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UID:1jhf7ilk9mh8ov8c7hqob6fg61@google.com
CATEGORIES:{lang hu}Differenciálegyenletek szeminárium{/lang}{lang en}Differential equations seminar{/lang}
SUMMARY:Sadegh Marzban (University of Szeged): A hybrid PDE-ABM model for infection dynamics: study on stochastic variability, application to SARS-COV-2 and influenza, and exploring some treatment options
LOCATION:Riesz Lecture Hall, 1st Floor, Bolyai Institute, Aradi Vértanúk tere 1., Sz
eged
DESCRIPTION;ENCODING=QUOTED-PRINTABLE:Abstract.
We propose a hybrid partial differential equation -- agent-b
ased (PDE--ABM) model to describe the spatio-temporal viral dynamics in a c
ell population. The virus concentration is considered as a continuous varia
ble and virus movement is modelled by diffusion, while changes in the state
s of cells (i.e. healthy, infected, dead) are represented by a stochastic a
gent-based model. The two subsystems are intertwined: the probability of an
agent getting infected in the ABM depends on the local viral concentration
, and the source term of viral production in the PDE is determined by the c
ells that are infected.
We develop a computational tool that allow
s us to study the hybrid system and the generated spatial patterns in detai
l. We systematically compare the outputs with a classical ODE system of vir
al dynamics, and find that the ODE model is a good approximation only if th
e diffusion coefficient is large.
We demonstrate that the model is
able to predict SARS--CoV--2 infection dynamics, and replicate the output
of in vitro experiments. Applying the model to influenza as well, we can ga
in insight into why the outcomes of these two infections are different.
DTSTAMP:20240329T022738Z
DTSTART;TZID=Europe/Budapest:20210923T110000
DTEND;TZID=Europe/Budapest:20210923T123000
SEQUENCE:0
TRANSP:OPAQUE
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