Study of links between people in urban areas based on mobility data for the city of São Paulo

Autores

  • Matheus de Moraes Gonçalves Correia
  • Jéssica Domingues Lamosa
  • Vander Luis de Souza Freitas
  • Lívia Rodrigues Tomás
  • Leonardo Bacelar Lima Santos

DOI:

https://doi.org/10.5540/03.2023.010.01.0104

Palavras-chave:

Complex Networks, COVID-19, Brazil, São Paulo

Resumo

Our study explores the average degree and clustering of a complex mobility network designed to model and simulate the COVID-19 pandemic. To construct this network, we utilized mobility data collected in São Paulo, creating a network in which each node represents an individual, and each edge weight denotes the duration of contact between individuals during a typical day. By analyzing data from an Origin-Destination Research, we calculated the average degree and weighted clustering coefficient of the network for various minimum contact duration. We aimed to understand the effect of increasing minimum contact duration on network structure. Our findings indicate that networks with different minimum contact duration remained sparse, as the average degree of the generated graphs decreased.

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Biografia do Autor

Matheus de Moraes Gonçalves Correia

INPE, São José dos Campos, SP

Jéssica Domingues Lamosa

UNIFESP, São José dos Campos, SP

Vander Luis de Souza Freitas

Department of Computing - UFOP, Ouro Preto, MG

Lívia Rodrigues Tomás

CEMADEN, São José dos Campos, SP

Leonardo Bacelar Lima Santos

CEMADEN, São José dos Campos, SP

Referências

Linda JS Allen et al. Mathematical epidemiology. Vol. 1945. Springer, 2008. doi: 10. 1007/978-3-540-78911-6.

Albert-László Barabási and Márton Pósfai. Network science. Cambridge: Cambridge University Press, 2016. isbn: 9781107076266 1107076269.

Wesley Cota et al. “Monitoring the number of COVID-19 cases and deaths in Brazil at municipal and federative units level”. In: (2020).

Vander LS Freitas, Gladston JP Moreira, and Leonardo BL Santos. “Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks toward SARS-CoV-2 containment”. In: PeerJ 8 (2020), e10287. issn: 2167-8359. doi: 10.7717/peerj.10287.

Vander Luis de Souza Freitas et al. “The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil”. In: Cadernos de Saúde Pública 36 (2020), e00184820. issn: 1678-4464. doi: 10.1590/0102-311X00184820.

J. D. Lamosa et al. “Topological indexes and community structure for urban mobility networks: Variations in a business day”. In: PLoS ONE 16.3 (3 March 2021), e0248126. issn:19326203. doi: 10.1371/journal.pone.0248126.

P. O. B. Netto and S. Jurkiewicz. Grafos: introdução e prática. Vol. 2. Blucher, 2017. isbn: 9788521211334.

Relatório Sintese (Pesquisa Origem-Destino). https://transparencia.metrosp.com.br/dataset/pesquisa-origem-e-destino/resource/b3d93105-f91e-43c6-b4c0-8d9c617a27fc.Online; accessed 04-December-2022. 2017.

Eduardo R Pinto, Erivelton G Nepomuceno, and Andriana SLO Campanharo. “Impact of network topology on the spread of infectious diseases”. In: TEMA (São Carlos) 21 (2020), pp. 95–115. doi: 10.5540/tema.2020.021.01.0095.

Duncan J Watts and Steven H Strogatz. “Collective dynamics of ‘small-world’networks”. In: nature 393.6684 (1998), pp. 440–442. doi: 10.1038/30918.

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Publicado

2023-12-18

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