Spatio-temporal waves and targeted vaccination in recurrent epidemic network models

Area of Science:

• Epidemiology
• Network Science
• Mathematical Biology

Background:

• Infectious disease dynamics are influenced by population connectivity.
• Long-term recurrent oscillations are characteristic of diseases with temporary immunity.
• The origins of these oscillations, particularly in sexually transmitted diseases like syphilis, are debated.

Purpose of the Study:

• To model the spatio-temporal patterns of disease dynamics using a network approach.
• To investigate the role of social behavior and heterogeneous connectivity in disease spread.
• To explore the origins of long-term recurrent oscillations in diseases with temporary immunity.

Main Methods:

• Development of a network model incorporating social behavior and connectivity.
• Analysis of disease spread patterns in realistic small-world networks.
• Derivation of a simple difference equation model to capture infection dynamics.

Main Results:

• Social and sexual behavior significantly influence long-term disease cycles in small-world networks.
• The model generates circular infection waves with unique spatial dynamics.
• Focal areas acting as pacemakers were identified as key drivers of infection spread.

Conclusions:

• Heterogeneous connectivity and individual behavior are crucial for understanding disease dynamics.
• Targeted vaccination strategies focusing on eliminating pacemakers can efficiently eradicate diseases.
• The derived difference equation model provides insights into disease origins and eradication.