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Financial-Times
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Excess mortality data compiled by the FT Visual & Data Journalism team

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Financial Times

Excess mortality during the Covid-19 pandemic

This repository contains excess mortality data for the period covering the 2020-21 Covid-19 pandemic. The data has been gathered from national, regional or municipal agencies that collect death registrations and publish official mortality statistics. These original data were reshaped into a standardised format by Financial Times journalists to allow cross-national comparisons, and have been used to inform the FT’s reporting on the pandemic.

The repository contains the excess mortality data for all known jurisdictions which publish all-cause mortality data meeting the following criteria:

  • daily, weekly or monthly level of granularity
  • includes equivalent historical data for at least one full year before 2020, and preferably at least five years (2015-2019)
  • includes data up to at least April 1, 2020

Most countries publish mortality data with a longer periodicity (typically quarterly or even annually), a longer publication lag time, or both. This sort of data is not suitable for ongoing analysis during an epidemic and is therefore not included here.

Data

All of the data can be found in the file data/ftexcessdeaths.csv.

Data definitions

For each jurisdiction and each weekly or monthly period, the data contains the following fields:

  • country
    : the country to which the data applies
  • region
    : where applicable, the subnational or administrative region. This duplicated
    country
    for national-level data
  • period
    : the period for which the data is collected. This can be “week” or “month”; data reported daily has been aggregated into weeks
  • year
    : the year within which the period ends. The is the same as the year element of the
    date
    field.
  • month
    : the month within which the period ends. This is the same as the month element of the
    date
    field.
  • week
    : week number is either taken exactly from countries’ own data, or is calculated using the following method: for countries reporting daily data, we take the most recent run of seven days in the data to be the most recent week, and then aggregate each prior seven-day run into a new week, with any trailing period fewer than seven days at start of January clipped off
  • date
    : the date at which the week ends
  • deaths
    : historical daily, weekly or monthly numbers of all-cause deaths for as far back as we have been able to obtain this data
  • expected_deaths
    : the expected number of deaths for the same place and period, adjusted for recent trends in mortality and population growth
  • excess_deaths
    : difference between
    deaths
    and
    expected deaths
    (negative values indicate fewer deaths than expected)
  • excess_deaths_pct
    :
    excess_deaths
    as a percentage of
    expected_deaths

Stories

"Excess mortality" refers to the difference between deaths from all causes during the pandemic and the historic seasonal average. For many of the jurisdictions shown here, this figure is higher than the official Covid-19 fatalities that are published by national governments each day. While not all of these deaths are necessarily attributable to the disease, it does leave a number of unexplained deaths that suggests that the official figures of deaths attributed may significant undercounts of the pandemic's impact.

The data published here were used to inform the following Financial Times stories and graphics:

This data has also been used in the reporting news stories from other publications:

This data has been used in the the following academic publications:

Sources

The data published here has been gathered and standardised from official sources, either directly by the Financial Times data team, or by the independent researchers Ariel Karlinsky and Dmitry Kobak, who maintain the World Mortality Dataset. Full details can be found here.

License and attribution

This software is published by the Financial Times under the MIT license.

The collected data in the

data
directory of this repository is available under the Creative Commons Attribution 4.0 International License.

If you use this data, you must attribute it to "Financial Times" as well as the relevant originating agency or agencies listed above. If it is published online, we would appreciate a link to our Coronavirus tracker page, where this material first appeared.

Please let us know if you are using this data by contacting us at [email protected]. We may be interested in reporting on your work.

Please note that MIT licence includes only the software, and the Creative Commons licence includes only the data included in this repository. Neither cover any FT content created and made available using the software or data, which is copyright © The Financial Times Limited, all rights reserved. For more information about re-publishing FT content, please contact our syndication department.

Contributors

Work on this project is led by John Burn-Murdoch of the FT Visual & Data Journalism team.

Additional contributors include Chris Giles, Valentina Romei, Henry Foy David Pilling, Laura Pitel, Martin Stabe and Aleksandra Wisniewska.

To contact the team, please email [email protected].

Related projects

Similar work is being done by The Economist, the New York Times, Our World in Data, Newsworthy and the team behind the World Mortality Dataset.

How you can help

If you are aware of a jurisdiction not already listed here which publishes all-cause mortality data that meets the criteria set out above, please send us a link to the source of that data at [email protected].

Alternatively, please submit a pull request to this repository adding the relevant information to the file sources.md.

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