IHME

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.

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.

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.