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Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil
Preprint
in English
| medRxiv
| ID: ppmedrxiv-20044370
Journal article
A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See journal article
ABSTRACT
BackgroundWe 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. MethodologyWe 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. ResultsThe 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. ConclusionsWe 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.
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Full text:
Available
Collection:
Preprints
Database:
medRxiv
Type of study:
Observational study
Language:
English
Year:
2020
Document type:
Preprint