https://www.socictopen.socict.org/files/original/6fc759f364e91f56633b9d0208c9a543.pdf 5caaadd0b91f4ff6d8f35754369acb05 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Severe airport sanitarian control could slow down the spreading of COVID-19 pandemics in Brazil Creator An entity primarily responsible for making the resource Wesley Dattilo, Sérvio Pontes Ribeiro, Alcides Castro e Silva, Alexandre Barbosa Reis, Aristóteles Góes-Neto, Luiz Carlos Junior Alcantara, Marta Giovanetti, Wendel Coura-Vital, Geraldo Wilson Fernandes, Vasco Ariston C. Azevedo Description An account of the resource 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. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource SIR model, SARS-CoV2 pandemic, Amazônia, Indigenous People, metapopulation dynamics, One-Ecohealth Identifier An unambiguous reference to the resource within a given context 10.7717/peerj.9446 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine