Universidade do Estado da Bahia - UNEB, Salvador, Bahia, Brazil; Centro Universitário SENAI/CIMATEC, Salvador, Bahia, Brazil; Núcleo de Pesquisa Aplicada e Inovação (NPAI), Universidade do Estado da Bahia-UNEB/Centro Universitário SENAI CIMATEC, Salvador, Bahia, Brazil.
Centro Universitário SENAI/CIMATEC, Salvador, Bahia, Brazil; Núcleo de Pesquisa Aplicada e Inovação (NPAI), Universidade do Estado da Bahia-UNEB/Centro Universitário SENAI CIMATEC, Salvador, Bahia, Brazil.
Epidemics. 2022 Jun;39:100587. doi: 10.1016/j.epidem.2022.100587. Epub 2022 Jun 1.
The COVID-19 pandemic, caused by the highly transmissible SARS-CoV-2 virus, has overloaded health systems in many contexts Conant and Wolfe (2008). Brazil has experienced more than 345,000 deaths, as of April/2021 Conant and Wolfe (2008), with dire consequences for the country's public and private health systems. This paper aims to estimate the synchronization graph between the cities' contagion waves from public COVID-19 data records. For this purpose, the Motif-Synchronization method Magwire et al. (2011) was applied to publicly available COVID-19 data records to determine the sequential relationship of occurrence of the waves among Bahia's cities. We find synchronization between waves of infection between cities, suggesting diffusion of the disease in Bahia and a potential role for inter-city transportation Saba et al. (2018), Saba et al. (2014), Araújo et al. (2018) in the dynamics of this phenomenon McKee and Stuckler (2020), Chinazzi et al. (2020), Tizzoni et al. (2014). Our main contribution lies in the use of the Motif-Synchronization method applied to COVID-19 data records, with the results revealing a pattern of disease spread that extends beyond city boundaries.
由高传染性 SARS-CoV-2 病毒引起的 COVID-19 大流行，使许多国家的卫生系统不堪重负。截至 2021 年 4 月，巴西已有超过 34.5 万人死亡，这对该国的公共和私营卫生系统造成了严重后果。本文旨在根据公开的 COVID-19 数据记录，估计城市间传染病波的同步图。为此，应用 Magwire 等人（2011）的 Motif-Synchronization 方法，对公开的 COVID-19 数据记录进行分析，以确定巴伊亚州各城市之间传染病波发生的先后顺序关系。我们发现城市间感染波之间存在同步现象，这表明疾病在巴伊亚州的传播和城市间交通在这一现象的动态中可能起到了一定作用，McKee 和 Stuckler（2020），Chinazzi 等人（2020），Tizzoni 等人（2014）。我们的主要贡献在于使用 Motif-Synchronization 方法应用于 COVID-19 数据记录，结果揭示了一种超越城市边界的疾病传播模式。
