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

  1. Sérvio Pontes Ribeiro
  2. Alcides Castro e Silva
  3. Wesley Dáttilo
  4. Alexandre Barbosa Reis
  5. Aristóteles Góes-Neto
  6. Luiz Carlos Junior Alcantara
  7. Marta Giovanetti
  8. Wendel Coura-Vital
  9. Geraldo Wilson Fernandes
  10. Vasco Ariston C. Azevedo

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Abstract

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.

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    SciScore for 10.1101/2020.03.26.20044370: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

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  2. Version published to 10.7717/peerj.9446
  3. Version published to 10.1101/2020.03.26.20044370v2 on medRxiv
  4. Version published to 10.1101/2020.03.26.20044370v1 on medRxiv