9) CBRN Battlespace Surveillance, Alerting & Response

Abstract

Improve the Department of Defense's capability to detect, identify, alert, and responds to deliberate releases and naturally occurring outbreaks of chemical and biological threat agents. Current predictive algorithms in development by JSTO are based on large in-hospital datasets from patients with comorbidities. Improving on the applicability and efficacy of these algorithms will focus on large, real-time human data collects of chemical and biological agent / agent proxy exposures. Additionally, studies will focus on examining the feasibility of specifically isolating indicators of respiratory infection, determining severity of infection, and predicting return to mission readiness after exposure. This capability will enable early implementation of countermeasures such as isolation, quarantine, and removal from an area, thus potentially reducing transmission, morbidity, and mortality rates. The maturation of algorithms will incorporate Machine Learning (ML) approaches for refining sensitivity and specificity.

Document Details

Document Type
Accomplishment
Publication Date
Oct 01, 2023
Source ID
f1c80e206be76a8a61dc335725054fc4

Tags

Readers

  • Computational Modeling and Simulation
  • Critical Infrastructure Protection in CBRN and WMD Threats.
  • Infectious Disease/Epidemiology

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks

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