rgho is an R package to access WHO GHO data from R via the Athena web service, an API providing a simple query interface to the World Health Organization’s data and statistics content.
As stated by the WHO website: The GHO data repository contains an extensive list of indicators, which can be selected by theme or through a multi-dimension query functionality. It is the World Health Organization’s main health statistics repository.
GHO data is composed of indicators structured in dimensions. The list of dimensions is available in vignette("b-dimensions", "rgho"), the list of indicators for the GHO dimension (the main dimension) in vignette("c-codes-gho", "rgho")).
It is possible to access dimensions with get_gho_dimensions():
get_gho_dimensions()## A 'GHO' object of 115 elements.
##
## Label ID
## 1 SUBSTANCE_ABUSE_ADVERTISING_TYPES ADVERTISINGTYPE
## 2 Age Group AGEGROUP
## 3 SUBSTANCE_ABUSE_ALCOHOL_POLICY_YEARS ALCOHOLPOLICYYEAR
## 4 Beverage Types ALCOHOLTYPE
## 5 SUBSTANCE_ABUSE_AWARENESS_ACTIVITY_TYPES AWARENESSACTIVITYTYPE
## 6 SUBSTANCE_ABUSE_BAC_GROUPS BACGROUP
## ...
##
## (Printing 6 first elements.)And codes for a given dimension with get_gho_codes():
get_gho_codes(dimension = "COUNTRY")## A 'GHO' object of 247 elements.
##
## Label ID
## 1 Aruba ABW
## 2 Afghanistan AFG
## 3 Angola AGO
## 4 Anguilla AIA
## 5 Albania ALB
## 6 Andorra AND
## ...
##
## (Printing 6 first elements.)
##
## Attributes:
##
## DS
## FIPS
## GEOMETRY
## IOC
## ISO
## ISO2
## ITU
## LAND_AREA_KMSQ_2012
## LANGUAGES_EN_2012
## MARC
## MORT
## SHORTNAMEES
## SHORTNAMEFR
## WHO
## WHOLEGALSTATUS
## WHO_REGION
## WHO_REGION_CODE
## WMO
## WORLD_BANK_INCOME_GROUP
## WORLD_BANK_INCOME_GROUP_CODE
## WORLD_BANK_INCOME_GROUP_GNI_REFERENCE_YEAR
## WORLD_BANK_INCOME_GROUP_RELEASE_DATEget_gho_codes(dimension = "GHO")## A 'GHO' object of 2232 elements.
##
## Label
## 1 Ambient air pollution attributable deaths
## 2 Ambient air pollution attributable DALYs per 100'000 children under 5 years
## 3 Household air pollution attributable deaths
## 4 Household air pollution attributable deaths in children under 5 years
## 5 Household air pollution attributable deaths per 100'000 capita
## 6 Household air pollution attributable deaths per 100'000 children under 5 years
## ID
## 1 AIR_1
## 2 AIR_10
## 3 AIR_11
## 4 AIR_12
## 5 AIR_13
## 6 AIR_14
## ...
##
## (Printing 6 first elements.)
##
## Attributes:
##
## CATEGORY
## DEFINITION_XML
## DISPLAY_ES
## DISPLAY_FR
## IMR_ID
## RENDERER_IDThe number of printed items can be changed by the option rgho.n.
The function search_dimensions() and search_codes() research a term in dimension or codes labels, respectively.
search_dimensions("region")## A 'GHO' object of 10 elements.
##
## Label ID
## 1 Subnational region DHSMICSGEOREGION
## 2 GBD Region GBDREGION
## 3 Region MGHEREG
## 4 OECD Region OECDREGION
## 5 WHO region REGION
## 6 Sub Region SUBREGION
## ...
##
## (Printing 6 first elements.)search_codes("neonatal", dimension = "GHO")## A 'GHO' object of 7 elements.
##
## Label
## 1 Number of neonatal deaths (thousands)
## 2 Neonatal mortality rate (per 1000 live births)
## 3 Distribution of causes of death among children aged <5 years (%) - Neonatal sepsis
## 4 Neonatal tetanus - number of reported cases
## 5 Neonates protected at birth against neonatal tetanus (PAB) (%)
## 6 Neonatal mortality rate (deaths per 1000 live births)
## ID
## 1 CM_03
## 2 WHOSIS_000003
## 3 WHS2_515
## 4 WHS3_56
## 5 WHS4_128
## 6 nmr
## ...
##
## (Printing 6 first elements.)
##
## Attributes:
##
## CATEGORY
## DEFINITION_XML
## DISPLAY_ES
## DISPLAY_FR
## IMR_ID
## RENDERER_IDIt is also possible to search results from an existing object.
result <- get_gho_codes(dimension = "REGION")
search_gho(result, "asia")## A 'GHO' object of 6 elements.
##
## Label
## 1 South East Asia region, stratum B (SEAR B)
## 2 South East Asia region, stratum D (SEAR D)
## 3 South-East Asia
## 4 South-East Asia
## 5 High income countries of the South-East Asia Region
## 6 Low- and middle-income countries of the South-East Asia Region
## ID
## 1 GBD_REG14_SEARB
## 2 GBD_REG14_SEARD
## 3 OECD_NON_SEAR
## 4 SEAR
## 5 WHO_HI_SEAR
## 6 WHO_LMI_SEARDimension codes can be filtered according to their attributes.
results <- get_gho_codes(dimension = "COUNTRY")
filter_gho(
results,
WHO_REGION_CODE == "EUR"
)## A 'GHO' object of 53 elements.
##
## Label ID
## 1 Albania ALB
## 2 Andorra AND
## 3 Armenia ARM
## 4 Austria AUT
## 5 Azerbaijan AZE
## 6 Belgium BEL
## ...
##
## (Printing 6 first elements.)
##
## Attributes:
##
## DS
## FIPS
## GEOMETRY
## IOC
## ISO
## ISO2
## ITU
## LAND_AREA_KMSQ_2012
## LANGUAGES_EN_2012
## MARC
## MORT
## SHORTNAMEES
## SHORTNAMEFR
## WHO
## WHOLEGALSTATUS
## WHO_REGION
## WHO_REGION_CODE
## WMO
## WORLD_BANK_INCOME_GROUP
## WORLD_BANK_INCOME_GROUP_CODE
## WORLD_BANK_INCOME_GROUP_GNI_REFERENCE_YEAR
## WORLD_BANK_INCOME_GROUP_RELEASE_DATEAttribute names and values can be displayed.
display_attributes(
results
)## [1] "code"
## [2] "DS"
## [3] "FIPS"
## [4] "GEOMETRY"
## [5] "IOC"
## [6] "ISO"
## [7] "ISO2"
## [8] "ITU"
## [9] "LAND_AREA_KMSQ_2012"
## [10] "LANGUAGES_EN_2012"
## [11] "MARC"
## [12] "MORT"
## [13] "SHORTNAMEES"
## [14] "SHORTNAMEFR"
## [15] "WHO"
## [16] "WHOLEGALSTATUS"
## [17] "WHO_REGION"
## [18] "WHO_REGION_CODE"
## [19] "WMO"
## [20] "WORLD_BANK_INCOME_GROUP"
## [21] "WORLD_BANK_INCOME_GROUP_CODE"
## [22] "WORLD_BANK_INCOME_GROUP_GNI_REFERENCE_YEAR"
## [23] "WORLD_BANK_INCOME_GROUP_RELEASE_DATE"display_attribute_values(
results,
"WHO_REGION_CODE"
)## [1] "AFR" "AMR" "EMR" "EUR" "SEAR" "WPR"An indicator can be downloaded as a data_frame with get_gho_data(). Here we use MDG_0000000001, Infant mortality rate (probability of dying between birth and age 1 per 1000 live births):
result <- get_gho_data(
dimension = "GHO",
code = "MDG_0000000001"
)
print(result, width = Inf)## # A tibble: 5,330 × 11
## GHO PUBLISHSTATE YEAR REGION WORLDBANKINCOMEGROUP COUNTRY
## <chr> <chr> <int> <chr> <chr> <chr>
## 1 MDG_0000000001 PUBLISHED 2001 AFR WB_LI BEN
## 2 MDG_0000000001 PUBLISHED 1999 AFR WB_LI BFA
## 3 MDG_0000000001 PUBLISHED 2006 AFR WB_LI BFA
## 4 MDG_0000000001 PUBLISHED 2007 AFR WB_LI BFA
## 5 MDG_0000000001 PUBLISHED 2009 AFR WB_LI BFA
## 6 MDG_0000000001 PUBLISHED 1992 AFR WB_UMI BWA
## 7 MDG_0000000001 PUBLISHED 1999 AFR WB_UMI BWA
## 8 MDG_0000000001 PUBLISHED 2015 AFR WB_UMI BWA
## 9 MDG_0000000001 PUBLISHED 2002 AFR WB_LI BEN
## 10 MDG_0000000001 PUBLISHED 2007 AFR WB_LI BEN
## `Display Value` Numeric Low High Comments
## <chr> <dbl> <dbl> <dbl> <chr>
## 1 87.4 [81.9-93.2] 87.4 81.9 93.2 <NA>
## 2 97.3 [92.3-102.5] 97.3 92.3 102.5 <NA>
## 3 82.7 [78.0-87.8] 82.7 78.0 87.8 <NA>
## 4 79.2 [74.6-84.1] 79.2 74.6 84.1 <NA>
## 5 72.5 [67.8-77.8] 72.5 67.8 77.8 <NA>
## 6 44.2 [38.9-49.7] 44.2 38.9 49.7 <NA>
## 7 53.1 [44.2-62.1] 53.1 44.2 62.1 <NA>
## 8 34.8 [18.6-58.1] 34.8 18.6 58.1 <NA>
## 9 85.2 [79.8-90.9] 85.2 79.8 90.9 <NA>
## 10 75.2 [67.7-82.3] 75.2 67.7 82.3 <NA>
## # ... with 5,320 more rowsThe filter argument in get_gho_data() allows request filtering:
result <- get_gho_data(
dimension = "GHO",
code = "MDG_0000000001",
filter = list(
REGION = "EUR",
YEAR = "2015"
)
)
print(result, width = Inf)## # A tibble: 54 × 11
## GHO PUBLISHSTATE YEAR REGION WORLDBANKINCOMEGROUP COUNTRY
## <chr> <chr> <int> <chr> <chr> <chr>
## 1 MDG_0000000001 PUBLISHED 2015 EUR WB_HI BEL
## 2 MDG_0000000001 PUBLISHED 2015 EUR WB_UMI BGR
## 3 MDG_0000000001 PUBLISHED 2015 EUR WB_HI DEU
## 4 MDG_0000000001 PUBLISHED 2015 EUR WB_HI EST
## 5 MDG_0000000001 PUBLISHED 2015 EUR WB_HI ISL
## 6 MDG_0000000001 PUBLISHED 2015 EUR WB_HI LUX
## 7 MDG_0000000001 PUBLISHED 2015 EUR WB_HI LVA
## 8 MDG_0000000001 PUBLISHED 2015 EUR WB_LMI MDA
## 9 MDG_0000000001 PUBLISHED 2015 EUR WB_HI PRT
## 10 MDG_0000000001 PUBLISHED 2015 EUR WB_HI AUT
## `Display Value` Numeric Low High Comments
## <chr> <dbl> <dbl> <dbl> <chr>
## 1 3.3 [3.0-3.6] 3.3 3.0 3.6 <NA>
## 2 9.3 [8.5-10.2] 9.3 8.5 10.2 <NA>
## 3 3.1 [2.9-3.3] 3.1 2.9 3.3 <NA>
## 4 2.3 [2.0-2.8] 2.3 2.0 2.8 <NA>
## 5 1.6 [1.1-2.3] 1.6 1.1 2.3 <NA>
## 6 1.5 [1.1-2.1] 1.5 1.1 2.1 <NA>
## 7 6.9 [5.1-9.5] 6.9 5.1 9.5 <NA>
## 8 13.6 [9.6-19.8] 13.6 9.6 19.8 <NA>
## 9 3.0 [2.5-3.6] 3.0 2.5 3.6 <NA>
## 10 2.9 [2.6-3.2] 2.9 2.6 3.2 <NA>
## # ... with 44 more rowsOther parameters than format can be specified to get_gho_data() (such as apikey, asof…). Parameters are listed on this page. Note that most parameters are not available to general users.
For details about how the requests are performed and the option availables (especially proxy settings) see vignette("e-details", "rgho").