though all are highly correlated. When mapped, actionable BRIC shows a shifted region of low resilience in the state when compared to conventional BRIC, suggesting that actionable and conventional BRICs are distinct. Scale differences show dissimilar drivers of resilience, with county‐level resilience driven by community, social, and environmental resilience and tract‐level resilience driven by social and institutional resilience. Actionable tract‐level BRIC appears to be the best representation of modifiable resilience for South Carolina, but it comes with trade‐offs, including calculation complexity and changing geographies over time. Regardless of scale, the resulting actionable indices offer a useful tracking mechanism for the state resilience office and highlight the importance of integrating top‐down and bottom‐up resilience perspectives to consider local drivers of resilience. The resulting methodology can be replicated in other states and localities to produce actionable and locally relevant resilience metrics.
... At the level of disaster resilience, Navid et al. proposed a quantitative method for assessing organizational resilience in sudden disasters considering preparedness actions (PAs) and verified the feasibility of the method [5]. McConkey et al. enhance community resilience by exploring the suitability of specific variables used in the BRIC index and the suitability of the variable capturing known events and expected activities that affect resiliency [6]. Žičkienė et al. put forward that the weighted sum of the impact of payment on the resilience of the main economic functions of the sector is regarded as the overall level of the impact of direct payment on the economic resilience of the sector [7]. ...
In the construction of urban rail transit projects, the disturbance of equipment, sudden failure, rainstorms, and other emergencies may bring serious safety risks. Resilience theory emphasizes the ability of the system to resist, adapt, absorb, and learn from risks in the whole process before, during, and after the occurrence of risks. It is introduced into the safety management of construction organization of urban rail transit projects to describe the ability of urban rail transit projects to cope with risks in the whole process of dealing with construction risks. This study defines the connotation of the resilience of the project construction organization and uses the literature frequency statistics method to determine the resilience evaluation indexes. The game theory combination weighting method is used to determine the index weights, and the cloud matter element model is used to establish the evaluation model of construction organization resilience of urban rail transit projects. Taking Nanchang West Station of Phase 1 Project of Nanchang Line 2 as an example, the validity and accuracy of the model are verified. The results show that the resilience grade of the construction organization of the project is “higher resilience,” which is consistent with the actual survey situation, and the evaluation model is reasonable. In addition, in the evaluation results, the key indexes and risk indexes of the project are determined, and the safety management measures of the construction organization of the project are put forward according to the key indexes and risk indexes.
... They reviewed research projects in which the concept of resilience had been used, including in terms of discrepancies in the very understanding of that term and the tools and methods used to study it. In the articles analysed, the researchers distinguished several domains of community resilience, including community capital, as well as social, economic, natural, human, physical, infrastructural, institutional domains (Ostadtaghizadeh et al., 2015; see also Mayunga, 2009;McConkey & Larson, 2022;Deng et al., 2022, p. 3). ...
On February 24, 2022, Russia attacked Ukraine, an independent country. Although the topic of academic library assistance directed to Ukrainian refugees has appeared in the media, the review of literature demonstrated that these activities have not been documented in the scientific literature so far.
The aim of the study was to find out what actions addressed to the Ukrainian refugees.
Polish academic libraries took to help build social resilience in case of war.
The study used quantitative and qualitative methods: the survey method and the heuristic method. The survey was sent to all directors of state academic libraries in Poland.
The collected data were divided into the domains: institutional, social, physical and economical. These domains were then used to design a library model of building community resilience in case of war, and to describe the links between these domains.
The multi-level spectrum of activities undertaken by the academic libraries in Poland to improve the situation of Ukrainians and described in this paper lead to the recognition that libraries: are important institutions of social trust, and in order to maintain this status, they have to respond to the needs of local communities on an ongoing basis.
Donor‐funded climate and disaster resilience programmes and projects aim to help build the capacities and resilience of communities. Measuring resilience is critical, therefore, in providing feedback, evidence, and accountability. This paper presents recent two‐year time‐series findings from an ongoing multi‐partner academic and practical collaboration pertaining to a climate change adaption project with rural communities in Cambodia. To measure community resilience, the study used the Flood Resilience Measurement for Communities, which measures, using mixed methods, disaster resilience capacities across five key dimensions of resilience: human, social, physical, natural, and financial capitals. The study analysed and reported changes in these areas of resilience in the selected villages, generating insights into the strengths and weaknesses of flood resilience capacities in the region. This paper provides valuable guidance as to where investment can be most effective in different communities, confirming the usefulness of the tool in measuring resilience and assessing the effectiveness of the project concerned.
2020. The Authors. This study reports a new and significantly enhanced analysis of US flood hazard at 30 m spatial resolution. Specific improvements include updated hydrography data, new methods to determine channel depth, more rigorous flood frequency analysis, output downscaling to property tract level, and inclusion of the impact of local interventions in the flooding system. For the first time, we consider pluvial, fluvial, and coastal flood hazards within the same framework and provide projections for both current (rather than historic average) conditions and for future time periods centered on 2035 and 2050 under the RCP4.5 emissions pathway. Validation against high-quality local models and the entire catalog of FEMA 1% annual probability flood maps yielded Critical Success Index values in the range 0.69–0.82. Significant improvements over a previous pluvial/fluvial model version are shown for high-frequency events and coastal zones, along with minor improvements in areas where model performance was already good. The result is the first comprehensive and consistent national-scale analysis of flood hazard for the conterminous US for both current and future conditions. Even though we consider a stabilization emissions scenario and a near-future time horizon, we project clear patterns of changing flood hazard (3σ changes in 100 years inundated area of −3.8 to +16% at 1° scale), that are significant when considered as a proportion of the land area where human use is possible or in terms of the currently protected land area where the standard of flood defense protection may become compromised by this time.
Background:
Determining the optimal number of hospital beds is a complex and challenging endeavor and requires models and techniques which are sensitive to the multi-level, uncertain, and dynamic variables involved. This study identifies and characterizes extant models and methods that can be used to determine the required number of beds at hospital and regional levels, comparing their advantages and challenges.
Methods:
A systematic search was conducted using Web of Science, Scopus, Embase and PubMed databases, with the search terms hospital bed capacity, hospital bed need, hospital, bed size, model, and method.
Results:
Twenty-three studies met the criteria to be included in the review. Of these studies, a total of 11 models and 5 methods were identified, mainly designed to determine hospital bed capacity at the regional level. Common determinants of the required number of hospital beds in these models included demographic changes, average length of stay, admission rates, and bed occupancy rates.
Conclusions:
There are no specific norms for the required number of beds at hospital and regional levels, but some of the identified models and methods may be used to estimate this number in different contexts. Moreover, it is important to consider alternative approaches to planning hospital capacity like care pathways to fix the limitations of "bed numbers".
The measurement of community disaster resilience through the development of a comprehensive set of composite indicators is becoming increasingly commonplace. Despite this growing trend, there is neither an agreement upon a standard procedure nor a comprehensive assessment of existing measurement frameworks in the relevant literature. To tackle these challenges, this study (1) proposes an overarching eight-step procedure for composite indicator building and (2) develops a meta-level assessment framework to allow for a systematic review of existing disaster resilience measurement frameworks in application of composite indicator building. This meta-level framework was established on the basis of the proposed eight-step composite indicator building procedure and qualified with the introduction of 19 dimensions and 36 metrics for quality assessment. In order to select relevant disaster resilience measures for this analysis, the study applied a systematic survey to collect measures based on four inclusion criteria: community-based, multifaceted, quantitative, and operationalized. Accordingly, 17 resilience measurement frameworks were chosen for further analysis in this review. The results of the quality assessment demonstrated that, from the theoretical perspective, resilience assessments originate from either the socio-ecological or engineering fields and can be classified into two main types of resilience indices and tools. This differs from results of the methodological perspective, which indicate that resilience measures can be characterized as deductive or similar to hierarchical and inductive assessments.
The growing risk of natural and artificial or manufactured hazards combined with a lack of community preparedness have revealed the necessity for comprehensive and effective metrics for evaluating and improving a community's resilience, i.e., the ability of communities to prepare for, withstand, and recover from disasters. In this paper, the authors review existing community resilience metrics and tools, classifying them into one of three main categories: community-level, sector-specific, or sociological. The paper provides short descriptions of each metric and comparisons across metrics within the three main categories and across classes. The authors assess the strengths and limitations of these metrics, discuss challenges in improving community resilience, and provide recommendations for the development of new measures of resilience. The paper concludes with an outlook on the future of community resilience, particularly the need for metrics that apply across hazards, geographic areas, and factors affecting resilience. The authors propose that effective metrics are characterized by: breadth, measures that address community resilience comprehensively; utility, measures that are able to be utilized by the relevant entities to undertake actions to improve resilience; and scientific merit, measures that are scientifically validated through statistical methods, case studies, and fieldwork.
The concept of disaster resilience has gained attention in political spheres and news outlets over the past few years, yet relatively few empirical measures of the concept exist. Furthermore, research into urban resilience has dwarfed our understanding of disaster resilience in rural places. This schism in what is known about the differences between urban and rural places becomes the topic of this article. Employing a suite of spatial and statistical techniques using an established measure of community resilience, the Baseline Resilience Indicators for Communities (BRIC), we focus on two key questions to better explain the resilience divide between urban and rural areas of the United States. Nonparametric rank analysis, analysis of variance, and logistic regression help describe the relationships between rurality and disaster resilience in contrast to resilience in urban areas. Pinpointing the driving factors, or characteristics, of resilience in rural America compared to metropolitan America, accomplished through binary logistic regression, revealed notable distinctions. Resilience in urban areas is primarily driven by economic capital, whereas community capital is the most important driver of disaster resilience in rural areas. Within rural areas there is considerable spatial variability in the components of disaster resilience. This suggests that attempts to enhance resilience cannot be approached using a one-size-fits-most strategy given the variability in the primary drivers of disaster resilience at county scales.
Resilience is now a ubiquitous concept in many science and policy circles. It is a polysemic concept that has been defined differently in different disciplines and contexts. An often used definition, in the context of community resilience, is provided by the National Academies. According to this definition resilience is “the ability to prepare and plan for, absorb, recover from and more successfully adapt to adverse events” (the four abilities). Over the past two decades various tools have been developed for assessing community resilience. This study examines 36 selected community resilience assessment tools to find out if they are suitable for adequately addressing the four abilities of resilience. A framework, identifying various measures that can contribute to addressing each of the four resilience abilities is developed. Evaluating selected tools using this framework indicates only few of them are reasonably suitable for addressing measures related to the four resilience abilities. Overall performance of the selected tools is particularly poor in terms of addressing measures related to absorption and adaptation abilities. Detailed results related to performance of each tool are provided. Developers can use these results to understand shortcomings of their assessment tools and address them in the revised versions.
The concept of resilience is increasingly used in academic and policy circles. To operationalize this concept and reduce the ambiguities surrounding it, since the turn of the century, various resilience assessment methodologies have been introduced. This paper provides a critical review of 36 selected community resilience assessment tools. These tools have been developed by a variety of entities, including national and local organizations, international donor organizations, and academic researchers. First, an overview of the selected tools is presented. This overview analysis shows that while some commonalities exist, there are also considerable differences between the tools. Next, based on literature review, an analytical framework is developed that identifies six criteria for evaluating performance of resilience assessment tools. These are, namely, addressing multiple dimensions of resilience, accounting for cross-scale relationships, capturing temporal dynamism, addressing uncertainties, employing participatory approaches, and developing action plans. Results show that limited success has been achieved in addressing these criteria. In terms of comprehensiveness, the environmental dimension has received relatively less attention in spite of its significance for building community resilience. Further improvements are needed to account for dynamics over time and across space. More attention to employing iterative processes that involve scenario-based planning is needed to better address challenges associated with uncertainties. Results also show that more attention needs to be paid to stakeholder participation in developing assessment tools. The paper concludes by highlighting several other areas of weakness that need to be addressed and discussing major challenges that still remain.
Introduction: In the past decade significant attention has been given to the development of tools that attempt to measure the vulnerability, risk or resilience of communities to disasters. Particular attention has been given to the development of composite indices to quantify these concepts mirroring their deployment in other fields such as sustainable development. Whilst some authors have published reviews of disaster vulnerability, risk and resilience composite indicator methodologies, these have been of a limited nature. This paper seeks to dramatically expand these efforts by analysing 106 composite indicator methodologies to understand the breadth and depth of practice.
Methods: An extensive search of the academic and grey literature was undertaken for composite indicator and scorecard methodologies that addressed multiple/all hazards; included social and economic aspects of risk, vulnerability or resilience; were sub-national in scope; explained the method and variables used; focussed on the present-day; and, had been tested or implemented. Information on the index construction, geographic areas of application, variables used and other relevant data was collected and analysed.
Results: Substantial variety in construction practices of composite indicators of risk, vulnerability and resilience were found. Five key approaches were identified in the literature, with the use of hierarchical or deductive indices being the most common. Typically variables were chosen by experts, came from existing statistical datasets and were combined by simple addition with equal weights. A minimum of 2 variables and a maximum of 235 were used, although approximately two thirds of methodologies used less than 40 variables. The 106 methodologies used 2298 unique variables, the most frequently used being common statistical variables such as population density and unemployment rate. Classification of variables found that on average 34% of the variables used in each methodology related to the social environment, 25% to the disaster environment, 20% to the economic environment, 13% to the built environment, 6% to the natural environment and 3% were other indices. However variables specifically measuring action to mitigate or prepare for disasters only comprised 12%, on average, of the total number of variables in each index. Only 19% of methodologies employed any sensitivity or uncertainty analysis and in only a single case was this comprehensive.
Discussion: A number of potential limitations of the present state of practice and how these might impact on decision makers are discussed. In particular the limited deployment of sensitivity and uncertainty analysis and the low use of direct measures of disaster risk, vulnerability and resilience could significantly limit the quality and reliability of existing methodologies. Recommendations for improvements to indicator development and use are made, as well as suggested future research directions to enhance the theoretical and empirical knowledge base for composite indicator development.
A leading challenge in measuring social vulnerability to hazards is for output metrics to better reflect the context in which vulnerability occurs. Through a meta-analysis of 67 flood disaster case studies (1997–2013), this paper profiles the leading drivers of social vulnerability to floods. The results identify demographic characteristics, socioeconomic status, and health as the leading empirical drivers of social vulnerability to damaging flood events. However, risk perception and coping capacity also featured prominently in the case studies, yet these factors tend to be poorly reflected in many social vulnerability indicators. The influence of social vulnerability drivers varied considerably by disaster stage and national setting, highlighting the importance of context in understanding social vulnerability precursors, processes, and outcomes. To help tailor quantitative indicators of social vulnerability to flood contexts, the article concludes with recommendations concerning temporal context, measurability, and indicator interrelationships.
The landscape of disaster resilience indicators is littered with wide range of tools, scorecards, indices that purport to measure disaster resilience in some manner. This paper examines the existing qualitative and quantitative approaches to resilience assessment in order to delineate common concepts and variables. Twenty seven different resilience assessment tools, indices, and scorecards were examined. Four different parameters were used to distinguish between them—focus (on assets baseline conditions); spatial orientation (local to global), methodology (top down or bottom up), and domain area (characteristics to capacities). There is no dominant approach across these characteristics. In a more detailed procedure, fourteen empirically based case studies were examined that had actually implemented one of the aforementioned tools, indices, or scorecards to look for overlaps in both concepts measured and variables. The most common elements in all the assessment approaches can be divided into attributes and assets (economic, social, environmental, infrastructure) and capacities (social capital, community functions, connectivity, and planning). The greatest variable overlap in the case studies is with specific measures of social capital based on religious affiliation and civic organizations, and for health access (measured by the number of physicians). Based on the analysis a core set of attributes/assets, capacities, and proxy measures are presented as a path forward, recognizing that new data may be required to adequately measure many of the dimensions of community disaster resilience.
The Community and Regional Resilience Institute has conducted a number of projects and case studies examining the nature and characteristics of community resilience in order to identify processes, tools, and resources that could assist communities in strengthening their resilient capacities. This article begins by describing a theoretical framework for community resilience developed from literature review and community practice. The authors review the Community and Regional Resilience Institute’s practical work to assist selected communities in understanding and improving their resilience through two rounds of case studies and provide summaries of community outcomes and implications of the community work. The article also briefly describes the collaborative development process used to build a web-enabled system of tools, resources, and resilience knowledge that can be used by all communities to build and strengthen resilience. Finally, the article presents key observations arising from the community and collaborative development work and discusses their implications for other communities desiring to improve their resilience.
Despite the ubiquity of disaster and the increasing toll in human lives and financial costs, much research and policy remain focused on physical infrastructure–centered approaches to such events. Governmental organizations such as the Department of Homeland Security, United States Federal Emergency Management Agency, United States Agency for International Development, and United Kingdom’s Department for International Development continue to spend heavily on hardening levees, raising existing homes, and repairing damaged facilities despite evidence that social, not physical, infrastructure drives resilience. This article highlights the critical role of social capital and networks in disaster survival and recovery and lays out recent literature and evidence on the topic. We look at definitions of social capital, measurement and proxies, types of social capital, and mechanisms and application. The article concludes with concrete policy recommendations for disaster managers, government decision makers, and nongovernmental organizations for increasing resilience to catastrophe through strengthening social infrastructure at the community level.
Social vulnerability refers to the socioeconomic and demographic factors that affect the resilience of communities. Studies have shown that in disaster events the socially vulnerable are more likely to be adversely affected, i.e. they are less likely to recover and more likely to die. Effectively addressing social vulnerability decreases both human suffering and the economic loss related to providing social services and public assistance after a disaster. This paper describes the development of a social vulnerability index (SVI), from 15 census variables at the census tract level, for use in emergency management. It also examines the potential value of the SVI by exploring the impact of Hurricane Katrina on local populations.
There is increasing policy and research interest in disaster resilience, yet the extant literature is still mired in definitional debates, epistemological orientations of researchers, and differences in basic approaches to measurement. As a consequence, there is little integration across domains and disciplines on community resilience assessment, its driving forces, and geographic variability. Using US counties as the study unit, this paper creates an empirically-based resilience metric called the Baseline Resilience Indicators for Communities (BRIC) that is both conceptually and theoretically sound, yet, easy enough to compute for use in a policy context. A common set of variables were used to measure the inherent resilience of counties in the United States according to six different domains or capitals as identified in the extant literature – social, economic, housing and infrastructure, institutional, community, and environmental. Data were from public and freely accessible data sources. Counties in the US Midwest and Great Plains states have the most inherent resilience, while counties in the west, along the US-Mexico border, and along the Appalachian ridge in the east contain the least resilience. Further, it was found that inherent resilience is not the opposite of social vulnerability, but a distinctly different construct both conceptually and empirically. While understanding the overall variability in resilience, the BRIC is easily deconstructed to its component parts to provide guidance to policy makers on where investments in intervention strategies may make a difference in the improvement of scores. Such evidence-based research has an opportunity to influence public policy focused on disaster risk.
The objective of this research was to establish a holistic framework for defining and measuring disaster resilience for a community at various scales. Seven dimensions of community resilience have been identified and are represented by the acronym PEOPLES: Capital. The proposed PEOPLES Resilience Framework provides the basis for development of quantitative and qualitative models that measure continuously the resilience of communities against extreme events or disasters in any or a combination of the above-mentioned dimensions. Over the longer term, this framework will enable the development of geospatial and temporal decision-support software tools that help planners and other key decision makers and stakeholders to assess and enhance the resilience of their communities.
The benefit-cost-ratio (BCR), used in cost-benefit analysis (CBA), is an indicator that attempts to summarize the overall value for money of a project. Disaster costs continue to rise and the demand has increased to demonstrate the economic benefit of disaster risk reduction (DRR) to policy makers. This study compiles and compares original CBA case studies reporting DRR BCRs, without restrictions as to hazard type, location, scale, or other parameters. Many results were identified supporting the economic effectiveness of DRR, however, key limitations were identified, including a lack of: sensitivity analyses, meta-analyses which critique the literature, consideration of climate change, evaluation of the duration of benefits, broader consideration of the process of vulnerability, and potential disbenefits of DRR measures. The studies demonstrate the importance of context for each BCR result. Recommendations are made regarding minimum criteria to consider when conducting DRR CBAs.
The number of people affected by natural hazards is growing, as many regions of the world become subject to multiple hazards. Although volume of geophysical, sociological and economic knowledge is increasing, so are the losses from natural catastrophes. The slow transfer from theory to practice might lay in the difficulties of the communication process from science to policy-making, including perceptions by stakeholders from disaster mitigation practice regarding the usability of developed tools. As scientific evidence shows, decision-makers are faced with the challenge of not only mitigating against single hazards and risks, but also multiple risks, which must include the consideration of their interrelations. As the multi-hazard and risk concept is a relatively young area of natural risk governance, there are only a few multi-risk models and the experience of practitioners as to how to use these models is limited. To our knowledge, scientific literature on stakeholders’ perceptions of multirisk models is lacking. In this article we identify perceptions of two decision-making tools, which involve multi-hazard and multi-risk. The first one is a generic, multi-risk framework based on the sequential Monte Carlo method to allow for a straightforward and flexible implementation of hazard interactions, which may occur in a complex system. The second is a decision-making tool that integrates directly input from stakeholders by attributing weights to different components and constructing risks ratings. Based on the feedback from stakeholders, we found that interest in multi-risk assessment is high but that its application remains hampered by the complexity of processes involved.
Several attempts have recently been made to identify the key indicators of community resilience and to group them into an overall resilience index. These studies support the evaluation of the effectiveness of resilience during recovery, and they also help establish a yardstick by which to monitor progress in resilience enhancement over time. We examine existing resilience indices in relation to economic principles and evaluate their potential to gauge and improve post-disaster economic recovery, with a focus on businesses. We conclude that the majority of indicators in use to date are not necessarily pertinent to
measuring resilience at the micro-, meso- and macro-economic levels in the aftermath of a disaster. Contending that business behavior is the key to short-term recovery, we propose a framework for choosing appropriate short-run indicators toward the goal of developing an effective economic resilience index.
The United Nations Office for Disaster Risk Reduction reported that the 2011 natural disasters, including the earthquake and tsunami that struck Japan, resulted in 55 billion. Enhancing community and system resilience could lead to massive savings through risk reduction and expeditious recovery. The rational management of such reduction and recovery is facilitated by an appropriate definition of resilience and associated metrics. In this article, a resilience definition is provided that meets a set of requirements with clear relationships to the metrics of the relevant abstract notions of reliability and risk. Those metrics also meet logically consistent requirements drawn from measure theory, and provide a sound basis for the development of effective decision-making tools for multihazard environments. Improving the resiliency of a system to meet target levels requires the examination of system enhancement alternatives in economic terms, within a decision-making framework. Relevant decision analysis methods would typically require the examination of resilience based on its valuation by society at large. The article provides methods for valuation and benefit-cost analysis based on concepts from risk analysis and management.
There is considerable federal interest in disaster resilience as a mechanism for mitigating the impacts to local communities, yet the identification of metrics and standards for measuring resilience remain a challenge. This paper provides a methodology and a set of indicators for measuring baseline characteristics of communities that foster resilience. By establishing baseline conditions, it becomes possible to monitor changes in resilience over time in particular places and to compare one place to another. We apply our methodology to counties within the Southeastern United States as a proof of concept. The results show that spatial variations in disaster resilience exist and are especially evident in the rural/urban divide, where metropolitan areas have higher levels of resilience than rural counties. However, the individual drivers of the disaster resilience (or lack thereof)-social, economic, institutional, infrastructure, and community capacities- vary widely.
Part I of this two-part paper provided an overview of the HAZUS-MH Flood Model and a discussion of its capabilities for characterizing riverine and coastal flooding. Included was a discussion of the Flood Information Tool, which permits rapid analysis of a wide variety of stream discharge data and topographic mapping to determine flood-frequencies over entire floodplains. This paper reports on the damage and loss estimation capability of the Flood Model, which includes a library of more than 900 damage curves for use in estimating damage to various types of buildings and infrastructure. Based on estimated property damage, the model estimates shelter needs and direct and indirect economic losses arising from floods. Analyses for the effects of flood warning, the benefits of levees, structural elevation, and flood mapping restudies are also facilitated with the Flood Model.
A resilient community is one that does not experience serious degradation in critical services when a hazard occurs and, in the event of degradation or failure, recovers to a similar or better level of service in a reasonable amount of time. The most efficient means of making a community resilient is to make its critical services and capital robust - minimize damage/loss probability or the consequences from damage/loss through mitigation. If a community's critical services and capital are not robust, efforts must be put into recovery. Based on the measurable aspects of community capital, we have developed a simulation model called ResilUS that operationalizes community resilience across multiple, hierarchical scales in relation to a range of policy and decision variables associated with each scale. ResilUS is implemented using fragility curves to model loss and Markov chains to model recovery with respect to time. ResilUS was applied to the 1994 Northridge earthquake disaster in order to calibrate several output variables with empirical data. ResilUS represents a significant step forward for spatial decision support for disaster mitigation and recovery planning, in comparison to existing loss estimation models.
The purpose of this study was to measure the sets of adaptive capacities for Economic Development and Social Capital in the
Norris et al. (2008) community resilience model with publicly accessible population indicators. Our approach involved five steps. First, we conducted
a literature review on measurements of the capacities. Second, we created an exhaustive “wish list” of relevant measures that
operationalized the concepts presented in the literature. Third, we identified data sources and searched for archival, population-level
data that matched our indicators. Fourth, we systematically tested correlations of indicators within and across the theoretical
elements and used this information to select a parsimonious group of indicators. Fifth, we combined the indicators into composites
of Economic Development and Social Capital and an additive index of Community Resilience using Mississippi county data, and
validated these against a well-established index of social vulnerability and aggregated survey data on collective efficacy.
We found that our measure of community resilience capacities correlated favorably and as expected when validated with the
archival and survey data. This study provides the first step in identifying existing capacities that may predict a community’s
ability to “bounce back” from disasters, thereby reducing post-trauma health and mental health problems.
KeywordsResilience-Community resilience-Social capital-Disasters
Resilience is widely seen as a desirable system property in environmental management. This paper explores the concept of resilience to natural hazards, using weather-related hazards in coastal megacities as an example. The paper draws on the wide literature on megacities, coastal hazards, hazard risk reduction strategies, and resilience within environmental management. Some analysts define resilience as a system attribute, whilst others use it as an umbrella concept for a range of system attributes deemed desirable. These umbrella concepts have not been made operational to support planning or management. It is recommended that resilience only be used in a restricted sense to describe specific system attributes concerning (i) the amount of disturbance a system can absorb and still remain within the same state or domain of attraction and (ii) the degree to which the system is capable of self-organisation. The concept of adaptive capacity, which has emerged in the context of climate change, can then be adopted as the umbrella concept, where resilience will be one factor influencing adaptive capacity. This improvement to conceptual clarity would foster much-needed communication between the natural hazards and the climate change communities and, more importantly, offers greater potential in application, especially when attempting to move away from disaster recovery to hazard prediction, disaster prevention, and preparedness.
Communities have the potential to function effectively and adapt successfully in the aftermath of disasters. Drawing upon literatures in several disciplines, we present a theory of resilience that encompasses contemporary understandings of stress, adaptation, wellness, and resource dynamics. Community resilience is a process linking a network of adaptive capacities (resources with dynamic attributes) to adaptation after a disturbance or adversity. Community adaptation is manifest in population wellness, defined as high and non-disparate levels of mental and behavioral health, functioning, and quality of life. Community resilience emerges from four primary sets of adaptive capacities--Economic Development, Social Capital, Information and Communication, and Community Competence--that together provide a strategy for disaster readiness. To build collective resilience, communities must reduce risk and resource inequities, engage local people in mitigation, create organizational linkages, boost and protect social supports, and plan for not having a plan, which requires flexibility, decision-making skills, and trusted sources of information that function in the face of unknowns.
During the past four decades (1960–2000), the United States experienced major transformations in population size, development patterns, economic conditions, and social characteristics. These social, economic, and built-environment changes altered the American hazardscape in profound ways, with more people living in high-hazard areas than ever before. To improve emergency management, it is important to recognize the variability in the vulnerable populations exposed to hazards and to develop place-based emergency plans accordingly. The concept of social vulnerability identifies sensitive populations that may be less likely to respond to, cope with, and recover from a natural disaster. Social vulnerability is complex and dynamic, changing over space and through time. This paper presents empirical evidence on the spatial and temporal patterns in social vulnerability in the United States from 1960 to the present. Using counties as our study unit, we found that those components that consistently increased social vulnerability for all time periods were density (urban), race/ethnicity, and socioeconomic status. The spatial patterning of social vulnerability, although initially concentrated in certain geographic regions, has become more dispersed over time. The national trend shows a steady reduction in social vulnerability, but there is considerable regional variability, with many counties increasing in social vulnerability during the past five decades.
• disasters
• inequality
Mitigation ameliorates the impact of natural hazards on communities by reducing loss of life and injury, property and environmental damage, and social and economic disruption. The potential to reduce these losses brings many benefits, but every mitigation activity has a cost that must be considered in our world of limited resources. In principle benefit-cost analysis (BCA) can be used to assess a mitigation activity’s expected net benefits (discounted future benefits less discounted costs), but in practice this often proves difficult. This paper reports on a study that refined BCA methodologies and applied them to a national statistical sample of FEMA mitigation activities over a ten-year period for earthquake, flood, and wind hazards. The results indicate that the overall benefit-cost ratio for FEMA mitigation grants is about 4 to 1, though the ratio varies according to hazard and mitigation type.
This study presents the first systematic literature review of academic research on the FEMA Community Rating System (CRS) program. The CRS is a voluntary program created in 1990 as a means to incentivize communities in the United States to implement floodplain management activities that surpass those required under the National Flood Insurance Program. As participating communities adopt additional flood mitigation measures, flood insurance policyholders in those communities receive reductions in their flood insurance premiums. To identify studies for inclusion, the authors searched three academic databases using the keywords “Community Rating System” and “Federal Emergency Management Agency” and “Community Rating System” and “FEMA.” The search uncovered 44 studies that met the selection criteria (e.g., peer-reviewed, focus on CRS, and empirical) and are included in the review. The findings provide significant insights into the current state of research on the CRS. This paper concludes by providing some recommendations to policymakers aiming to enhance communities’ resilience to floods and by outlining a future research agenda for the academic and practitioner communities.
The allure of disaster resilience studies continues to garner interest by policy makers and academics alike. While there are advances in assessing communities’ resilience to natural hazards at different scales, monitoring changes in resilience lags behind. This paper updates the 2010 Baseline Resilience Index for Communities (BRIC) using the six different domains of disaster resilience. The purpose is to test for significant spatial and temporal change in county index values by providing a comparative assessment of increased or decreased resilience over a five-year period across the U.S. The significance of monitoring change is to empirically demonstrate the dynamic nature of resilience and the causal mechanisms that lead to increasing or decreasing resilience in places. Such evidence sets the stage for implementing intervention policies or programs designed to enhance disaster resilience. The national distribution of BRIC index values in 2015 is generally similar to the 2010 BRIC distribution, but there are some notable regional differences. For example, there is a decrease in resilience in the South, the Great Lakes states, and the Central U.S., with improved resilience in the west and Pacific Coast states. The individual domains of institutional resilience and community capital, have the highest and lowest level of variation, respectively.
Resilience planning and emergency management require policymakers and agency leaders to make difficult decisions regarding which at-risk populations should be given priority in the allocation of limited resources. Our work focuses on benchmarking neighborhood resilience by developing a unified, multi-factor index of local and regional resilience capacity: the Resilience to Emergencies and Disasters Index (REDI). The strength of the REDI methodology is the integration of measures of physical, natural, and social systems – operationalized through the collection and analysis of large-scale, heterogeneous, and high resolution urban data – to classify and rank the relative resilience capacity embedded in localized urban systems. Feature selection methodologies are discussed to justify the selection of included indicator variables. Hurricane Sandy is used to validate the REDI scores by measuring the recovery periods for neighborhoods directly impacted by the storm. Using over 12,000,000 records for New York City’s 311 service request system, we develop a proxy for neighborhood activity, both pre- and post-event. Hurricane Sandy had a significant and immediate impact on neighborhoods classified as least resilient based on the calculated REDI scores, while the most resilient neighborhoods were shown to better withstand disruption to normal activity patterns and more quickly recover to pre-event functional capacity.
Due to persistent and serious threats from natural disasters around the globe, many have turned to resilience and vulnerability research to guide disaster preparation, recovery, and adaptation decisions. In response, scholars and practitioners have put forth a variety of disaster indices, based on quantifiable metrics, to gauge levels of resilience and vulnerability. However, few indices are empirically validated using observed disaster impacts and, as a result, it is often unclear which index should be preferred for each decision at hand. Thus, we compare and empirically validate five of the top U.S. disaster indices, including three resilience indices and two vulnerability indices. We use observed disaster losses, fatalities, and disaster declarations from the southeastern United States to empirically validate each index. We find that disaster indices, though thoughtfully substantiated by literature and theoretically persuasive, are not all created equal. While four of the five indices perform as predicted in explaining damages, only three explain fatalities and only two explain disaster declarations as expected by theory. These results highlight the need for disaster indices to clearly state index objectives and structure underlying metrics to support validation of the results based on these goals. Further, policymakers should use index results carefully when developing regional policy or investing in resilience and vulnerability improvement projects.
The federal government plays a significant role in emergency management, which generally refers to activities associated with avoiding and responding to natural and human-caused hazards. Emergency management in the United States is highly decentralized and contextual in nature: activities often involve multiple jurisdictions as well as a vast number of agencies, nongovernmental organizations, and private sector entities. In addition, the number and type of actors involved in an incident will vary tremendously depending on the context and severity of the event. Similarly, the legal framework through which emergency management functions and activities are authorized is also decentralized and stems from multiple authorities. Congress annually appropriates funds for a wide range of activities and efforts related to emergency management. For example, between 2005 and 2011 Congress provided an average of 120 billion through various federal agencies to help the Gulf Coast Region recover from the hurricanes that hit the Gulf Coast in 2005 and 2008. In recent years congressional interest in emergency management has focused on funding, program administration, and program coordination-both among federal agencies and state emergency management agencies. This report provides an introduction to the principles and foundations of federal emergency management in the United States and a description of the activities of the federal agencies that provide assistance, focusing primarily on the Federal Emergency Management Agency, but also including information on the National Guard, Department of Agriculture, Department of Defense, Army Corps of Engineers, Department of Health and Human Services, Department of Housing and Urban Development, Department of Transportation, Environmental Protection Agency, Forest Service, and Small Business Administration. This report is designed to provide Members of Congress and congressional staff with a general overview of principles and foundations of federal emergency management in the United States as well as the types of activities provided by various federal agencies. The report begins with a description of the four phases of emergency management: (1) mitigation, (2) preparedness, (3) response, and (4) recovery, and includes examples of some of the activities that take place in each of these phases. The report then discusses a recent movement at the federal level to carry out these phases of emergency management through a system of frameworks. The frameworks include (1) the National Prevention Framework, (2) the National Protection Framework, (3) the National Mitigation Framework, (4) the National Response Framework, and (5) the National Disaster Recovery Framework. The frameworks are used to designate roles and responsibilities and coordinate various activities. Next, this report describes the process for requesting federal assistance for major disasters, emergencies, and fire suppression. The declaration section also includes brief summaries of the types of assistance provided through each type of declaration. This discussion is followed by description of federal-to-state cost shares, how federal assistance is funded, and the process through which FEMA requests assistance from other federal entities. The section then provides a description of the close-out process-the process in which FEMA terminates its recovery efforts. The report includes a discussion of key federal laws and policies that influence federal emergency management, and concludes by highlighting some of the federal activities that take place in response to emergencies and disasters.
Objective: Data from a sample of 391 respondents who responded to ABC News Hurricane Katrina Anniversary Poll, August 2006, are used to test the relationship between predictor variables (social vulnerability index, insurance and severity of damage in living area) and the dependent variable (perceived disaster impact). Methods: Multiple regression is used to test the theoretical relationships. The dependent variable disaster impact is regressed on seven predictor variables simultaneously. Results: Social vulnerability has a statistically significant, positive effect on perceived disaster impact. Fully insured variable has a statistically significant, negative effect on disaster impact. Finally, severely damaged living area has a statistically significant, positive effect on disaster impact. Conclusion: The social vulnerability theory holds true in the context of Hurricane Katrina. Those who possess mixed characteristics of social vulnerability tend to be more affected by the impact of a disaster. Insurance tends to help lessen the disaster impact when individuals have the policies that cover all of their property. Finally, those who live in areas that are severely damaged from a disaster tend to experience more impact than those whose living areas are less damaged or not damaged.
This article contributes to the disaster literature by measuring and connecting two concepts that are highly related but whose relationship is rarely empirically evaluated: social vulnerability and community resilience. To do so, we measure community resilience and social vulnerability in counties across the United States and find a correlation between high levels of vulnerability and low levels of resilience, indicating that the most vulnerable counties also tend to be the least resilient. We also find regional differences in the distribution of community resilience and social vulnerability, with the West being particularly vulnerable while the Southeast is prone to low levels of resilience. By looking at both social vulnerability and community resilience, we are able to map communities’ social risks for harm from threats as well as their capacities for recovering and adapting in the aftermath of hazards. This provides a more complete portrait of the communities that might need the most assistance in emergency planning and response, as well as whether such interventions will need to be tailored toward reducing damage or finding the path to recovery.
How communities respond to and recover from damaging hazard events could be contextualized in terms of their disaster resilience. Although numerous efforts have sought to explain the determinants of disaster resilience, the ability to measure the concept is increasingly being seen as a key step toward disaster risk reduction. The development of standards that are meaningful for measuring resilience remains a challenge, however. This is partially because there are few explicit sets of procedures within the literature that outline how to measure and compare communities in terms of their resilience. The primary purpose of this article is to advance the understanding of the multidimensional nature of disaster resilience and to provide an externally validated set of metrics for measuring resilience at subcounty levels of geography. A set of metrics covering social, economic, institutional, infrastructural, community-based, and environmental dimensions of resilience was identified, and the validity of the metrics is addressed via real-world application using Hurricane Katrina and the recovery of the Mississippi Gulf Coast in the United States as a case study.
Indicators of natural disaster resilience are factors that impact the ability to cope with and adapt to a natural disaster and climate change events. They can either contribute to or detract from resilience. Existing research has emphasized the importance of quantifying resilience in order to estimate baseline resilience and measure progress toward resilience enhancement. Previous attempts at quantification of resilience have not incorporated place-specific indicators or differential weighting of indicators for prioritization of resilience enhancement actions. Previous research efforts have also not incorporated spatial and temporal contexts when attempting to quantify resilience indicators. This research demonstrates the importance for quantifying resilience place-specific indicators, differential weighting of indicators, and the spatial and temporal contexts of indicators for resilience estimation and quantification through a case study of Sarasota County, Florida. This case study was conducted in four phases: preliminary interviews, plan review, focus group, and spatial analysis. Preliminary interviews were intended to contribute to development of research goals. The plan review process served to identify Sarasota County's planning priorities to determine possible indicators of resilience unique to Sarasota County as well as existing and planned county hazard mitigation strategies. The focus group was concerned with identifying resilience indicators through a workshop with officials from Sarasota County. The spatial analysis portion used findings from all three previous phases to demonstrate spatial patterns of resilience. This research demonstrates that although national resilience quantification metrics are useful, local scale resilience estimates appear more useful if community hazard mitigation and climate change adaptation is the primary goal.
The focus of this article is planning for resiliency in the aftermath of a catastrophe. First, the authors offer their conception of planning for resiliency as a goal for recovering communities, and the benefits of planning in efforts to create more resilient places. Next, they discuss major issues associated with planning for postdisaster recovery, including barriers posed by federal and state governments to planning for resiliency, the promise and risks of compact urban form models for guiding rebuilding, and the failure to involve citizens in planning for disasters. Finally, they discuss lessons from prior research that address these issues and policy recommendations that foster predisaster recovery planning for resilient communities.
Change is a constant force, in nature and in society. Research suggests that resilience pertains to the ability of a system to sustain itself through change via adaptation and occasional transformation. This article is based on the premises that communities can develop resilience by actively building and engaging the capacity to thrive in an environment characterized by change, and that community resilience is an important indicator of social sustainability. Community resilience, as defined herein, is the existence, development, and engagement of community resources by community members to thrive in an environment characterized by change, uncertainty, unpredictability, and surprise. The U.S. Roundtable on Sustainable Forests commissioned a research project to develop a theoretically and empirically based definition of community resilience as well as an associated measurement instrument. In this article, the research is presented, the emergent definition and dimensions of community resilience are posited, and the Community Resilience Self Assessment is introduced.
Community resilience is a term that describes the community's ability to function amidst crises or disruptions. Community resilience is perceived as a fundamental element in emergency preparedness and as a mean of ensuring social stability in the face of crises, including disasters. However, there is a paucity of empiric evidence for this conjecture. This paper demonstrates the use of the Conjoint Community Resilience Assessment Measurement (CCRAM) for estimating the ability of a community to be resilient in the face of disaster. Six factors of community resilience were identified based on a study conducted in nine small to medium size towns (N = 886): Leadership, collective efficacy, preparedness, place attachment, social trust and social relationship. Multiple logistic regressions yielded the CCRAM protective factors for perceived community resilience. Receiver Operating Characteristic (ROC) analysis confirmed the quality of the CCRAM as a diagnostic tool for perceived community resilience. The CCRAM tool is presented as a potential provider of information for authorities and decision makers as an aid for foreseeing and planning towards the challenges present during emergency times.
There is considerable research interest on the meaning and measurement of resilience from a variety of research perspectives including those from the hazards/disasters and global change communities. The identification of standards and metrics for measuring disaster resilience is one of the challenges faced by local, state, and federal agencies, especially in the United States. This paper provides a new framework, the disaster resilience of place (DROP) model, designed to improve comparative assessments of disaster resilience at the local or community level. A candidate set of variables for implementing the model are also presented as a first step towards its implementation.
How does the government or a business plan for an unimaginable disaster-a meltdown at a nuclear power plant, a gigantic oil spill, or a nuclear attack? Lee Clarke examines actual attempts to "prepare" for these catastrophes and finds that the policies adopted by corporations and government agencies are fundamentally rhetorical: the plans have no chance to succeed, yet they serve both the organizations and the public as symbols of control, order, and stability. These "fantasy documents" attempt to inspire confidence in organizations, but for Clarke they are disturbing persuasions, soothing our perception that we ultimately cannot control our own technological advances. For example, Clarke studies corporations' plans for cleaning up oil spills in Prince William Sound prior to the Exxon Valdez debacle, and he finds that the accepted strategies were not just unrealistic but completely untenable. Although different organizations were required to have a cleanup plan for huge spills in the sound, a really massive spill was unprecedented, and the accepted policy was little more than a patchwork of guesses based on (mostly unsuccessful) cleanups after smaller accidents. While we are increasingly skeptical of big organizations, we still have no choice but to depend on them for protection from large-scale disasters. We expect their specialists to tell the truth, and yet, as Clarke points out, reassuring rhetoric (under the guise of expert prediction) may have no basis in fact or truth because no such basis is attainable. In uncovering the dangers of planning when implementation is a fantasy, Clarke concludes that society would be safer, smarter, and fairer if organizations could admit their limitations. "An incursion into new territory written with insight and flair, Clarke's book achieves a revolution in understanding plans as an organizational activity-how they come about, why they go awry, and the often-disastrous disconnect between plans and an organization's ability to carry them out. A book that will fascinate general readers, administrators, organization theorists, and disaster buffs, Mission Improbable stands as a valuable companion volume to Pressman and Wildavsky's Implementation."âDiane Vaughan, author of The Challenger Launch Decision
The City Resilience Index
- S Bhoite
- K Birtill
- S Gillespie
- B E Morera
- J Silva
- S Stratton-Short
Bhoite, S., K. Birtill, S. Gillespie, B. E. Morera, J. da Silva, and S. Stratton-Short. 2014. The City
Resilience Index, 1-31. New York, NY: The Rockefeller Foundation. https://www.urbanresponse.org/system/files/content/resource/files/main/city-resilience-framework-arupapril-2014.pdf.
Community Resilience Planning Guide for Buildings and Infrastructure Systems
- S Cauffman
Cauffman, S. 2015. "Community Resilience Planning Guide for Buildings and Infrastructure
Systems." Electroindustry 20 (7): 8.
City Resilience Framework
- J Da Silva
- M Moench
da Silva, J., and M. Moench. 2014. City Resilience Framework, 1-21. New York, NY: The Rockefeller
Foundation. http://www.seachangecop.org/files/documents/URF_Booklet_Final_for_
Bellagio.pdf%5Cn.http://www.rockefellerfoundation.org/uploads/files/0bb537c0-d872-467f-9470-b20f57c32488.pdf%5Cn.http://resilient-cities.iclei.org/fileadmin/sites/
resilient-cities/files/Image.
Community Resilience Indicator Analysis, County-Level Analysis of Commonly Used Indicators from Peer-Reviewed Research
- L Edgeman
- C Freeman
- C Burdi
- J Hutchison
- K Marsh
- K Pfeiffer
Edgeman, L., C. Freeman, C. Burdi, J. Hutchison, K. Marsh, and K. Pfeiffer. 2019. Community
Resilience Indicator Analysis, County-Level Analysis of Commonly Used Indicators from Peer-Reviewed Research, 2020 Update. https://www.fema.gov/sites/default/files/2020-11/
fema_community-resilience-indicator-analysis.pdf.
Pursuing Community Resilience Over Time
- S Mcconkey
McConkey, S. 2018. Pursuing Community Resilience Over Time. Illinois State Water Survey
Contract Report 2018-01. Champaign. http://hdl.handle.net/2142/99948.
NIST Special Publication 1190, II
CRS Report for Congress Federal Emergency Management: A Brief Introduction
- B R Lindsay
Lindsay, B. R. 2012. CRS Report for Congress Federal Emergency Management: A Brief
Introduction. Washington D.C.: Congressional Research Service.