Incidence and time until disease detection in a stochastic model with vaccination and general transmission
In this study, we focus on the detection of a vaccine-preventable communicable disease using a stochastic SIR com-partmental model, which includes an additional compartment for individuals protected by vaccination. Althoughthe vaccine is administered as a preventive measure before the onset of the d...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universidad Complutense de Madrid (UCM) |
| Repositorio: | Docta Complutense |
| Idioma: | inglés |
| OAI Identifier: | oai:docta.ucm.es:20.500.14352/127382 |
| Acceso en línea: | https://hdl.handle.net/20.500.14352/127382 |
| Access Level: | acceso abierto |
| Palabra clave: | 519.2:61 616 Detection of the disease Imperfect vaccine Markov chain Stochastic epidemic model Medicina Estadística aplicada 2404.01 Bioestadística 6310.03 Enfermedad |
| Sumario: | In this study, we focus on the detection of a vaccine-preventable communicable disease using a stochastic SIR com-partmental model, which includes an additional compartment for individuals protected by vaccination. Althoughthe vaccine is administered as a preventive measure before the onset of the disease, its efficacy diminishes with time,which requires booster doses for susceptible individuals. Using a continuous-time Markov chain, we examine thetime required for disease detection (i.e., full confirmation of the disease) and analyze the incidence rates before detec-tion, both within the vaccinated group and throughout the population. To illustrate the usefulness of our theoreticalderivations and algorithmic schemes, we will present a numerical study involving the above descriptors for outbreaksof foot-and-mouth disease (FMD) in cattle. |
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