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English Data
Region:
Uganda
- [uga]
Profile:
Select what profile you want:
Disaster type
Multi-hazard profile
FLOOD
HAILSTORM
DROUGHT
STORM
LANDSLIDE
EPIDEMIC
ACCIDENT
FIRE
RAINSTORM
LIGHTNING
WINDSTORM
DROWNING
RAINS
OTHER
ANIMAL ATTACK
FAMINE
MUDSLIDE
THUNDERSTORM
EARTHQUAKE
AVALANCHE
INTOXICATION
PEST INFESTATION
PLAGUE
CONTAMINATION
FOREST FIRE
FLASH FLOOD
CONFLICT
HEAT WAVE
SEDIMENTATION
SNOWSTORM
STRUCTURAL COLLAPSE
TORNADO
District
ALL
ABIM
ADJUMANI
AGAGO
ALEBTONG
AMOLATAR
AMUDAT
AMURIA
AMURU
APAC
ARUA
BUDAKA
BUDUDA
BUGIRI
BUGWERI
BUHWEJU
BUIKWE
BUKEDEA
BUKOMANSIMBI
BUKWO
BULAMBULI
BULIISA
BUNDIBUGYO
BUNYANGABU
BUSHENYI
BUSIA
BUTALEJA
BUTAMBALA
BUTEBO
BUVUMA
BUYENDE
DOKOLO
GOMBA
GULU
HOIMA
IBANDA
IGANGA
ISINGIRO
JINJA
KAABONG
KABALE
KABAROLE
KABERAMAIDO
KAGADI
KAKUMIRO
KALAKI
KALANGALA
KALIRO
KALUNGU
KAMPALA
KAMULI
KAMWENGE
KANUNGU
KAPCHORWA
KAPELEBYONG
KARENGA
KASESE
KASSANDA
KATAKWI
KATERERE
KAYUNGA
KAZO
KIBAALE
KIBINGO
KIBOGA
KIBUKU
KIKUUBE
KIRUHURA
KIRYANDONGO
KISORO
KITAGWENDA
KITGUM
KOBOKO
KOLE
KOTIDO
KUMI
KWANIA
KWEEN
KYANKWANZI
KYEGEGWA
KYENJOJO
KYOTERA
LAMWO
LIRA
LUUKA
LUWERO
LWENGO
LYANTONDE
MADI OKOLLO
MANAFWA
MARACHA
MASAKA
MASINDI
MAYUGE
MBALE
MBARARA
MITOOMA
MITYANA
MOROTO
MOYO
MPIGI
MUBENDE
MUKONO
NABILATUK
NAKAPIRIPIRIT
NAKASEKE
NAKASONGOLA
NAMAYINGO
NAMISINDWA
NAMUTUMBA
NAPAK
NEBBI
NGORA
NTOROKO
NTUNGAMO
NWOYA
OBONGI
OMORO
OTUKE
OYAM
PADER
PAKWACH
PALLISA
RAKAI
RUBANDA
RUBIRIZI
RUKIGA
RUKUNGIRI
RWAMPARA
SERERE
SHEEMA
SIRONKO
SOROTI
SSEMBABULE
TORORO
WAKISO
YUMBE
ZOMBO
Uganda
Profile:
This Country Profile shows a set of typical results known as "Preliminary Analysis" comming from the disaster database. Charts, Maps and tables below will provide you with a basic understanding of the effects of many types of disasters occurred in the region.
Click here for more info
Composition of Disasters
Deaths
DataCards
Indirectly Affected + Directly affected
Houses Destroyed + Houses Damaged
Temporal Behaviour
Deaths
DataCards
Houses Destroyed , Houses Damaged
Indirectly Affected, Directly affected
>
Spatial Distribution
Deaths
DataCards
Houses Destroyed + Houses Damaged
Indirectly Affected + Directly affected
Statistics
Composition of Disasters
get it as Excel
Event
DataCards
Deaths
Injured
Missing
Houses
Destroyed
Houses
Damaged
Indirectly Affected
Directly affected
Relocated
Evacuated
Losses $USD
Losses $Local
Education centers
Hospitals
Damages in crops Ha.
Lost Cattle
Damages in roads Mts
ACCIDENT
243
9713
37059
132
ANIMAL ATTACK
46
39
59
1
18720
3682
22
CONTAMINATION
3
2
35
60
DROUGHT
640
268
4920473
25685
190
DROWNING
70
378
37
1
17
EARTHQUAKE
17
278
1331
3688
6770
113700
EPIDEMIC
284
2524
2672
6
299607
382
20
50
477
1639
FAMINE
31
536
280911
1700
FIRE
270
193
467
43
7013
1402
49442
87
493
6000
10
3453
FLASH FLOOD
2
100
FLOOD
1331
483
579
27
35195
30263
4140775
1827
331381
62444
534
135
79704
1322
255861
FOREST FIRE
3
3
107
HAILSTORM
643
49
320
51
5327
2057
283628
50
3700
160
4
44467
551
HEAT WAVE
1
INTOXICATION
7
38
2
LANDSLIDE
332
2718
118
967
2443
445
433675
195
5771
1053
64
2
7824
13
80535
LIGHTNING
106
219
493
5
11
67
2
55
MUDSLIDE
28
22
298
129
6541
1
2
OTHER
39
102
11
203
64587
150
5
3628
30
PLAGUE
5
RAINS
66
3
41
331
97
141640
400
24
16456
1
RAINSTORM
123
29
158
2
1192
69
81474
107
3116
21
STORM
451
232
460
5
4118
2463
475353
500
470
140
177
10
20172
60
STRUCTURAL COLLAPSE
1
12
183
50
THUNDERSTORM
21
14
20
3
2470
55
TORNADO
1
154
51
350
WINDSTORM
83
1
8
482
97
10486
43
1
830
Spatial Distribution
get it as Excel
Geography
Code
DataCards
Deaths
Injured
Missing
Houses
Destroyed
Houses
Damaged
Indirectly Affected
Directly affected
Relocated
Evacuated
Losses $USD
Losses $Local
Education centers
Hospitals
Damages in crops Ha.
Lost Cattle
Damages in roads Mts
ABIM
314
33
5
3
76577
ADJUMANI
301
23
17
232
55
1506
AGAGO
329
31
13
52
3002123
300000
4
ALEBTONG
308
11
12
13
57
4115
3
2
AMOLATAR
315
14
1
AMUDAT
311
26
52
2
254
6606
20140
51
7
AMURIA
216
75
24
20
10652
1343
760061
2430
42
4485
AMURU
316
14
15
10
24
300
300
27357
6
369
APAC
302
24
135
457
87
1167
6000
16
1500
119
ARUA
303
166
259
568
188
3
42944
247
40
13
1
300
189
BUDAKA
217
28
24
7
138
52
BUDUDA
218
141
2393
62
950
583
330152
2005
444
22
47
1
4793
8
4080
BUGIRI
201
23
80
397
18
33
4875
117
19
22
BUHWEJU
424
13
7
2
8
812
262
BUIKWE
108
22
30
31
17
30
178
BUKEDEA
219
32
1
1
671
20
18287
2509
400
79
2
3174
BUKOMANSIMBI
105
36
4
8
109
61
601
4
540
BUKWO
220
26
15
2
1
74134
1
46
35
BULAMBULI
215
91
199
2
17
2708
327
236673
2500
42124
BULIISA
416
11
66
12
49
764
5
1
BUNDIBUGYO
401
42
434
144
78
15906
2000
923
BUSHENYI
402
59
381
376
2
8
24165
400
54
130
BUSIA
202
22
67
224
2
2112
15
9
BUTALEJA
221
110
14
68
2
671
61
85992
36
123
133
124
3605
2
BUTAMBALA
106
8
1
2965
BUVUMA
123
5
24
210
BUYENDE
205
7
12
1630
10500
DOKOLO
317
12
1
24008
4
52600
GOMBA
121
9
4
3
44
14
827
6
200
GULU
305
55
238
557
1
4242
18911
10
20
HOIMA
403
53
434
351
56
1
6482
11
1
100
IBANDA
417
35
64
44
130
17922
2
309
2
IGANGA
203
24
457
980
15
26158
2
ISINGIRO
418
47
27
24
18
27765
7
JINJA
204
54
257
1168
450
62
7426
4
1
KAABONG
318
97
159
13
201
2
804505
KABALE
404
138
288
514
975
36
23742
4
67
500
16
3762
KABAROLE
405
76
506
2636
2840
6783
175637
100
4
3061
108
KABERAMAIDO
213
12
7
46
3464
KALANGALA
101
26
88
136
672
652
3433
750
55
KALIRO
222
2
1
KALUNGU
118
19
103
22
742
91
KAMPALA
102
136
4604
17336
2
347
1196
88216
97
76
26
1
41
KAMULI
227
42
116
531
56
302
1
13106
52
16
KAMWENGE
413
41
6
2
3646
456
36480
1
10
KANUNGU
414
26
10
46
150
2904
734
49
KAPCHORWA
206
42
114
189
107
6894
59
350
100
7
2
13
KASESE
406
142
352
729
7
976
1277
33519
19
9011
2320
56
3
19617
396
KATAKWI
207
105
23
50
6713
10000
239895
15045
99
5
20001
KAYUNGA
112
57
35
179
236
18
4913
8
20
KIBAALE
407
57
178
253
53
35
2924
11
2958
KIBOGA
103
46
96
226
4
22
1171
3
180
KIBUKU
210
20
62
76
246667
4
15
KIRUHURA
420
21
5
2433
5
KIRYANDONGO
409
4
38
107
13
436
KISORO
408
134
56
116
319
4
45079
12
100
9
1
6163
116620
KITGUM
323
48
224
293
200
1538
30
1000
KOBOKO
319
16
10
1
267
5403
KOLE
322
17
48
455
4
632
7
KOTIDO
306
63
595
123
157
182081
KUMI
208
35
100
279
556
1
33960
2
1
KWEEN
228
4
3620
300
KYANKWANZI
117
22
1
131
63
750
2
504
20
KYEGEGWA
415
3
119
4
KYENJOJO
427
6
47
139
9
5
1918
500
1
LAMWO
324
28
2
20416
7
554
LIRA
307
61
169
1191
2
724
778
10667
10
40000
3
2071
10
LUUKA
226
9
40
15
3554
3
LUWERO
104
22
204
905
24
150
4
LWENGO
119
21
5
169
4446
2
605
LYANTONDE
114
11
10
5
14685
24
MANAFWA
223
82
2
85
274
1942
1759
53
15
1053
7
MARACHA
320
4
92000
MASAKA
120
46
487
1646
112
13780
116464
5
1
1001
MASINDI
426
33
200
591
1
10
57990
5082
16
MAYUGE
214
28
66
55
167
7228
1
MBALE
209
88
229
1022
14
584
1214
30980
38
39
2
1132
1
MBARARA
410
192
498
876
6
1387
156
43473
500
10
2425
MITOOMA
423
22
4
11
6
2199
3
1733
MITYANA
115
19
18
26
12
6196
MOROTO
325
78
123
291
5
1
2143781
300
679
930
MOYO
309
37
34
48
1
752
937
4929
87
1
3279
MPIGI
122
28
529
1275
175
458
1513
3700
31
1880
500
MUBENDE
107
41
218
314
1740
375742
1
2
133
MUKONO
124
87
452
1634
1470
405
10195
7
360
1
NAKAPIRIPIRIT
312
47
11
128
116824
NAKASEKE
116
15
5
38
3
289
2
NAKASONGOLA
109
31
95
237
492
200
278597
16
NAMAYINGO
225
1
80
NAMUTUMBA
224
20
4
15
611
42
215998
1
184
1
NAPAK
326
61
16
1
39
193
81140
NEBBI
310
108
139
489
364
24
324744
5
1
3352
NGORA
229
3
2337
618
NTOROKO
421
35
22
4
94
40
15728
4
500
22
NTUNGAMO
411
68
107
374
615
51612
50
1
NWOYA
331
9
8
17
4000
3642
OTUKE
327
39
11
35
856
52996
150
9
3407
3
OYAM
321
14
3
27
225
14347
5
263
PADER
330
13
35
98
PALLISA
230
56
143
506
2
430
104
1712
105
17
2
100
10
RAKAI
110
48
119
450
1197
68
32495
100
5
1024
RUKUNGIRI
412
40
59
305
7
7732
20
2
1989
6
SERERE
211
21
1
392
70
21956
103
SIRONKO
232
116
85
119
4465
761
48033
512
100
101
17571
98
SOROTI
231
40
77
247
290
28716
1
20931
163000
SSEMBABULE
111
45
22
198
402
78
6090
29
2073
TORORO
212
90
74
470
107
2
3410
3
4
1064
WAKISO
113
48
195
593
1092
322
2915
150
23
900
YUMBE
313
19
11
40
1
62
ZOMBO
328
84
7
88
19
1083
82
245874
4
205
Temporal Behaviour
get it as Excel
Year
DataCards
Deaths
Injured
Missing
Houses
Destroyed
Houses
Damaged
Indirectly Affected
Directly affected
Relocated
Evacuated
Losses $USD
Losses $Local
Education centers
Hospitals
Damages in crops Ha.
Lost Cattle
Damages in roads Mts
1933
4
100
1945
1
5
8
1964
2
36
1966
2
257
1323
6752
1970
2
120
1982
1
1986
1
1989
16
4
1
1
23
1
700
1990
16
176
60
7
16
1991
17
175
53
2
2
300
1
1992
38
265
60
14
23
18
32
351
1993
14
48
23
1852000
1994
37
683
61
2734
20
100000
150
1
2620
10
1995
40
949
5628
2
25
13
95
171
10
931
1996
19
65
136
1
540
303
11
1997
32
243
201
31
6367
17
1520
119
1998
57
335
927
68
267
230123
3706
1700
62
3809
600
1999
45
1797
360
6
80
5
1901
6000
2000
88
3429
10095
51
277644
120
2001
103
1814
10908
62
60
6810
2900
40
2
70
6
2002
144
2230
11195
2
496
458
154119
420
39
2
4563
5000
2003
89
478
269
373
230
781591
727
500
4
1
430
165
2004
63
121
395
3037
2
27851
122
100
15
1
1041
20
2005
98
109
174
2
2048
1238
354236
2549
6
200
2006
69
383
72
7
45
1359
94078
200
4
27
40
2007
263
276
93
1
13728
53
3102318
1802
300350
40000
165
8217
41
20
2008
121
203
149
843
1895
14198
198
87
59
1
2673
53
2009
468
207
163
712
421
1307602
617
73
1
1271
2010
559
2143
316
962
4716
429
929776
249
477
3623
110
2
19475
7
164221
2011
698
709
651
45
6518
585
738666
103
762
103
107
2
23133
1165
167116
2012
210
116
234
19
353
12271
179104
500
150
16
1
259
3
2013
363
105
118
4
3367
434
90491
7370
600
19
2
16675
46
2014
211
84
102
1254
54
162809
70
61
22433
2015
294
28
32
1372
191
199020
150
46
27979
50
2016
163
106
20
2221
1382
70895
82
4
18787
2017
275
38
411
51
8453
14914
352406
37
22
32
2
41175
2018
223
19
5
4
7666
467
289286
21906
18279
243
132
12664
110
2020
1
9
Uganda
Summary:
DataCards: 4847
Period:
1933 - 2020
Highest Mortality:
ACCIDENT: 9713 Deaths; 243 DataCards
LANDSLIDE: 2718 Deaths; 332 DataCards
EPIDEMIC: 2524 Deaths; 284 DataCards
Highest Housing Damages:
FLOOD: 65458 Houses; 1331 DataCards
EARTHQUAKE: 10458 Houses; 17 DataCards
FIRE: 8415 Houses; 270 DataCards
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