IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v11y2019i4p92-d220787.html
   My bibliography  Save this article

Epidemic Spreading in Urban Areas Using Agent-Based Transportation Models

Author

Listed:
  • Jürgen Hackl

    (Institute of Construction and Infrastructure Management, ETH Zurich, 8093 Zurich, Switzerland)

  • Thibaut Dubernet

    (Institute for Transport Planning and Systems, ETH Zurich, 8093 Zurich, Switzerland)

Abstract

Human mobility is a key element in the understanding of epidemic spreading. Thus, correctly modeling and quantifying human mobility is critical for studying large-scale spatial transmission of infectious diseases and improving epidemic control. In this study, a large-scale agent-based transport simulation (MATSim) is linked with a generic epidemic spread model to simulate the spread of communicable diseases in an urban environment. The use of an agent-based model allows reproduction of the real-world behavior of individuals’ daily path in an urban setting and allows the capture of interactions among them, in the form of a spatial-temporal social network. This model is used to study seasonal influenza outbreaks in the metropolitan area of Zurich, Switzerland. The observations of the agent-based models are compared with results from classical SIR models. The model presented is a prototype that can be used to analyze multiple scenarios in the case of a disease spread at an urban scale, considering variations of different model parameters settings. The results of this simulation can help to improve comprehension of the disease spread dynamics and to take better steps towards the prevention and control of an epidemic.

Suggested Citation

  • Jürgen Hackl & Thibaut Dubernet, 2019. "Epidemic Spreading in Urban Areas Using Agent-Based Transportation Models," Future Internet, MDPI, vol. 11(4), pages 1-14, April.
    • Handle: RePEc:gam:jftint:v:11:y:2019:i:4:p:92-:d:220787
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/11/4/92/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/11/4/92/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Stephen Eubank & Hasan Guclu & V. S. Anil Kumar & Madhav V. Marathe & Aravind Srinivasan & Zoltán Toroczkai & Nan Wang, 2004. "Modelling disease outbreaks in realistic urban social networks," Nature, Nature, vol. 429(6988), pages 180-184, May.
    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. Seyyed-Mahdi Hosseini-Motlagh & Mohammad Reza Ghatreh Samani & Behnam Karimi, 2023. "Resilient and social health service network design to reduce the effect of COVID-19 outbreak," Annals of Operations Research, Springer, vol. 328(1), pages 903-975, September.
    2. Moritz Kersting & Andreas Bossert & Leif Sörensen & Benjamin Wacker & Jan Chr. Schlüter, 2021. "Predicting effectiveness of countermeasures during the COVID-19 outbreak in South Africa using agent-based simulation," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
    3. Fatima-Zohra Younsi & Djamila Hamdadou, 2021. "Dynamic Contact Network Simulation Model Based on Multi-Agent Systems," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 16(4), pages 1-21, October.
    4. Abderrahim Zannou & Abdelhak Boulaalam & El Habib Nfaoui, 2020. "SIoT: A New Strategy to Improve the Network Lifetime with an Efficient Search Process," Future Internet, MDPI, vol. 13(1), pages 1-23, December.
    5. Patrick Urrutia & David Wren & Chrysafis Vogiatzis & Ruriko Yoshida, 2022. "SARS-CoV-2 Dissemination Using a Network of the US Counties," SN Operations Research Forum, Springer, vol. 3(2), pages 1-23, June.
    6. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2023. "Design of control strategies to help prevent the spread of COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 219-238.

    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. 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.
    2. Michał Wielechowski & Katarzyna Czech & Łukasz Grzęda, 2020. "Decline in Mobility: Public Transport in Poland in the time of the COVID-19 Pandemic," Economies, MDPI, vol. 8(4), pages 1-24, September.
    3. Burris, Courtney & Nikolaev, Alexander & Zhong, Shiran & Bian, Ling, 2021. "Network effects in influenza spread: The impact of mobility and socio-economic factors," Socio-Economic Planning Sciences, Elsevier, vol. 78(C).
    4. Floriana Gargiulo & Sônia Ternes & Sylvie Huet & Guillaume Deffuant, 2010. "An Iterative Approach for Generating Statistically Realistic Populations of Households," PLOS ONE, Public Library of Science, vol. 5(1), pages 1-9, January.
    5. Saturnino Luz & Masood Masoodian, 2022. "Exploring Environmental and Geographical Factors Influencing the Spread of Infectious Diseases with Interactive Maps," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    6. Mark S. Handcock & Adrian E. Raftery & Jeremy M. Tantrum, 2007. "Model‐based clustering for social networks," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 170(2), pages 301-354, March.
    7. Pablo D. Fajgelbaum & Amit Khandelwal & Wookun Kim & Cristiano Mantovani & Edouard Schaal, 2021. "Optimal Lockdown in a Commuting Network," American Economic Review: Insights, American Economic Association, vol. 3(4), pages 503-522, December.
    8. Bisin, Alberto & Moro, Andrea, 2022. "Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique," Journal of Economic Behavior & Organization, Elsevier, vol. 198(C), pages 370-388.
    9. Hakan Yilmazkuday, 2021. "Welfare costs of COVID‐19: Evidence from US counties," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 826-848, September.
    10. Wang, Weihong & Chen, MingMing & Min, Yong & Jin, Xiaogang, 2016. "Structural diversity effects of multilayer networks on the threshold of interacting epidemics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 254-262.
    11. Wiriya Mahikul & Somkid Kripattanapong & Piya Hanvoravongchai & Aronrag Meeyai & Sopon Iamsirithaworn & Prasert Auewarakul & Wirichada Pan-ngum, 2020. "Contact Mixing Patterns and Population Movement among Migrant Workers in an Urban Setting in Thailand," IJERPH, MDPI, vol. 17(7), pages 1-11, March.
    12. Stefano Guarino & Enrico Mastrostefano & Massimo Bernaschi & Alessandro Celestini & Marco Cianfriglia & Davide Torre & Lena Rebecca Zastrow, 2021. "Inferring Urban Social Networks from Publicly Available Data," Future Internet, MDPI, vol. 13(5), pages 1-45, April.
    13. Hartwell, Christopher A., 2021. "What Drove the First Response to the COVID-19 Pandemic? The Role of Institutions and Leader Attributes," MPRA Paper 110563, University Library of Munich, Germany.
    14. Eugenio Valdano & Chiara Poletto & Armando Giovannini & Diana Palma & Lara Savini & Vittoria Colizza, 2015. "Predicting Epidemic Risk from Past Temporal Contact Data," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-19, March.
    15. Alberto Bisin & Andrea Moro, 2020. "Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses," NBER Working Papers 27590, National Bureau of Economic Research, Inc.
    16. Richard C. Larson, 2007. "Simple Models of Influenza Progression Within a Heterogeneous Population," Operations Research, INFORMS, vol. 55(3), pages 399-412, June.
    17. Askitas, Nikos & Tatsiramos, Konstantinos & Verheyden, Bertrand, 2020. "Lockdown Strategies, Mobility Patterns and COVID-19," IZA Discussion Papers 13293, Institute of Labor Economics (IZA).
    18. 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.
    19. Wang, Wenjun & Pan, Lin & Yuan, Ning & Zhang, Sen & Liu, Dong, 2015. "A comparative analysis of intra-city human mobility by taxi," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 134-147.
    20. Sheng Wei & Lei Wang, 2020. "Examining the population flow network in China and its implications for epidemic control based on Baidu migration data," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-10, December.

    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:jftint:v:11:y:2019:i:4:p:92-:d:220787. 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.