Skip to main content Accessibility help

COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters

  • Jonathan M. Links (a1) (a2), Brian S. Schwartz (a1) (a3), Sen Lin (a4), Norma Kanarek (a1), Judith Mitrani-Reiser (a4), Tara Kirk Sell (a1) (a5), Crystal R. Watson (a1) (a5), Doug Ward (a6), Cathy Slemp (a7), Robert Burhans (a7), Kimberly Gill (a8), Tak Igusa (a4), Xilei Zhao (a4), Benigno Aguirre (a8), Joseph Trainor (a8), Joanne Nigg (a8), Thomas Inglesby (a1) (a5), Eric Carbone (a9) and James M. Kendra (a8)...



Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster.


We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties.


The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature.


The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127–137)


Corresponding author

Correspondence and reprint requests to Jonathan M. Links, Johns Hopkins University, 258 Garland Hall, 3400 N Charles St, Baltimore, MD 21218 (e-mail:


Hide All
1. Gordon, JE. Structures: or, Why Things Don’t Fall Down. Harmondsworth, New York: Penguin Books; 1978.
2. Department of Homeland Security. Presidential Policy Directive/PPD-8: National Preparedness. Washington, DC: Department of Homeland Security; 2011. Accessed May 9, 2017.
3. Department of Homeland Security. National Infrastructure Protection Plan: Partnering for Critical Infrastructure and Security. Published 2013. Accessed April 29, 2016.
4. Bruneau, M, Chang, SE, Eguchi, RT, et al. A framework to quantitatively assess and enhance the seismic resilience of communities. Earthq Spectra. 2003;19(4):733-752.
5. Pfefferbaum, RL, Pfefferbaum, B, Van Horn, RL, et al. Building community resilience to disasters through a community-based intervention: CART applications. J Emerg Manag. 2013;11(2):151-159.
6. Pfefferbaum, RL, Pfefferbaum, B, Van Horn, RL, et al. The Communities Advancing Resilience Toolkit (CART): an intervention to build community resilience to disasters. J Public Health Manag Pract. 2013;19(3):250-258.
7. Cutter, SL, Barnes, L, Berry, M, et al. A place-based model for understanding community resilience to natural disasters. Glob Environ Change. 2008;18(4):598-606.
8. Chandra, A, Acosta, J, Meredith, LS, et al. Understanding Community Resilience in the Context of National Health Security. Rand Working Paper. Published February 2010. Accessed May 9, 2017.
9. Chandra, A, Acosta, J, Stern, S, et al. Building Community Resilience to Disasters. Rand Technical Report. Published 2011. Accessed May 9, 2017.
10. Plough, A, Fielding, JE, Chandra, A, et al. Building community disaster resilience: perspectives from a large urban county department of public health. Am J Public Health. 2013;103(7):1190-1197.
11. Chandra, A, Williams, M, Plough, A, et al. Getting actionable about community resilience: the Los Angeles County Community Disaster Resilience Project. Am J Public Health. 2013;103(7):1181-1189.
12. Wells, KB, Tang, J, Lizaola, E, et al. Applying community engagement to disaster planning: developing the vision and design for the Los Angeles County Community Disaster Resilience Initiative. Am J Public Health. 2013;103(7):1172-1180.
13. Maglio, PP, Sepulveda, MJ, Mabry, PL. Mainstreaming modeling and simulation to accelerate public health innovation. Am J Public Health. 2014;104(7):1181-1186.
14. Checkland, P. Systems Thinking, Systems Practice: Includes a 30-Year Retrospective. Chichester, United Kingdom: John Wiley & Sons; 1999.
15. Meadows, DH, Wright, D. Thinking in Systems: A Primer. White River Junction, VT: Chelsea Green Pub; 2008.
16. Forrester, JW. System dynamics, systems thinking, and soft OR. Syst Dynam Rev. 1994;10(2-3):245-256. doi: 10.1002/sdr.4260100211
17. Mabry, PL, Olster, DH, Morgan, GD, et al. Interdisciplinarity and systems science to improve population health: a view from the NIH Office of Behavioral and Social Sciences Research. Am J Prev Med. 2008;35(2)(suppl):S211-S224.
18. Sterman, J. Business Dynamics: Systems Thinking and Modeling for a Complex World. Boston: Irwin/McGraw-Hill; 2000.
19. Homer, JB, Hirsch, GB. System dynamics modeling for public health: background and opportunities. Am J Public Health. 2006;96(3):452-458.
20. Hovmand, PS. Community Based System Dynamics. Springer; 2014; Accessed May 9, 2017.
21. Leischow, SJ, Milstein, B. Systems thinking and modeling for public health practice. Am J Public Health. 2006;96(3):403-405.
22. Lyon, AR, Maras, MA, Pate, CM, et al. Modeling the impact of school-based universal depression screening on additional service capacity needs: a system dynamics approach. Adm Policy Ment Health. 2016;43(2):168-188.
23. Sakia, RM. The Box-Cox transformation technique - a review. Statistician. 1992;41(2):169-178.
24. Box, GEP, Cox, DR. An analysis of transformations. J R Stat Soc B. 1964;26(2):211-252.
25. Norris, FH, Stevens, SP, Pfefferbaum, B, et al. Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. Am J Community Psychol. 2008;41(1-2):127-150.
26. Miles, SB, Chang, SE. Modeling community recovery from earthquakes. Earthq Spectra. 2006;22(2):439-458.
27. Burby, RJ, Deyle, RE, Godschalk, DR, et al. Creating hazard resilient communities through land-use planning. Nat Hazards Rev. 2000;1(2):99-106.
28. Aguirre, BE, Wenger, D, Vigo, G. Test of the emergent norm theory of collective behavior. Sociol Forum. 1998;13(2):301-320.
29. Simpson, B, Willer, R. Beyond altruism: sociological foundations of cooperation and prosocial behavior. Annu Rev Sociol. 2015;41(1):43-63.
30. Kendra, JM, Wachtendorf, T. Elements of resilience after the World Trade Center disaster: reconstituting New York City’s Emergency Operations Centre. Disasters. 2003;27(1):37-53.
31. Kendra, JM, Wachtendorf, T. Reconsidering convergence and converger legitimacy in response to the World Trade Center disaster. Research in Social Problems in Public Policy. 2003;11:97-122.
32. Kendra, JM, Wachtendorf, T. Improvisation, creativity, and the art of emergency management. In: Durmaz H, Sevinc B, Yayla AS, Ekici S, eds. Vol 19: Understanding and Responding to Terrorism. NATO Security Through Science Series E: Human and Societal Dynamics. 2007:324-335.
33. Jacob, B, Mawson, AR, Payton, M, et al. Disaster mythology and fact: hurricane Katrina and social attachment. Public Health Rep. 2008;123(5):555-566.
34. Wisner, B, Blaikie, P, Cannon, T, et al. At Risk: Natural Hazards, People’s Vulnerability, and Disasters. 2nd ed. New York: Psychology Press; 2004.


Type Description Title
Supplementary materials

Links supplementary material
Figure S1

 Word (620 KB)
620 KB
Supplementary materials

Links supplementary material
Figure S2

 Word (1.1 MB)
1.1 MB
Supplementary materials

Links supplementary material
Figure S3

 Word (937 KB)
937 KB
Supplementary materials

Links supplementary material
Figure S4

 Word (943 KB)
943 KB


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed