The correspondence between the structure of the terrestrial mobility network and the spreading of COVID-19 in Brazil.

Vander Luis de Souza Freitas,Leonardo Bacelar Lima Santos,Jeferson Feitosa Mendes,Thais Cláudia Roma de Oliveira Konstantyner,Cátia Souza do Nascimento Sepetauskas

doi:10.1590/0102-311x00184820

Abstract

The inter-cities mobility network is of great importance in understanding outbreaks, especially in Brazil, a continental-dimension country. We adopt the data from the Brazilian Ministry of Health and the terrestrial flow of people between cities from the Brazilian Institute of Geography and Statistics database in two scales: cities from Brazil, without the North region, and from the São Paulo State. Grounded on the complex networks approach, and considering that the mobility network serves as a proxy for the SARS-CoV-2 spreading, the nodes and edges represent cities and flows, respectively. Network centrality measures such as strength and degree are ranked and compared to the list of cities, ordered according to the day that they confirmed the first case of COVID-19. The strength measure captures the cities with a higher vulnerability of receiving new cases. Besides, it follows the interiorization process of SARS-CoV-2 in the São Paulo State when the network flows are above specific thresholds. Some countryside cities such as Feira de Santana (Bahia State), Ribeirão Preto (São Paulo State), and Caruaru (Pernambuco State) have strength comparable to 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.

Highlights

The world is currently facing a global public health emergency due to the COVID-19 pandemic, declared on March 11th, 2020 by the World Health Organization (WHO) 1
We focus on two versions of each network for certain flow thresholds η, the η0 (η = 0) that is the original network from the IBGE data and ηd (η = d)
The diameter of the networks for varying η is computed and the higher threshold with maximum diameter is found for both networks: ηd = 507.55 for Brazil whitouth North region and ηd = 169.9 for São Paulo State

Summary

Introduction

The world is currently facing a global public health emergency due to the COVID-19 pandemic, declared on March 11th, 2020 by the World Health Organization (WHO) 1. As of June 4th, 2020, more than 6.7 million cases have been confirmed worldwide, with almost 400,000 deaths. In Brazil, the first documented case was in the city of São Paulo on February 26th, 2020. There are about 615,000 confirmed cases and 34,000 deaths in the national territory 2 The complex network approach 8 emerges as a natural mechanism to handle mobility data computationally, taking areas as nodes (fixed) and movements between origins and destinations as connections (flows). The cities that receive more people are more vulnerable to SARS-CoV-2. The betweenness centrality, on the other hand, considers the entire network to depict the topological importance of a city in the routes that are more likely to be used

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