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  1. Article: Urban mobility patterns and the spatial distribution of infections in Santiago de Chile.

    Bedoya-Maya, Felipe / Calatayud, Agustina / Giraldez, Francisca / Sánchez González, Santiago

    Transportation research. Part A, Policy and practice

    2022  Volume 163, Page(s) 43–54

    Abstract: The process of a virus spread is inherently spatial. Even though Latin America became the epicenter of the COVID-19 pandemic in May 2020, there is still little evidence of the relationship between urban mobility and virus propagation in the region. This ... ...

    Abstract The process of a virus spread is inherently spatial. Even though Latin America became the epicenter of the COVID-19 pandemic in May 2020, there is still little evidence of the relationship between urban mobility and virus propagation in the region. This paper combines network analysis of mobility patterns in public transportation with a spatial error correction model for Santiago de Chile. Results indicate that a 10% higher number of daily public transportation trips received by an administrative unit in the city was associated with a 1.3% higher number of confirmed COVID-19 cases per 100,000 inhabitants. Following these findings, we propose an empirical method to identify and classify neighborhoods according to the level and type of risk for COVID-19-like disease propagation, helping policymakers manage mobility during the initial stages of an epidemic outbreak.
    Language English
    Publishing date 2022-07-09
    Publishing country England
    Document type Journal Article
    ZDB-ID 2015887-7
    ISSN 0965-8564 ; 0191-2607
    ISSN 0965-8564 ; 0191-2607
    DOI 10.1016/j.tra.2022.06.011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Understanding the Effect of Traffic Congestion on Accidents Using Big Data

    Santiago Sánchez González / Felipe Bedoya-Maya / Agustina Calatayud

    Sustainability, Vol 13, Iss 7500, p

    2021  Volume 7500

    Abstract: Understanding the temporal and spatial dynamics of traffic accidents are a key determinant in their mitigation. This article leverages big data and a Poisson model with fixed effects to understand the causality of traffic congestion on road accidents in ... ...

    Abstract Understanding the temporal and spatial dynamics of traffic accidents are a key determinant in their mitigation. This article leverages big data and a Poisson model with fixed effects to understand the causality of traffic congestion on road accidents in ten cities in Latin America: Bogota, Buenos Aires, Lima, Mexico City, Montevideo, Rio de Janeiro, San Salvador, Santiago, Santo Domingo, and Sao Paulo. Analyzing over 10 billion observations in 2019, results show a positive non-linear causality of congestion on the number of accidents. Overall, the results suggest that a 10% reduction in traffic delay would reduce accidents by 3.4%, equivalent to over 72 thousand traffic accidents. Sao Paulo and Mexico City would be particularly benefited, with reductions of 5.4% and 4.7%, respectively. The results of this paper aim to support policymakers in emerging economies in implementing measures to reduce congestion and, with it, the related direct and indirect costs borne by societies.
    Keywords traffic accidents ; congestion ; big data ; Latin America ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Subject code 380
    Language English
    Publishing date 2021-07-01T00:00:00Z
    Publisher MDPI AG
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Containing the spatial spread of COVID-19 through the trucking network.

    Calatayud, Agustina / Bedoya-Maya, Felipe / Sánchez González, Santiago / Giraldez, Francisca

    Transport policy

    2021  Volume 115, Page(s) 4–13

    Abstract: The trucking industry is the backbone of domestic supply chains. In the context of the COVID-19 pandemic, road transportation has been essential to guarantee the supply of basic goods to confined urban areas. However, the connectivity of the trucking ... ...

    Abstract The trucking industry is the backbone of domestic supply chains. In the context of the COVID-19 pandemic, road transportation has been essential to guarantee the supply of basic goods to confined urban areas. However, the connectivity of the trucking network can also act as an efficient virus spreader. This paper applies network science to uncover the characteristics of the trucking network in one major Latin American country -Colombia- and provides evidence on freight networks' ability to spread contagious diseases spatially. Network metrics, official COVID-19 records at the municipality level, and a zero-inflated negative binomial model are used to test the association between network topology and confirmed COVID-19 cases. Results suggest that: (i) the number of COVID-19 cases in a municipality is linked to its level and type of network centrality; and (ii) being a port-city and a primary economic hub in the trucking network is associated with a higher probability of contracting earlier a pandemic. Based on these results, a risk-based approach is proposed to help policymakers implement containment measures.
    Language English
    Publishing date 2021-11-01
    Publishing country Netherlands
    Document type Journal Article
    ISSN 0967-070X
    ISSN 0967-070X
    DOI 10.1016/j.tranpol.2021.10.022
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Vulnerability of international freight flows to shipping network disruptions

    Calatayud, Agustina / Mangan, John / Palacin, Roberto

    Transportation research / E Vol. 108 , p. 195-208

    a multiplex network perspective

    2017  Volume 108, Page(s) 195–208

    Author's details Agustina Calatayud, John Mangan, Roberto Palacin
    Keywords Maritime transportation ; Logistics ; Complex networks ; Vulnerability ; International trade
    Language English
    Publisher Elsevier
    Publishing place Amsterdam
    Document type Article
    ZDB-ID 1380969-6 ; 2013782-5
    ISSN 1366-5545
    ISSN 1366-5545
    Database ECONomics Information System

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