Beyond the Original BRIC Model is the central topic of this scientific publication.
Abstract
This paper reviews the development and adaptations of the BRIC (Baseline Resilience Indicators for Communities) method for measuring local community resilience to disasters, grounded in the DROP (Disaster Resilience of Place) theoretical framework. The point of departure is the analysis of the DROP framework, which defines resilience as a dynamic process conditioned by pre-existing social, economic, institutional, and infrastructural conditions, as well as their interaction with natural systems. The first part of the paper discusses the theoretical value of this framework, as well as the practical challenges of its application arising from the limited availability of reliable data and the lack of standardized methodological approaches. The second part of the paper presents a detailed analysis of the development of resilience dimensions in contemporary literature, including socio-demographic structure, well-being and social capital, economic stability, institutional capacities, infrastructure, geographical and spatial characteristics, cooperation, and risk analysis. Through a comparative approach, it is shown that, although differently labeled, these indicators essentially converge on the same conceptual cores and reveal developmental discontinuities relative to the original DROP framework and the initial BRIC method. The central part of the paper examines the evolution of the BRIC method and its adaptations across different national contexts, including analyses of indicator applications in Norway, England, Nepal, Hungary, and Australia. Particular attention is paid to the role of the OECD methodological guidelines in indicator selection, with an emphasis on their frequent partial implementation, especially in areas related to handling missing data, reliability testing, and sensitivity analyses. In conclusion, the paper demonstrates that the BRIC method possesses high conceptual potential and broad applicability; however, without deeper contextual adaptation, stricter methodological discipline, and the integration of spatial and local approaches, its validity and operational usefulness in community resilience planning may remain limited.
Conclusions
By synthesizing the qualitative analysis of the indicators and their variations used for measuring resilience, and by placing them within the same context of application for the final assessment of resilience, that is, for obtaining a resilience index, it is possible to draw specific conclusions regarding which indicators were not developed within the BRIC method in Susan Cutter’s 2010 study, without taking into account her 2014 work, which represents an adaptation of the original method. By comparing the indicators of the BRIC method with the indicators of other methodological approaches for measuring resilience—such as the Climate Disaster Resilience Index (Prashar, Shaw, & Takeuchi, 2012), the Disaster Resilience of Communities Index (Mayunga, 2007), the Coastal Cities Resilience Index (Simonovic & Peck, 2013), the Climate Vulnerability and Capacity Assessment Index (Garg, et al., 2007), as well as other relevant methodological approaches published in earlier periods in which more than 80 indicators in total were identified—specific differences can be observed. These differences refer to indicators and corresponding indicator variations that are not applied within the BRIC method but have an influence on the optimal measurement of resilience because they take into account, or may take into account, the specificities of a particular country or territory in relation to the economic, social, geographical, demographic, and other characteristics, that is, the dimensions of resilience contained in the BRIC method. The specificity of each local community emerges from the interplay between its geographical and spatial characteristics and the attributes of its social organization, which directly shape the development level of infrastructural systems, the degree of institutional maturity, the scope and quality of cooperation, capacities for conducting risk analyses, and the prevailing social and economic characteristics. It is this multifaceted constellation of factors that gives the resilience of different communities its distinctive forms and dynamics.
Considering the current, expanded formulation of the BRIC method, it can be concluded that it is structured around six resilience dimensions. Social resilience reflects a community’s capacity to recover rapidly from disasters and captures demographic and social attributes, including population structure, educational attainment, healthcare capacity, and social cohesion. Within the BRIC method, this dimension is operationalized through indicators such as the population-to-education ratio, availability of communication, social cohesion measured by language proficiency, working-age population, health insurance, healthcare capacity, commodity reserves, and availability of healthcare workers.
Economic resilience measures the capacity of communities to recover, including employment levels, average household income, economic diversification, and access to financial resources. In the BRIC method, it is defined through the following indicators: property ownership, employment rate, income equality by affiliation, independence from the primary or tourism sector, income equality by gender, enterprise size, geographical distribution of large retail companies at the regional and national levels, and employment in public institutions.
Infrastructural resilience measures the availability and quality of infrastructure, such as the transport network, healthcare facilities, utility services, and access to drinking water, as well as the capacity to maintain logistical communication and transport during disasters. In the BRIC method, the following indicators are defined: types of housing structures, availability of temporary and service accommodation, healthcare accommodation capacity, evacuation road routes, quality of the housing construction stock, availability of temporary shelters, availability of educational institutions, logistical infrastructure, and broadband internet services.
Institutional resilience encompasses the ability of local and state institutions to plan, coordinate, and implement risk management activities, including disaster prevention and response, through emergency plans, preparedness of local response teams, and civil protection capacities. In the BRIC method, it is defined through the following indicators: expenditures for disaster response, insurance against natural disasters, coordination of competences, experience in providing disaster assistance, local disaster training, the relationship between local and state authorities, proximity to large urban conglomerations, population stability within the territory, distance from potential accident-prone areas, and insurance of agricultural activities.
Social well-being resilience integrates the community’s capacity to facilitate easier communication and coordination during disasters by fostering interpersonal relationships, awareness, and mutual connectedness among individuals through organizations and joint activities. In the BRIC method, it is defined by the following indicators: local population domicile stability, political engagement, religious beliefs and religious organizations, civil society organizations, humanitarian and volunteer organizations, and civic preparedness and disaster response skills.
Ecological resilience concerns the assessment of the resilience of resources to disasters, including the capacity of ecosystems to regenerate after stress events and resilience to climate change. In the BRIC method, the following indicators are used: local food suppliers, disaster protection measures, electricity use efficiency, permeable surfaces, and efficient water use.
Within the BRIC method, however, a shortcoming is observed in the indicator dimensions, which are insufficiently precise to encompass the aforementioned specificities adequately. Therefore, in the method’s modification and further development, it is necessary to integrate new or adapted indicators to enable a more comprehensive and accurate determination of the resilience index. In this way, a basis is created for resilience measurement that is more closely aligned with the actual conditions and needs of individual communities, thereby significantly enhancing the validity and applicability of the results obtained through the BRIC approach. “The way in which resilience to disasters caused by natural hazards is manifested differs clearly between urban and rural environments. The drivers of disaster resilience differ, indicating the need for resilience-building efforts to be adapted to the local context rather than applied universally across all locations, or even to all urban or rural areas. Social, economic, and ecological processes that have transformed the nation provide the fundamental context for disaster resilience patterns: regional specificity, unique differences between urban and rural areas within and across geographic regions, and variations in drivers among similarly classified areas such as rural counties” (Cutter, Ash, & Emrich, 2016, p. 1251).
The complexity of assessing local community resilience has necessitated a multidimensional approach to indicator selection, allowing the analytical process to incorporate a broader, yet more context-appropriate, set of resilience dimensions. Such an approach is essential for capturing the resilience phenomenon from multiple angles and, in turn, for producing a more comprehensive and more precise account of local communities’ capacity to respond to crises.
However, indicators are susceptible to methodological decisions made during their construction, meaning that the selection of procedures and parameters can significantly influence the final results. The BRIC method was conceived and developed as an analytical tool to support decision-making in disaster risk reduction. For this reason, its authors emphasized that confident methodological choices were deliberately made to ensure that the index would be transparent in interpretation and sufficiently intuitive for practical use by decision-makers. In this way, BRIC is ensured not to remain merely an academic construct but also to function as a helpful instrument in risk management processes (Cutter, Burton, & Emrich, 2010). Although indicator selection inevitably involves trade-offs between methodological rigor and interpretive simplicity, the enhanced version of the BRIC method developed by Susan Cutter has been incorporated into official disaster risk assessment practices in the United States.
A central limitation of the existing evidence base is its restricted geographical and cultural coverage. Much of the research to date has focused on regions such as the United States and Europe, which constrains the extent to which findings can be transferred to other socio-economic settings without deliberate contextual adaptation and localization. Future work should therefore encompass a wider range of countries and regions—particularly those at different levels of development and characterized by distinct socio-economic conditions—in order to assess more comprehensively the applicability of the BRIC method and the DROP framework across diverse contexts. There is also a clear need to further refine and adapt existing indicators, especially in the domains of social, economic, and infrastructural resilience. Indicators such as age structure, labor force employment, education, access to transportation, language competencies, and communication capacities remain insufficiently addressed in parts of the literature and warrant particular attention. In parallel, efforts should be directed toward developing new indicators that better capture the complexity and multidimensionality of local community resilience while remaining sensitive to the specificities of different geographic settings. Measuring local communities’ resilience to natural disasters using the BRIC method—and tailoring the indicator set for a resilience index—constitutes a methodological challenge in its own right. Resilience cannot be observed directly; rather, it is inferred from a broad constellation of contributing factors. A key weakness in prior studies lies in the implementation of assessment tools and in their effectiveness in improving outcomes, particularly with respect to selecting adequate indicators. As a scientific field, resilience measurement continues to evolve, and there remains no fully satisfactory approach for identifying and contextually adapting the indicators to be measured an issue that may reflect both the accelerating pace of societal change and the environmental transformations associated with contemporary development.
With regard to institutional resilience, there is a further requirement to develop more precise and comprehensive indicators capable of more accurately assessing institutional capacity to respond to disasters. This includes strengthening existing emergency intervention plans and developing additional approaches for evaluating and enhancing local institutional capabilities. Overall, the literature points to a clear need for further research and for the development of integrated approaches to disaster resilience measurement. Future work should expand analyses across diverse geographical and cultural contexts and advance methodological tools that enable a more comprehensive assessment of local community resilience (Milenković, Cvetković, & Renner, 2024).
One of the main methodological weaknesses identified in earlier BRIC-based studies is that OECD guidelines were most often omitted precisely in those segments where difficulties arise—namely, in data collection, indicator quality assessment, and indicator comparability. These are also the stages at which weaknesses in research design and in the selection of optimal resilience indicators would be expected to be most visible.
A further shortcoming concerns the limited use of appropriate instruments for generating the evidence required to construct optimal resilience indicators for a geographically defined research setting. In particular, expert assessment is often insufficient within the domains represented by the indicator groups used in these studies. Moreover, fieldwork—specifically surveys and interviews—is not adequately employed in cases where public data from state and other institutions are unavailable.
Methodological decisions should be guided by the results of multivariate analyses, including the grouping of indicators and the determination of weights within composite indices (OECD/European Union/EC-JRC, 2008). In addition, in an effort to reduce the number of measured indicators, Cutter and collaborators published a study in 2022 that, alongside correlation-based approaches, applied Principal Component Analysis (PCA). “However, PCA did not lead to factors that are conceptually justified and aligned with the contemporary understanding of community resilience and its drivers” (Derakhshan, Blackwood, Habets, Effgen, & Cutter, 2022, p. 5).
In practical terms, indicator and indicator-group selection for resilience assessment should therefore be pursued through a balanced, dual-track process. The first track involves statistical testing, including correlation-based screening and other quantitative diagnostics. The second track involves expert evaluation and the use of field research (surveys and interviews) to identify which indicators should be retained in the measurement framework.
Overall, while the BRIC method performs strongly in supporting the identification of relevant resilience indicators, it does not provide a complete set of universally transferable indicators suitable for all countries or territories in which disaster resilience is to be assessed. The application of BRIC and the DROP theoretical framework is therefore contingent on further adaptation and refinement for successful use in specific local contexts. In practice, such adaptation must be undertaken precisely in the domains represented by indicators not covered by the BRIC method. By integrating selected indicators derived from the research’s theoretical framework into the BRIC indicator groups, localization would be achieved, thereby rendering the resulting measures both meaningful and measurable for a specific territory or country, such as Serbia. The specific indicators incorporated into the modified method will depend on data availability, statistical procedures, expert judgment, and fieldwork, through which feasibility of data collection can be established and indicator use optimized for the construction of a resilience index.
How to cite
Milenković, D., Cvetković, V., Beriša, H., Jakovljević, V., Gačić, J., & Cvetković, V. (2026). Beyond the Original BRIC Model: Gaps, Limitations, and Adaptation of Community Resilience Indicators for Local Contexts. International Journal of Disaster Risk Management, 8(1), 55-76. https://doi.org/10.66050/2tmggc50.
