Correlating USA COVID-19 cases at epidemic onset days to domestic flights passenger inflows by state

J. A. Ruiz-Gayosso (), M. del Castillo-Escribano (), E. Hernández-Ramírez (), M. del Castillo-Mussot, A. Pérez-Riascos () and J. Hernández-Casildo ()
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J. A. Ruiz-Gayosso: Facultad de Ciencias, Universidad Nacional Autónoma de Mexico, Mexico City 04510, Mexico
M. del Castillo-Escribano: Escuela Nacional de Estudios Superiores, Universidad Nacional Autónoma de Mexico, Morelia 58190, Mexico
E. Hernández-Ramírez: Instituto de Investigaciones Económicas, Universidad Nacional Autónoma de Mexico, Mexico City 04510, Mexico
M. del Castillo-Mussot: Instituto de Física, Universidad Nacional Autónoma de Mexico, Mexico City 04510, Mexico
A. Pérez-Riascos: Instituto de Física, Universidad Nacional Autónoma de Mexico, Mexico City 04510, Mexico
J. Hernández-Casildo: Escuela Superior de Física y Matemáticas, Instituto Politécnico Nacional, Mexico City 07738, Mexico
Authors registered in the RePEc Author Service: Eric Hernández Ramírez ()

International Journal of Modern Physics C (IJMPC), 2021, vol. 32, issue 01, 1-14

Abstract: In the USA, COVID-19 first infection cases were imported by external travelers. At the epidemic onset days, we assume that the disease partially spreads due to domestic passengers air transportation in its densely connected airport network. Taking into account all USA states, we arranged COVID-19 infected cases data in a convenient common time origin timeline as if the beginning of the epidemic would have occurred simultaneously in every state. Looking for a trend between cases and air passengers, we obtained with this timeline very good statistical Pearson and Spearman correlations between accumulated infected cases by state and a positive power of the product TP, where T is the domestic flight passengers (travelers) inflow by state before the epidemic and P is its population. We also found a good correlation between percentages of urban area by state and their COVID-19 daily new cases growth rates at onset days.

Keywords: COVID-19; diffusion; human mobility; scaling laws (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1142/S0129183121500145

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