sources: 30200

{
    "link": "https://www.mortality.org/Data/STMF ; https://github.com/akarlinsky/world_mortality/ ; https://github.com/dkobak/excess-mortality",
    "retrievedDate": "2024-07-31",
    "additionalInfo": "All-cause mortality data is from the Human Mortality Database (HMD) Short-term Mortality Fluctuations project and the World Mortality Dataset (WMD). Both sources are updated weekly.\n\nWe do not use the data from some countries in WMD because they fail to meet the following data quality criteria: 1) at least three years of historical data; and 2) data published either weekly or monthly. The full list of excluded countries and reasons for exclusion can be found in this spreadsheet: https://docs.google.com/spreadsheets/d/1JPMtzsx-smO3_K4ReK_HMeuVLEzVZ71qHghSuAfG788/edit?usp=sharing.\n\nFor a full list of source information (i.e., HMD or WMD) country by country, see: https://ourworldindata.org/excess-mortality-covid#source-information-country-by-country.\n\nWe calculate P-scores using the reported deaths data from HMD and WMD and the projected deaths since 2020 from WMD (which we use for all countries and regions, including for deaths broken down by age group). The P-score is the percentage difference between the reported number of weekly or monthly deaths since 2020 and the projected number of deaths for the same period based on previous years (years available from 2015 until 2019).\n\nWe calculate the number of weekly deaths for the United Kingdom by summing the weekly deaths from England & Wales, Scotland, and Northern Ireland.\n\nFor important issues and caveats to understand when interpreting excess mortality data, see our excess mortality page at https://ourworldindata.org/excess-mortality-covid.\n\nFor a more detailed description of the HMD data, including week date definitions, the coverage (of individuals, locations, and time), whether dates are for death occurrence or registration, the original national source information, and important caveats, see the HMD metadata file at https://www.mortality.org/Public/STMF_DOC/STMFmetadata.pdf.\n\nFor a more detailed description of the WMD data, including original source information, see their GitHub page at https://github.com/akarlinsky/world_mortality.\nIn response to the COVID-19 pandemic, the HMD team decided to establish a new data resource: Short-term Mortality Fluctuations (STMF) data series. Objective and internationally comparable data are crucial to determine the effectiveness of different strategies used to address epidemics. Weekly death counts provide the most objective and comparable way of assessing the scale of short-term mortality elevations across countries and time. More details about this data project can be found in the recently published paper (https://www.nature.com/articles/s41597-021-01019-1).\n\nBefore using the data, please consult the STMF Methodological Note (https://www.mortality.org/File/GetDocument/Public/STMF_DOC/STMFNote.pdf), which provides a more comprehensive description of this data project, including important aspects related to data collection and data processing. We also recommend that you read the STMF Metadata (https://www.mortality.org/File/GetDocument/Public/STMF_DOC/STMFmetadata.pdf). This document includes country-specific information about data availability, completeness, data sources, as well as specific features of included data.\n\nData will be frequently updated and new countries will be added. Data are published under CC BY 4.0 license.\n\nFor citing STMF data, please follow the HMD data citation guidelines (https://www.mortality.org/Research/CitationGuidelines).\n\nHMD provides an online STMF visualization toolkit (https://mpidr.shinyapps.io/stmortality).\nWorld Mortality Dataset: international data on all-cause mortality.\n\nThis dataset contains country-level data on all-cause mortality in 2015\u20132024 collected from various sources. They are currently providing data for 122 countries and territories.\n\nFor a complete and up-to-date list of notes on the dataset, please refer to their GitHub page at https://github.com/akarlinsky/world_mortality/.\n\nFor the list of sources that they use, please go to https://github.com/akarlinsky/world_mortality/#sou rces.\n\nPublished paper available at https://elifesciences.org/articles/69336.\nThe data are sourced from the World Mortality Dataset (https://github.com/akarlinsky/world_mortality). Excess mortality is computed relative to the baseline obtained using linear extrapolation of the 2015\u201319 trend (different baselines for 2020, 2021, and 2022). In each subplot in the figure below, gray lines are 2015\u201319, black line is baseline for 2020, red line is 2020, blue line is 2021, orange line is 2022. Countries are sorted by the total excess mortality as % of the 2020 baseline.\n\nFor more details, refer to https://github.com/dkobak/excess-mortality#excess-mortality-during-the-covid-19-pandemic.",
    "dataPublishedBy": "HMD. Human Mortality Database. Max Planck Institute for Demographic Research (Germany), University of California, Berkeley (USA), and French Institute for Demographic Studies (France). Available at www.mortality.org.; Karlinsky & Kobak 2021, Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset, eLife https://doi.org/10.7554/eLife.69336; Karlinsky & Kobak, 2021, Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset. eLife 10:e69336. https://elifesciences.org/articles/69336"
}