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SUMMARY:A numerical simulation of an edge-based SEIR model on random netwo
rks
DTSTART;VALUE=DATE-TIME:20180709T064000Z
DTEND;VALUE=DATE-TIME:20180709T070000Z
DTSTAMP;VALUE=DATE-TIME:20200813T142817Z
UID:indico-contribution-313@conferences.maths.unsw.edu.au
DESCRIPTION:Speakers: Cherrylyn Alota (University of the Philippines Dilim
an / University of the Philippines Cebu)\nNetworks representing the spread
of infectious diseases in populations have been widely studied. Here\, w
e formulate an SEIR model using an edge-based approach on a static random
network with arbitrary degree distribution. The corresponding basic reprod
uction number and final epidemic size are computed. The SEIR model is used
to investigate the stochasticity of the SEIR dynamics. Assuming exposed\
, infection and recovery each happen at constant rates\, stochastic simula
tions of the SEIR dynamics are performed applying continuous-time Gillespi
e's algorithm given a Poisson or a power law with exponential cut-off degr
ee distributions. The resulting simulations match well with the numerical
predictions of the SEIR model given the initial conditions. Final epidemi
c size remains unchanged when the initial infecteds are varied. On the oth
er hand\, varying the disease parameters of the SEIR model affects the tim
e when the epidemic accelerates\, the peak of the epidemic\, and the final
epidemic size. These results capture scenarios of an epidemic in a netwo
rk implying control strategies in the disease transmissions.\n\nhttps://co
nferences.maths.unsw.edu.au/event/2/contributions/313/
LOCATION:University of Sydney New Law School/--020
URL:https://conferences.maths.unsw.edu.au/event/2/contributions/313/
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