IDEAS home Printed from https://ideas.repec.org/a/plo/pgph00/0002253.html
   My bibliography  Save this article

The potential of resilience indicators to anticipate infectious disease outbreaks, a systematic review and guide

Author

Listed:
  • Clara Delecroix
  • Egbert H van Nes
  • Ingrid A van de Leemput
  • Ronny Rotbarth
  • Marten Scheffer
  • Quirine ten Bosch

Abstract

To reduce the consequences of infectious disease outbreaks, the timely implementation of public health measures is crucial. Currently used early-warning systems are highly context-dependent and require a long phase of model building. A proposed solution to anticipate the onset or termination of an outbreak is the use of so-called resilience indicators. These indicators are based on the generic theory of critical slowing down and require only incidence time series. Here we assess the potential for this approach to contribute to outbreak anticipation. We systematically reviewed studies that used resilience indicators to predict outbreaks or terminations of epidemics. We identified 37 studies meeting the inclusion criteria: 21 using simulated data and 16 real-world data. 36 out of 37 studies detected significant signs of critical slowing down before a critical transition (i.e., the onset or end of an outbreak), with a highly variable sensitivity (i.e., the proportion of true positive outbreak warnings) ranging from 0.03 to 1 and a lead time ranging from 10 days to 68 months. Challenges include low resolution and limited length of time series, a too rapid increase in cases, and strong seasonal patterns which may hamper the sensitivity of resilience indicators. Alternative types of data, such as Google searches or social media data, have the potential to improve predictions in some cases. Resilience indicators may be useful when the risk of disease outbreaks is changing gradually. This may happen, for instance, when pathogens become increasingly adapted to an environment or evolve gradually to escape immunity. High-resolution monitoring is needed to reach sufficient sensitivity. If those conditions are met, resilience indicators could help improve the current practice of prediction, facilitating timely outbreak response. We provide a step-by-step guide on the use of resilience indicators in infectious disease epidemiology, and guidance on the relevant situations to use this approach.

Suggested Citation

  • Clara Delecroix & Egbert H van Nes & Ingrid A van de Leemput & Ronny Rotbarth & Marten Scheffer & Quirine ten Bosch, 2023. "The potential of resilience indicators to anticipate infectious disease outbreaks, a systematic review and guide," PLOS Global Public Health, Public Library of Science, vol. 3(10), pages 1-21, October.
    • Handle: RePEc:plo:pgph00:0002253
    DOI: 10.1371/journal.pgph.0002253
    as

    Download full text from publisher

    File URL: https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0002253
    Download Restriction: no
    File URL: https://journals.plos.org/globalpublichealth/article/file?id=10.1371/journal.pgph.0002253&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pgph.0002253?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. Cees Diks & Cars Hommes & Juanxi Wang, 2019. "Critical slowing down as an early warning signal for financial crises?," Empirical Economics, Springer, vol. 57(4), pages 1201-1228, October.
    Full references (including those not matched with items on IDEAS)

    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. Isaak Mengesha & Debraj Roy, 2025. "Carbon pricing drives critical transition to green growth," Nature Communications, Nature, vol. 16(1), pages 1-19, December.
    2. Hayette Gatfaoui & Isabelle Nagot & Philippe de Peretti, 2016. "Are critical slowing down indicators useful to detect financial crises?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01339815, HAL.
    3. Iwanicz-Drozdowska Małgorzata & Kurowski Łukasz, 2021. "Keep your friends close and your enemies closer – the case of monetary policy and financial imbalances," German Economic Review, De Gruyter, vol. 22(4), pages 383-414, November.
    4. Maria Alina Carataș & Elena Cerasela Spătariu & Raluca Andreea Trandafir, 2019. "Triggers of the Economic Crisis," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 237-241, December.
    5. Haoyu Wen & Massimo Pica Ciamarra & Siew Ann Cheong, 2018. "How one might miss early warning signals of critical transitions in time series data: A systematic study of two major currency pairs," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-22, March.
    6. repec:plo:pone00:0232888 is not listed on IDEAS
    7. Chen, Zheng & Fan, Peiyi & Hou, Xintong & Feng, Guolin & Qian, Zhonghua, 2024. "Effective detection of early warning signal with power spectrum in climate change system," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    8. Javier García-Algarra & Gonzalo Gómez-Bengoechea & Mary Luz Mouronte-López, 2025. "Convergence Speed and Growth Patterns: A Dynamical Systems Approach," Computational Economics, Springer;Society for Computational Economics, vol. 65(2), pages 615-636, February.
    9. Qingyuan Han, 2025. "Understanding price momentum, market fluctuations, and crashes: insights from the extended Samuelson model," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-37, December.
    10. Manfred Füllsack & Simon Plakolb & Georg Jäger, 2021. "Predicting regime shifts in social systems modelled with agent-based methods," Journal of Computational Social Science, Springer, vol. 4(1), pages 163-185, May.
    11. Jan Willem van den End, 2019. "Applying Complexity Theory to Interest Rates: Evidence of Critical Transitions in the Euro Area," Credit and Capital Markets, Credit and Capital Markets, vol. 52(1), pages 1-33.
    12. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
    13. Safarzyńska, Karolina & van den Bergh, Jeroen C.J.M., 2017. "Integrated crisis-energy policy: Macro-evolutionary modelling of technology, finance and energy interactions," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 119-137.
    14. Ismail, Mohd Sabri & Noorani, Mohd Salmi Md & Ismail, Munira & Razak, Fatimah Abdul & Alias, Mohd Almie, 2022. "Early warning signals of financial crises using persistent homology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).

    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:pgph00:0002253. 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: globalpubhealth (email available below). General contact details of provider: https://journals.plos.org/globalpublichealth .

    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.