Dynamics of Respiratory Infectious Diseases in Incarcerated and Free-Living Populations: A Simulation Modeling Study

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• Correctional facilities are high-risk settings for respiratory infectious disease outbreaks.
• Importation and exportation of diseases from these facilities pose significant public health concerns.

Purpose of the Study:

• To model the transmission dynamics of respiratory infectious diseases within and between correctional facilities and communities.
• To identify key factors governing disease spread and the relative importance of different transmission routes.

Main Methods:

• Developed a stochastic simulation model for disease transmission.
• Utilized machine-learning meta-models to analyze findings across various parameters.
• Investigated infection dynamics, governing factors, and transmission routes (e.g., staff, incarcerations, releases).

Main Results:

• Identified a "magnification-reflection dynamic" where community outbreaks amplify in correctional facilities and then re-emerge larger in the community.
• This dynamic is most pronounced with smaller community sizes, R-effective near 1, and low correctional immunity.
• Correctional staff are a primary infection route into prisons, while incarcerations/releases are more significant for jails.

Conclusions:

• Substantial magnification-reflection dynamics exist across diverse pathogens and settings.
• Findings highlight the critical role of correctional facility-community interactions in disease transmission.
• Model insights are robust and applicable to various public health decision-making contexts.