Dissemin is shutting down on January 1st, 2025

Published in

PeerJ, PeerJ, (8), p. e9446, 2020

DOI: 10.7717/peerj.9446

Links

Tools

Export citation

Search in Google Scholar

Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Red circle
Preprint: archiving forbidden
Red circle
Postprint: archiving forbidden
Green circle
Published version: archiving allowed
Data provided by SHERPA/RoMEO

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 the first occurrence of the virus coming from abroad. Methodology We developed a 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 the 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 city 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 the cities. The more a city 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.