IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i10p3356-d357054.html
   My bibliography  Save this article

The Predictive Capacity of Air Travel Patterns during the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness

Author

Listed:
  • Panayotis Christidis

    (Directorate C: Energy and Transport, Joint Research Centre, European Commission, c/Inca Garcilaso 3, ES-41092 Sevilla, Spain)

  • Aris Christodoulou

    (Directorate C: Energy and Transport, Joint Research Centre, European Commission, c/Inca Garcilaso 3, ES-41092 Sevilla, Spain)

Abstract

Air travel has a decisive role in the spread of infectious diseases at the global level. We present a methodology applied during the early stages of the COVID-19 pandemic that uses detailed aviation data at the final destination level in order to measure the risk of the disease spreading outside China. The approach proved to be successful in terms of identifying countries with a high risk of infected travellers and as a tool to monitor the evolution of the pandemic in different countries. The high number of undetected or asymptomatic cases of COVID-19, however, limits the capacity of the approach to model the full dynamics. As a result, the risk for countries with a low number of passengers from Hubei province appeared as low. Globalization and international aviation connectivity allow travel times that are much shorter than the incubation period of infectious diseases, a fact that raises the question of how to react in a potential new pandemic.

Suggested Citation

  • Panayotis Christidis & Aris Christodoulou, 2020. "The Predictive Capacity of Air Travel Patterns during the Global Spread of the COVID-19 Pandemic: Risk, Uncertainty and Randomness," IJERPH, MDPI, vol. 17(10), pages 1-15, May.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3356-:d:357054
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/10/3356/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/10/3356/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Njoya, Eric Tchouamou & Christidis, Panayiotis & Nikitas, Alexandros, 2018. "Understanding the impact of liberalisation in the EU-Africa aviation market," Journal of Transport Geography, Elsevier, vol. 71(C), pages 161-171.
    2. Gold, Lukas & Balal, Esmaeil & Horak, Tomas & Cheu, Ruey Long & Mehmetoglu, Tugba & Gurbuz, Okan, 2019. "Health screening strategies for international air travelers during an epidemic or pandemic," Journal of Air Transport Management, Elsevier, vol. 75(C), pages 27-38.
    3. Zhong Sun & Karuppiah Thilakavathy & S. Suresh Kumar & Guozhong He & Shi V. Liu, 2020. "Potential Factors Influencing Repeated SARS Outbreaks in China," IJERPH, MDPI, vol. 17(5), pages 1-11, March.
    4. Paolo Bajardi & Chiara Poletto & Jose J Ramasco & Michele Tizzoni & Vittoria Colizza & Alessandro Vespignani, 2011. "Human Mobility Networks, Travel Restrictions, and the Global Spread of 2009 H1N1 Pandemic," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
    5. Christidis, Panayotis, 2016. "Four shades of Open Skies: European Union and four main external partners," Journal of Transport Geography, Elsevier, vol. 50(C), pages 105-114.
    6. Abate, Megersa & Christidis, Panayotis, 2020. "The impact of air transport market liberalization: Evidence from EU's external aviation policy," Economics of Transportation, Elsevier, vol. 22(C).
    7. Varvara A. Mouchtouri & Eleni P. Christoforidou & Maria an der Heiden & Cinthia Menel Lemos & Margherita Fanos & Ute Rexroth & Ulrike Grote & Evelien Belfroid & Corien Swaan & Christos Hadjichristodou, 2019. "Exit and Entry Screening Practices for Infectious Diseases among Travelers at Points of Entry: Looking for Evidence on Public Health Impact," IJERPH, MDPI, vol. 16(23), pages 1-53, November.
    8. Haoran Yang & Frédéric Dobruszkes & Jiaoe Wang & Martin Dijst & Patrick Wiik, 2018. "Comparing China's urban systems in high-speed railway and airline networks," ULB Institutional Repository 2013/269363, ULB -- Universite Libre de Bruxelles.
    9. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    10. Zhu, Zhenran & Zhang, Anming & Zhang, Yahua, 2018. "Connectivity of intercity passenger transportation in China: A multi-modal and network approach," Journal of Transport Geography, Elsevier, vol. 71(C), pages 263-276.
    11. Wang, Jiaoe & Du, Delin & Huang, Jie, 2020. "Inter-city connections in China: High-speed train vs. inter-city coach," Journal of Transport Geography, Elsevier, vol. 82(C).
    12. Vittoria Colizza & Alain Barrat & Marc Barthelemy & Alain-Jacques Valleron & Alessandro Vespignani, 2007. "Modeling the Worldwide Spread of Pandemic Influenza: Baseline Case and Containment Interventions," PLOS Medicine, Public Library of Science, vol. 4(1), pages 1-16, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mueller, Falko, 2022. "Examining COVID-19-triggered changes in spatial connectivity patterns in the European air transport network up to June 2021," Research in Transportation Economics, Elsevier, vol. 94(C).
    2. Shuangjin Li & Shuang Ma & Junyi Zhang, 2023. "Building a system dynamics model to analyze scenarios of COVID-19 policymaking in tourism-dependent developing countries: A case study of Cambodia," Tourism Economics, , vol. 29(2), pages 488-512, March.
    3. Scott Orford & Yingling Fan & Philip Hubbard, 2023. "Urban public health emergencies and the COVID-19 pandemic. Part 1: Social and spatial inequalities in the COVID-city," Urban Studies, Urban Studies Journal Limited, vol. 60(8), pages 1329-1345, June.
    4. Cheng-Hong Yang & Borcy Lee & Pey-Huah Jou & Yu-Fang Chung & Yu-Da Lin, 2023. "Analysis and Forecasting of International Airport Traffic Volume," Mathematics, MDPI, vol. 11(6), pages 1-19, March.
    5. Salesi, Vinolia Kilinaivoni & Kan Tsui, Wai Hong & Fu, Xiaowen & Gilbey, Andrew, 2022. "Strategies for South Pacific Region to address future pandemics: Implications for the aviation and tourism sectors based on a systematic literature review (2010–2021)," Transport Policy, Elsevier, vol. 125(C), pages 107-126.
    6. Xin Li & Peixin Lu & Lianting Hu & Tianhui Huang & Long Lu, 2020. "Factors Associated with Mental Health Results among Workers with Income Losses Exposed to COVID-19 in China," IJERPH, MDPI, vol. 17(15), pages 1-11, August.
    7. Gualini, Andrea & Zou, Li & Dresner, Martin, 2023. "Airline strategies during the pandemic: What worked?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
    8. Choi, Youngran & Zou, Li & Dresner, Martin, 2022. "The effects of air transport mobility and global connectivity on viral transmission: Lessons learned from Covid-19 and its variants," Transport Policy, Elsevier, vol. 127(C), pages 22-30.
    9. Myung Ja Kim & C. Michael Hall & Mark Bonn, 2021. "Does International Travel Frequency Affect COVID-19 Biosecurity Behavior in the United States?," IJERPH, MDPI, vol. 18(8), pages 1-17, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huang, Yan & Zong, Huiming, 2022. "The intercity railway connections in China: A comparative analysis of high-speed train and conventional train services," Transport Policy, Elsevier, vol. 120(C), pages 89-103.
    2. Warnock-Smith, David & Christidis, Panayotis, 2021. "European Union-Latin America/Caribbean air transport connectivity and competitiveness in different air policy contexts," Journal of Transport Geography, Elsevier, vol. 92(C).
    3. Li, Tao & Wang, Jiaoe & Huang, Jie & Yang, Wenyue & Chen, Zhuo, 2021. "Exploring the dynamic impacts of COVID-19 on intercity travel in China," Journal of Transport Geography, Elsevier, vol. 95(C).
    4. Abate, Megersa & Christidis, Panayotis & Purwanto, Alloysius Joko, 2020. "Government support to airlines in the aftermath of the COVID-19 pandemic," Journal of Air Transport Management, Elsevier, vol. 89(C).
    5. Bernardo, Valeria & Fageda, Xavier, 2020. "Impacts of competition on connecting travelers: Evidence from the transatlantic aviation market," Transport Policy, Elsevier, vol. 96(C), pages 141-151.
    6. Xiaoyan Mu & Anthony Gar-On Yeh & Xiaohu Zhang, 2021. "The interplay of spatial spread of COVID-19 and human mobility in the urban system of China during the Chinese New Year," Environment and Planning B, , vol. 48(7), pages 1955-1971, September.
    7. Haoran Zhang & Ying Chai & Xuyu Yang & Wenli Zhao, 2022. "High-Speed Rail and Urban Growth Disparity: Evidence from China," Sustainability, MDPI, vol. 14(13), pages 1-13, July.
    8. Zhang, Yahua & Zhang, Anming & Wang, Jiaoe, 2020. "Exploring the roles of high-speed train, air and coach services in the spread of COVID-19 in China," Transport Policy, Elsevier, vol. 94(C), pages 34-42.
    9. Salesi, Vinolia Kilinaivoni & Kan Tsui, Wai Hong & Fu, Xiaowen & Gilbey, Andrew, 2022. "Strategies for South Pacific Region to address future pandemics: Implications for the aviation and tourism sectors based on a systematic literature review (2010–2021)," Transport Policy, Elsevier, vol. 125(C), pages 107-126.
    10. Sunio, Varsolo & Mateo-Babiano, Iderlina, 2022. "Pandemics as ‘windows of opportunity’: Transitioning towards more sustainable and resilient transport systems," Transport Policy, Elsevier, vol. 116(C), pages 175-187.
    11. Cheng, Junmei & Chen, Zhenhua, 2021. "Impact of high-speed rail on the operational capacity of conventional rail in China," Transport Policy, Elsevier, vol. 110(C), pages 354-367.
    12. Tchouamou Njoya, Eric & Buhari Isah, Aliyu, 2023. "Assessing the economic impact of the single African air transport market: The case of Tanzania," Research in Transportation Economics, Elsevier, vol. 101(C).
    13. Wang, Yiqiao & Lu, Qiaoyi & Cao, Xianbin & Zhou, Xuesong & Latora, Vito & Tong, Lu Carol & Du, Wenbo, 2020. "Travel time analysis in the Chinese coupled aviation and high-speed rail network," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    14. Zhangfeng Yao & Kunhui Ye & Liang Xiao & Xiaowei Wang, 2021. "Radiation Effect of Urban Agglomeration’s Transportation Network: Evidence from Chengdu–Chongqing Urban Agglomeration, China," Land, MDPI, vol. 10(5), pages 1-21, May.
    15. Liu, Shuli & Wan, Yulai & Zhang, Anming, 2020. "Does China’s high-speed rail development lead to regional disparities? A network perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 138(C), pages 299-321.
    16. Chow, Clement Kong Wing & Tsui, Wai Hong Kan & Wu, Hanjun, 2021. "Airport subsidies and domestic inbound tourism in China," Annals of Tourism Research, Elsevier, vol. 90(C).
    17. Huang, Yan & Zong, Huiming, 2020. "The spatial distribution and determinants of China’s high-speed train services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 56-70.
    18. Yan Hong & Gangwei Cai & Zhoujin Mo & Weijun Gao & Lei Xu & Yuanxing Jiang & Jinming Jiang, 2020. "The Impact of COVID-19 on Tourist Satisfaction with B&B in Zhejiang, China: An Importance–Performance Analysis," IJERPH, MDPI, vol. 17(10), pages 1-19, May.
    19. Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020. "Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss," Journal of International Money and Finance, Elsevier, vol. 104(C).
    20. Rob Hyndman & Heather Booth & Farah Yasmeen, 2013. "Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models," Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 261-283, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:17:y:2020:i:10:p:3356-:d:357054. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.