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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/3081| Modeling the COVID-19 pandemic - parameter identification and reliability of predictions | |
| Klaus Hackl. | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| 10.1101/2020.04.07.20056937 | |
| In this paper, we try to identify the parameters in an elementary epidemic model, the so-called SI-model, via non-linear regression using data of the COVID-19 pandemic. This is done based on the data for the number of total infections and daily infections, respectively. Studying the convergence behavior of the two parameter sets obtained this way, we attempt to estimate the reliability of predictions made concerning the future course of the epidemic. We validate this procedure using data for the case numbers in China and South Korea. Then we apply it in order to find predictions for Germany, Italy and the United States. The results are encouraging, but no final judgment on the validity of the procedure can yet be made. | |
| www.medrxiv.org | |
| 2020 | |
| Artículo | |
| https://www.medrxiv.org/content/10.1101/2020.04.07.20056937v2.full.pdf | |
| Inglés | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Artículos científicos |
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