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College of Arts and Sciences


Baseline Resilience Indicators for Communities

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 can be used to compare 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 is available at two time-periods, 2010 and 2015 for the continental U.S., with 2015 also including Alaska and Hawaii.

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. Developed for U.S. counties, BRIC can compare one county to another, help to understand the specific drivers of resilience for individual counties, and monitor improvements in resilience over time.

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) for each sub-index (or capital) are scaled from 0 to 1 with 1 meaning increasing resilience in a procedure call linear min-max scaling (where X-min/max-min).  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 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)




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.

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.

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).

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.

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.

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.

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