IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/g9mxt.html
   My bibliography  Save this paper

A radically simple way to monitor life expectancy

Author

Listed:
  • Kashnitsky, Ilya

    (University of Southern Denmark)

  • Raksha, Alexei
  • Aburto, José Manuel
  • Schöley, Jonas
  • Vaupel, James W

Abstract

NOTE: this is an early registration of the research idea and findings in form of slides for a talk presented at EAPS Mort workshop on 2021-09-22 (video: https://youtu.be/rOndHnuajH4?t=2370) Period Life Expectancy is the key summary measure of current mortality. Elimination of the direct influence of population age structure allows to meaningfully compare mortality levels and changes across the populations and over time. Calculation of life expectancy demands high quality detailed data on death and population counts disaggregated by sex and age. Such data is only available for the more developed countries. Moreover, even in the most developed countries, it becomes available with a considerable time lag. And for the majority of countries across the world timely and high quality deaths statistics is not available. In situations of mortality shocks such as the COVID–19 pandemic near real time mortality level comparisons are crucial. Building on the studied regularities of human mortality, we offer a method of reliable life expectancy short-casting based only on the time series of its previous values and the time series of total deaths counts observed in the population, not disaggregated by sex and age. The radical simplicity of the method allows to monitor changes in life expectancy in near real time, if time disaggregated (daily, weekly, or monthly) total death counts are available.

Suggested Citation

  • Kashnitsky, Ilya & Raksha, Alexei & Aburto, José Manuel & Schöley, Jonas & Vaupel, James W, 2021. "A radically simple way to monitor life expectancy," OSF Preprints g9mxt, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:g9mxt
    DOI: 10.31219/osf.io/g9mxt
    as

    Download full text from publisher

    File URL: https://osf.io/download/614de8b89ef82f003dccf2c3/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/g9mxt?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
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:osfxxx:g9mxt. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.