IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03407115.html
   My bibliography  Save this paper

Monitoring COVID-19 contagion growth

Author

Listed:
  • A. Agosto
  • Alexandra Campmas

    (Larefi - Laboratoire d'analyse et de recherche en économie et finance internationales - UB - Université de Bordeaux)

  • P. Giudici
  • A. Renda

Abstract

We present a statistical model that can be employed to monitor the time evolution of the COVID-19 contagion curve and the associated reproduction rate. The model is a Poisson autoregression of the daily new observed cases and dynamically adapt its estimates to explain the evolution of contagion in terms of a short-term and long-term dependence of case counts, allowing for a comparative evaluation of health policy measures. We have applied the model to 2020 data from the countries most hit by the virus. Our empirical findings show that the proposed model describes the evolution of contagion dynamics and determines whether contagion growth can be affected by health policies. Based on our findings, we can draw two health policy conclusions that can be useful for all countries in the world. First, policy measures aimed at reducing contagion are very useful when contagion is at its peak to reduce the reproduction rate. Second, the contagion curve should be accurately monitored over time to apply policy measures that are cost-effective. © 2021 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Suggested Citation

  • A. Agosto & Alexandra Campmas & P. Giudici & A. Renda, 2021. "Monitoring COVID-19 contagion growth," Post-Print hal-03407115, HAL.
    • Handle: RePEc:hal:journl:hal-03407115
    DOI: 10.1002/sim.9020
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Marco Bonetti & Ugofilippo Basellini, 2021. "Epilocal: A real-time tool for local epidemic monitoring," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(12), pages 307-332.
    2. Ugofilippo Basellini & Carlo Giovanni Camarda, 2020. "Modelling COVID-19 mortality at the regional level in Italy," Working Papers axq0sudakgkzhr-blecv, French Institute for Demographic Studies.
    3. Ray, Evan L. & Brooks, Logan C. & Bien, Jacob & Biggerstaff, Matthew & Bosse, Nikos I. & Bracher, Johannes & Cramer, Estee Y. & Funk, Sebastian & Gerding, Aaron & Johansson, Michael A. & Rumack, Aaron, 2023. "Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1366-1383.

    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:hal:journl:hal-03407115. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.