| Title |
COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters
|
|---|---|
| Published in |
Disaster Medicine and Public Health Preparedness (Highwire), June 2017
|
| DOI | 10.1017/dmp.2017.39 |
| Pubmed ID | |
| Authors |
Jonathan M. Links, Brian S. Schwartz, Sen Lin, Norma Kanarek, Judith Mitrani-Reiser, Tara Kirk Sell, Crystal R. Watson, Doug Ward, Cathy Slemp, Robert Burhans, Kimberly Gill, Tak Igusa, Xilei Zhao, Benigno Aguirre, Joseph Trainor, Joanne Nigg, Thomas Inglesby, Eric Carbone, James M. Kendra |
| Abstract |
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. 2017;page 1 of 11). |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 75% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Practitioners (doctors, other healthcare professionals) | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 146 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 146 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 27 | 18% |
| Student > Master | 22 | 15% |
| Researcher | 13 | 9% |
| Other | 10 | 7% |
| Student > Bachelor | 8 | 5% |
| Other | 21 | 14% |
| Unknown | 45 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 25 | 17% |
| Engineering | 14 | 10% |
| Medicine and Dentistry | 9 | 6% |
| Environmental Science | 9 | 6% |
| Psychology | 5 | 3% |
| Other | 29 | 20% |
| Unknown | 55 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 March 2022.
All research outputs
#2,118,532
of 25,728,855 outputs
Outputs from Disaster Medicine and Public Health Preparedness (Highwire)
#134
of 1,451 outputs
Outputs of similar age
#39,667
of 330,875 outputs
Outputs of similar age from Disaster Medicine and Public Health Preparedness (Highwire)
#3
of 34 outputs
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So far Altmetric has tracked 1,451 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.4. This one has done particularly well, scoring higher than 90% of its peers.
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We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.