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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8586| Time-resolving the COVID-19 outbreak using frequency domain analysis | |
| Keno Krewer Mischa Bonn | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://doi.org/10.1101/2020.05.07.20094078 | |
| https://www.medrxiv.org/content/10.1101/2020.05.07.20094078v1 | |
| Difficulties assessing and predicting the current outbreak of the severe acute respiratory syndrome coronavirus 2 can be traced, in part, to the limitations of a static description of a dynamic system. Fourier transforming the time-domain data of infections and fatalities into the frequency domain makes the dynamics easily accessible. Defining a quantity like the “case fatality” as a spectral density allows a more sensible comparison between different countries and demographics during an ongoing outbreak. Such a case fatality informs not only how many of the confirmed cases end up as fatalities, but also when. For COVID-19, knowing this time and using the entire case fatality spectrum allows determining that an outbreak had entered a steady-state (most likely its end) about 14 days before this is obvious from time-domain data. The lag between confirmations and deaths also helps to estimate the effectiveness of contact management: The larger the lag, the less time the average confirmed person had to infect people before quarantine. | |
| bioRxiv | |
| 11-05-2020 | |
| Preimpreso | |
| Inglés | |
| Público en general | |
| VIRUS RESPIRATORIOS | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Materiales de Consulta y Comunicados Técnicos |
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| Time-resolving the COVID-19 outbreak using frequency domain analysis.pdf | 919.72 kB | Adobe PDF | Visualizar/Abrir |