Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling

Area of Science:

• Epidemiology
• Computational Biology
• Public Health Modeling

Background:

• Communicable disease transmission models are crucial for evaluating public health interventions.
• Agent-based models (ABMs) offer a sophisticated approach to disease modeling by simulating individual agent interactions.
• The accuracy of ABMs heavily relies on the quality and granularity of input data, particularly regarding social interactions.

Purpose of the Study:

• To develop and implement methods for assigning synthetic populations to specific social environments within agent-based models.
• To create realistic shared characteristics for agents, including age-based distributions in schools, workplaces, and public transit.
• To enhance the spatial and temporal predictive capabilities of infectious disease transmission models.

Main Methods:

• Generation of a synthetic population for the United States to support the Models of Infectious Disease Agent Study.
• Development of distinct techniques to assign age-appropriate populations to schools, workplaces, and public transit systems.
• Integration of these shared characteristics into agent-based disease transmission models.

Main Results:

• Successfully created shared characteristics for agents, enabling more realistic simulations of social interactions.
• Demonstrated the feasibility of assigning populations to diverse settings like educational institutions, employment locations, and transportation networks.
• Improved the ability of agent-based models to predict disease spread with greater spatial and temporal accuracy.

Conclusions:

• The developed methods for creating agent characteristics significantly enhance the realism of agent-based disease transmission models.
• Accurate representation of population distribution in key social settings is vital for reliable disease spread prediction.
• These advancements contribute to more effective testing of prevention and intervention strategies for communicable diseases.