1. The 2018 California Wildfires: Integration of Rapid DNA to Dramatically Accelerate Victim Identification.
- Author
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Gin, Kim, Tovar, Jason, Bartelink, Eric J., Kendell, Ashley, Milligan, Colleen, Willey, P., Wood, James, Tan, Eugene, Turingan, Rosemary S., and Selden, Richard F.
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MASS casualties , *WILDFIRE prevention , *SHORT tandem repeat analysis , *DNA fingerprinting , *DISASTER victims , *DNA , *WILDFIRES - Abstract
In November 2018, Butte County, California, was decimated by the Camp Fire, the deadliest wildfire in state history. Over 150,000 acres were destroyed, and at its peak, the fire consumed eighty acres per minute. The speed and intensity of the oncoming flames killed scores of people, and weeks before the fire was contained, first responders began searching through the rubble of 18,804 residences and commercial buildings. As with most mass disasters, conventional identification modalities (e.g., fingerprints, odontology, hardware) were utilized to identify victims. The intensity and duration of the fire severely degraded most of the remains, and these approaches were useful in only 22 of 84 cases. In the past, the remaining cases would have been subjected to conventional DNA analysis, which may have required months to years. Instead, Rapid DNA technology was utilized (in a rented recreational vehicle outside the Sacramento morgue) in the victim identification effort. Sixty‐nine sets of remains were subjected to Rapid DNA Identification and, of these, 62 (89.9%) generated short tandem repeat profiles that were subjected to familial searching; essentially all these profiles were produced within hours of sample receipt. Samples successfully utilized for DNA identification included blood, bone, liver, muscle, soft tissue of unknown origin, and brain. In tandem with processing of 255 family reference samples, 58 victims were identified. This work represents the first use of Rapid DNA Identification in a mass casualty event, and the results support the use of Rapid DNA as an integrated tool with conventional disaster victim identification modalities. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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