Strategies for Disease Containment: A Biological-Behavioral-Intervention Computational Informatics Framework.

Area of Science:

• Computational informatics
• Epidemiology
• Public health

Background:

• Infectious disease outbreaks necessitate integrated strategies combining disease dynamics, social behavior, and resource management.
• Existing models often lack the granularity to capture heterogeneous group behavior and optimize interventions effectively.

Purpose of the Study:

• To develop and utilize a computational informatics framework integrating disease modeling, social behavior, and resource logistics for infectious disease containment.
• To optimize intervention timelines and resource allocation for effective outbreak management.

Main Methods:

• Developed a framework combining infectious disease modeling (expanding on SEIR models) with social behavior, employment stratifications, and resource logistics.
• Incorporated heterogeneous group behavior, interaction dynamics, asymptomatic/post-recovery transmission, hospitalization, and funeral events.
• Applied the framework to analyze and optimize containment strategies for the West Africa Ebola outbreak and the COVID-19 pandemic in the US.

Main Results:

• Timely interventions (within 1.5 months) can reduce infections by 90% and achieve containment in 6-8 months with minimal additional resources.
• Delayed interventions (within 5 months) lead to 10-100 fold increases in infections/deaths and 2-4 fold longer containment times.
• The framework's disease module is adaptable to different pathogens and captures time-variant human behavior and healthcare worker transmission.

Conclusions:

• Early and optimized interventions are critical for effective infectious disease containment, significantly reducing infections, deaths, and resource needs.
• The developed computational framework and associated web-based tool provide valuable insights for policy-making, disease management, and resource allocation.
• Real-time computational systems are essential for proactive pandemic preparedness and response, accurately predicting disease spread and health burdens.