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Predicting human contacts through alternating direction method of multipliers

Author

Listed:
  • Chunlin Huang

    (National Computer Network Emergency Response, Technical Team/Coordination Center of China, Beijing 100029, P. R. China)

  • Dongbo Bu

    (Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, P. R. China3University of Chinese Academy of Sciences, Beijing 100049, P. R. China)

Abstract

Transmission of respiratory infectious diseases depends greatly on human close-proximity contacts, making thorough understanding of current and upcoming contacts essential for epidemic containment. Although different devices and software have been developed for contact data collection, there are few effective methods for contact prediction available in the near future as far as the authors know. In this study, we propose an approach to predict human contacts. We first extract human features together with their significances from the human contacts through alternating direction method of multipliers (ADMM), then predict future significances based on periodicity of contacts, and finally construct future contacts from human features and future significances. With the help of contact data collected in a Chinese University, we compare this approach with a trivial method of directly averaging known contacts. The comparison shows that our approach generates contacts deviating less from the true ones.

Suggested Citation

  • Chunlin Huang & Dongbo Bu, 2019. "Predicting human contacts through alternating direction method of multipliers," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 30(07), pages 1-18, July.
    • Handle: RePEc:wsi:ijmpcx:v:30:y:2019:i:07:n:s012918311940014x
    DOI: 10.1142/S012918311940014X
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