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Epidemic model on a network: Analysis and applications to COVID-19

Author

Listed:
  • Bustamante-Castañeda, F.
  • Caputo, J.-G.
  • Cruz-Pacheco, G.
  • Knippel, A.
  • Mouatamide, F.

Abstract

We analyze an epidemic model on a network consisting of susceptible–infected–recovered equations at the nodes coupled by diffusion using a graph Laplacian. We introduce an epidemic criterion and examine different isolation strategies: we prove that it is most effective to isolate a node of highest degree. The model is also useful to evaluate deconfinement scenarios and prevent a so-called second wave. The model has few parameters enabling fitting to the data and the essential ingredient of importation of infected; these features are particularly important for the current COVID-19 epidemic.

Suggested Citation

  • Bustamante-Castañeda, F. & Caputo, J.-G. & Cruz-Pacheco, G. & Knippel, A. & Mouatamide, F., 2021. "Epidemic model on a network: Analysis and applications to COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    • Handle: RePEc:eee:phsmap:v:564:y:2021:i:c:s0378437120308189
    DOI: 10.1016/j.physa.2020.125520
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    Citations

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    Cited by:

    1. Saha, Dipa & Mitra, Sayantan & Sensharma, Ankur, 2023. "Critically spanning epidemic outbreak cluster in random geometric networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
    2. Yang, Bo & Yu, Zhenhua & Cai, Yuanli, 2022. "The impact of vaccination on the spread of COVID-19: Studying by a mathematical model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 590(C).
    3. Pascoal, R. & Rocha, H., 2022. "Population density impact on COVID-19 mortality rate: A multifractal analysis using French data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).

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