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On the global time evolution of the Covid-19 pandemic: Logistic modeling

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  • Miranda, L.C.M.
  • Devezas, Tessaleno

Abstract

In this article it is presented a multi-logistic model to describe the time evolution of the Covid-19 pandemics. The model is not intended as paragon for the accurate prediction of the future number of people infected, but instead as a useful phenomenological approach for a comprehensive understanding of the pandemic development, able to uncover some hidden aspects of its unfolding. Our results, using OWID data of total cases and daily cases of Covid-19 from March 12, 2020, up to September 27, 2021, brought to light that the pandemic has unfolded globally as a multi-step logistic, namely six logistic phases, each with its own characteristic duration and intensity. Moreover, it is demonstrated how differently the pandemics spread among different countries and continents. The methodology is tested regarding its ability of forecasting, and is demonstrated that it works well in the range of circa 30 days within a margin of less than 3% error while a given phase is still in development. The case study of Portugal demonstrates the benefit of preventive sanitary measures, as well as shows how disastrous it may be the absence of such measures due to hesitations and/or political positions. Completing the article, a qualitative analysis is presented to scrutinize the possible causes of the asymmetry observed in the diffusion of Covid-19 among the different continents and countries.

Suggested Citation

  • Miranda, L.C.M. & Devezas, Tessaleno, 2022. "On the global time evolution of the Covid-19 pandemic: Logistic modeling," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    • Handle: RePEc:eee:tefoso:v:175:y:2022:i:c:s0040162521008180
    DOI: 10.1016/j.techfore.2021.121387
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    References listed on IDEAS

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    1. Debecker, Alain & Modis, Theodore, 2021. "Poorly known aspects of flattening the curve of COVID-19," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    2. Devezas, Tessaleno, 2020. "The struggle SARS-CoV-2 vs. homo sapiens–Why the earth stood still, and how will it keep moving on?," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    3. Modis, Theodore, 1994. "Determination of the Uncertainties in S-Curve Logistic Fits," OSF Preprints n53pd, Center for Open Science.
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    2. Zubcoff, Jose-Jacobo & Olcina, Jorge & Morales, Javier & Mazón, Jose-Norberto & Mayoral, Asunción M., 2023. "Usefulness of open data to determine the incidence of COVID-19 and its relationship with atmospheric variables in Spain during the 2020 lockdown," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).

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