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Measures to assess a warning vaccination level in a stochastic SIV model with imperfect vaccine

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Abstract

A stochastic Markovian Susceptible-Infectious-Susceptible (SIS) model, with infection reintroduction is considered to represent the evolution of an epidemic process within a finite population. Disease is assumed to be a contact disease whose effect can be prevented by a vaccine. Before the epidemic process emerges, individuals got vaccinated to assure that the population is protected by herd immunity. In consequence, we formulate the model by adding a new compartment for vaccine protected individuals. The administered vaccine is not a perfect one and consequently it fails in a proportion of vaccinated individuals that are not protected against the vaccine preventable communicable disease. Hence, while the infectious process is in progress, the initial vaccine coverage declines and herd immunity could be lost. A threshold on the size of the vaccinated group is included as a warning measure on the protection of the community. Our objective is to define and study random characteristics, depending on the vaccination eligible group, that could advise health authorities when to launch a new vaccination program to recover the initial immunity level.

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CRUE-CSIC (Acuerdos Transformativos 2021)

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