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Compensating for population sampling in simulations of epidemic spread on temporal contact networks

Author

Listed:
  • Mathieu Génois

    (Aix Marseille Université, Université de Toulon, CNRS, CPT)

  • Christian L. Vestergaard

    (Aix Marseille Université, Université de Toulon, CNRS, CPT)

  • Ciro Cattuto

    (Data Science Laboratory, ISI Foundation)

  • Alain Barrat

    (Aix Marseille Université, Université de Toulon, CNRS, CPT
    Data Science Laboratory, ISI Foundation)

Abstract

Data describing human interactions often suffer from incomplete sampling of the underlying population. As a consequence, the study of contagion processes using data-driven models can lead to a severe underestimation of the epidemic risk. Here we present a systematic method to alleviate this issue and obtain a better estimation of the risk in the context of epidemic models informed by high-resolution time-resolved contact data. We consider several such data sets collected in various contexts and perform controlled resampling experiments. We show how the statistical information contained in the resampled data can be used to build a series of surrogate versions of the unknown contacts. We simulate epidemic processes on the resulting reconstructed data sets and show that it is possible to obtain good estimates of the outcome of simulations performed using the complete data set. We discuss limitations and potential improvements of our method.

Suggested Citation

  • Mathieu Génois & Christian L. Vestergaard & Ciro Cattuto & Alain Barrat, 2015. "Compensating for population sampling in simulations of epidemic spread on temporal contact networks," Nature Communications, Nature, vol. 6(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9860
    DOI: 10.1038/ncomms9860
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    Cited by:

    1. Mattia Mazzoli & Riccardo Gallotti & Filippo Privitera & Pere Colet & José J. Ramasco, 2023. "Spatial immunization to abate disease spreading in transportation hubs," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    2. Hanjue Xia & Johannes Horn & Monika J Piotrowska & Konrad Sakowski & André Karch & Hannan Tahir & Mirjam Kretzschmar & Rafael Mikolajczyk, 2021. "Effects of incomplete inter-hospital network data on the assessment of transmission dynamics of hospital-acquired infections," PLOS Computational Biology, Public Library of Science, vol. 17(5), pages 1-18, May.

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