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Data analysis on Coronavirus spreading by macroscopic growth laws

Author

Listed:
  • P. Castorina

    (INFN, Sezione di Catania, I-95123 Catania, Italy)

  • A. Iorio

    (#x2020;Faculty of Mathematics and Physics, Charles University, V Holešovičkách 2, 18000 Prague 8, Czech Republic)

  • D. Lanteri

    (INFN, Sezione di Catania, I-95123 Catania, Italy†Faculty of Mathematics and Physics, Charles University, V Holešovičkách 2, 18000 Prague 8, Czech Republic3Dipartimento di Fisica e Astronomia, Università di Catania, Italy)

Abstract

To evaluate the effectiveness of the containment on the epidemic spreading of the new Coronavirus disease 2019, we carry on an analysis of the time evolution of the infection in a selected number of different Countries, by considering well-known macroscopic growth laws, the Gompertz law, and the logistic law. We also propose here a generalization of Gompertz law. Our data analysis permits an evaluation of the maximum number of infected individuals. The daily data must be compared with the obtained fits, to verify if the spreading is under control. From our analysis, it appears that the spreading reached saturation in China, due to the strong containment policy of the national government. In Singapore a large growth rate, recently observed, suggests the start of a new strong spreading. For South Korea and Italy, instead, the next data on new infections will be crucial to understand if the saturation will be reached for lower or higher numbers of infected individuals.

Suggested Citation

  • P. Castorina & A. Iorio & D. Lanteri, 2020. "Data analysis on Coronavirus spreading by macroscopic growth laws," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 31(07), pages 1-12, July.
    • Handle: RePEc:wsi:ijmpcx:v:31:y:2020:i:07:n:s012918312050103x
    DOI: 10.1142/S012918312050103X
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    Cited by:

    1. Pantano, Eleonora & Scarpi, Daniele & Vannucci, Virginia & Bilotta, Eleonora & Pantano, Pietro, 2022. "Probability-density risk-maps for tourism during emergencies," Annals of Tourism Research, Elsevier, vol. 92(C).
    2. Khalid A. Kheirallah & Belal Alsinglawi & Abdallah Alzoubi & Motasem N. Saidan & Omar Mubin & Mohammed S. Alorjani & Fawaz Mzayek, 2020. "The Effect of Strict State Measures on the Epidemiologic Curve of COVID-19 Infection in the Context of a Developing Country: A Simulation from Jordan," IJERPH, MDPI, vol. 17(18), pages 1-11, September.
    3. Abbasimehr, Hossein & Paki, Reza, 2021. "Prediction of COVID-19 confirmed cases combining deep learning methods and Bayesian optimization," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).

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