---
res:
bibo_abstract:
- In this article, we develop two independent and new approaches to model epidemic
spread in a network. Contrary to the most studied models, those developed here
allow for contacts with different probabilities of transmitting the disease (transmissibilities).
We then examine each of these models using some mean field type approximations.
The first model looks at the late-stage effects of an epidemic outbreak and allows
for the computation of the probability that a given vertex was infected. This
computation is based on a mean field approximation and only depends on the number
of contacts and their transmissibilities. This approach shares many similarities
with percolation models in networks. The second model we develop is a dynamic
model which we analyze using a mean field approximation which highly reduces the
dimensionality of the system. In particular, the original system which individually
analyses each vertex of the network is reduced to one with as many equations as
different transmissibilities. Perhaps the greatest contribution of this article
is the observation that, in both these models, the existence and size of an epidemic
outbreak are linked to the properties of a matrix which we call the R-matrix.
This is a generalization of the basic reproduction number which more precisely
characterizes the main routes of infection.@eng
bibo_authorlist:
- foaf_Person:
foaf_givenName: Arturo
foaf_name: Gómez, Arturo
foaf_surname: Gómez
- foaf_Person:
foaf_givenName: Goncalo
foaf_name: Oliveira, Goncalo
foaf_surname: Oliveira
foaf_workInfoHomepage: http://www.librecat.org/personId=58abbde8-f455-11eb-a497-98c8fd71b905
bibo_doi: 10.1038/s41598-022-19827-9
bibo_volume: 13
dct_date: 2023^xs_gYear
dct_identifier:
- UT:001003345000051
dct_isPartOf:
- http://id.crossref.org/issn/2045-2322
dct_language: eng
dct_publisher: Springer Nature@
dct_title: New approaches to epidemic modeling on networks@
...