IHME

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Revision as of 19:08, 28 February 2024 by Kexin.Shang (talk | contribs) (February 2024 Update)
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The Institute for Health Metrics and Evaluation (IHME) provides data on the Global Burdens of Disease that can be accessed here http://ghdx.healthdata.org/gbd-results-tool. IHME provides data on multiple metrics that we pull into IFs, including deaths, DALYs, incidence, prevelance, violence and forecasts for each. The latest IFs data update for this series was in August 2019, covering 189 economies over the years 1990-2017. This data pull is done using Python.

IFs Series

There are currently 146 series that are pulled from the IHME into IFs. 

Instructions on Pulling IHME Series

  1. The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. Select "Only countries and territories", "All years", "Cause", "All Ages", "Number", the correct measure (i.e. "Deaths"), "Male" "Female" and "Both", and select all causes. This process might differ depending on the series being pulled in, so just be aware of that.
  2. Once data is downloaded, a Python script is used to concord and clean the data so it can be pulled into IFs. To do this, you need to have the folder "PythonOutput&Scripts" and "Pythonfiles" in the file path C/Users/Public. WIthin the Pythonfiles folder, you will put the data downloaded from the IHME website in the IHMEDownloads folder, in the respective folder. For example, for Deaths by disease series, you will put the downloaded data in the HistDeathFileData folder.
  3. Once the data is in the folder, you can run the corresponding Python script. The Python script will pull in the data from the corresponding Excel files, clean it, correspond it to the right IFs series, and concord the countries to the correct country concordance. All you need to do is run the Python script for the series you are trying to pull. For example, for the deaths by diesease series, you will run the DataforIFs-IHME-HistoricalDeathFile.py script.
  4. Once the script is done running, the completed Excel file will be located in the PythonOutput&Scripts folder.
  5. Pull in the data into IFs using the IFs data import tool.

Things to Be Aware of While Pulling

For the historical deaths by disease series, the data are in millions in IFs. So you will need to do this conversion before you import.

HealthDetailedDeathsCtry

August 2019 Update

For the 2019 update, we have added historical deaths by disease by sex data for the years 1990-2017. These are new series, as we only had totals and not aggregated by sex.

February 2024 Update

Original Source: VizHub - GBD Results (healthdata.org)

GBD Estimate: Cause of death or injury

Measure: Deaths

Metric: Rate

Cause: Select all level 2 causes (note: “Sense organ disease” is not available for Deaths Rate)

CauseID Cause cause_name category
1 Other CD Other infectious diseases Communicable, maternal, neonatal, and nutritional diseases
1 Other CD Maternal and neonatal disorders Communicable, maternal, neonatal, and nutritional diseases
1 Other CD Nutritional deficiencies Communicable, maternal, neonatal, and nutritional diseases
2 Malignant Neoplasms Neoplasms Communicable, maternal, neonatal, and nutritional diseases
3 Cardiac Cardiovascular diseases Communicable, maternal, neonatal, and nutritional diseases
4 Digestive Digestive diseases Communicable, maternal, neonatal, and nutritional diseases
5 Respiratory Chronic respiratory diseases Communicable, maternal, neonatal, and nutritional diseases
6 Other NCD Neurological disorders Non-communicable
6 Other NCD Substance use disorders Non-communicable
6 Other NCD Skin and subcutaneous diseases Non-communicable
6 Other NCD Sense organ diseases Non-communicable
6 Other NCD Musculoskeletal disorders Non-communicable
6 Other NCD Other non-communicable diseases Non-communicable
7 Road Injuries Transport injuries Non-communicable
8 Other Unintentional Injuries Unintentional injuries Non-communicable
9 Intentional Injuries Self-harm and interpersonal violence Non-communicable
10 Diabetes Diabetes and kidney diseases Non-communicable
11 HIV HIV/AIDS and sexually transmitted infections Non-communicable
12 Diarrhea Enteric infections Non-communicable
13 Malaria Neglected tropical diseases and malaria Injuries
14 Respiratory Infection Respiratory infections and tuberculosis Injuries
15 Mental Health Mental disorders Injuries

Location: Select all countries and territories

Age: Select the values in Age_Name

IHME_Age_ID Age_Name Age_IFs
5 1 to 4 p2
6 5 to 9 p3
7 10 to 14 p4
8 15 to 19 p5
9 20 to 24 p6
10 25 to 29 p7
11 30 to 34 p8
12 35 to 39 p9
13 40 to 44 p10
14 45 to 49 p11
15 50 to 54 p12
16 55 to 59 p13
17 60 to 64 p14
18 65 to 69 p15
19 70 to 74 p16
20 75 to 79 p17
28 <1 year p1
30 80 to 84 p18
31 85 to 89 p19
32 90 to 94 p20
235 95 + p21

Sex: Male(1), Female(2)

Year: 2019 (Use the most recent available year.)

The Source Unit is Deaths per 100,000. (IHME_GBD_2019_A3_MEASURE_METRIC_DEFINITIONS_Y2020M10D15.XLSX (live.com) from Global Burden of Disease (GBD) data and tools guide | Institute for Health Metrics and Evaluation (healthdata.org))

Need to use Formula /100 to transform the Unit to Deaths per 1,000.