Epidemic spreading on contact networks with adaptive weights

Area of Science:

• Epidemiology
• Network Science
• Mathematical Biology

Background:

• Contact networks are used to model population interactions for disease spread.
• Traditional models often overlook the dynamic nature and varying strengths of contacts.
• Adaptive contact strengths, reflecting relationship intimacy, are crucial but often ignored.

Purpose of the Study:

• To propose a modified Susceptible-Infected-Susceptible (SIS) epidemic model incorporating adaptive weighted networks.
• To analyze the impact of adaptive contact weights on disease dynamics, including population extermination, extinction, and persistence.
• To investigate conditions under which adaptive weights influence epidemic thresholds and endemic levels.

Main Methods:

• Development of a modified SIS model with a birth-death process and nonlinear infectivity.
• Integration of an adaptive and weighted contact network where link weights decrease with disease progression.
• Application of mathematical and numerical analyses to derive conditions for disease dynamics.

Main Results:

• Conditions for population extermination, disease extinction, and infection persistence were mathematically established.
• Fixed contact weights were found to potentially trigger epidemic incidence.
• Adaptive weights do not alter the epidemic threshold but accelerate disease decay and reduce the endemic level.

Conclusions:

• Adaptive contact weights play a significant role in modulating epidemic dynamics, particularly in disease decay and endemic levels.
• The study highlights the importance of considering the dynamic nature of social contacts in epidemiological models.
• Findings suggest potential control strategies by leveraging the adaptive nature of contact strengths.