About: The inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. Grounded on the complex networks approach, cities are here represented as nodes and the flows as weighted edges - these geographical graphs, (geo)graphs, are handled in a Geographical Information System. We adopt the IBGE database from 2016, which contains the weekly flow of people between cities in terrestrial vehicles. The present work aims to investigate the correspondences of the networks' measures, like strength, degree, and betweenness with the emergence of cities with confirmed cases of COVID-19 in Brazil, and special attention is given to the state of Sao Paulo. We show that the results are better when certain thresholds are applied to the networks' flows to neglect the lowest-frequency travels. The correspondences presented statistical significance for most measures up to a certain period. Until the end of April, the best matchings are with the strength measure (total flow related to a node/city) under a high flow threshold in the Sao Paulo state, when the most connected cities are reached. After this stage, the lower thresholds become more suitable, indicating a possible signature of the outbreak interiorization process. Surprisingly, some countryside cities such as Campina Grande (state of Paraiba), Feira de Santana (state of Bahia), and Caruaru (state of Pernambuco) have higher strengths than some states' capitals. Furthermore, some cities from the Sao Paulo state such as Presidente Prudente and Ribeirao Preto are captured in the top-rank positions of all the analyzed network measures under different flow thresholds. Their importance in mobility is crucial and they are potential super spreaders like the states' capitals. Our analysis offers additional tools for understanding and decision support to inter-cities mobility interventions regarding the SARS-CoV-2 and other epidemics.   Goto Sponge  NotDistinct  Permalink

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  • The inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. Grounded on the complex networks approach, cities are here represented as nodes and the flows as weighted edges - these geographical graphs, (geo)graphs, are handled in a Geographical Information System. We adopt the IBGE database from 2016, which contains the weekly flow of people between cities in terrestrial vehicles. The present work aims to investigate the correspondences of the networks' measures, like strength, degree, and betweenness with the emergence of cities with confirmed cases of COVID-19 in Brazil, and special attention is given to the state of Sao Paulo. We show that the results are better when certain thresholds are applied to the networks' flows to neglect the lowest-frequency travels. The correspondences presented statistical significance for most measures up to a certain period. Until the end of April, the best matchings are with the strength measure (total flow related to a node/city) under a high flow threshold in the Sao Paulo state, when the most connected cities are reached. After this stage, the lower thresholds become more suitable, indicating a possible signature of the outbreak interiorization process. Surprisingly, some countryside cities such as Campina Grande (state of Paraiba), Feira de Santana (state of Bahia), and Caruaru (state of Pernambuco) have higher strengths than some states' capitals. Furthermore, some cities from the Sao Paulo state such as Presidente Prudente and Ribeirao Preto are captured in the top-rank positions of all the analyzed network measures under different flow thresholds. Their importance in mobility is crucial and they are potential super spreaders like the states' capitals. Our analysis offers additional tools for understanding and decision support to inter-cities mobility interventions regarding the SARS-CoV-2 and other epidemics.
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  • Brazil
  • Bahia
  • Member states of Mercosur
  • States of Brazil
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