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Meeting radiation dosimetry capacity requirements of population-scale exposures by geostatistical sampling.

Eliseos J MucakiEliseos J MucakiRuipeng LuBen C ShirleyEdward WallerJoan H M Knoll
Published in: PloS one (2020)
We modeled 30 scenarios, including 22 urban/high-density and 2 rural/low-density scenarios under various weather conditions. Multiple (3-10) rounds of sampling and kriging were required for the dosimetry maps to converge, requiring between 58 and 347 samples for different scenarios. On average, 70±10% of locations where populations are expected to receive an exposure ≥2Gy were identified. Under sub-optimal sampling conditions, the number of iterations and samples were increased, and accuracy was reduced. Geostatistical mapping limits the number of required dose assessments, the time required, and radiation exposure to first responders. Geostatistical analysis will expedite triaging of acute radiation exposure in population-scale nuclear events.
Keyphrases
  • high density
  • climate change
  • liver failure
  • south africa
  • high resolution
  • respiratory failure
  • monte carlo
  • drug induced
  • radiation therapy
  • intensive care unit
  • genetic diversity