Project Overview

The BRIC index considers six broad categories of community disaster resilience: social, economic, community capital, institutional, infrastructural, and environmental at the county level. Used as an initial baseline for monitoring existing attributes of resilience to natural hazards, BRIC compares places to one another, to determine the specific drivers of resilience for counties, and to monitor improvements in resilience over time. Presently, county-level BRIC (CBRIC) is available for three time-periods, 2010, 2015, and 2020 for the continental U.S., with 2015 and 2020 including Alaska and Hawaii.

BRIC Capitals and Sample Variables

• Human Well-Being/Cultural/Social—physical attributes of populations, values and belief systems (educational attainment equality, pre-retirement age, personal transportation access, communication capacity, English language competency, non-special needs populations, health insurance , mental health support, food security, access to physicians)
• Economic/Financial—economic assets and livelihoods (homeownership, employment rate, racial/ethnic income inequality, non-dependence on primary/tourism sector employment, gender income inequality, business size, large retail with regional/national distribution, federal employment)
• Infrastructure/Built Environment/Housing—buildings and infrastructure (sturdier housing types, temporary housing availability, medical care capacity, evacuation routes, housing stock construction quality, temporary shelter availability, school restoration potential, industrial re-supply potential, high-speed internet infrastructure)
• Institutional/Governance—access to resources and the power to influence their distribution (mitigation spending, flood insurance coverage, governance performance regimes, jurisdictional fragmentation, disaster aid experience, local disaster training, population stability, nuclear accident planning, crop insurance coverage)
• Community Capacity—social networks and connectivity among individuals and groups (volunteerism, religious affiliation, attachment to place, political engagement, citizen disaster training, civic organizations)
• Environmental/Natural—natural resource base and environmental conditions (local food supplies, natural flood buffers, energy use, perviousness, water stress)

The current list of BRIC variables, computations, and sources is available as a PDF.

 

Index Construction and Methods

The BRIC index uses a capitals approach in providing an overall baseline assessment for monitoring existing attributes of resilience to natural hazards. The BRIC index uses 49 variables arrayed in the six broad capitals (or categories) of community resilience. The input variables (largely derived from open-source federal government sources) and raw values first are transformed into rates, percentages, differences, or averages. All datasets are checked for completeness. There are no missing values in county-level datasets used in BRIC with three exceptions. Two null values in community capacity and one null value in political and jurisdictional fragmentation were replaced with the national average for that variable. Sub-county datasets (e.g., point, zip code, voting precinct) are aggregated to county scale, again resulting in no missing values. Within each sub-index (or capital) the input variables are scaled from 0 to 1 in a procedure called linear min-max scaling (where X-min/max-min) where 1 means increasing resilience. This allows for the unit standardization of the input variables and the normalization of values ranging from 0-1. The values of the variables in each sub-index are then averaged to create an overall score for that capital to reduce the impact of the different number of variables within each sub-index. Once constructed, the sub-index scores are summed to create the overall BRIC score which theoretically ranges from 0-6 for each county. See Cutter, Ash & Emrich article "The geographies of community disaster resilience" for additional details on internal consistency of the sub-indices and other BRIC construction analytics.

 

BRIC Data

The BRIC Index can be used to compare places to one another, determine the specific drivers of resilience for counties, and monitor improvements in resilience over time. Presently, county-level BRIC is available for three time-periods, 2010, 2015, and 2020 for the continental U.S., with 2015 and 2020 versions including Alaska and Hawaii.

• County Composite BRIC Scores for 2020 [download Excel file]
• County Composite BRIC Scores for 2015 [download Excel file]
• County Composite BRIC Scores for 2010 [download Excel file]
• BRIC 2020 Maps
• BRIC 2015 Maps

 

Selected Academic Publications Referencing BRIC:

Bakkensen, L.A., Fox-Lent, C., Read, L.K. and Linkov, I., 2017. Validating resilience and vulnerability indices in the context of natural disasters. Risk Analysis, 37(5), pp.982-1004.

Camacho, C., Bower, P., Webb, R.T. and Munford, L., 2023. Measurement of community resilience using the Baseline Resilience Indicator for Communities (BRIC) framework: A systematic review, International Journal of Disaster Risk Reduction 95, 103870.

Coetzee, C., Van Niekerk, D. and Raju, E., 2018. Reconsidering disaster resilience: a nonlinear systems paradigm in agricultural communities in Southern Africa. Natural Hazards, 90(2), pp.777-801.

Csizovszky, A., 2023. Have Hungarian districts become more resilient? –A comparison of the 2014 and 2020 Baseline Indicators for Communities (BRICs), European Journal of Sustainable Development 12(3), pp. 185-197.

Cutter, S.L., Ash, K.D. and Emrich, C.T., 2016. Urban–rural differences in disaster resilience. Annals of the American Association of Geographers, 106(6), pp.1236-1252.

Daramola, A.Y., Oni, O.T., Ogundele, O. and Adesanya, A., 2016. Adaptive capacity and coping response strategies to natural disasters: a study in Nigeria. International Journal of Disaster Risk Reduction, 15, pp.132-147.

Davidson, J., Jacobson, C., Lyth, A., Dedekorkut-Howes, A., Baldwin, C., Ellison, J., Holbrook, N., Howes, M., Serrao-Neumann, S., Singh-Peterson, L. and Smith, T., 2016. Interrogating resilience: toward a typology to improve its operationalization. Ecology and Society, 21(2).

Javadpoor, M., Sharifi, A., and Roosta, M., 2021. An adaptation of the Baseline Resilience Indicators for Communities (BRIC) for assessing resilience of Iranian provinces, International Journal of Disaster Risk Reduction 66, 102609.

Kotzee, I. and Reyers, B., 2016. Piloting a social-ecological index for measuring flood resilience: A composite index approach. Ecological Indicators, 60, pp.45-53.

Lin, P., Wang, N. and Ellingwood, B.R., 2016. A risk de-aggregation framework that relates community resilience goals to building performance objectives. Sustainable and Resilient Infrastructure, 1(1-2), pp.1-13.

McConkey, S.A. and Larson, E.R., 2022.  Measuring community disaster resilience over time, J. Homeland Security and Emergency Management 19(3), pp. 281-321.

McEwen, L., Garde-Hansen, J., Holmes, A., Jones, O. and Krause, F., 2017. Sustainable flood memories, lay knowledges and the development of community resilience to future flood risk. Transactions of the Institute of British Geographers, 42(1), pp.14-28.

Meerow, S., Newell, J.P. and Stults, M., 2016. Defining urban resilience: A review. Landscape and Urban Planning, 147, pp.38-49.

Montz, B.E., Tobin, G.A. and Hagelman, R.R., 2017. Natural Hazards: Explanation and Integration. Guilford Publications.

Ostadtaghizadeh, A., Ardalan, A., Paton, D., Khankeh, H. and Jabbari, H., 2016. Community disaster resilience: a qualitative study on Iranian concepts and indicators. Natural Hazards, 83(3), pp.1843-1861.

Parsons, M., Glavac, S., Hastings, P., Marshall, G., McGregor, J., McNeill, J., Morley, P., Reeve, I. and Stayner, R., 2016. Top-down assessment of disaster resilience: a conceptual framework using coping and adaptive capacities. International Journal of Disaster Risk Reduction, 19, pp.1-11.

Rose, A., 2017. Empirical Analysis. In Defining and Measuring Economic Resilience from a Societal, Environmental and Security Perspective (pp. 59-68). Springer, Singapore.

Sayers, P., Penning-Rowsell, E.C. and Horritt, M., 2018. Flood vulnerability, risk, and social disadvantage: current and future patterns in the UK. Regional Environmental Change, 18(2), pp.339-352.

Scherzer, S., Lujala, P., and Rod, J.K., 2019. A community index for Norway: An adaptation of the Baseline Resilience Indicators for Communities (BRIC), International Journal of Disaster Risk Reduction 36, 101107.

Shao, W., Gardezi, M., and Xian, S., 2018. Examining the effects of objective hurricane risks and community resilience on risk perceptions of hurricanes at the county level in the U.S Gulf Coast: an innovative approach. Annals of the American Association of Geographers, 108(5), pp.1389-1405.

Sharifi, A., 2016. A critical review of selected tools for assessing community resilience. Ecological Indicators, 69, pp.629-647.

Sharifi, A. and Yamagata, Y., 2016. On the suitability of assessment tools for guiding communities towards disaster resilience. International Journal of Disaster Risk Reduction, 18, pp.115-124.

Sharifi, A. and Yamagata, Y., 2016. Principles and criteria for assessing urban energy resilience: A literature review. Renewable and Sustainable Energy Reviews, 60, pp.1654-1677.

Twilley, R.R., Bentley, S.J., Chen, Q., Edmonds, D.A., Hagen, S.C., Lam, N.S.N., Willson, C.S., Xu, K., Braud, D., Peele, R.H. and McCall, A., 2016. Co-evolution of wetland landscapes, flooding, and human settlement in the Mississippi River Delta Plain. Sustainability Science, 11(4), pp.711-731.

Yoon, D.K., Kang, J.E. and Brody, S.D., 2016. A measurement of community disaster resilience in Korea. Journal of Environmental Planning and Management, 59(3), pp.436-460.