Measuring the mobility impact on the COVID-19 pandemic

被引:5
|
作者
Nepomuceno, Thyago Celso C. [1 ,2 ]
Garcez, Thalles Vitelli [1 ]
Silva, Lucio Camara e [1 ]
Coutinho, Artur Paiva [1 ]
机构
[1] Univ Fed Pernambuco, Nucleo Tecnol, Km 59 S-N, Caruaru, PE, Brazil
[2] Sapienza Univ Rome, Dipartimento Ingn Informat Automat & Gest Antonio, Via Ariosto 25, Rome, Italy
关键词
COVID-19; mobility; interventions; social distancing; quarantines; prediction; generalized linear regression; geographic information systems; optimized hotspots analysis; BRAZIL;
D O I
10.3934/mbe.2022332
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:7032 / 7054
页数:23
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