Facets (new session)
Description
Metadata
Settings
owl:sameAs
Inference Rule:
b3s
b3sifp
dbprdf-label
facets
http://dbpedia.org/resource/inference/rules/dbpedia#
http://dbpedia.org/resource/inference/rules/opencyc#
http://dbpedia.org/resource/inference/rules/umbel#
http://dbpedia.org/resource/inference/rules/yago#
http://dbpedia.org/schema/property_rules#
http://www.ontologyportal.org/inference/rules/SUMO#
http://www.ontologyportal.org/inference/rules/WordNet#
http://www.w3.org/2002/07/owl#
ldp
oplweb
skos-trans
virtrdf-label
None
About:
Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil
Goto
Sponge
NotDistinct
Permalink
An Entity of Type :
schema:ScholarlyArticle
, within Data Space :
covidontheweb.inria.fr
associated with source
document(s)
Type:
Academic Article
research paper
schema:ScholarlyArticle
New Facet based on Instances of this Class
Attributes
Values
type
Academic Article
research paper
schema:ScholarlyArticle
isDefinedBy
Covid-on-the-Web dataset
title
Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil
Creator
Giovanetti, Marta
Coura-Vital, Wendel
Reis, Alexandre
Alcantara, Junior
Ariston, Vasco
»more»
source
MedRxiv
abstract
Background. We investigated a likely scenario of COVID-19 spreading in Brazil through the complex airport network of the country, for the 90 days after the first national occurrence of the disease. After the confirmation of the first imported cases, the lack of a proper airport entrance control resulted in the infection spreading in a manner directly proportional to the amount of flights reaching each city, following first occurrence of the virus coming from abroad. Methodology. We developed a SIR (Susceptible-Infected-Recovered) model divided in a metapopulation structure, where cities with airports were demes connected by the number of flights. Subsequently, we further explored the role of Manaus airport for a rapid entrance of the pandemic into indigenous territories situated in remote places of the Amazon region. Results. The expansion of the SARS-CoV-2 virus between cities was fast, directly proportional to the airport closeness centrality within the Brazilian air transportation network. There was a clear pattern in the expansion of the pandemic, with a stiff exponential expansion of cases for all cities. The more an airport showed closeness centrality, the greater was its vulnerability to SARS-CoV-2. Conclusions. We discussed the weak pandemic control performance of Brazil in comparison with other tropical, developing countries, namely India and Nigeria. Finally, we proposed measures for containing virus spreading taking into consideration the scenario of high poverty.
has issue date
2020-03-27
(
xsd:dateTime
)
bibo:doi
10.1101/2020.03.26.20044370
has license
medrxiv
sha1sum (hex)
9b4523d559e329de3285744224611b9d969a111c
schema:url
https://doi.org/10.1101/2020.03.26.20044370
resource representing a document's title
Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil
resource representing a document's body
covid:9b4523d559e329de3285744224611b9d969a111c#body_text
is
schema:about
of
named entity 'flights'
named entity 'closeness centrality'
named entity 'infection'
named entity 'flights'
named entity 'cities'
»more»
◂◂ First
◂ Prev
Next ▸
Last ▸▸
Page 1 of 4
Go
Faceted Search & Find service v1.13.91 as of Mar 24 2020
Alternative Linked Data Documents:
Sponger
|
ODE
Content Formats:
RDF
ODATA
Microdata
About
OpenLink Virtuoso
version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software