Estimation of COVID-19 dynamics “on a back-of-envelope”: Does the simplest SIR model provide quantitative parameters and predictions?
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DOI: 10.1016/j.chaos.2020.109841
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- Eugene B. Postnikov, 2016. "Dynamical prediction of flu seasonality driven by ambient temperature: influenza vs. common cold," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(1), pages 1-6, January.
- Fanelli, Duccio & Piazza, Francesco, 2020. "Analysis and forecast of COVID-19 spreading in China, Italy and France," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
- Eugene B. Postnikov, 2016. "Dynamical prediction of flu seasonality driven by ambient temperature: influenza vs. common cold," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(1), pages 1-6, January.
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- Bagal, Dilip Kumar & Rath, Arati & Barua, Abhishek & Patnaik, Dulu, 2020. "Estimating the parameters of susceptible-infected-recovered model of COVID-19 cases in India during lockdown periods," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
- Freire-Flores, Danton & Llanovarced-Kawles, Nyna & Sanchez-Daza, Anamaria & Olivera-Nappa, Álvaro, 2021. "On the heterogeneous spread of COVID-19 in Chile," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
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- Milad Haghani & Michiel C. J. Bliemer, 2020. "Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCoV literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2695-2726, December.
- Qiu, Hong & Wang, Qian & Wu, Qun & Zhou, Hongyong, 2022. "Does flattening the curve make a difference? An investigation of the COVID-19 pandemic based on an SIR model," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 159-165.
- Daniele Proverbio & Françoise Kemp & Stefano Magni & Andreas Husch & Atte Aalto & Laurent Mombaerts & Alexander Skupin & Jorge Gonçalves & Jose Ameijeiras-Alonso & Christophe Ley, 2021. "Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-21, May.
- Nathan H. Schumaker & Sydney M. Watkins, 2021. "Adding Space to Disease Models: A Case Study with COVID-19 in Oregon, USA," Land, MDPI, vol. 10(4), pages 1-13, April.
- Srivastava, H.M. & Saad, Khaled M. & Khader, M.M., 2020. "An efficient spectral collocation method for the dynamic simulation of the fractional epidemiological model of the Ebola virus," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
- Iván Area & Henrique Lorenzo & Pedro J. Marcos & Juan J. Nieto, 2021. "One Year of the COVID-19 Pandemic in Galicia: A Global View of Age-Group Statistics during Three Waves," IJERPH, MDPI, vol. 18(10), pages 1-14, May.
- Adak, Debadatta & Majumder, Abhijit & Bairagi, Nandadulal, 2021. "Mathematical perspective of Covid-19 pandemic: Disease extinction criteria in deterministic and stochastic models," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
- Arash Najmaei & Zahra Sadeghinejad, 2023. "Green and sustainable business models: historical roots, growth trajectory, conceptual architecture and an agenda for future research—A bibliometric review of green and sustainable business models," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 957-999, February.
- Jones, Andrew & Strigul, Nikolay, 2021. "Is spread of COVID-19 a chaotic epidemic?," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
- Yeşilkanat, Cafer Mert, 2020. "Spatio-temporal estimation of the daily cases of COVID-19 in worldwide using random forest machine learning algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
- S. A. Trigger & A. M. Ignatov, 2022. "Strain-stream model of epidemic spread in application to COVID-19," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(11), pages 1-8, November.
- Haiyue Chen & Benedikt Haus & Paolo Mercorelli, 2021. "Extension of SEIR Compartmental Models for Constructive Lyapunov Control of COVID-19 and Analysis in Terms of Practical Stability," Mathematics, MDPI, vol. 9(17), pages 1-25, August.
- Consolini, Giuseppe & Materassi, Massimo, 2020. "A stretched logistic equation for pandemic spreading," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
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Keywords
Covid-19; Compartmental epidemic model; SIR model; Logistic regression;All these keywords.
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