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indicator_code
stringclasses
1 value
country_iso3
stringclasses
47 values
who_region
stringclasses
1 value
year
int64
1.99k
2.02k
dim1_type
stringclasses
1 value
dim1
stringclasses
3 values
dim2_type
stringclasses
1 value
dim2
stringclasses
1 value
value_numeric
float64
0.71
179
value_low
float64
0.52
162
value_high
float64
0.87
207
value_display
stringlengths
13
19
last_updated
stringclasses
1 value
WHOSIS_000016
MLI
AFR
2,023
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
11.585024
8.658528
14.705498
11.6 [8.7-14.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ETH
AFR
1,997
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
35.573047
30.461342
41.419198
35.6 [30.5-41.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
NGA
AFR
2,011
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
16.000184
13.949526
18.234734
16.0 [13.9-18.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GHA
AFR
2,009
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
8.908995
7.834398
10.148589
8.9 [7.8-10.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
TZA
AFR
1,997
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
15.481783
13.917535
17.225346
15.5 [13.9-17.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ERI
AFR
2,023
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
3.91283
2.09635
5.91747
3.9 [2.1-5.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SYC
AFR
2,012
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
1.578437
1.182269
2.085128
1.6 [1.2-2.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
BDI
AFR
2,020
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
10.902329
8.027601
13.881541
10.9 [8.0-13.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
COD
AFR
2,014
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
13.193012
10.313499
16.640955
13.2 [10.3-16.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SWZ
AFR
1,993
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
8.444203
5.049104
10.404877
8.4 [5.0-10.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GAB
AFR
2,016
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
5.435285
2.593213
9.144968
5.4 [2.6-9.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GIN
AFR
1,993
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
26.198679
22.708594
30.612437
26.2 [22.7-30.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GAB
AFR
2,013
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
6.049827
3.12708
9.879271
6.0 [3.1-9.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
BFA
AFR
1,992
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
27.825908
24.265215
31.737001
27.8 [24.3-31.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
TZA
AFR
2,019
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
9.163404
6.812425
11.20756
9.2 [6.8-11.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SLE
AFR
2,006
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
17.48401
15.210362
20.093333
17.5 [15.2-20.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CIV
AFR
1,995
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
16.275976
14.138556
18.514167
16.3 [14.1-18.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SSD
AFR
2,019
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
13.58602
10.30305
17.728023
13.6 [10.3-17.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GNB
AFR
2,019
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
7.676525
4.731175
11.189072
7.7 [4.7-11.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
COM
AFR
2,002
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
7.601847
6.151024
9.445278
7.6 [6.2-9.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MLI
AFR
2,004
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
19.854942
17.520167
22.490815
19.9 [17.5-22.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SSD
AFR
2,006
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
18.901427
14.681311
24.235434
18.9 [14.7-24.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
BDI
AFR
1,993
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
69.755431
60.082336
80.804354
69.8 [60.1-80.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
COG
AFR
2,004
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
9.748922
8.093516
11.869912
9.7 [8.1-11.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SEN
AFR
2,008
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
13.287702
12.106611
14.600296
13.3 [12.1-14.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
TZA
AFR
1,992
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
17.640225
15.523067
19.993932
17.6 [15.5-20.0]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
AGO
AFR
2,020
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
9.797095
7.639914
12.479264
9.8 [7.6-12.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ZWE
AFR
2,023
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
4.01659
1.781294
5.8109
4.0 [1.8-5.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ETH
AFR
2,018
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
5.05243
3.655131
6.445327
5.1 [3.7-6.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ZWE
AFR
2,023
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
4.441688
1.939839
6.458636
4.4 [1.9-6.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SYC
AFR
2,002
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
1.998377
1.61273
2.477619
2.0 [1.6-2.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MWI
AFR
1,995
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
20.534435
18.354021
22.857049
20.5 [18.4-22.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
STP
AFR
1,991
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
13.088431
10.136036
16.820963
13.1 [10.1-16.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
TZA
AFR
2,008
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
9.996499
8.473786
11.669857
10.0 [8.5-11.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
TZA
AFR
2,011
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
9.75438
8.019979
11.563107
9.8 [8.0-11.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MLI
AFR
2,012
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
15.009634
12.608624
17.788499
15.0 [12.6-17.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CAF
AFR
2,020
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
19.401155
12.986643
26.676521
19.4 [13.0-26.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SSD
AFR
2,006
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
18.719454
14.316615
24.253722
18.7 [14.3-24.3]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CIV
AFR
1,994
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
16.59758
14.382178
18.926795
16.6 [14.4-18.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GAB
AFR
2,002
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
8.507304
6.336543
11.425453
8.5 [6.3-11.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MUS
AFR
2,015
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
0.783123
0.671457
0.905256
0.8 [0.7-0.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CAF
AFR
2,021
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
35.571229
23.41346
49.051961
35.6 [23.4-49.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GAB
AFR
2,011
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
6.746494
3.71789
10.781396
6.7 [3.7-10.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MDG
AFR
2,003
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
13.456334
11.79402
15.301513
13.5 [11.8-15.3]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
COM
AFR
2,022
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
3.085789
2.035064
4.182173
3.1 [2.0-4.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
UGA
AFR
2,023
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
7.530396
5.075961
9.997745
7.5 [5.1-10.0]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GHA
AFR
2,011
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
8.334685
7.248104
9.581937
8.3 [7.2-9.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SSD
AFR
2,013
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
13.821782
10.735797
17.722307
13.8 [10.7-17.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GIN
AFR
1,991
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
27.353683
23.397978
32.269291
27.4 [23.4-32.3]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SWZ
AFR
2,017
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
5.608609
3.331951
9.398389
5.6 [3.3-9.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
NER
AFR
2,005
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
27.707137
22.357887
32.160679
27.7 [22.4-32.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ZWE
AFR
2,002
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
8.298864
7.280859
9.739292
8.3 [7.3-9.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ERI
AFR
2,013
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
5.410518
3.533266
7.576372
5.4 [3.5-7.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
NER
AFR
2,000
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
32.921172
28.234267
37.743812
32.9 [28.2-37.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MUS
AFR
2,020
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
0.959089
0.806773
1.129977
1.0 [0.8-1.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GNB
AFR
2,003
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
20.240662
16.377201
24.098002
20.2 [16.4-24.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CMR
AFR
2,005
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
18.177466
16.132059
20.557695
18.2 [16.1-20.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GIN
AFR
1,994
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
25.043493
21.99648
28.911656
25.0 [22.0-28.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MDG
AFR
2,009
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
11.028672
9.639054
12.492298
11.0 [9.6-12.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CPV
AFR
2,003
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
1.745663
1.572688
1.933621
1.7 [1.6-1.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MOZ
AFR
1,994
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
30.876147
24.858514
37.62907
30.9 [24.9-37.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
UGA
AFR
1,997
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
16.236573
14.52997
18.253542
16.2 [14.5-18.3]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
NER
AFR
2,005
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
27.865008
22.633048
31.993801
27.9 [22.6-32.0]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MUS
AFR
2,010
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
1.010068
0.929863
1.099421
1.0 [0.9-1.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
BWA
AFR
2,004
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
6.884678
5.640278
8.667198
6.9 [5.6-8.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
NAM
AFR
2,001
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
8.472744
7.192181
9.987917
8.5 [7.2-10.0]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
RWA
AFR
1,995
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
62.435876
56.673452
68.505459
62.4 [56.7-68.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
LBR
AFR
2,006
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
12.646237
10.778829
14.825225
12.6 [10.8-14.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CMR
AFR
2,015
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
14.633169
12.048919
17.403106
14.6 [12.0-17.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GNQ
AFR
2,016
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
10.708224
8.37702
13.740307
10.7 [8.4-13.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
KEN
AFR
1,990
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
11.348684
9.950645
12.91353
11.3 [10.0-12.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MLI
AFR
2,018
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
13.359784
10.639715
16.405189
13.4 [10.6-16.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
COD
AFR
2,008
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
15.869122
13.21541
19.019444
15.9 [13.2-19.0]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ETH
AFR
2,011
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
10.159131
8.545336
12.039619
10.2 [8.5-12.0]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CPV
AFR
2,004
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
1.97095
1.839401
2.112616
2.0 [1.8-2.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
AGO
AFR
2,014
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
12.716296
9.666285
16.531152
12.7 [9.7-16.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GAB
AFR
1,993
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
9.768261
6.6517
14.161104
9.8 [6.7-14.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SYC
AFR
1,997
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
2.202016
1.792796
2.720955
2.2 [1.8-2.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MRT
AFR
2,005
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
9.124089
7.6279
11.050522
9.1 [7.6-11.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GHA
AFR
2,012
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
7.441788
6.401085
8.632615
7.4 [6.4-8.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
UGA
AFR
1,992
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
18.147387
15.796875
20.901549
18.1 [15.8-20.9]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SEN
AFR
2,011
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
8.495068
7.592024
9.510429
8.5 [7.6-9.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GNQ
AFR
2,010
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
13.562605
10.609996
17.402919
13.6 [10.6-17.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GHA
AFR
2,019
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
6.748517
5.467336
8.188646
6.7 [5.5-8.2]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
BWA
AFR
2,018
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
4.080326
3.013935
5.466158
4.1 [3.0-5.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SEN
AFR
1,990
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
23.159956
21.117476
25.507486
23.2 [21.1-25.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ZMB
AFR
1,990
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
17.257848
14.603324
20.473214
17.3 [14.6-20.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MRT
AFR
1,997
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
10.589711
9.081786
12.490481
10.6 [9.1-12.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
RWA
AFR
2,011
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
9.755889
8.514013
11.145028
9.8 [8.5-11.1]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ETH
AFR
2,020
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
3.767758
2.577934
5.008626
3.8 [2.6-5.0]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SYC
AFR
2,006
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
1.204938
0.942017
1.533132
1.2 [0.9-1.5]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ZWE
AFR
1,997
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
8.080541
6.941198
9.443048
8.1 [6.9-9.4]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
MOZ
AFR
2,023
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
5.627279
3.827236
7.596618
5.6 [3.8-7.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
CIV
AFR
1,992
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
17.283686
14.935322
19.802992
17.3 [14.9-19.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
LSO
AFR
2,009
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
6.228542
5.142626
7.556459
6.2 [5.1-7.6]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
ETH
AFR
2,008
SEX
SEX_FMLE
AGEGROUP
AGEGROUP_YEARS05-09
13.457016
11.462044
15.762237
13.5 [11.5-15.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
SEN
AFR
1,993
SEX
SEX_MLE
AGEGROUP
AGEGROUP_YEARS05-09
22.387725
20.285839
24.820894
22.4 [20.3-24.8]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
COM
AFR
2,008
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
6.229829
5.090844
7.708889
6.2 [5.1-7.7]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
GMB
AFR
1,991
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
20.465165
16.040767
26.284021
20.5 [16.0-26.3]
2025-04-15T09:25:23.79+02:00
WHOSIS_000016
NGA
AFR
2,008
SEX
SEX_BTSX
AGEGROUP
AGEGROUP_YEARS05-09
16.818665
15.028653
18.765486
16.8 [15.0-18.8]
2025-04-15T09:25:23.79+02:00
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Africa — WHO GHO: Mortality rate among children ages 5 to 9 years (per 1000 children aged 5)

Indicator code: WHOSIS_000016 HuggingFace slug: electricsheepafrica/africa-who-mortality-rate-among-children-ages-5-to-9-years Source: WHO Global Health Observatory License: CC BY 4.0 — WHO Open Data


Dataset Description

This dataset contains country-level observations for the WHO GHO indicator "Mortality rate among children ages 5 to 9 years (per 1000 children aged 5)" (WHOSIS_000016) across African nations, spanning 1990–2023. It is part of the Electric Sheep Africa collection — a unified, ML-ready repository of African data.

Data is sourced directly from the WHO Global Health Observatory OData API and repackaged as Parquet files with a consistent schema. All values are drawn from NumericValue (the float-precision field), not the display string. Confidence interval bounds (value_low, value_high) are included where available.


Coverage

Countries 47 African nations
Years 1990 – 2023
Total rows 4,794
Region filter WHO AFRO (ParentLocationCode = 'AFR')

Countries included: AGO, BDI, BEN, BFA, BWA, CAF, CIV, CMR, COD, COG, COM, CPV, DZA, ERI, ETH, GAB, GHA, GIN, GMB, GNB … and 27 more


Sub-dimensions

  • SEX: SEX_BTSX, SEX_FMLE, SEX_MLE

When an indicator is stratified (e.g., by sex or age group), each unique combination of country × year × dimension produces a separate row. Filter on dim1 / dim2 for the stratum you need, or aggregate across strata.


Schema

Column Type Description
indicator_code string GHO indicator code (e.g., WHOSIS_000016)
country_iso3 string ISO 3166-1 alpha-3 country code
who_region string WHO region code (always AFR here)
year int Observation year
value_numeric float Point estimate (primary ML target)
value_low float Lower confidence bound (if available)
value_high float Upper confidence bound (if available)
value_display string Formatted display string, e.g. "58.3 [57.7–59.0]"
dim1_type string Dimension 1 type, e.g. SEX, RESIDENCEAREATYPE
dim1 string Dimension 1 value, e.g. SEX_BTSX, RURAL
dim2_type string Dimension 2 type (if present)
dim2 string Dimension 2 value (if present)
last_updated string WHO data last-updated timestamp

Usage

from datasets import load_dataset

ds = load_dataset("electricsheepafrica/africa-who-mortality-rate-among-children-ages-5-to-9-years")
df = ds["train"].to_pandas()

# Both-sexes, national level only
national = df[df.get("dim1", "").str.endswith("_BTSX") | df.get("dim1", pd.Series()).isna()]

# Time series for one country
kenya = df[df["country_iso3"] == "KEN"].sort_values("year")

Citation

@misc{who_gho_whosis_000016,
  title     = {WHO Global Health Observatory: Mortality rate among children ages 5 to 9 years (per 1000 children aged 5)},
  author    = {World Health Organization},
  year      = {2023},
  url       = {https://www.who.int/data/gho/data/indicators/indicator-details/GHO/WHOSIS_000016},
  note      = {Repackaged by Electric Sheep Africa}
}

Repackaged by Electric Sheep Africa from WHO GHO open data. Original data © World Health Organization, licensed CC BY 4.0.

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