A New Perspective on Determining Disease Invasion and Population Persistence in Heterogeneous Environments

Area of Science:

• Ecology
• Epidemiology
• Network Science

Background:

• Heterogeneous environments pose challenges for understanding disease spread and population dynamics.
• Existing models may not fully capture the interplay of network structure, local dynamics, and dispersal.

Purpose of the Study:

• Introduce a novel quantitative index, the network heterogeneity index (H).
• Develop a tool to analyze disease propagation and population persistence in heterogeneous systems.
• Provide a unified measure reflecting network structure, patch dynamics, and dispersal.

Main Methods:

• Mathematical analysis to define and derive the network heterogeneity index (H).
• Exploration of multiple mathematical representations of H.
• Demonstration of H's non-negativity (H >= 0).

Main Results:

• The network heterogeneity index (H) effectively integrates network structure, patch dynamics, and dispersal rates.
• Multiple valid representations of H were derived.
• H was shown to be non-negative (H >= 0).

Conclusions:

• The network heterogeneity index (H) is a valuable tool for ecological and epidemiological studies.
• H aids in predicting disease invasibility and population persistence in diverse heterogeneous environments.
• The index offers a comprehensive approach to modeling complex spatial dynamics.