Modeling the coronavirus disease 2019 incubation period: impact on quarantine policy
The incubation period of coronavirus disease 2019 (COVID-19) is not always observed exactly due to uncertain onset times of infection and disease symptoms. In this paper, we demonstrate how to estimate the distribution of incubation and its association with patient demographic factors when the exact...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/344010 |
| Acceso en línea: | https://hdl.handle.net/2117/344010 https://dx.doi.org/10.3390/math8091631 |
| Access Level: | acceso abierto |
| Palabra clave: | COVID-19 Generalized odds-rate class of models Incubation period Infectious disease Interval censoring Left censoring Quarantine policy Classificació AMS::90 Operations research, mathematical programming Àrees temàtiques de la UPC::Matemàtiques i estadística |
| Sumario: | The incubation period of coronavirus disease 2019 (COVID-19) is not always observed exactly due to uncertain onset times of infection and disease symptoms. In this paper, we demonstrate how to estimate the distribution of incubation and its association with patient demographic factors when the exact dates of infection and symptoms’ onset may not be observed. The findings from analysis of the confirmed COVID-19 cases indicate that age could be associated with the incubation period, and an age-specific quarantine policy might be more efficient than a unified one in confining COVID-19. |
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