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This study introduces a framework to predict infectious disease spread and behavior, identifying stable equilibria for self-managing policies. It reveals two endemic equilibria based on vaccination rates, guiding optimized public health strategies.

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Public Health Policy

Background:

  • Predicting infectious disease dynamics is challenging due to variable human behavior.
  • Understanding the feedback loop between disease incidence and behavioral responses is crucial for effective control.

Conclusions:

  • The proposed framework enables anticipation of long-term disease consequences.
  • It facilitates the design of vaccination strategies that balance public health and societal impact.
  • Identified equilibria offer insights into sustainable disease management under varying vaccination levels.