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http://conacyt.repositorioinstitucional.mx/jspui/handle/1000/8865| Policy Implications of an Approximate Linear Infection Model for SARS-CoV-2 | |
| John McCarthy Bob Dumas | |
| Acceso Abierto | |
| Atribución-NoComercial-SinDerivadas | |
| https://doi.org/10.1101/2020.06.04.20122549 | |
| https://www.medrxiv.org/content/10.1101/2020.06.04.20122549v1 | |
| Abstract We propose a linear model of infection probability, and prove that this is a good approximation to a more refined model in which we assume infections come from a series of independent risks. We argue that the linearity assumption makes interpreting and using the model much easier, without significantly diminishing the reliability of the model. Competing Interest Statement Both authors received funding as Consultants for Delaware North, a company that may be affected by the research reported in the paper. Funding Statement Both authors received funding as Consultants for Delaware North, a company that may be affected by the research reported in the paper. McCarthy received funding from the National Institutes of Health, Grant R01 AG052550-01A1, and the National Science Foundation, Grant DMS 1565243 | |
| bioRxiv | |
| 08-06-2020 | |
| Preimpreso | |
| Inglés | |
| Público en general | |
| VIRUS RESPIRATORIOS | |
| Aparece en las colecciones: | Materiales de Consulta y Comunicados Técnicos |
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| Fichero | Tamaño | Formato | |
|---|---|---|---|
| Policy Implications of an Approximate Linear Infection Model for SARS-CoV-2.pdf | 266.63 kB | Adobe PDF | Visualizar/Abrir |