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Estimating the infection horizon of COVID-19 in eight countries with a data-driven approach.
- Source :
-
Chaos, solitons, and fractals [Chaos Solitons Fractals] 2020 Jun; Vol. 135, pp. 109842. Date of Electronic Publication: 2020 Apr 27. - Publication Year :
- 2020
-
Abstract
- The COVID-19 pandemic has affected all countries of the world producing a substantial number of fatalities accompanied by a major disruption in their social, financial and educational organization. The strict disciplinary measures implemented by China were very effective and thus were subsequently adopted by most world countries to various degrees. The infection duration and number of infected persons are of critical importance for the battle against the pandemic. We use the quantitative landscape of the disease spreading in China as a benchmark and utilize infection data from eight countries to estimate the complete evolution of the infection in each of these countries. The analysis predicts successfully both the expected number of daily infections per country and, perhaps more importantly, the duration of the epidemic in each country. Our quantitative approach is based on a Gaussian spreading hypothesis that is shown to arise as a result of imposed measures in a simple dynamical infection model. This may have consequences and shed light in the efficiency of policies once the phenomenon is over.<br />Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (© 2020 Elsevier Ltd. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 0960-0779
- Volume :
- 135
- Database :
- MEDLINE
- Journal :
- Chaos, solitons, and fractals
- Publication Type :
- Academic Journal
- Accession number :
- 32341627
- Full Text :
- https://doi.org/10.1016/j.chaos.2020.109842