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Incorporating Realism: Damage Zone-Based Population Sorting for Nuclear Detonation Modeling
Suzanne Wright1, Neelima Yeddanapudi1, Christian Paletta2
1In support of Administration for Strategic Preparedness and Response (ASPR), Leidos Inc, United States.
Objective:
Response agencies use mathematical modeling to quantify the consequences of mass-casualty incidents. Medical consequence models estimate the number of people to be treated for their injuries and rely on triage protocols based on injury severity to estimate the number of people who are expected to die. Available models ignore the time required to be rescued, which presents an incomplete picture of how many people would live long enough to be rescued and treated. We propose a new damage zone-based population sorting algorithm to improve estimates of people who would require treatment after a nuclear detonation in a U.S. urban setting.
Methods:
We expanded the Administration for Strategic Preparedness and Response (ASPR)nuclear detonation model to include specific blast injuries such as casualties with fractures or hemorrhage. We evaluated 3 population sorting methods: no sorting (i.e., count everyone as treatable), sorting based on Department of War (DOW)/North Atlantic Treaty Organization (NATO) expectant rules, and damage zone-based population sorting. Damage zone-based population sorting introduces a new population category termed unrescuable, who are expected to die before being rescued based on the damage zone, injury severity, and the expected timing of response operations. We assessed the impact of population sorting on the number of injured and the number of injuries to be treated.
Results:
Damage zone-based sorting significantly decreases the estimates of expectants and increases estimates of the population requiring medical treatment for the most serious trauma injuries compared to population sorting based on DOW/NATO expectant rules.
Conclusion:
The new damage zone-based population sorting method represents an important modeling refinement that incorporates realism into modeling results estimating the number of trauma-injured people requiring treatment and numbers of specific trauma injuries that would need to be treated in the aftermath of a nuclear detonation. We saw that the choice of population sorting method can influence the allocation of medical countermeasures required to respond in mass-casualty incidents, impacting medical countermeasure requirements, development, and investments.
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