IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0235732.html
   My bibliography  Save this article

Modeling future spread of infections via mobile geolocation data and population dynamics. An application to COVID-19 in Brazil

Author

Listed:
  • Pedro S Peixoto
  • Diego Marcondes
  • Cláudia Peixoto
  • Sérgio M Oliva

Abstract

Mobile geolocation data is a valuable asset in the assessment of movement patterns of a population. Once a highly contagious disease takes place in a location the movement patterns aid in predicting the potential spatial spreading of the disease, hence mobile data becomes a crucial tool to epidemic models. In this work, based on millions of anonymized mobile visits data in Brazil, we investigate the most probable spreading patterns of the COVID-19 within states of Brazil. The study is intended to help public administrators in action plans and resources allocation, whilst studying how mobile geolocation data may be employed as a measure of population mobility during an epidemic. This study focuses on the states of São Paulo and Rio de Janeiro during the period of March 2020, when the disease first started to spread in these states. Metapopulation models for the disease spread were simulated in order to evaluate the risk of infection of each city within the states, by ranking them according to the time the disease will take to infect each city. We observed that, although the high-risk regions are those closer to the capital cities, where the outbreak has started, there are also cities in the countryside with great risk. The mathematical framework developed in this paper is quite general and may be applied to locations around the world to evaluate the risk of infection by diseases, in special the COVID-19, when geolocation data is available.

Suggested Citation

  • Pedro S Peixoto & Diego Marcondes & Cláudia Peixoto & Sérgio M Oliva, 2020. "Modeling future spread of infections via mobile geolocation data and population dynamics. An application to COVID-19 in Brazil," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-23, July.
  • Handle: RePEc:plo:pone00:0235732
    DOI: 10.1371/journal.pone.0235732
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0235732
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0235732&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0235732?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. D. Brockmann & L. Hufnagel & T. Geisel, 2006. "The scaling laws of human travel," Nature, Nature, vol. 439(7075), pages 462-465, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    RePEc Biblio mentions

    As found on the RePEc Biblio, the curated bibliography for Economics:
    1. > Economics of Welfare > Health Economics > Economics of Pandemics > Specific pandemics > Covid-19 > Modelling

    Citations

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


    Cited by:

    1. Arindam Ray & Wolfgang Jank & Kaushik Dutta & Matthew Mullarkey, 2023. "An LSTM + Model for Managing Epidemics: Using Population Mobility and Vulnerability for Forecasting COVID-19 Hospital Admissions," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 440-457, March.
    2. Kuchler, Theresa & Russel, Dominic & Stroebel, Johannes, 2022. "JUE Insight: The geographic spread of COVID-19 correlates with the structure of social networks as measured by Facebook," Journal of Urban Economics, Elsevier, vol. 127(C).
    3. M. R. Martines & R. V. Ferreira & R. H. Toppa & L. M. Assunção & M. R. Desjardins & E. M. Delmelle, 2021. "Detecting space–time clusters of COVID-19 in Brazil: mortality, inequality, socioeconomic vulnerability, and the relative risk of the disease in Brazilian municipalities," Journal of Geographical Systems, Springer, vol. 23(1), pages 7-36, January.
    4. Timo Mitze & Reinhold Kosfeld, 2022. "The propagation effect of commuting to work in the spatial transmission of COVID-19," Journal of Geographical Systems, Springer, vol. 24(1), pages 5-31, January.
    5. Hamza Zubair & Ampol Karoonsoontawong & Kunnawee Kanitpong, 2022. "Effects of COVID-19 on Travel Behavior and Mode Choice: A Case Study for the Bangkok Metropolitan Area," Sustainability, MDPI, vol. 14(15), pages 1-26, July.
    6. María Hierro & Adolfo Maza, 2023. "Spatial contagion during the first wave of the COVID‐19 pandemic: Some lessons from the case of Madrid, Spain," Regional Science Policy & Practice, Wiley Blackwell, vol. 15(3), pages 474-492, April.
    7. Francesc Aràndiga & Antonio Baeza & Isabel Cordero-Carrión & Rosa Donat & M. Carmen Martí & Pep Mulet & Dionisio F. Yáñez, 2020. "A Spatial-Temporal Model for the Evolution of the COVID-19 Pandemic in Spain Including Mobility," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    8. Izabela Sobiech Pellegrini, 2022. "Untimely Reopening? Increase in the Number of New COVID‐19 Cases After Reopening in One Brazilian State," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(4), pages 675-693, August.

    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. Ferreira, A.S. & Raposo, E.P. & Viswanathan, G.M. & da Luz, M.G.E., 2012. "The influence of the environment on Lévy random search efficiency: Fractality and memory effects," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(11), pages 3234-3246.
    2. Miguel Picornell & Tomás Ruiz & Maxime Lenormand & José Ramasco & Thibaut Dubernet & Enrique Frías-Martínez, 2015. "Exploring the potential of phone call data to characterize the relationship between social network and travel behavior," Transportation, Springer, vol. 42(4), pages 647-668, July.
    3. Moshe B Hoshen & Anthony H Burton & Themis J V Bowcock, 2007. "Simulating disease transmission dynamics at a multi-scale level," International Journal of Microsimulation, International Microsimulation Association, vol. 1(1), pages 26-34.
    4. Maxime Lenormand & Miguel Picornell & Oliva G Cantú-Ros & Antònia Tugores & Thomas Louail & Ricardo Herranz & Marc Barthelemy & Enrique Frías-Martínez & José J Ramasco, 2014. "Cross-Checking Different Sources of Mobility Information," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-10, August.
    5. Huang, Feihu & Qiao, Shaojie & Peng, Jian & Guo, Bing & Xiong, Xi & Han, Nan, 2019. "A movement model for air passengers based on trip purpose," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 798-808.
    6. Shanshan Wan & Zhuo Chen & Cheng Lyu & Ruofan Li & Yuntao Yue & Ying Liu, 2022. "Research on disaster information dissemination based on social sensor networks," International Journal of Distributed Sensor Networks, , vol. 18(3), pages 15501329221, March.
    7. Varga, Levente & Tóth, Géza & Néda, Zoltán, 2017. "An improved radiation model and its applicability for understanding commuting patterns in Hungary," MPRA Paper 76806, University Library of Munich, Germany.
    8. Magdziarz, M. & Scheffler, H.P. & Straka, P. & Zebrowski, P., 2015. "Limit theorems and governing equations for Lévy walks," Stochastic Processes and their Applications, Elsevier, vol. 125(11), pages 4021-4038.
    9. Chaogui Kang & Yu Liu & Diansheng Guo & Kun Qin, 2015. "A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint," PLOS ONE, Public Library of Science, vol. 10(11), pages 1-11, November.
    10. Medino, Ary V. & Lopes, Sílvia R.C. & Morgado, Rafael & Dorea, Chang C.Y., 2012. "Generalized Langevin equation driven by Lévy processes: A probabilistic, numerical and time series based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 572-581.
    11. Li, Ze-Tao & Nie, Wei-Peng & Cai, Shi-Min & Zhao, Zhi-Dan & Zhou, Tao, 2023. "Exploring the topological characteristics of urban trip networks based on taxi trajectory data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    12. Liu, Jian-Guo & Li, Ren-De & Guo, Qiang & Zhang, Yi-Cheng, 2018. "Collective iteration behavior for online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 490-497.
    13. Bilazeroğlu, Ş. & Göktepe, S. & Merdan, H., 2023. "Effects of the random walk and the maturation period in a diffusive predator–prey system with two discrete delays," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    14. Chen, Ning & Zhu, Xuzhen & Chen, Yanyan, 2019. "Information spreading on complex networks with general group distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 671-676.
    15. Camille Roth & Soong Moon Kang & Michael Batty & Marc Barthélemy, 2011. "Structure of Urban Movements: Polycentric Activity and Entangled Hierarchical Flows," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
    16. Cai, Hua & Zhan, Xiaowei & Zhu, Ji & Jia, Xiaoping & Chiu, Anthony S.F. & Xu, Ming, 2016. "Understanding taxi travel patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 590-597.
    17. Hu, Beibei & Xia, Xuanxuan & Sun, Huijun & Dong, Xianlei, 2019. "Understanding the imbalance of the taxi market: From the high-quality customer’s perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    18. Toru Nakamura & Toru Takumi & Atsuko Takano & Fumiyuki Hatanaka & Yoshiharu Yamamoto, 2013. "Characterization and Modeling of Intermittent Locomotor Dynamics in Clock Gene-Deficient Mice," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-8, March.
    19. Chen, Roger B., 2018. "Models of count with endogenous choices," Transportation Research Part B: Methodological, Elsevier, vol. 117(PB), pages 862-875.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0235732. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.