jschoeley / lifetablesglobal

Global deaths, population, lifetables and excess mortality based on WPP data

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Global life expectancy deficits 20/21 based on WPP data

Jonas Schöley

Calculate global life expectancy deficits 2020/21 based on World Population Prospects 2022 data on deaths and population. These are estimates based on incomplete and uncertain data and may only act as a rough sanity check for other modeling tasks.

Data desciption

Input data

Output data

  • out/41-lifetablesglobal.rds

    • id: Row ID
    • region: Two letter ISO 3166-1 alpha-2 country code
    • sex: Male/Female
    • year: Gregorian year
    • age_start: Start of age group in years
    • age_width: Width of age group in years
    • death_actual_wpp: Actual number of deaths from WPP (may be observed or estimated)
    • exposure_actual_wpp: Actual population exposure from WPP (mid year estimates)
    • c19cases_coverage: Covid-19 cases via COVerAGE-DB
    • c19deaths_coverage: Covid-19 deaths via COVerAGE-DB
    • mx_actual_wpp: Life table death rate estimates calculated from WPP data
    • mx_expected_wpp_mean: Expected life table death rate estimates calculated from WPP data (mean prediction)
    • mx_expected_wpp_q05: Expected life table death rate estimates calculated from WPP data (5% prediction interval)
    • mx_expected_wpp_q95: Expected life table death rate estimates calculated from WPP data (95% prediction interval)
    • ex_actual_wpp: Life expectancy estimates calculated from WPP data
    • ex_expected_wpp_mean: Expected life table death rate estimates calculated from WPP data (mean prediction)
    • ex_expected_wpp_q05: Expected life table death rate estimates calculated from WPP data (5% prediction interval)
    • ex_expected_wpp_q95: Expected life table death rate estimates calculated from WPP data (95% prediction interval)

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Global deaths, population, lifetables and excess mortality based on WPP data


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