Measuring the mobility impact on the COVID-19 pandemic

Thyago Celso C. Nepomuceno; Thalles Vitelli Garcez; Lúcio Camara e Silva; Artur Paiva Coutinho; Thyago Celso C. Nepomuceno; Thalles Vitelli Garcez; Lúcio Camara e Silva; Artur Paiva Coutinho

doi:10.3934/mbe.2022332

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 7: 7032-7054. doi: 10.3934/mbe.2022332

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Measuring the mobility impact on the COVID-19 pandemic

1.
Núcleo de Tecnologia, Federal University of Pernambuco, Km 59, s/n, Nova Caruaru, Caruaru, PE, Brazil
2.
Dipartimento di Ingegneria Informatica Automatica e Gestionale Antonio Ruberti, Sapienza University of Rome, Via Ariosto, 25, Roma, Italy

Academic Editor: Daniel Rossit

Received: 28 December 2021 Revised: 11 April 2022 Accepted: 25 April 2022 Published: 12 May 2022

This assessment aims at measuring the impact of different location mobility on the COVID-19 pandemic. Data over time and over the 27 Brazilian federations in 5 regions provided by Google's COVID-19 community mobility reports and classified by place categories (retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences) are autoregressed on the COVID-19 incidence in Brazil using generalized linear regressions to measure the aggregate dynamic impact of mobility on each socioeconomic category. The work provides a novel multicriteria approach for selecting the most appropriate estimation model in the context of this application. Estimations for the time gap between contagion and data disclosure for public authorities' decision-making, estimations regarding the propagation rate, and the marginal mobility contribution for each place category are also provided. We report the pandemic evolution on the dimensions of cases and a geostatistical analysis evaluating the most critical cities in Brazil based on optimized hotspots with a brief discussion on the effects of population density and the carnival.
- COVID-19,
- mobility,
- interventions,
- social distancing,
- quarantines,
- prediction,
- generalized linear regression,
- geographic information systems,
- optimized hotspots analysis
Citation: Thyago Celso C. Nepomuceno, Thalles Vitelli Garcez, Lúcio Camara e Silva, Artur Paiva Coutinho. Measuring the mobility impact on the COVID-19 pandemic[J]. Mathematical Biosciences and Engineering, 2022, 19(7): 7032-7054. doi: 10.3934/mbe.2022332

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Abstract

This assessment aims at measuring the impact of different location mobility on the COVID-19 pandemic. Data over time and over the 27 Brazilian federations in 5 regions provided by Google's COVID-19 community mobility reports and classified by place categories (retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences) are autoregressed on the COVID-19 incidence in Brazil using generalized linear regressions to measure the aggregate dynamic impact of mobility on each socioeconomic category. The work provides a novel multicriteria approach for selecting the most appropriate estimation model in the context of this application. Estimations for the time gap between contagion and data disclosure for public authorities' decision-making, estimations regarding the propagation rate, and the marginal mobility contribution for each place category are also provided. We report the pandemic evolution on the dimensions of cases and a geostatistical analysis evaluating the most critical cities in Brazil based on optimized hotspots with a brief discussion on the effects of population density and the carnival.

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