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Region: Kenya - [ken]          Profile:

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Kenya        

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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
CONFLICT912510
DROUGHT56968121541497045360
DROWNING951402
ELECTROCUTION10123
EPIDEMIC301443464263731
FIRE473200316441517917793482000
FLOOD7355631361122647770885207630397954552571497461200015703
FOREST FIRE41755000043790
LANDSLIDE451051462213222459186
LIGHTNING811271
MUDSLIDE671
PLAGUE1
RAINS481023622487
ROAD ACCIDENT11911800189212512
STORM254
STRUCTURAL COLLAPSE22641836140
SUBSIDENCE311
THUNDERSTORM192314311380000152
WINDSTORM30154101004151000003


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
BARINGO017356386359174342000216067
BOMET023140733
BUNGOMA0379851043211532
BUSIA04654541149424122952177050
EMBU055163441154831
GARISSA06464651100351011102000
HOMABAY077212767595294372962234395257
ISIOLO08413427555354285959177540
KAJIADO095965259017
KAKAMEGA1085109155247891591090
KEIYO-MARAKWET112855163150907900
KERICHO123952472141010
KIAMBU1318513479511879268202332942000000100
KILIFI149445449497035650512530
KIRINYAGA155844373631666784988
KISII168181463725313274600006
KISUMU17118127155412615280211005153272
KITUI1812546771092653443
KWALE19463762252443983
LAIKIPIA205339201020810000001100
LAMU211710517417224
MACHAKOS221451501633114804131
MAKUENI2312387193131099568220000060
MANDERA2448334723002000148521500546497462046152
MARSABIT2557622028202841124661110
MERU26104804322229841357000031380213
MIGORI27687730137447613107
MOMBASA28645830208236267352
MURANGA29108988679244553013504738
NAIROBI304574403692444846924114025000050
NAKURU31153232209100622794180000066007
NANDI324062544138
NAROK3371104234761936402100001956
NYAMIRA342514347240791
NYANDARUA35833125341136780781374105045360
NYERI3683482218103985051337212000000600
SAMBURU3717197189826
SIAYA386669282321001250403021510000005113
TAITA-TAVETA3952521812348120
TANA-RIVER409731339751884287984800006018
THARAKA-NITHI4125201836548
TRANS-NZOIA4250297414172003257225000002800
TURKANA436413013104391002356702481300000361451
UASIN-GISHU442827813610002
VIHIGA45242928
WAJIR463561880223400
WEST POKOT4773705960925752101
22


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
19974
2002327711
200397327215655700
200421000
200529111581401100
2006211725043543271694217756201000
2007231111624848
200890625132112094334529271556929746127282000
200943028296633041375372856761553500004045615
201030214815689034152888461362223418931085
201127736273113763119411300315260000030045362
201213724712829274391316374601
201312017213920316543510410650
2014221224111306149679
20155487239524171163807932023950001603
20165256726051453194181403087000
2017152185
2019823913795122510
Kenya

Tóm tắt:
Các thẻ dữ liệu: 3608
Thời gian:1997 - 2019

Tỷ lệ tử vong cao nhất:
ROAD ACCIDENT: 1800 Người chết; 1191 Các thẻ dữ liệu
FLOOD: 563 Người chết; 735 Các thẻ dữ liệu
EPIDEMIC: 443 Người chết; 301 Các thẻ dữ liệu
Thiệt hại lớn nhất về nhà ở:
FLOOD: 30355 Nhà ở; 735 Các thẻ dữ liệu
FIRE: 4594 Nhà ở; 473 Các thẻ dữ liệu
LANDSLIDE: 215 Nhà ở; 45 Các thẻ dữ liệu


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