[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/eee/intfor/v38y2022i2p423-438.html
   My bibliography  Save this article

Forecasting for COVID-19 has failed

Author

Listed:
  • Ioannidis, John P.A.
  • Cripps, Sally
  • Tanner, Martin A.
Abstract
Epidemic forecasting has a dubious track-record, and its failures became more prominent with COVID-19. Poor data input, wrong modeling assumptions, high sensitivity of estimates, lack of incorporation of epidemiological features, poor past evidence on effects of available interventions, lack of transparency, errors, lack of determinacy, consideration of only one or a few dimensions of the problem at hand, lack of expertise in crucial disciplines, groupthink and bandwagon effects, and selective reporting are some of the causes of these failures. Nevertheless, epidemic forecasting is unlikely to be abandoned. Some (but not all) of these problems can be fixed. Careful modeling of predictive distributions rather than focusing on point estimates, considering multiple dimensions of impact, and continuously reappraising models based on their validated performance may help. If extreme values are considered, extremes should be considered for the consequences of multiple dimensions of impact so as to continuously calibrate predictive insights and decision-making. When major decisions (e.g. draconian lockdowns) are based on forecasts, the harms (in terms of health, economy, and society at large) and the asymmetry of risks need to be approached in a holistic fashion, considering the totality of the evidence.

Suggested Citation

  • Ioannidis, John P.A. & Cripps, Sally & Tanner, Martin A., 2022. "Forecasting for COVID-19 has failed," International Journal of Forecasting, Elsevier, vol. 38(2), pages 423-438.
    • Handle: RePEc:eee:intfor:v:38:y:2022:i:2:p:423-438
    DOI: 10.1016/j.ijforecast.2020.08.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0169207020301199
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijforecast.2020.08.004?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. Nassim Nicholas Taleb & Yaneer Bar-Yam & Pasquale Cirillo, 2020. "On Single Point Forecasts for Fat-Tailed Variables," Papers 2007.16096, arXiv.org.
    2. Neil M. Ferguson & Christl A. Donnelly & Roy M. Anderson, 2001. "Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain," Nature, Nature, vol. 413(6855), pages 542-548, October.
    3. Seth Flaxman & Swapnil Mishra & Axel Gandy & H. Juliette T. Unwin & Thomas A. Mellan & Helen Coupland & Charles Whittaker & Harrison Zhu & Tresnia Berah & Jeffrey W. Eaton & Mélodie Monod & Azra C. Gh, 2020. "Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe," Nature, Nature, vol. 584(7820), pages 257-261, August.
    4. N. M. Ferguson & A. C. Ghani & C. A. Donnelly & T. J. Hagenaars & R. M. Anderson, 2002. "Estimating the human health risk from possible BSE infection of the British sheep flock," Nature, Nature, vol. 415(6870), pages 420-424, January.
    5. Neil M. Ferguson & Christl A. Donnelly & Roy M. Anderson, 2001. "Erratum: Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain," Nature, Nature, vol. 414(6861), pages 329-329, November.
    6. Andrea Saltelli & Gabriele Bammer & Isabelle Bruno & Erica Charters & Monica Di Fiore & Emmanuel Didier & Wendy Nelson Espeland & John Kay & Samuele Lo Piano & Deborah Mayo & Roger Pielke Jr & Tommaso, 2020. "Five ways to ensure that models serve society: a manifesto," Nature, Nature, vol. 582(7813), pages 482-484, June.
    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. Brigid Unim & Nienke Schutte & Martin Thissen & Luigi Palmieri, 2022. "Innovative Methods Used in Monitoring COVID-19 in Europe: A Multinational Study," IJERPH, MDPI, vol. 20(1), pages 1-15, December.
    2. Ivan L. Pitt, 2022. "The system-wide effects of dispatch, response and operational performance on emergency medical services during Covid-19," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    3. Taleb, Nassim Nicholas & Bar-Yam, Yaneer & Cirillo, Pasquale, 2022. "On single point forecasts for fat-tailed variables," International Journal of Forecasting, Elsevier, vol. 38(2), pages 413-422.
    4. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    5. González, Marta Ramos & Ureña, Antonio Partal & Fernández-Aguado, Pilar Gómez, 2023. "Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
    6. Deniz Dutz & Michael Greenstone & Ali Hortaçsu & Santiago Lacouture & Magne Mogstad & Azeem M. Shaikh & Alexander Torgovitsky & Winnie van Dijk, 2023. "Representation and Hesitancy in Population Health Research: Evidence from a COVID-19 Antibody Study," NBER Working Papers 30880, National Bureau of Economic Research, Inc.
    7. Jakubek, Dariusz & Ocłoń, Paweł & Nowak-Ocłoń, Marzena & Sułowicz, Maciej & Varbanov, Petar Sabev & Klemeš, Jiří Jaromír, 2023. "Mathematical modelling and model validation of the heat losses in district heating networks," Energy, Elsevier, vol. 267(C).
    8. Kathryn S Taylor & James W Taylor, 2022. "Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-25, March.
    9. Choudhury, Nishat Alam & Ramkumar, M. & Schoenherr, Tobias & Singh, Shalabh, 2023. "The role of operations and supply chain management during epidemics and pandemics: Potential and future research opportunities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(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. Ian E. Fellows & Mark S. Handcock, 2023. "Modeling of networked populations when data is sampled or missing," METRON, Springer;Sapienza Università di Roma, vol. 81(1), pages 21-35, April.
    2. Wenting Yang & Jiantong Zhang & Ruolin Ma, 2020. "The Prediction of Infectious Diseases: A Bibliometric Analysis," IJERPH, MDPI, vol. 17(17), pages 1-19, August.
    3. repec:sae:envval:v:15:y:2006:i:4:p:441-462 is not listed on IDEAS
    4. Hennessy, David A. & Rault, Arnaud, 2023. "On systematically insufficient biosecurity actions and policies to manage infectious animal disease," Ecological Economics, Elsevier, vol. 206(C).
    5. Foliano, Francesca & Tonei, Valentina & Sevilla, Almudena, 2024. "Social restrictions, leisure and well-being," Labour Economics, Elsevier, vol. 87(C).
    6. Emanuele Amodio & Michele Battisti & Antonio Francesco Gravina & Andrea Mario Lavezzi & Giuseppe Maggio, 2023. "School‐age vaccination, school openings and Covid‐19 diffusion," Health Economics, John Wiley & Sons, Ltd., vol. 32(5), pages 1084-1100, May.
    7. Wang, Peipei & Liu, Haiyan & Zheng, Xinqi & Ma, Ruifang, 2023. "A new method for spatio-temporal transmission prediction of COVID-19," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    8. Pelagatti, Matteo & Maranzano, Paolo, 2021. "Assessing the effectiveness of the Italian risk-zones policy during the second wave of COVID-19," Health Policy, Elsevier, vol. 125(9), pages 1188-1199.
    9. Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
    10. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    11. Valentina Aprigliano & Alessandro Borin & Francesco Paolo Conteduca & Simone Emiliozzi & Marco Flaccadoro & Sabina Marchetti & Stefania Villa, 2021. "Forecasting Italian GDP growth with epidemiological data," Questioni di Economia e Finanza (Occasional Papers) 664, Bank of Italy, Economic Research and International Relations Area.
    12. Fox, John A. & Hanawa Peterson, Hikaru, 2004. "Risks and implications of bovine spongiform encephalopathy for the United States: insights from other countries," Food Policy, Elsevier, vol. 29(1), pages 45-60, February.
    13. Giorgio Fabbri & Salvatore Federico & Davide Fiaschi & Fausto Gozzi, 2024. "Mobility decisions, economic dynamics and epidemic," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 77(1), pages 495-531, February.
    14. Nicholas R. Magliocca, 2020. "Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus," Land, MDPI, vol. 9(12), pages 1-25, December.
    15. Li, Xun & Lai, Weizheng & Wan, Qianqian & Chen, Xi, 2022. "Role of professionalism in response to the COVID-19 pandemic: Does a public health or medical background help?," China Economic Review, Elsevier, vol. 71(C).
    16. Wan, Jinming & Ichinose, Genki & Small, Michael & Sayama, Hiroki & Moreno, Yamir & Cheng, Changqing, 2022. "Multilayer networks with higher-order interaction reveal the impact of collective behavior on epidemic dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    17. Lin Ma & Gil Shapira & Damien de Walque & Quy‐Toan Do & Jed Friedman & Andrei A. Levchenko, 2022. "The Intergenerational Mortality Trade‐Off Of Covid‐19 Lockdown Policies," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1427-1468, August.
    18. Roy Cerqueti & Raffaella Coppier & Alessandro Girardi & Marco Ventura, 2022. "The sooner the better: lives saved by the lockdown during the COVID-19 outbreak. The case of Italy," The Econometrics Journal, Royal Economic Society, vol. 25(1), pages 46-70.
    19. Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios & Chen, Zhi & Gaba, Anil & Tsetlin, Ilia & Winkler, Robert L., 2022. "The M5 uncertainty competition: Results, findings and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1365-1385.
    20. Rob Deardon & Babak Habibzadeh & Hau Yi Chung, 2012. "Spatial measurement error in infectious disease models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(5), pages 1139-1150, November.
    21. Wen, Xin & Heinisch, Verena & Müller, Jonas & Sasse, Jan-Philipp & Trutnevyte, Evelina, 2023. "Comparison of statistical and optimization models for projecting future PV installations at a sub-national scale," Energy, Elsevier, vol. 285(C).

    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:intfor:v:38:y:2022:i:2:p:423-438. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijforecast .

    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.