IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v150y2021ics0960077921005105.html
   My bibliography  Save this article

On the heterogeneous spread of COVID-19 in Chile

Author

Listed:
  • Freire-Flores, Danton
  • Llanovarced-Kawles, Nyna
  • Sanchez-Daza, Anamaria
  • Olivera-Nappa, Álvaro

Abstract

Non-pharmaceutical interventions (NPIs) have played a crucial role in controlling the spread of COVID-19. Nevertheless, NPI efficacy varies enormously between and within countries, mainly because of population and behavioral heterogeneity. In this work, we adapted a multi-group SEIRA model to study the spreading dynamics of COVID-19 in Chile, representing geographically separated regions of the country by different groups. We use national mobilization statistics to estimate the connectivity between regions and data from governmental repositories to obtain COVID-19 spreading and death rates in each region. We then assessed the effectiveness of different NPIs by studying the temporal evolution of the reproduction number Rt. Analysing data-driven and model-based estimates of Rt, we found a strong coupling of different regions, highlighting the necessity of organized and coordinated actions to control the spread of SARS-CoV-2. Finally, we evaluated different scenarios to forecast the evolution of COVID-19 in the most densely populated regions, finding that the early lifting of restriction probably will lead to novel outbreaks.

Suggested Citation

  • Freire-Flores, Danton & Llanovarced-Kawles, Nyna & Sanchez-Daza, Anamaria & Olivera-Nappa, Álvaro, 2021. "On the heterogeneous spread of COVID-19 in Chile," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:chsofr:v:150:y:2021:i:c:s0960077921005105
    DOI: 10.1016/j.chaos.2021.111156
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921005105
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2021.111156?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "A SIR model assumption for the spread of COVID-19 in different communities," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    2. Chimmula, Vinay Kumar Reddy & Zhang, Lei, 2020. "Time series forecasting of COVID-19 transmission in Canada using LSTM networks," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    3. Contreras, Sebastián & Biron-Lattes, Juan Pablo & Villavicencio, H. Andrés & Medina-Ortiz, David & Llanovarced-Kawles, Nyna & Olivera-Nappa, Álvaro, 2020. "Statistically-based methodology for revealing real contagion trends and correcting delay-induced errors in the assessment of COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    4. Postnikov, Eugene B., 2020. "Estimation of COVID-19 dynamics “on a back-of-envelope”: Does the simplest SIR model provide quantitative parameters and predictions?," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    5. Contreras, Sebastián & Villavicencio, H. Andrés & Medina-Ortiz, David & Biron-Lattes, Juan Pablo & Olivera-Nappa, Álvaro, 2020. "A multi-group SEIRA model for the spread of COVID-19 among heterogeneous populations," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    6. Sebastian Contreras & Jonas Dehning & Matthias Loidolt & Johannes Zierenberg & F. Paul Spitzner & Jorge H. Urrea-Quintero & Sebastian B. Mohr & Michael Wilczek & Michael Wibral & Viola Priesemann, 2021. "The challenges of containing SARS-CoV-2 via test-trace-and-isolate," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    7. Lalwani, Soniya & Sahni, Gunjan & Mewara, Bhawna & Kumar, Rajesh, 2020. "Predicting optimal lockdown period with parametric approach using three-phase maturation SIRD model for COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    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. Contreras, Sebastian & Oróstica, Karen Y. & Daza-Sanchez, Anamaria & Wagner, Joel & Dönges, Philipp & Medina-Ortiz, David & Jara, Matias & Verdugo, Ricardo & Conca, Carlos & Priesemann, Viola & Oliver, 2023. "Model-based assessment of sampling protocols for infectious disease genomic surveillance," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Li, Tingting & Guo, Youming, 2022. "Modeling and optimal control of mutated COVID-19 (Delta strain) with imperfect vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).

    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. Contreras, Sebastian & Oróstica, Karen Y. & Daza-Sanchez, Anamaria & Wagner, Joel & Dönges, Philipp & Medina-Ortiz, David & Jara, Matias & Verdugo, Ricardo & Conca, Carlos & Priesemann, Viola & Oliver, 2023. "Model-based assessment of sampling protocols for infectious disease genomic surveillance," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Jose M. Martin-Moreno & Antoni Alegre-Martinez & Victor Martin-Gorgojo & Jose Luis Alfonso-Sanchez & Ferran Torres & Vicente Pallares-Carratala, 2022. "Predictive Models for Forecasting Public Health Scenarios: Practical Experiences Applied during the First Wave of the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(9), pages 1-16, May.
    4. Matouk, A.E., 2020. "Complex dynamics in susceptible-infected models for COVID-19 with multi-drug resistance," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    5. Ahed Abugabah & Farah Shahid, 2023. "Intelligent Health Care and Diseases Management System: Multi-Day-Ahead Predictions of COVID-19," Mathematics, MDPI, vol. 11(4), pages 1-19, February.
    6. Wang, Peipei & Zheng, Xinqi & Ai, Gang & Liu, Dongya & Zhu, Bangren, 2020. "Time series prediction for the epidemic trends of COVID-19 using the improved LSTM deep learning method: Case studies in Russia, Peru and Iran," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    7. Yulan Li & Kun Ma, 2022. "A Hybrid Model Based on Improved Transformer and Graph Convolutional Network for COVID-19 Forecasting," IJERPH, MDPI, vol. 19(19), pages 1-17, September.
    8. Mohamed M. Mousa & Fahad Alsharari, 2021. "A Comparative Numerical Study and Stability Analysis for a Fractional-Order SIR Model of Childhood Diseases," Mathematics, MDPI, vol. 9(22), pages 1-12, November.
    9. Zhao, Xinxing & Li, Kainan & Ang, Candice Ke En & Cheong, Kang Hao, 2023. "A deep learning based hybrid architecture for weekly dengue incidences forecasting," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    10. Yunhan Huang & Quanyan Zhu, 2022. "Game-Theoretic Frameworks for Epidemic Spreading and Human Decision-Making: A Review," Dynamic Games and Applications, Springer, vol. 12(1), pages 7-48, March.
    11. Li, Tangjuan & Xiao, Yanni, 2023. "Optimal strategies for coordinating infection control and socio-economic activities," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 533-555.
    12. Talal Daghriri & Michael Proctor & Sarah Matthews, 2022. "Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    13. Lorenzo Menculini & Andrea Marini & Massimiliano Proietti & Alberto Garinei & Alessio Bozza & Cecilia Moretti & Marcello Marconi, 2021. "Comparing Prophet and Deep Learning to ARIMA in Forecasting Wholesale Food Prices," Forecasting, MDPI, vol. 3(3), pages 1-19, September.
    14. Zahra Dehghan Shabani & Rouhollah Shahnazi, 2020. "Spatial distribution dynamics and prediction of COVID‐19 in Asian countries: spatial Markov chain approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 12(6), pages 1005-1025, December.
    15. Asamoah, Joshua Kiddy K. & Owusu, Mark A. & Jin, Zhen & Oduro, F. T. & Abidemi, Afeez & Gyasi, Esther Opoku, 2020. "Global stability and cost-effectiveness analysis of COVID-19 considering the impact of the environment: using data from Ghana," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    16. Alaa El-Sakran & Reem Salman & Ayman Alzaatreh, 2022. "Impacts of Emergency Remote Teaching on College Students Amid COVID-19 in the UAE," IJERPH, MDPI, vol. 19(5), pages 1-21, March.
    17. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "A SIR model assumption for the spread of COVID-19 in different communities," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    18. Crokidakis, Nuno, 2020. "COVID-19 spreading in Rio de Janeiro, Brazil: Do the policies of social isolation really work?," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    19. Lin William Cong & Ke Tang & Bing Wang & Jingyuan Wang, 2021. "An AI-assisted Economic Model of Endogenous Mobility and Infectious Diseases: The Case of COVID-19 in the United States," Papers 2109.10009, arXiv.org.
    20. Bowen Long & Fangya Tan & Mark Newman, 2023. "Forecasting the Monkeypox Outbreak Using ARIMA, Prophet, NeuralProphet, and LSTM Models in the United States," Forecasting, MDPI, vol. 5(1), pages 1-11, January.

    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:eee:chsofr:v:150:y:2021:i:c:s0960077921005105. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.