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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&nbsp;<font style="background-color: rgb(255, 255, 255);">[http://ghdx.healthdata.org/gbd-results-tool 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.</font>
The Institute for Health Metrics and Evaluation (IHME) provides data on the Global Burdens of Disease that can be accessed here&nbsp;<font style="background-color: rgb(255, 255, 255);">[http://ghdx.healthdata.org/gbd-results-tool http://ghdx.healthdata.org/gbd-results-tool]. IHME provides data on multiple metrics that we pull into IFs, including deaths, DALYs, incidence, prevalence, violence and forecasts for each. The latest IFs data update for this series was in March 2025, covering 188 economies over the years 198/90-2021. There have been major changes in this update which will be noted below.</font>  
= Instructions on Pulling IHME data =


= IFs Series =
=== Preprocessors on Prevalence and Incidence ===


= Instructions on Pulling IHME Series =
==== Update in March 2025 ====
The data can be accessed from the GBD tool at <font style="background-color: rgb(255, 255, 255);">http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. [https://github.com/shangkexin/The_Institute_for_Health_Metrics_and_Evaluation_IHME Python scripts] used from last data pull can be accessed and adjusted for future data pulls. An updated country concordance table can be found [https://1drv.ms/x/c/64a1920f95dbe644/EWHhcKUK3ldEoIgMqLc6O0QB5ylEO7D509sB2273fFWu-g?e=vbtEsa here].</font>
{| class="wikitable"
|Variable
|GBD Estimate
|Measure
|Metric
|Cause
|Location
|Age
|Sex
|Year
|Decimal Places
|-
|ViolencePoliticalConflictTerror
|Cause of death  or injury
|Deaths
|Rate
|Conflict and  terrorism
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolencePoliticalPoliceExecution
|Cause of death or  injury
|Deaths
|Rate
|Executions and police  conflict
|Select all countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceSelfHarm
|Cause of death or  injury
|Deaths
|Rate
|Self-harm
|Select all  countries and territories
|All Ages
|Both
|Select all
|4
|-
|SocietalViolenceDeathsTotal
|Cause of death or  injury
|Deaths
|Rate
|Interpersonal  violence + Conflict and terrorism + Executions and police conflict
|Select all  countries and territories
|All Ages
|Both
|Select all
|4
|-
|ViolenceInterpersonChild
|Cause of death or  injury
|Deaths
|Rate
|Interpersonal violence against all children death rate
|Select all  countries and territories
|0-14
|Both
|Select all
|4
|-
|ViolenceInterpersonWomenAdult
|Cause of death or  injury
|Deaths
|Rate
|Interpersonal  violence
|Select all  countries and territories
|>= 15
|Female
|Select all
|4
|-
|DrOpiodPrevIHME
|Cause of death or  injury
|Prevalence
|Percent
|Opioid Use Disorders
|Select  all countries and territories
|All Ages
|Both
|Select all
|4
|-
|DrugPrevalenceAmphetaminesIHME
|Cause of death or  injury
|Prevalence
|Percent
|Amphetamine Use Disorders
|Select all  countries and territories
|All Ages
|Both
|Select all
|5
|-
|DrugPrevalenceCocaineIHME
|Cause of death or  injury
|Prevalence
|Percent
|Cocaine Use Disorders
|Select all  countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsHIV
|Cause of death or  injury
|Deaths
|Number
|HIV/AIDs
|Select all  countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEDthsMalar
|Cause of death or  injury
|Deaths
|Number
|Malaria
|Select all  countries and territories
|All Ages
|Both
|Select all
|5
|-
|IHMEInciHIVNumber
|Cause of death or  injury
|Incidence
|Number
|HIV/AIDs
|Select all  countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEInciMalariaNumber
|Cause of death or  injury
|Incidence
|Number
|Malaria
|Select all  countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevHIV
|Cause of death or  injury
|Prevalence
|Percent
|HIV/AIDs
|Select all  countries and territories
|All Ages
|Both
|Select all
|3
|-
|IHMEPrevHIVNumber
|Cause of death or  injury
|Prevalence
|Number
|HIV/AIDs
|Select all  countries and territories
|All Ages
|Both
|Select all
|
|-
|IHMEPrevMalariaNumber
|Cause of death or  injury
|Prevalence
|Number
|Malaria
|Select all  countries and territories
|All Ages
|Both
|Select all
|
|-
|ViolenceInterpersonOther
|Cause of death or  injury
|Deaths
|Rate
|Death rate from Interpersonal violence for males aged over 15
|Select all  countries and territories
|>= 15
|Both
|Select all
|
|-
|ViolenceInterpersonWomenChild
|Cause of death or  injury
|Deaths
|Rate
|Deaths from interpersonal violence (Violence against women and children)
|Select all  countries and territories
|Sum of Child and WomenAdult
|Both
|Select all
|
|}
Note: 


#The data can be accessed from the GBD tool at&nbsp;<font style="background-color: rgb(255, 255, 255);">[http://ghdx.healthdata.org/gbd-results-tool 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.</font>
* ViolenceInterpersonChild & ViolenceInterpersonWomenAdult have changed a lot, we identify the Age by comparing the trend of old data in IFsHistSeries and the new data from GBD.
#<font style="background-color: rgb(255, 255, 255);">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.</font>
** In March 2025, the ages have shifted from >20 for adults to >15. To get this data, do a summation of 15-19 and 20+
#<font style="background-color: rgb(255, 255, 255);">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.</font>
* Be aware of the definition of each preprocessor and its unit so that you can find the exact match in the IHME GBD variables.
#<font style="background-color: rgb(255, 255, 255);">Once the script is done running, the completed Excel file will be located in the PythonOutput&Scripts folder.</font>
* Some regions in IFs are not provided by IHME yet, we are encouraged to use proxies. For example, use Singapore, Albania, and Mali for Hong Kong, Kosovo, and Sahrawi respectively. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally. To do this use SeriesPopulation. For instance, Kosovo’s number of deaths = Albania’s number of deaths * Kosovo’s Population / Albania’s Population.
#Pull in the data into IFs using the IFs data import tool.


= Things to Be Aware of While Pulling =
=== Tables Used in Hist+Forecast Display ===


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.
==== Update in March 2025 ====
The data can be accessed from the GBD tool at <font style="background-color: rgb(255, 255, 255);">http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Note that a detailed death cause mapping table can be found [[IFs.db#HealthDetailedDeathsCtry|here]].</font>


== August 2019 Update ==
There are 45 tables in total related to detailed death tables in IFs. For each of 15 death causes in IFs, we have a total death table and two tables by sex group. These 45 tables can be searched by using the following naming conventions IHMEDths___, IHMEDths___Females, and IHMEDths___Males, where ___ denotes the cause of death in IFs. These 15 causes are, Cardio, Diabet, Diarrh, Digest, HIV, Intlj, Malar, MalNeopl, MentHlth, OthCD, OthNCD, OthUnintlj, Respinfec, Respiratory, Roadacc. Below is the causes used for each table:
{| class="wikitable"
|Table
|Name in Source
|-
|IHMEDthsCardio
|Cardiovascular diseases
|-
|IHMEDthsCardioFemales
|Cardiovascular diseases
|-
|IHMEDthsCardioMales
|Cardiovascular diseases
|-
|IHMEDthsDiabet
|Diabetes mellitus
|-
|IHMEDthsDiabetFemales
|Diabetes mellitus
|-
|IHMEDthsDiabetMales
|Diabetes mellitus
|-
|IHMEDthsDiarrh
|Diarrheal diseases
|-
|IHMEDthsDiarrhFemales
|Diarrheal diseases
|-
|IHMEDthsDiarrhMales
|Diarrheal diseases
|-
|IHMEDthsDigest
|Digestive diseases
|-
|IHMEDthsDigestFemales
|Digestive diseases
|-
|IHMEDthsDigestMales
|Digestive diseases
|-
|IHMEDthsHIV
|HIV/AIDS
|-
|IHMEDthsHIVFemales
|HIV/AIDS
|-
|IHMEDthsHIVMales
|HIV/AIDS
|-
|IHMEDthsIntIj
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjFemales
|Self-harm and interpersonal violence
|-
|IHMEDthsIntIjMales
|Self-harm and interpersonal violence
|-
|IHMEDthsMalar
|Malaria
|-
|IHMEDthsMalarFemales
|Malaria
|-
|IHMEDthsMalarMales
|Malaria
|-
|IHMEDthsMalNeopl
|Neoplasms
|-
|IHMEDthsMalNeoplFemales
|Neoplasms
|-
|IHMEDthsMalNeoplMales
|Neoplasms
|-
|IHMEDthsMentHlth
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthFemales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsMentHlthMales
|Neurological disorders + Mental disorders + Substance use disorders
|-
|IHMEDthsOthCD
|Communicable, maternal, neonatal, and nutritional diseases, excluding  individual causes in IFs
|-
|IHMEDthsOthCDFemales
|Communicable, maternal, neonatal, and nutritional diseases, excluding  individual causes in IFs
|-
|IHMEDthsOthCDMales
|Communicable, maternal, neonatal, and nutritional diseases, excluding  individual causes in IFs
|-
|IHMEDthsOthNCD
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDFemales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthNCDMales
|Non-communicable diseases, excluding individual causes in IFs
|-
|IHMEDthsOthUnintIj
|Unintentional injuries
|-
|IHMEDthsOthUnintIjFemales
|Unintentional injuries
|-
|IHMEDthsOthUnintIjMales
|Unintentional injuries
|-
|IHMEDthsRespinfec
|Lower respiratory infections + Upper respiratory infections + Otitis  media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecFemales
|Lower respiratory infections + Upper respiratory infections + Otitis  media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespinfecMales
|Lower respiratory infections + Upper respiratory infections + Otitis  media + COVID-19 + Other COVID-19 pandemic-related outcomes
|-
|IHMEDthsRespiratory
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryFemales
|Chronic respiratory diseases
|-
|IHMEDthsRespiratoryMales
|Chronic respiratory diseases
|-
|IHMEDthsRoadacc
|Transport injuries
|-
|IHMEDthsRoadaccFemales
|Transport injuries
|-
|IHMEDthsRoadaccMales
|Transport injuries
|}


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.
= Demographic Related IHME Preprocessors =
 
=== Life Expectancy ===
Life expectancy data can be pulled from <font style="background-color: rgb(255, 255, 255);">http://ghdx.healthdata.org/gbd-results-tool. The filters should be:</font>
 
GBD Estimate All-cause mortality
 
Measure LE
 
Metric Years
 
Location All territories and countries
 
Age 0-6 days
 
Sex Both, Male, Female
 
Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Metric Name
|Decimal Places
|-
|LifeExpectIHMEBothSexesHistOnly
|0-6 days
|Both
|1950-2021
|Years
|3
|-
|LifeExpectIHMEMaleHistOnly
|0-6 days
|Male
|1950-2021
|Years
|3
|-
|LifeExpectIHMEFemaleHistOnly
|0-6 days
|Female
|1950-2021
|Years
|3
|}
 
=== Infant Mortality ===
Life expectancy data can be pulled from <font style="background-color: rgb(255, 255, 255);">http://ghdx.healthdata.org/gbd-results-tool</font>. The filters should be:
 
GBD Estimate All-cause mortality
 
Measure Life Tables
 
Metric Years
 
Location All territories and countries
 
Age Stated below
 
Sex Both
 
Year All
{| class="wikitable"
|Variable
|Age
|Sex
|Year
|Decimal Places
|-
|InfMortRateIHME
|< 1 year
|Both
|1950-2021
|4
|-
|Under5MortRateIHME
|Calculation of < 1 year, 12-23 months, and 2-4 year
|Both
|1950-2021
|4
|}
'''CALCULATIONS:'''
 
In order to get the right value for Under5MortRateIHME, we have to calculate it. It should be:
 
PoD under 5 = PoD under 1 + PoD 12-23 months * Probability of not dying under 1+ PoD 2-4 years * Probability of not dying under 2.
 
An example is posted below for Iraq:
{| class="wikitable"
|<1 year
|All causes
|Probability of death
|2019
|0.019244
|-
|12-23 months
|All causes
|Probability of death
|2019
|0.001482
|-
|2-4 years
|All causes
|Probability of death
|2019
|0.002298
|}
 
 
The PoD for under 2 would be = 0.019244 + 0.001482 * ( 1 - 0.019244) = 0.020698;
 
The PoD for under 5 would be = 0.020698 + 0.002298 * ( 1 - 0.020698) = 0.022948.
 
The final data point is '''0.022948'''.
 
= Tables in IFs.db =
 
=== HealthDetailedDeathsCtry ===
Detailed instruction on pulling number of deaths for IFs death categories can be found [[IFs.db#HealthDetailedDeathsCtry|here]].

Latest revision as of 14:46, 28 March 2025

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, prevalence, violence and forecasts for each. The latest IFs data update for this series was in March 2025, covering 188 economies over the years 198/90-2021. There have been major changes in this update which will be noted below.

Instructions on Pulling IHME data

Preprocessors on Prevalence and Incidence

Update in March 2025

The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Python scripts used from last data pull can be accessed and adjusted for future data pulls. An updated country concordance table can be found here.

Variable GBD Estimate Measure Metric Cause Location Age Sex Year Decimal Places
ViolencePoliticalConflictTerror Cause of death or injury Deaths Rate Conflict and terrorism Select all countries and territories All Ages Both Select all 4
ViolencePoliticalPoliceExecution Cause of death or injury Deaths Rate Executions and police conflict Select all countries and territories All Ages Both Select all 4
ViolenceSelfHarm Cause of death or injury Deaths Rate Self-harm Select all countries and territories All Ages Both Select all 4
SocietalViolenceDeathsTotal Cause of death or injury Deaths Rate Interpersonal violence + Conflict and terrorism + Executions and police conflict Select all countries and territories All Ages Both Select all 4
ViolenceInterpersonChild Cause of death or injury Deaths Rate Interpersonal violence against all children death rate Select all countries and territories 0-14 Both Select all 4
ViolenceInterpersonWomenAdult Cause of death or injury Deaths Rate Interpersonal violence Select all countries and territories >= 15 Female Select all 4
DrOpiodPrevIHME Cause of death or injury Prevalence Percent Opioid Use Disorders Select all countries and territories All Ages Both Select all 4
DrugPrevalenceAmphetaminesIHME Cause of death or injury Prevalence Percent Amphetamine Use Disorders Select all countries and territories All Ages Both Select all 5
DrugPrevalenceCocaineIHME Cause of death or injury Prevalence Percent Cocaine Use Disorders Select all countries and territories All Ages Both Select all 5
IHMEDthsHIV Cause of death or injury Deaths Number HIV/AIDs Select all countries and territories All Ages Both Select all 5
IHMEDthsMalar Cause of death or injury Deaths Number Malaria Select all countries and territories All Ages Both Select all 5
IHMEInciHIVNumber Cause of death or injury Incidence Number HIV/AIDs Select all countries and territories All Ages Both Select all
IHMEInciMalariaNumber Cause of death or injury Incidence Number Malaria Select all countries and territories All Ages Both Select all
IHMEPrevHIV Cause of death or injury Prevalence Percent HIV/AIDs Select all countries and territories All Ages Both Select all 3
IHMEPrevHIVNumber Cause of death or injury Prevalence Number HIV/AIDs Select all countries and territories All Ages Both Select all
IHMEPrevMalariaNumber Cause of death or injury Prevalence Number Malaria Select all countries and territories All Ages Both Select all
ViolenceInterpersonOther Cause of death or injury Deaths Rate Death rate from Interpersonal violence for males aged over 15 Select all countries and territories >= 15 Both Select all
ViolenceInterpersonWomenChild Cause of death or injury Deaths Rate Deaths from interpersonal violence (Violence against women and children) Select all countries and territories Sum of Child and WomenAdult Both Select all

Note:

  • ViolenceInterpersonChild & ViolenceInterpersonWomenAdult have changed a lot, we identify the Age by comparing the trend of old data in IFsHistSeries and the new data from GBD.
    • In March 2025, the ages have shifted from >20 for adults to >15. To get this data, do a summation of 15-19 and 20+
  • Be aware of the definition of each preprocessor and its unit so that you can find the exact match in the IHME GBD variables.
  • Some regions in IFs are not provided by IHME yet, we are encouraged to use proxies. For example, use Singapore, Albania, and Mali for Hong Kong, Kosovo, and Sahrawi respectively. Be mindful that for tables with units in rate or percent, proximal values can be directly applied; however, when values are in numbers or headcounts, you will need to borrow the population figures to apply values proportionally. To do this use SeriesPopulation. For instance, Kosovo’s number of deaths = Albania’s number of deaths * Kosovo’s Population / Albania’s Population.

Tables Used in Hist+Forecast Display

Update in March 2025

The data can be accessed from the GBD tool at http://ghdx.healthdata.org/gbd-results-tool. You can download the data based on the table below for each series. Note that a detailed death cause mapping table can be found here.

There are 45 tables in total related to detailed death tables in IFs. For each of 15 death causes in IFs, we have a total death table and two tables by sex group. These 45 tables can be searched by using the following naming conventions IHMEDths___, IHMEDths___Females, and IHMEDths___Males, where ___ denotes the cause of death in IFs. These 15 causes are, Cardio, Diabet, Diarrh, Digest, HIV, Intlj, Malar, MalNeopl, MentHlth, OthCD, OthNCD, OthUnintlj, Respinfec, Respiratory, Roadacc. Below is the causes used for each table:

Table Name in Source
IHMEDthsCardio Cardiovascular diseases
IHMEDthsCardioFemales Cardiovascular diseases
IHMEDthsCardioMales Cardiovascular diseases
IHMEDthsDiabet Diabetes mellitus
IHMEDthsDiabetFemales Diabetes mellitus
IHMEDthsDiabetMales Diabetes mellitus
IHMEDthsDiarrh Diarrheal diseases
IHMEDthsDiarrhFemales Diarrheal diseases
IHMEDthsDiarrhMales Diarrheal diseases
IHMEDthsDigest Digestive diseases
IHMEDthsDigestFemales Digestive diseases
IHMEDthsDigestMales Digestive diseases
IHMEDthsHIV HIV/AIDS
IHMEDthsHIVFemales HIV/AIDS
IHMEDthsHIVMales HIV/AIDS
IHMEDthsIntIj Self-harm and interpersonal violence
IHMEDthsIntIjFemales Self-harm and interpersonal violence
IHMEDthsIntIjMales Self-harm and interpersonal violence
IHMEDthsMalar Malaria
IHMEDthsMalarFemales Malaria
IHMEDthsMalarMales Malaria
IHMEDthsMalNeopl Neoplasms
IHMEDthsMalNeoplFemales Neoplasms
IHMEDthsMalNeoplMales Neoplasms
IHMEDthsMentHlth Neurological disorders + Mental disorders + Substance use disorders
IHMEDthsMentHlthFemales Neurological disorders + Mental disorders + Substance use disorders
IHMEDthsMentHlthMales Neurological disorders + Mental disorders + Substance use disorders
IHMEDthsOthCD Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
IHMEDthsOthCDFemales Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
IHMEDthsOthCDMales Communicable, maternal, neonatal, and nutritional diseases, excluding individual causes in IFs
IHMEDthsOthNCD Non-communicable diseases, excluding individual causes in IFs
IHMEDthsOthNCDFemales Non-communicable diseases, excluding individual causes in IFs
IHMEDthsOthNCDMales Non-communicable diseases, excluding individual causes in IFs
IHMEDthsOthUnintIj Unintentional injuries
IHMEDthsOthUnintIjFemales Unintentional injuries
IHMEDthsOthUnintIjMales Unintentional injuries
IHMEDthsRespinfec Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
IHMEDthsRespinfecFemales Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
IHMEDthsRespinfecMales Lower respiratory infections + Upper respiratory infections + Otitis media + COVID-19 + Other COVID-19 pandemic-related outcomes
IHMEDthsRespiratory Chronic respiratory diseases
IHMEDthsRespiratoryFemales Chronic respiratory diseases
IHMEDthsRespiratoryMales Chronic respiratory diseases
IHMEDthsRoadacc Transport injuries
IHMEDthsRoadaccFemales Transport injuries
IHMEDthsRoadaccMales Transport injuries

Demographic Related IHME Preprocessors

Life Expectancy

Life expectancy data can be pulled from http://ghdx.healthdata.org/gbd-results-tool. The filters should be:

GBD Estimate All-cause mortality

Measure LE

Metric Years

Location All territories and countries

Age 0-6 days

Sex Both, Male, Female

Year All

Variable Age Sex Year Metric Name Decimal Places
LifeExpectIHMEBothSexesHistOnly 0-6 days Both 1950-2021 Years 3
LifeExpectIHMEMaleHistOnly 0-6 days Male 1950-2021 Years 3
LifeExpectIHMEFemaleHistOnly 0-6 days Female 1950-2021 Years 3

Infant Mortality

Life expectancy data can be pulled from http://ghdx.healthdata.org/gbd-results-tool. The filters should be:

GBD Estimate All-cause mortality

Measure Life Tables

Metric Years

Location All territories and countries

Age Stated below

Sex Both

Year All

Variable Age Sex Year Decimal Places
InfMortRateIHME < 1 year Both 1950-2021 4
Under5MortRateIHME Calculation of < 1 year, 12-23 months, and 2-4 year Both 1950-2021 4

CALCULATIONS:

In order to get the right value for Under5MortRateIHME, we have to calculate it. It should be:

PoD under 5 = PoD under 1 + PoD 12-23 months * Probability of not dying under 1+ PoD 2-4 years * Probability of not dying under 2.

An example is posted below for Iraq:

<1 year All causes Probability of death 2019 0.019244
12-23 months All causes Probability of death 2019 0.001482
2-4 years All causes Probability of death 2019 0.002298


The PoD for under 2 would be = 0.019244 + 0.001482 * ( 1 - 0.019244) = 0.020698;

The PoD for under 5 would be = 0.020698 + 0.002298 * ( 1 - 0.020698) = 0.022948.

The final data point is 0.022948.

Tables in IFs.db

HealthDetailedDeathsCtry

Detailed instruction on pulling number of deaths for IFs death categories can be found here.