Epidemic outbreaks in two-scale community networks

Area of Science:

• Epidemiology
• Mathematical Biology
• Network Science

Background:

• Epidemic modeling often simplifies population structures.
• Understanding community-level dynamics is crucial for predicting disease spread.
• Previous models lacked detailed community interaction parameters.

Purpose of the Study:

• To analyze a continuous-time susceptible-infected-susceptible (SIS) model with distinct intra- and inter-community infection probabilities.
• To provide a framework for describing localized, faster epidemic spread within communities.
• To express epidemic outbreak probability as a metastable infection probability.

Main Methods:

• Utilized a mean-field approximation for epidemic diffusion.
• Modeled population structure using an adjacency matrix of clusters and a vector of community sizes.
• Analyzed a continuous-time SIS model.

Main Results:

• Developed a model where infection dynamics differ within and between local communities.
• Demonstrated that community structure impacts epidemic spread rates.
• Established that epidemic thresholds depend on community size and inter-community connections.

Conclusions:

• The proposed model offers a compact description of clustered epidemic spread.
• Metastable infection probability is a key outcome influenced by network topology.
• The model provides insights into epidemic outbreaks in structured populations.