Disaster Research Protocols

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NIEHS Rapid Acquisition of Pre- and Post-Incident Disaster Data (RAPIDD) Protocol Designer 

In 2023, the DR2 Program released a new Rapid Acquisition of Pre- and Post-Incident Disaster Data (RAPIDD) Protocol Designer that allows researchers to go through a virtual module, deciding specific study criteria that is then compiled into a downloadable file containing an individualized protocol for users to submit for IRB approval. Included in the Protocol Designer are nearly 500 publicly available materials that have previously been approved by NIH’s IRB.

Originally created in 2015, the NIEHS RAPIDD protocol (943KB) contains surveys, checklists, and other documents needed to expedite IRB approval following disaster events. Over the years, universities including the University of Texas Medical Branch (978KB), Oregon State University, and Texas A&M University have adapted RAPIDD for use in their own research reviews.

RAPIDD also addresses the collection of data and samples from disaster response workers who may be exposed to environmental contaminants. It can be used as a modifiable template by researchers for different disasters and public health emergencies, as suits their institutions or communities.

group of scientists in a lab

The goals of RAPIDD are to:

  • Provide researchers with a standardized methodology and instruments that have been approved and used in previous disasters
  • Provide researchers with study documents, questionnaires, surveys, supply lists, and staff requirements
  • Decrease the time researchers must spend designing studies, improving the ability to collect perishable data
  • Help researchers collect biological samples and socio-demographic, health, exposure, and lifestyle information immediately before or after deployment to a disaster area
  • Help researchers establish a well-characterized disaster response worker cohort that will enable future analysis
  • Assist research teams by sharing data and insights collected across different disaster sites by enabling the use of Common Data Elements, when applicable