The stochastic SEIR model before extinction: computational approaches
We study a stochastic epidemic model of Susceptible-Exposed-Infective-Removed (SEIR) type and we quantify its behavior during an outbreak. More specifically, we model the epidemic by a continuous-time Markov chain and we develop efficient computational procedures for the distribution of the duration...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2015 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/101973 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/101973 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.22-76 616-036.22 519.217 519.216 Stochastic SEIR epidemic model Extinction time Ratio-of-expectations distribution Procesos estocásticos Enfermedades infecciosas 3212 Salud Publica 2404.01 Bioestadística 1208.06 Procesos de Markov 3202 Epidemiología |
| Sumario: | We study a stochastic epidemic model of Susceptible-Exposed-Infective-Removed (SEIR) type and we quantify its behavior during an outbreak. More specifically, we model the epidemic by a continuous-time Markov chain and we develop efficient computational procedures for the distribution of the duration of an outbreak. We also study the evolution of the epidemic before its extinction using the ratio-of-expectations (RE) distribution for the number of individuals in the various classes of the model. The obtained results are illustrated by numerical examples including an application to an outbreak of Marburg hemorrhagic fever |
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