A hierarchical intervention scheme based on epidemic severity in a community network

Area of Science:

• Epidemiology
• Mathematical Modeling
• Network Science

Background:

• Targeted medicines and vaccines for emerging infectious diseases are often lacking.
• Community isolation is a primary intervention strategy.
• The role of intercommunity connections in epidemic spread is not well understood.

Purpose of the Study:

• To quantitatively analyze the impact of intercommunity edges on infectious disease transmission.
• To develop a hierarchical intervention scheme based on epidemic severity.

Main Methods:

• Established a four-dimensional edge-based compartmental model with two communities.
• Derived the basic reproduction number and outbreak threshold.
• Applied the model to the SARS outbreak in Singapore and simulated on various network distributions.

Main Results:

• Classified epidemic spread into two cases based on within-community and intercommunity transmission rates.
• Demonstrated that intercommunity edges critically influence outbreaks in one case.
• Obtained explicit formulas for the basic reproduction number and outbreak threshold.
• Validated theoretical findings through numerical simulations and a real-world case study.

Conclusions:

• The study provides a novel framework for understanding and controlling epidemics based on intercommunity connectivity.
• The findings offer insights into designing effective public health interventions for emerging infectious diseases.
• The developed hierarchical intervention scheme can guide policy decisions during outbreaks.