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Generating a heterosexual bipartite network embedded in social network.

Asma Azizi1, Zhuolin Qu2, Bryan Lewis3

  • 1Department of Mathematics, University of California, Irvine, CA 92697 USA.

Applied Network Science
|November 1, 2021
PubMed
Summary

This study introduces a new method for creating realistic heterosexual networks using social activity data. This approach helps in understanding and controlling the spread of sexually transmitted infections (STIs).

Keywords:
B2K networkBipartite networkHeterosexual networkJoint degree distributionSexually transmitted infectionsSocial contact network

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Area of Science:

  • Epidemiology
  • Network Science
  • Computational Social Science

Background:

  • The spread of sexually transmitted infections (STIs) is heavily influenced by the structure of sexual networks.
  • Current methods for generating sexual networks often overlook crucial demographic and social factors, limiting their real-world applicability.
  • Accurate network modeling is essential for developing effective STI mitigation strategies.

Purpose of the Study:

  • To develop a novel approach for generating heterosexual networks that incorporate realistic social mixing patterns.
  • To embed a bipartite heterosexual network within a larger social contact network derived from daily activities.
  • To utilize this enhanced network model for simulating STI transmission, such as chlamydia in New Orleans.

Main Methods:

  • Simulation of a large-scale urban population, capturing daily activities (work, school, home).
  • Extraction of a social contact network based on co-location and interaction data.
  • Integration of the social contact network to define a bipartite heterosexual network, reflecting demographic correlations.
  • Application of the model to simulate chlamydia spread in a young, sexually active population.

Main Results:

  • The developed approach successfully generates heterosexual networks reflecting complex social mixing patterns.
  • The embedded network captures correlations in age, location, and socioeconomic status.
  • The model provides a framework for investigating STI spread influenced by social structures.

Conclusions:

  • This method offers a more realistic representation of sexual networks by integrating social contact data.
  • The approach can improve the accuracy of STI transmission models and the evaluation of intervention strategies.
  • The study demonstrates the utility of the model in understanding chlamydia transmission dynamics in a specific urban community.