.cache who daly global
Reading
This is a 196-row, 2-column slice extracted from the 'Notes' sheet of the WHO Global Health Estimates 2021 DALY workbook, not the burden-of-disease data itself. The first column (__UNNAMED__0) is almost entirely empty (null_rate 0.9694) with just 6 distinct free-text notes, while the second column holds 190 near-unique entries that look like a list of countries plus a few header lines. The structure suggests the file was parsed starting on the wrong sheet — the substantive DALY estimates live elsewhere in the workbook. Before any analysis, repoint the loader at the data sheets; this 'Notes' tab is essentially metadata and a country roster.
citing: row_count · column_count · columns[0].null_rate · columns[0].n_unique · columns[1].n_unique · columns[1].top_values · source
Charts the summary said to look at first
Show data table
| value | count | share |
|---|---|---|
| Global Health Estimates 2021 Summary Tables This workbook contains summary burden of disease estimates from the WHO Global Health Estimates (GHE). The estimates are based on analysis of latest available national information on levels of mortality and cause distributions as of the end of 2023 together with latest available information from WHO programs for causes of public health importance. Data, methods and cause categories are described in a Technical Paper (1) available on the WHO website. Population estimates are from the 2022 revision of the UN World Population Prospects (2). This spreadsheet includes estimates for disability-adjusted life year (DALY), globally, by cause, age and sex, for the years 2000, 2010, 2015, 2019, 2020 and 2021. Documentation, country-level and regional-level summary tables are available on the WHO website ( https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates ). Depending on the available data sources, the cause-specific estimates will have quite substantial uncertainty ranges. Due to changes in data and some methods, these estimates are not comparable to previously-released WHO estimates. The preparation of these statistics was undertaken by the WHO Department of Data and Analytics, in collaboration with WHO technical programs. For further queries, please send an email to healthstat@who.int . References: (1) WHO methods and data sources for global burden of disease 2000-2021. Global Health Estimates Technical Paper WHO/DDI/DNA/GHE/2020.3.Geneva: World Health Organization; 2024 (https://www.who.int/docs/default-source/gho-documents/global-health-estimates/GlobalBurden_method_2000_2021.pdf). (2) World Population Prospects: The 2024 revision. New York: United Nations, Department of Economic and Social Affairs, Population Division; 2024 (https://esa.un.org/unpd/wpp/). | 1 | 0.5% |
| Recommended citation: | 1 | 0.5% |
| Global Health Estimates 2021: Disease burden by Cause, Age, Sex, by Country and by Region, 2000-2021. Geneva, World Health Organization; 2024. | 1 | 0.5% |
| List of Countries | 1 | 0.5% |
| Note: WHO Member States with a population of less than 90,000 in 2021 were not included in the analysis. | 1 | 0.5% |
| Countries, areas or territories included | 1 | 0.5% |
Show data table
| value | count | share |
|---|---|---|
| Global Health Estimates 2021 Summary Tables This workbook contains summary burden of disease estimates from the WHO Global Health Estimates (GHE). The estimates are based on analysis of latest available national information on levels of mortality and cause distributions as of the end of 2023 together with latest available information from WHO programs for causes of public health importance. Data, methods and cause categories are described in a Technical Paper (1) available on the WHO website. Population estimates are from the 2022 revision of the UN World Population Prospects (2). This spreadsheet includes estimates for disability-adjusted life year (DALY), globally, by cause, age and sex, for the years 2000, 2010, 2015, 2019, 2020 and 2021. Documentation, country-level and regional-level summary tables are available on the WHO website ( https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates ). Depending on the available data sources, the cause-specific estimates will have quite substantial uncertainty ranges. Due to changes in data and some methods, these estimates are not comparable to previously-released WHO estimates. The preparation of these statistics was undertaken by the WHO Department of Data and Analytics, in collaboration with WHO technical programs. For further queries, please send an email to healthstat@who.int . References: (1) WHO methods and data sources for global burden of disease 2000-2021. Global Health Estimates Technical Paper WHO/DDI/DNA/GHE/2020.3.Geneva: World Health Organization; 2024 (https://www.who.int/docs/default-source/gho-documents/global-health-estimates/GlobalBurden_method_2000_2021.pdf). (2) World Population Prospects: The 2024 revision. New York: United Nations, Department of Economic and Social Affairs, Population Division; 2024 (https://esa.un.org/unpd/wpp/). | 1 | 0.5% |
| Recommended citation: | 1 | 0.5% |
| Global Health Estimates 2021: Disease burden by Cause, Age, Sex, by Country and by Region, 2000-2021. Geneva, World Health Organization; 2024. | 1 | 0.5% |
| List of Countries | 1 | 0.5% |
| Note: WHO Member States with a population of less than 90,000 in 2021 were not included in the analysis. | 1 | 0.5% |
| Countries, areas or territories included | 1 | 0.5% |
Show data table
| value | count | share |
|---|---|---|
| GLOBAL DALYs BY CAUSE, AGE AND SEX, 2000-2021 | 1 | 0.5% |
| July 2024 | 1 | 0.5% |
| World Health Organization | 1 | 0.5% |
| Geneva, Switzerland | 1 | 0.5% |
| https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates | 1 | 0.5% |
| Afghanistan | 1 | 0.5% |
| Albania | 1 | 0.5% |
| Algeria | 1 | 0.5% |
| Angola | 1 | 0.5% |
| Antigua and Barbuda | 1 | 0.5% |
| Argentina | 1 | 0.5% |
| Armenia | 1 | 0.5% |
| Australia | 1 | 0.5% |
| Austria | 1 | 0.5% |
| Azerbaijan | 1 | 0.5% |
| Bahamas | 1 | 0.5% |
| Bahrain | 1 | 0.5% |
| Bangladesh | 1 | 0.5% |
| Barbados | 1 | 0.5% |
| Belarus | 1 | 0.5% |
Show data table
| value | count | share |
|---|---|---|
| GLOBAL DALYs BY CAUSE, AGE AND SEX, 2000-2021 | 1 | 0.5% |
| July 2024 | 1 | 0.5% |
| World Health Organization | 1 | 0.5% |
| Geneva, Switzerland | 1 | 0.5% |
| https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates | 1 | 0.5% |
| Afghanistan | 1 | 0.5% |
| Albania | 1 | 0.5% |
| Algeria | 1 | 0.5% |
| Angola | 1 | 0.5% |
| Antigua and Barbuda | 1 | 0.5% |
| Argentina | 1 | 0.5% |
| Armenia | 1 | 0.5% |
| Australia | 1 | 0.5% |
| Austria | 1 | 0.5% |
| Azerbaijan | 1 | 0.5% |
| Bahamas | 1 | 0.5% |
| Bahrain | 1 | 0.5% |
| Bangladesh | 1 | 0.5% |
| Barbados | 1 | 0.5% |
| Belarus | 1 | 0.5% |
Schema
2 columns| Alerts | ||||
|---|---|---|---|---|
| __UNNAMED__0 | categorical | 96.9% | 6 |
long_tail
null_rate
|
| GLOBAL HEALTH ESTIMATES 2021 SUMMARY TABLES: | categorical | 3.1% | 190 |
long_tail
|
__UNNAMED__0
categorical metadata long_tail null_rateThis unnamed column appears to be the spillover text from a spreadsheet header/cover sheet — likely the title block, citation, and notes from a WHO Global Health Estimates 2021 workbook rather than a real data field. Of 196 rows, 96.94% are null and only 6 distinct non-null strings exist, each appearing once, including the workbook preamble, a 'Recommended citation:' label, and 'List of Countries'. The column carries documentation prose, not observations. Treatment: Drop; this is sheet-header text from an Excel import, not a data column.
- n
- 196
- nulls
- 190 (96.9%)
- unique
- 6
- top_value
- Global Health Estimates 2021 Summary Tables This workbook contains summary burden of disease estimates from the WHO Global Health Estimates (GHE). The estimates are based on analysis of latest available national information on levels of mortality and cause distributions as of the end of 2023 together with latest available information from WHO programs for causes of public health importance. Data, methods and cause categories are described in a Technical Paper (1) available on the WHO website. Population estimates are from the 2022 revision of the UN World Population Prospects (2). This spreadsheet includes estimates for disability-adjusted life year (DALY), globally, by cause, age and sex, for the years 2000, 2010, 2015, 2019, 2020 and 2021. Documentation, country-level and regional-level summary tables are available on the WHO website ( https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates ). Depending on the available data sources, the cause-specific estimates will have quite substantial uncertainty ranges. Due to changes in data and some methods, these estimates are not comparable to previously-released WHO estimates. The preparation of these statistics was undertaken by the WHO Department of Data and Analytics, in collaboration with WHO technical programs. For further queries, please send an email to healthstat@who.int . References: (1) WHO methods and data sources for global burden of disease 2000-2021. Global Health Estimates Technical Paper WHO/DDI/DNA/GHE/2020.3.Geneva: World Health Organization; 2024 (https://www.who.int/docs/default-source/gho-documents/global-health-estimates/GlobalBurden_method_2000_2021.pdf). (2) World Population Prospects: The 2024 revision. New York: United Nations, Department of Economic and Social Affairs, Population Division; 2024 (https://esa.un.org/unpd/wpp/).
- top_rate
- 0.1667
- cardinality
- 6
- entropy
- 2.585
- entropy_ratio
- 1
GLOBAL HEALTH ESTIMATES 2021 SUMMARY TABLES:
categorical metadata long_tailThis appears to be a header/title column from a WHO Global Health Estimates 2021 summary table that has been read in as data, mixing document metadata (title, date 'July 2024', publisher 'World Health Organization', URL) with country names (Afghanistan, Albania, Algeria...). With 190 unique values across 196 rows and entropy_ratio of 1.0, nearly every value is distinct and the top value occurs only once (top_rate 0.0053). The 3.06% null rate and long_tail alert are consistent with a malformed import where the real country list is buried under preamble rows. Treatment: Re-parse the source file with a correct header row and skip the preamble; then split metadata from the country identifier column.
- n
- 196
- nulls
- 6 (3.1%)
- unique
- 190
- top_value
- GLOBAL DALYs BY CAUSE, AGE AND SEX, 2000-2021
- top_rate
- 0.005263
- cardinality
- 190
- entropy
- 7.57
- entropy_ratio
- 1