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Visual Analytics for Decision-Making During Pandemics.

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This study introduces PanViz 2.0, a visual analytics system for pandemic preparedness. It supports decision-making through integrated epidemiological models and interactive analysis for better public health emergency response.

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Area of Science:

  • Public Health
  • Epidemiology
  • Health Informatics
  • Visual Analytics

Background:

  • The Southwestern U.S. faces challenges in managing current pandemics and preparing for future health emergencies.
  • Effective decision-making is crucial for pandemic response and recovery.
  • Existing systems may lack integrated analytical and interactive capabilities.

Purpose of the Study:

  • To introduce a trans-disciplinary collaboration for improved pandemic management and preparedness.
  • To present the PanViz 2.0 system, a visual analytics application for public health decision-making.
  • To outline future extensions for enhanced scenario exploration and mitigation strategy analysis.

Main Methods:

  • Development of a trans-disciplinary collaborative framework involving researchers, healthcare practitioners, and community partners.
  • Creation of the PanViz 2.0 system, integrating an epidemiological model with an interactive visual interface.
  • Utilizing human-guided analytical environments for efficient decision-making.

Main Results:

  • The PanViz 2.0 system provides a tightly coupled epidemiological model and interactive interface for pandemic preparedness.
  • The framework enables effective and efficient decision-making through interactive, human-guided analytical environments.
  • Current work focuses on extending the system for "what-if" scenarios and interactive machine learning.

Conclusions:

  • The collaborative approach and PanViz 2.0 system enhance pandemic preparedness and response capabilities.
  • Future work will expand the system's analytical functions to support complex public health crisis decision-making.
  • The system facilitates informed decisions regarding mitigation strategies during health emergencies.