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Updated: May 26, 2026

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading
Published on: May 22, 2021
Identifying the starting point of a spreading process in complex networks
Cesar Henrique Comin1, Luciano da Fontoura Costa
1Institute of Physics of São Carlos-University of São Paulo, São Carlos, São Paulo, Brazil. chc@usp.br
Identifying epidemic origins is crucial. This study proposes a network analysis method using node centrality measures (degree, betweenness, closeness, eigenvector) to pinpoint contamination source nodes effectively in epidemic spreading scenarios.
Area of Science:
- Network Science
- Epidemiology
- Computational Social Science
Background:
- Understanding epidemic origins is vital for effective containment.
- Identifying the initial source node in a network is a complex challenge.
Purpose of the Study:
- To propose and validate a methodology for identifying source nodes in epidemic spreading.
- To analyze the effectiveness of centrality measures in pinpointing contamination origins.
Main Methods:
- Analysis of three epidemic spreading schemes.
- Calculation and comparison of node centrality measures: degree, betweenness, closeness, and eigenvector centrality.
- Validation on theoretical complex network models and a real-world email network.
Main Results:
- Source nodes tend to exhibit the highest centrality values across different measures.
- The proposed methodology effectively identifies source nodes in both theoretical and real-world networks.
- Centrality measures provide a reliable basis for source localization in epidemic networks.
Conclusions:
- Node centrality analysis is an effective approach for identifying epidemic source locations.
- The validated methodology offers a practical tool for epidemiological investigations.
- This research contributes to the understanding and management of infectious disease outbreaks.
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