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Crisis Cleanup

Crisis Cleanup is a web platform that connects disaster recovery organization volunteers with people who need help after a disaster. The Crisis Cleanup platform has been used to connected 105,290 volunteers from 765 organizations with 27,676 households in 31 states and 69 disasters in 5 countries; a new disaster every two weeks.

Crisis Cleanup works best in a collaborative environment where multiple voluntary organizations and agencies work together and coordinate efforts. Because these organizations do not take orders from one another, Crisis Cleanup is designed to facilitate Collaborative Accountability models of inter-agency interaction, rather than command-and-control operations, or or heirarchical accountability models of interaction.

This is the primary repository for the main Crisis Cleanup web application, a collaborative map-based coordination tool. This implementation is built with Ruby on Rails, a PostgreSQL database and run on the Heroku stack.

Other Project Stats (As of 2017-08-24)

  • 25%: Increase in volunteer efficiency through elimination of time spent on travel, coordination, collaboration, and management.
  • 6,919: Additional households helped because of Crisis Cleanup.
  • 1.7 Million: Number of volunteer hours facilitated.
  • 415,000: Volunteer hours to survivors enabled by Crisis Cleanup that would have otherwise been wasted in management, travel, and overhead.
  • $151.1 Million: Minimum total market value of services to survivors.
  • $1,435: Value of each cleanup volunteer to his/her community.
  • $37.8 Million: Additional market value of services to survivors that would have otherwise been wasted in travel, management, overhead, and standing in lines.
  • $20,271: Money Crisis Cleanup has saved survivors every single day since July 18, 2012.
  • $8,192: Average commercial value of service to each homeowner.
  • $142: Return on investment to survivors, for every $1 invested in Crisis Cleanup.

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Crisis Cleanup on Rails and PostgreSQL

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  • HTML 82.6%
  • Ruby 11.8%
  • CSS 3.4%
  • JavaScript 2.2%