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SARS-CoV-2 Spread Forecast Dynamic Model Validation through Digital Twin Approach, Catalonia Case Study

Author

Listed:
  • Pau Fonseca i Casas

    (Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain)

  • Joan Garcia i Subirana

    (Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain)

  • Víctor García i Carrasco

    (Department of Statistics and Operations Research, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain)

  • Xavier Pi i Palomés

    (Open University of Catalonia, Computer Science, Multimedia and Telecommunications Studies, 08860 Barcelona, Spain)

Abstract

The spread of the SARS-CoV-2 modeling is a challenging problem because of its complex nature and lack of information regarding certain aspects. In this paper, we explore a Digital Twin approach to model the pandemic situation in Catalonia. The Digital Twin is composed of three different dynamic models used to perform the validations by a Model Comparison approach. We detail how we use this approach to obtain knowledge regarding the effects of the nonpharmaceutical interventions and the problems we faced during the modeling process. We use Specification and Description Language (SDL) to represent the compartmental forecasting model for the SARS-CoV-2. Its graphical notation simplifies the different specialists’ understanding of the model hypotheses, which must be validated continuously following a Solution Validation approach. This model allows the successful forecasting of different scenarios for Catalonia. We present some formalization details, discuss the validation process and present some results obtained from the validation model discussion, which becomes a digital twin of the pandemic in Catalonia.

Suggested Citation

  • Pau Fonseca i Casas & Joan Garcia i Subirana & Víctor García i Carrasco & Xavier Pi i Palomés, 2021. "SARS-CoV-2 Spread Forecast Dynamic Model Validation through Digital Twin Approach, Catalonia Case Study," Mathematics, MDPI, vol. 9(14), pages 1-17, July.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:14:p:1660-:d:594462
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    References listed on IDEAS

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    1. Mr. Pragyan Deb & Davide Furceri & Mr. Jonathan David Ostry & Nour Tawk, 2020. "The Effect of Containment Measures on the COVID-19 Pandemic," IMF Working Papers 2020/159, International Monetary Fund.
    2. Chen, Simiao & Prettner, Klaus & Kuhn, Michael & Bloom, David E., 2021. "The economic burden of COVID-19 in the United States: Estimates and projections under an infection-based herd immunity approach," The Journal of the Economics of Ageing, Elsevier, vol. 20(C).
    3. Cleo Anastassopoulou & Lucia Russo & Athanasios Tsakris & Constantinos Siettos, 2020. "Data-based analysis, modelling and forecasting of the COVID-19 outbreak," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-21, March.
    4. Ndaïrou, Faïçal & Area, Iván & Nieto, Juan J. & Silva, Cristiana J. & Torres, Delfim F.M., 2021. "Fractional model of COVID-19 applied to Galicia, Spain and Portugal," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
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