Spatial Dynamics for Spreading Sars-COV-2 in Brazil
DOI:
https://doi.org/10.17533/udea.rib.v44n3e345708Keywords:
networks, graphs theory, SARS-CoV-2, COVID-19, information retrievalAbstract
This paper exposes the problem of the current SARS-CoV-2 pandemic that is plaguing humanity. It reports that authors claim that pandemics can become routine, considering that the viral exchange between species has occurred more frequently due to the regular presence of man in various ecosystems. It presents a brief characterization of interstate passenger transport in Brazil. Describes the concept of PageRank, a metric that classifies web pages. Reminds the concepts of scheduling and correlation. It obtains, via open data, information on interstate and international transport in Brazil. It creates, in the form of a graph, a passenger flow network and performs a preliminary exploratory analysis there. Semantically paralleling the network created with the web, it calculates its PageRank metric and establishes its correlation with the date of the first infection in each Federative Unit in the country. Finally, it outlines a predictability of the ordinal days when each Federative Unit would be infected by means of linear regression, highlighting that, in addition to the calculations, the methodology has more relevance as a result presented.
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