Person:
López Herrero, María Jesús

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First Name
María Jesús
Last Name
López Herrero
URI
https://hdl.handle.net/20.500.14352/77420
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Estudios estadísticos
Department
Estadística y Ciencia de los Datos
Area
Estadística e Investigación Operativa
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2012 - 20205
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Start date: 1994 × Subject: 519.217 ×

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Now showing 1 - 5 of 5
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    Measuring infection transmission in a stochastic SIV model with infection reintroduction and imperfect vaccine
    (Acta Biotheoretica, 2020) Gamboa Pérez, María; López Herrero, María Jesús
    An additional compartment of vaccinated individuals is considered in a SIS stochastic epidemic model with infection reintroduction. The quantification of the spread of the disease is modeled by a continuous time Markov chain. A well-known measure of the initial transmission potential is the basic reproduction number R, which determines the herd immunity threshold or the critical proportion of immune individuals required to stop the spread of a disease when a vaccine offers a complete protection. Due to repeated contacts between the typical infective and previously infected individuals, R overestimates the average number of secondary infections and leads to, perhaps unnecessary, high immunization coverage. Assuming that the vaccine is imperfect, alternative measures to R are defined in order to study the influence of the initial coverage and vaccine efficacy on the transmission of the epidemic.
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    The stochastic SEIR model before extinction: computational approaches
    (Applied Mathematics and Computation, 2015) Artalejo Rodríguez, Jesús Manuel; Economou, A.; López Herrero, María Jesús
    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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    Stochastic epidemic models: new behavioral indicators of the disease spreading
    (Applied Mathematical Modelling, 2014) Artalejo Rodríguez, Jesús Manuel; López Herrero, María Jesús
    The purpose of this paper is to propose new indicators of the dynamics of infectious disease spread in stochastic epidemic models, including both global system-oriented descriptors (e.g. the final size measured as the number of individuals infected on a least one occasion during an outbreak) and individual-oriented descriptors (e.g. the time to reach an individual run of infections). We focus on birth-and-death models and the basic SIR epidemic model but the methodology remains valid for other nonlinear stochastic epidemic models. The theory is illustrated by numerical experiments which demonstrate that the proposed behavioral indicators can be applied efficiently
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    The single server retrial queue with finite population: a BSDE approach
    (Operational Research, 2012) Artalejo Rodríguez, Jesús Manuel; López Herrero, María Jesús; Matsatsinis, Nikolaos F.
    This paper uses the block-structured state-dependent event (BSDE) approach to generalize the scalar version of the single server retrial queue with finite population. The simple scalar version only involves exponential random variables, which make the underlying Markov chain tractable. However, this is a drawback in applications where the exponentiality is not a realistic assumption and the flows are correlated. The BSDE approach provides a versatile tool to deal with a non-exponential model with correlated flows, but keeping tractable the dimensionality of the block-structured Markov chain. We focus on the investigation of the limiting distribution of the system state and the waiting time. The theory is illustrated by numerical experiments, which demonstrate that the proposed BSDE approach can be applied efficiently
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    The deterministic SIS epidemic model in a Markovian random environment
    (Journal of Mathematical Biology, 2016) Economou, Antonis; López Herrero, María Jesús
    We consider the classical deterministic susceptible-infective-susceptible epidemic model, where the infection and recovery rates depend on a background environmental process that is modeled by a continuous time Markov chain. This framework is able to capture several important characteristics that appear in the evolution of real epidemics in large populations, such as seasonality effects and environmental influences. We propose computational approaches for the determination of various distributions that quantify the evolution of the number of infectives in the population.