IDEAS home Printed from https://ideas.repec.org/a/spr/compst/v40y2025i6d10.1007_s00180-025-01640-3.html
   My bibliography  Save this article

Analysis of excess deaths from COVID-19 in El Salvador through time series

Author

Listed:
  • W. O. Campos

    (Universidad de El Salvador)

Abstract

The databases of deaths in El Salvador are analyzed for the years from 2015 to 2020. From these databases, the monthly time series of the number of deaths per month is constructed for the aforementioned years, treating the following five cases: Death from kidney disease, death from some type of failure (heart attack, respiratory failure, cardiorespiratory failure), death from cancer, death from causes other than firearms or traffic accidents (causes that are considered to have suffered intervention in 2020 due to the mandatory quarantine that was imposed), finally a model that includes all causes of death is considered. Time series models are adjusted, in each case, to predict the months of the year 2020. These forecasts are compared with real cases and the underreporting of deaths from COVID-19 is measured according to official data. In each case, two models are adjusted: Box–Jenkins Method (Seasonal Autoregressive Integrated Moving Average, SARIMA) and Holt-Winters Additive Method (it is optimized with a developed heuristic). This work shows that there are many people who really died from COVID-19, but the official record lists them in other cases. In such a way that there is high statistical evidence of under-registration from official data provided by the government on deaths from COVID-19, in the period covered by this study.

Suggested Citation

  • W. O. Campos, 2025. "Analysis of excess deaths from COVID-19 in El Salvador through time series," Computational Statistics, Springer, vol. 40(6), pages 3321-3357, July.
  • Handle: RePEc:spr:compst:v:40:y:2025:i:6:d:10.1007_s00180-025-01640-3
    DOI: 10.1007/s00180-025-01640-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s00180-025-01640-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s00180-025-01640-3?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.

    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:spr:compst:v:40:y:2025:i:6:d:10.1007_s00180-025-01640-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.