C12674: CoPE-WELL Computer Model of Community Functioning in DisastersNovelty:
A software program to predict and simulate the time-course of community functioning and well-being resilience during and after a disaster, for every county in the nation.
Value Proposition:
Research shows that many people and communities believe they are significantly more prepared for emergencies and natural disasters than they actually are. This gap in conceptual preparedness leaves many communities completely unprepared for catastrophic events, such as Hurricane Katrina and the recent tornado in Moore, OK. Predicting a communitys response based on its current assets can help risk analysts suggest preventive measures to limit death and damage and build resilience. Current models of community resilience at best only offer a static score of a communitys resilience to a hazard. Further, existing models are based on incomplete or inaccurate conceptual frameworks of resilience. This technology, the Composite of Post-Event Well-being (CoPE-WELL) model, generates a time-series of color-coded maps of the country, depicting each countys predicted functioning over time, during and after a disaster. The advantages include:
• Standardizes county data on communal assets, level of preparedness, emergency management activities
• Outputs a color-coded depiction of each countys pre- and post-disaster functioning, resistance, and resilience over an extended time frame
• Validated with historical data on actual responses to natural disasters
Technical Details:
Johns Hopkins researchers have created a novel tool to predict the time-course of community functioning and well-being during and after a disaster. The technology is a MatLab computer program that uses systems dynamics modeling to generate predictions of a communitys response and resilience at the county level. Inputs obtained from county-level datasets were normalized to build a standardized dataset for entry in to the computer model. The model can be operated with an interface that enables users to query the selected elements of model or can be advanced to offer greater flexibility and features, allowing users to input additional years data, add new elements, and reorganize the model. The utility of the model is in both predicting a communitys resilience and in testing candidate interventions to boost resilience.
Looking for Partners:
To develop and commercialize the technology as a risk assessment and intervention planning tool to mitigate deleterious effects of mass catastrophes and natural disasters.
Stage of Development:
Software program has been created and tested
Data Availability:
Prototype
