Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Quentin Griette"'
Publikováno v:
Mathematical Biosciences and Engineering, Vol 19, Iss 1, Pp 537-594 (2022)
The COVID-19 outbreak, which started in late December 2019 and rapidly spread around the world, has been accompanied by an unprecedented release of data on reported cases. Our objective is to offer a fresh look at these data by coupling a phenomenolo
Externí odkaz:
https://doaj.org/article/2df3043a85ca4561a6b2e01472a78fb5
Publikováno v:
Mathematics in Applied Sciences and Engineering, Vol 2, Iss 3, Pp 149-160 (2021)
We provide a new method to analyze the COVID-19 cumulative reported cases data based on a two-step process: first we regularize the data by using a phenomenological model which takes into account the endemic or epidemic nature of the time period, the
Externí odkaz:
https://doaj.org/article/d1ae697fae4d4e8198230a8f513c140f
Autor:
Quentin Griette, Pierre Magal
Publikováno v:
Infectious Disease Modelling, Vol 6, Iss , Pp 273-283 (2021)
With the spread of COVID-19 across the world, a large amount of data on reported cases has become available. We are studying here a potential bias induced by the daily number of tests which may be insufficient or vary over time. Indeed, tests are har
Externí odkaz:
https://doaj.org/article/db56cfd599b14d24bfeedd57a9b96a71
Publikováno v:
Biology, Vol 11, Iss 3, p 345 (2022)
In this article we study the efficacy of vaccination in epidemiological reconstructions of COVID-19 epidemics from reported cases data. Given an epidemiological model, we developed in previous studies a method that allowed the computation of an insta
Externí odkaz:
https://doaj.org/article/1281cae6e54a469d89daa5e6e8659e05
Publikováno v:
Biology, Vol 9, Iss 6, p 132 (2020)
We investigate the age structured data for the COVID-19 outbreak in Japan. We consider a mathematical model for the epidemic with unreported infectious patient with and without age structure. In particular, we build a new mathematical model and a new
Externí odkaz:
https://doaj.org/article/371cc64c4512493eac5fb7eb0775e86a
Publikováno v:
European Journal of Applied Mathematics, Pp 1-29
This work describes a hyperbolic model for cell-cell repulsion with population dynamics. We consider the pressure produced by a population of cells to describe their motion. We assume that cells try to avoid crowded areas and prefer locally empty spa
Externí odkaz:
https://doaj.org/article/ee7ce5acf7cc44bc99d657cefb8c7e89
The emergence and the spread of multi-adapted pathogens is often viewed as a slow process resulting from the incremental accumulation of single adaptations. In bacteria, for instance, multidrug resistance to antibiotics may result from the sequential
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afdfe1972d7dd4feba6ed94430c095ad
https://doi.org/10.1101/2022.07.16.500289
https://doi.org/10.1101/2022.07.16.500289
Publikováno v:
Mathematical Models and Methods in Applied Sciences. 31:861-905
In this work, we describe a hyperbolic model with cell–cell repulsion with a dynamics in the population of cells. More precisely, we consider a population of cells producing a field (which we call “pressure”) which induces a motion of the cells
Publikováno v:
Discrete and Continuous Dynamical Systems - Series B. 26:1931-1966
In this work we describe a hyperbolic model with cell-cell repulsion with a dynamics in the population of cells. More precisely, we consider a population of cells producing a field (which we call "pressure") which induces a motion of the cells follow
Publikováno v:
Journal of Mathematical Biology
Journal of Mathematical Biology, Springer Verlag (Germany), 2020, 80 (7), pp.2257-2300. ⟨10.1007/s00285-020-01495-w⟩
Journal of Mathematical Biology, Springer Verlag (Germany), 2020, 80 (7), pp.2257-2300. ⟨10.1007/s00285-020-01495-w⟩
In this work, we discuss a cell-cell repulsion model based on a hyperbolic Keller-Segel equation with two populations, which aims at describing the cell growth and dispersion in the co-culture experiment from the work of Pasquier et al. (Biol Direct