Core recruitment effects in SIS models with constant total populations

Area of Science:

• Epidemiology
• Mathematical Biology
• Infectious Disease Modeling

Background:

• Sexually transmitted infections (STIs) pose significant public health challenges.
• Traditional epidemiological models often assume homogeneous mixing or simplified population structures.
• Understanding disease dynamics in structured populations is crucial for effective control strategies.

Purpose of the Study:

• To investigate the epidemiological dynamics of a sexually transmitted disease using Susceptible-Infected-Susceptible (SIS) models.
• To explore the impact of recruitment between core and non-core subpopulations on disease transmission.
• To analyze deviations from standard R0 (basic reproduction number) threshold behavior.

Main Methods:

• Development and analysis of a set of SIS mathematical models.
• Incorporation of disease prevalence-dependent recruitment between subpopulations.
• Examination of model behavior for endemic equilibria and oscillatory dynamics (limit cycles).

Main Results:

• The models exhibit complex dynamics that diverge from traditional R0 threshold predictions.
• In one model scenario, an additional pair of endemic equilibria emerge.
• In another scenario, the models generate a limit cycle, indicating sustained oscillations in disease prevalence.

Conclusions:

• Disease transmission dynamics can be significantly altered by population structure and mixing.
• Prevalence-dependent recruitment can lead to richer epidemiological behaviors than simpler models predict.
• These findings highlight the importance of considering subpopulation interactions in STI modeling and control.