Kenya county fact_sheets_dec2011

Table of Contents

Foreword by CRA Chairman i
Acknowledgements ii
Introduction iii
List of Abbreviations iv
Description of the Data and their Sources v
What does the Data say? vii
County Fact Sheets
1. Baringo County 1
2. Bomet County 2
3. Bungoma County 3
4. Busia County 4
5. Elgeyo-Marakwet County 5
6. Embu County 6
7. Garissa County 7
8. Homa Bay County 8
9. Isiolo County 9
10. Kajiado County 10
11. Kakamega County 11
12. Kericho County 12
13. Kiambu County 13
14. Kilifi County 14
15. Kirinyaga County 15
16. Kisii County 16
17. Kisumu County 17
18. Kitui County 18
19. Kwale County 19
20. Laikipia County 20
21. Lamu County 21
22. Machakos County 22
23. Makueni County 23
24. Mandera County 24
25. Marsabit County 25
26. Meru County 26
27. Migori County 27
28. Mombasa County 28
29. Murang’a County 29
30. Nairobi County 30
31. Nakuru County 31
32. Nandi County 32
33. Narok County 33

34. Nyamira County 34
35. Nyandarua County 35
36. Nyeri County 36
37. Samburu County 37
38. Siaya County 38
39. Taita Taveta County 39
40. Tana River County 40
41. Tharaka Nithi County 41
42. Trans Nzoia County 42
43. Turkana County 43
44. Uasin Gishu County 44
45. Vihiga County 45
46. Wajir County 46
47. West Pokot County 47

Foreword by CRA Chairman
The Commission on Revenue Allocation is a new institution created by the Constitution of Kenya.

The principal function of the Commission is to make recommendations on the basis of equitable sharing of
revenue raised nationally between the national government and the county governments and among the county
governments. It has other several functions enumerated in Article 216 of the Constitution.

Reliable data is the cornerstone of firm policy decisions. We take this opportunity to launch this first edition of the
County Facts Sheets. At a glance, the Fact Sheets provide important summary information of each county, such as,
population, health, education and infrastructure.

This document carries vital data on each of the 47 counties which should be useful to many stakeholders,
including those who are aspiring to join the counties either in elective or appointive offices. It will also be useful to
development partners, academic institutions and the civil servants in both national and county governments.

This document is part of a series of other publications which are being launched by our Commission. The objective
of the publications is to educate Kenyans on the role of the Commission, and the funding arrangements for Kenya’s
new system of devolved government.

Every effort has been made to ensure the facts in this document are accurate. We would however, request anyone
who spots a major error to point it out to us through our contacts indicated at the back cover of this booklet.

Micah Cheserem
Chairman, Commission on Revenue Allocation

i Kenya: County Fact Sheets

Acknowledgements

CRA acknowledges the contribution and support of several key partners in the preparation of this inaugural
version of the Kenya County Fact Sheets.

First, the Commission acknowledges the contribution of the Kenya National Bureau of Statistics (KNBS),
which is the official source of most data appearing in these Fact Sheets. Contributions from KNBS signal the
beginning of a long term partnership in the generation and dissemination of comprehensive county-level
data, and its application towards the formulation of sound policy decisions not only by the CRA, but also by
other government and non-governmental organizations.

Secondly, CRA acknowledges support from the World Bank’s Fiscal Decentralization Knowledge Program
(FDKP). Launched in November 2010 with financial assistance from the Australian Agency for International
Development (AusAid), FDKP is supporting the Kenya’s Government to develop and implement the public
finance provisions of the new Constitution. FDKP’s main objective is to share evidence-based knowledge with
Kenyan policy makers, consisting of international experiences with decentralization and also of data analysis
on Kenya.

To all our other partners, we also say a hearty THANK YOU, and we look forward to your continued support
and partnership.

Kenya: County Fact Sheets ii

Introduction
Immediately after the next General Elections, forty-seven County Governments will replace the Provincial
and Local Government administration systems, which were created at independence. However, most of the
data that is collected and compiled in Kenya today can be mapped to either districts or provinces, and very
little has been done to date to re-map these data to the county level.

The Kenya County Fact Sheets seek precisely to fill this void and to start fleshing out the demographic, socio-
economic and administrative contours of Kenya’s future counties.

Anticipated users of these Fact Sheets include:
a) Public sector organizations that are now accelerating their planning for the transition and formulation of
post-devolution policies;
b) Civil society organizations—the public, media, businesses—who need to engage knowledgeably with the
National and the County Governments; and,
c) Development partners who will need to refocus their strategies and programs to the new administrative
and service delivery environment.

Among other uses, the Fact Sheets will enable readers to (i) get a full picture of the main characteristics of
each of Kenya’s counties, and (ii) compare their performance across a wide range of indicators to the national
average, or to the situation in other counties. This knowledge, ideally will guide policy, from the targeting of
policies across space and interventions to laying the foundations of a county performance monitoring system.

The reader will find that the Fact Sheets reveal significant disparities across counties on many fronts—health
and education outcomes, funding per capita and access to infrastructure and to services. In highlighting
these disparities, the Fact Sheets might help to identify each county’s immediate-, medium- and longer-term
priorities for economic development and poverty reduction. They also constitute a useful baseline against
which progress can be measured, as Counties come into existence and start taking increasing responsibility
for service delivery at the local level.

Obviously, from the point of view of the CRA, this information will be a key input into our recommendations
to Parliament on a revenue sharing formula, which will need to be transparent, rule-based and grounded into
a solid assessment of county needs.

It is our hope that the Fact Sheets will inform public discourse and contribute to improved policy coordination
between National and County Governments, among county governments and with non-governmental stake
holders.

iii Kenya: County Fact Sheets

List of Abbreviations
CDF Constituency Development Fund
CRA Commission on Revenue Allocation
DDP District Development Plan
DRC District Roads Committee
FDKP Fiscal Decentralization Knowledge Program
GoK Government of Kenya
KIHBS Kenya Integrated Household Budget Survey
KNBS Kenya National Bureau of Statistics
KRB Kenya Roads Board
KURA Kenya Urban Roads Authority
LA Local Authority
LATF Local Authority Transfer Fund
MoH Ministry of Health
REPLF Rural Electrification Programme Levy Fund
RMLF Road Maintenance Levy Fund
SBP Single Business Permit
TFDG Task Force on Devolved Government
WB World Bank

Kenya: County Fact Sheets iv

Description of the Data and their Sources

DATA / VARIABLE DESCRIPTION AND SOURCE
Population The data on population and number of households are from the 2009 Kenya
Population and Housing Census Report published in August 2010, by the
Kenya National Bureau of Statistics (KNBS).

Surface area and density Each Fact Sheet contains a map showing population density variations within
each county, based on the number of districts in existence in December
2008. The information on density is based on the 2009 Census.

Poverty rate County poverty data have been computed based on the Kenya Integrated
Household Baseline Survey (KIHBS) district poverty estimates of 2005/06.
County poverty rates are derived simply by dividing the total number of
poor people in each county in 2005/06 by the total population in each
county.

Urban population This information is based on 2009 Census data and includes “core urban”
and “peri-urban” residents within towns having at least 2,000 inhabitants.

Health data Data on immunization and on diseases i.e. malaria, TB and HIV have been
obtained from the Division of Health Management Information Systems
(HMIS). The data includes routine information collected on a monthly and
annual basis from health facilities throughout the country. Health statistics
shown in these Fact Sheets have been computed as follows:
• Fully-immunized population under 1 year – This is the number of fully
immunized children below the age of 1 year as a proportion of the overall
population of children below the age of 1 year.
• Malaria (as % of all first outpatient visits) – This computation reflects the
malaria burden. It is based on “confirmed malaria cases” (not “clinical
malaria”) as a percentage of total first out-patient diseases (OPD)
attendances at health facilities.
• TB in every 10,000 people – This figure is the record of new cases of
tuberculosis (TB) detected in every 10,000 people.
• HIV-positive ante-natal care clients – This is the percentage of ante-natal
care (ANC) clients tested for HIV at designated testing sites, whose results
turn out to be positive.

Education data The proportion of population with primary and secondary education is
based on the 2009 Census.

Constituency These data are CDF actual allocations (2003/04 – 2008/09) and estimates
Development Fund (2009/10) for each of the 210 constituencies, which in turn are mapped
to county boundaries. The data have been obtained from the CDF Board
Website http://www.cdf.go.ke/ . Information on actual CDF spending or
audited financial data was not available.

Local Authority Transfer These data have been obtained from LATF Annual Report and Review of
Fund (LATF), Road Local Authority Financial Performance for the fiscal years 2007/08 and
Maintenance Levy Fund 2008/09. Taken together, LATF, SBP and Property taxes have constituted
(RMLF), Single Business the lion’s share of resources available to Kenya’s Local Authorities. While
the latter two might be taken as a rough indicator of the core of future

v Kenya: County Fact Sheets

DATA / VARIABLE DESCRIPTION AND SOURCE
Permit (SBP) and property county own-source revenue streams, LATF might be used as an indicator of
rates future needs of urban areas, and of the partial costs that could be faced by
counties in delivering services.

Rural Electrification Data come from the Rural Electrification Authority (REA) and relate to
Programme Levy Fund approved (not actual) spending on rural electrification programmes for the
(REPLF) period 2003/04 – 2008/09.

Access to improved water, These data are generated from the 2009 Census, and present the proportion
improved sanitation and of Kenya households with access. Definitions for access to improved water
electricity and sanitation are based on the Joint Monitoring Programme (JMP) for
Water Supply and Sanitation by the World Health Organization (WHO) and
UNICEF. Accordingly, improved water sources include well/borehole, piped
and rain-harvested water; while, improved sanitation includes connection
to a main sewer, septic tank and cesspool as well as ventilated improved pit
(VIP) latrine and covered pit latrine.

Road Network This data is generated from District Development Plans (DDP), and reflects
the proportion of Kenya’s classified road network that is paved, and in good
or fair maintenance condition.

Service coverage These estimates are generated based on the Kenya Integrated Household
Budget Survey (KIHBS). 2005/06.
• Delivered in a health centre – This is the proportion of children between
the ages of 0 – 60 months who were reported to have been born in a
health center i.e. hospital, clinic or maternity home.
• Qualified medical assistant during birth – This is the proportion of
children between the ages of 0 – 60 months whose births were assisted
by a qualified medical personnel i.e. a doctor, midwife or nurse.
• Had all vaccinations – This is the proportion of children between
the ages of 12 – 60 months who had had all necessary vaccinations,
specifically BCG, any dose of polio, any dose of DPT and measles.
• Adequate height for age – This is the proportion of children between
the ages of 6 – 60 months who were not below the adequate or
recommended height for their respective ages.
• Can read & write – This is the proportion of children between the ages
of 10 – 14 years who could read and write.
• Attending School, 15-18 years – This is the proportion of children
between the ages of 15 – 18 years who were attending school
(irrespective of the level) at the time of the survey.

Population and Following promulgation of the current Constitution, the number of
proportion of nationally constituencies is to increase from 210 to 290. Since the process of
registered voters in each distributing the 290 constituencies among the 47 counties has not been
constituency finalized, the constituency distribution shown in these Fact Sheets is based
on the current 210 constituencies. Constituency populations are based on
the 2009 Census, while county proportions of nationally registered voters is
based on Independent Electoral and Boundaries Commission (IEBC) records
as per the 2010 Constitutional Referendum.

Kenya: County Fact Sheets vi

What does the Data say?

These Fact Sheets testify to inter-county variations (thanks to agglomerations effects) and will generate
on several fronts, and it is important for the reader the bulk of future county own revenues.
to consider implications of these differences. For
example, the demographic data presented in the first Like urbanization, the distribution of poverty will
part of the Fact Sheets reveal extensive variations in have important implications for the design of fiscal
county populations and densities. Both population transfers to counties. Besides highlighting the wide
and density will determine the cost of delivering disparities in the distribution of poverty across Kenya,
services in the counties and therefore should drive the Fact Sheets point to a connection between county
the allocation of future transfers from the center to poverty rates and other variables such as access
the sub-national units. to social services, urbanization or infrastructure
development. To assess the performance of Kenya’s
The socio-economic profile of these populations and counties in meeting the service and development
hence, the social fabric of Kenya’s counties is also needs of their population, it will be vital to develop
heterogeneous. While Kenya is urbanizing rapidly -- systems for tracking the evolution of these key
much faster than the overall population growth rate indicators at the county level over time.
-- the Fact Sheets show that most counties are still
predominantly rural. Only five counties are more than A major limitation in preparing the Fact Sheets has
50% urban and majority of counties have at least 80% been the absence of current fiscal information—
of their populations residing in rural areas. (See figure revenues and expenditures—at sub national level. In
1). This is important from a political economy point particular it has been impossible to date to assess the
of view. In Kenya’s future County Assemblies, most geographic allocation of deconcentrated spending by
members will be representing rural constituencies: the the central government, and therefore to develop a
challenge will be to protect service delivery in urban complete and clear picture of financial flows at the
areas, which are poles of economic development local level. Still, the Local Authority data displayed

Figure 1: Only five counties are more than 50% urban
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Kajiado

Kakamega
Marsabit

Samburu
Kericho

Wajir
Elgeyo Marakwet
Nairobi

Nakuru

Siaya
Pokot
Mombasa

Kisumu
Machakos

Taita Taveta

Kisii

Bomet

Busia
Kiambu

Vihiga

Bungoma

Lamu

Murang'a
Embu

Turkana

Kitui
Migori

Laikipia

Garissa

Homa Bay

Narok
Isiolo

Nyandarua

Nandi
Nyeri

Nyamira

Meru
Kwale
Mandera

Makueni
Baringo
Tana River
Kilifi

Trans Nzoia

Kirinyaga

Tharaka Nithi
U. Gishu

Urban Rural
Data Source: KNBS

vii Kenya: County Fact Sheets

in the Fact Sheets provide some interesting insights Consistent with its mandate, the CRA will work
into, the types of urban service and infrastructure with county governments to identify and enhance
development costs that counties will be inheriting ,as own source revenues. This is essential to minimize
well as the own-revenue sources that counties will dependence by counties on transfers. The focus of
require to finance them. county governments should therefore be on wealth
creation, which will no doubt have multiplier effects
With specific reference to Local Authorities, within and across counties.
transfers from the central government previously
comprised of approximately 40% of local incomes, The data on education and health, water and
with property rates and business permits making up sanitation, access to electricity and the road
the biggest components of own-source revenues, network all tell the story of historical inequities and
especially for urban authorities. Rural authorities to some extent of the failure of the state to equalize
generally relied almost 50% on transfers, except in opportunities for all Kenyans (see figure 3). Kenyans
regions with touristic resources (e.g. game parks). have embraced devolution with such passion because
The important point here is that, depending on their they expect that it will help fill these service delivery
characteristics, counties will have varying capacity gaps. Again, tracking county performance over time
to generate revenue from their own resources (see on these indicators will provide a good measure of the
figure 2). With county functions increasing vastly extent to which the constitutional promise has been
over the next years, county own revenue sources are met. In addition identifying good performers among
likely to remain comparable to what LAs collected, Kenya’s counties will generate lessons for others to
the importance of transfers will be major. Designing emulate. Identifying good performance requires
them in a way that provides appropriate funding for credible county-level statistics, a major motivation
counties to meet their functions while taking into for these Fact Sheets.
account own-revenue potential is a key challenge.
Figure 2: Counties will have varying capacity to meet service delivery costs from their own revenue
100%

90%
Strong dependence on transfers Strong own revenue base
80%

70%

60%

50%

40%

30%

20%

10%

0%
Kirinyaga
Marakwet

Nyandarua

Murang'a
Kakamega

Kajiado

Embu
Lamu
Bungoma

Kwale

Mombasa

Samburu
Homa Bay

Vihiga
Nandi

Nakuru
Bomet

Tharaka

Isiolo
Narok
Nyamira

Mandera

Migori

Kisumu

Kilifi
Wajir

Makueni

Kitui

Kericho

Machakos
Tana River
Kisii
Turkana

Siaya

Meru

Marsabit

Nyeri

Kiambu
West Pokot
Garissa

Busia

Laikipia
Baringo

Taita Taveta

Nairobi
Trans Nzoia

Uasin Gishu

Transfers Own revenues
Data Source: LATF Annual Report for 2008/09

Kenya: County Fact Sheets viii

Figure 3: County pattern of infrastructure development – Roads, electricity & water

Source: World Bank (2011). Infrastructure for Shared Growth in Kenya – A Bumpy Ride to Prosperity, August 2011

ix Kenya: County Fact Sheets

As stated in the Foreword, data is the cornerstone These Fact Sheets are obviously incomplete. Perhaps
of firm policy decisions, and the CRA will work the most glaring omission is information on county
with all relevant agencies, particularly the Kenya contributions to Kenya’s Gross Domestic Product
National Bureau of Statistics (KNBS) to ensure that (GDP), which to date has not been disaggregated
under Kenya’s new system of devolved government, below the national level. Nonetheless, the CRA
decisions on the equitable sharing of revenue are has settled on the option of quickly releasing this
evidence-based, objective, trusted and predictable. work-in-progress version of the Fact Sheets, so
In collaboration with the KNBS and other agencies, that the information therein might contribute to
the CRA will also ensure that data definitions and the finalization of critical devolution-related policy
norms are standardized, and that data collection decisions and public debate. The Kenya County Fact
and reporting mechanisms are synchronized across Sheets will be updated periodically, as part of what
all counties. Especially, it will be the goal of the CRA must become a regular exercise of data collection
to establish consensus around baseline data. To this and performance tracking at the local level. The CRA
end, data that will be used by the CRA in formulating invites all readers to submit their suggestions for
its revenue-sharing recommendations will need to be future publications.
accurate, regularly updated, independent and free of
any local manipulation.

Kenya: County Fact Sheets x

BARINGO COUNTY
General Information (2009) Baringo Rank1 Kenya2
Population 555,561 33 821,491
Surface area (km²) 11,015 14 12,368
Density (people per km²) 50 33 66
Poverty rate, based on KIHBS (%) 57.4 32 47.2
Share of urban population (%) 11 43 29.9
Urban population in largest towns
- Kabarnet 25,346 78
- Eldama Ravine 17,872 93
- Marigat 6,661 144
- Maji Mazuri 4,265 179
- Mogotio 3,701 186
- Timboroa 3,150 197

Health and Education Outcomes Baringo Rankᵅ Kenyaᵇ
Fully-immunized pop <1yr (%, 2010/11) 32.7 45 64.0
Malaria (as % of all 1st outpatient visits) 11.8 8 27.7
TB in every 10,000 people (2009/10) 6 2 39.0
HIV+ ante-natal care clients (%, 2010) 3.0 16 5.9
Population with primary education (%) 67.7 27 66.6
Population with secondary education (%) 11.7 22 12.7
Funding Per Capita in Kshs. (2008/09) Baringo Rankᵅ Kenyaᵇ
Constituency Development Fund (CDF) 378 8 300
Local Authority Transfer Fund (LATF) 190 29 218
Single Business Permit revenues by LAs 26 28 48
Property tax revenues by LAs 6 32 70
Rural Electrification Programme Fund 147 7 88 Constituency Population and County Voter Statistics
Total 747 13 725 County’s share of na�onally 1.3%
registered voters in 2010
Access to Infrastructure Baringo Rankᵅ Kenyaᵇ
Improved water (% households 2009) 35.1 46 66.5
162
Improved sanitation (% households 2009) 57.0 37 87.8
Popula�on in 000’s (2009)

Electricity (% households 2009) 9.6 23 22.7 133
Paved roads (as % of total roads) 15.7 4 9.4
105
Good/fair roads (as % of total roads) 54.6 11 43.5 94

Service Coverage Baringo Rankᵅ Kenyaᵇ
61
Delivered in a health centre 32.9 21 37.5
Qualified medical assistant during birth 33.6 23 37.6
Had all vaccinations 76.5 24 75.0
Adequate height for age 51.8 36 59.8
Can read & write 67.3 27 66.4 Baringo Baringo Eldama Baringo Mogo�o
Central East Ravine North
Attending School, 15-18 years 87.4 5 70.9
ᵅ Except poverty rate, malaria TB & HIV, all rankings are in descending order i.e. highest to lowest. Source: KNBS.
ᵇ All entries in the ‘Kenya’ column show County averages.

Rural Electrification Allocations, Kshs Millions CDF Allocations, Kshs Millions
81 257
77
74
209 210 210

54
47 151

108

11 30

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10
Source: Rural Electrification Authority. Source: CDF Board Website. Source: Ministry of Medical Services.

Kenya: County Fact Sheets 1

BOMET COUNTY
General Information (2009) Bomet Rankᵅ Kenyaᵇ
Population 724,186 24 821,491
Surface area (km²) 2,471 39 12,368
Share of urban population (%) 18.3 24 29.9
- Bomet 83,729 29
- Sotik 8,366 132

Health and Education Outcomes Bomet Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Bomet Rankᵅ Kenyaᵇ
Access to Infrastructure Bomet Rankᵅ Kenyaᵇ
Improved water (% households 2009) 40.8 46 66.5 233

Paved roads (as % of total roads) 5.4 4 9.4 164
Good/fair roads (as % of total roads) 39.6 11 43.5 139

Service Coverage Bomet Rankᵅ Kenyaᵇ
Can read & write 74.7 18 66.4 Bomet So�k Chepalungu Konoin

99 98 257

209 210 210

57 151
48
108

29

30
0
2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


2 Kenya: County Fact Sheets

BUNGOMA COUNTY
General Information (2009) Bungoma Rankᵅ Kenyaᵇ
Population 1,630,934 3 821,491
Surface area (km²) 3,593 23 12,368
- Kimilili 94,927 23
- Bungoma 55,867 40
- Webuye 41,344 59
- Malakisi 17,083 98
- Chwele 7,206 141
- Kapsokwony 6,152 153
- Cheptais 3,899 183
- Tongaren 2,793 203

Health and Education Outcomes Bungoma Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Bungoma Rankᵅ Kenyaᵇ
Access to Infrastructure Bungoma Rankᵅ Kenyaᵇ

320
Electricity (% households 2009) 4.5 38 22.7
Paved roads (as % of total roads) 6.0 22 9.4 256 244
Good/fair roads (as % of total roads) 46.7 21 43.5 230 230

179 172
Service Coverage Bungoma Rankᵅ Kenyaᵇ
Can read & write 60.5 32 66.4 Kimilili Amagoro Sirisia Webuye Kanduyi Bumula Mt. Elgon

368
114 118
106 311 314
95
262
225
68
170

35
5

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10



BUSIA COUNTY
General Information (2009) Busia Rankᵅ Kenyaᵇ
Population 488,075 38 821,491
Surface area (km²) 1,134 43 12,368
- Busia 51,981 43
- Malaba 21,477 84
- Port Victoria 6,561 146
- Nambale 4,941 171
- Bumala 3,504 189

Health and Education Outcomes Busia Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Busia Rankᵅ Kenyaᵇ
Total 1,035 6 725 County’s share of na�onally 1.8%
Access to Infrastructure Busia Rankᵅ Kenyaᵇ

Good/fair roads (as % of total roads) 58.6 7 43.5
Service Coverage Busia Rankᵅ Kenyaᵇ 122

Delivered in a health centre 30.7 24 37.5 94
67
Can read & write 56.7 35 66.4 Nambale Butula Funyula Budalangi

100 287
88
235 238 237

174

46 126
41
32

33
4

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


ELGEYO MARAKWET COUNTY
General Information (2009) E. Marakwet Rankᵅ Kenyaᵇ
Population 369,998 40 821,491
Surface area (km²) 3,030 28 12,368
- Iten/Tambach 42,312 56
- Kapsowar 4,492 177
- Kapcherop 3,168 196

Health and Education Outcomes E. Marakwet Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) E. Marakwet Rankᵅ Kenyaᵇ
Access to Infrastructure E. Marakwet Rankᵅ Kenyaᵇ
Improved sanitation (% households 2009) 81.2 29 87.8 109 108

74
Service Coverage E. Marakwet Rankᵅ Kenyaᵇ
Can read & write 77.6 15 66.4 Keiyo South Marakwet West Marakwet East Keiyo North

122
198

161 162 162
77
65 116
63
86

27
24
1

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


EMBU COUNTY
General Information (2009) Embu Rankᵅ Kenyaᵇ
Population 516,212 36 821,491
Surface area (km²) 2,818 30 12,368
- Embu 60,673 37
- Runyenjes 19,548 88
- Siakago 2,694 204

Health and Education Outcomes Embu Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Embu Rankᵅ Kenyaᵇ
Property tax revenues by LAs - - 70
Access to Infrastructure Embu Rankᵅ Kenyaᵇ
Improved sanitation (% households 2009) 98.2 11 87.8 155

142
89
Service Coverage Embu Rankᵅ Kenyaᵇ
Can read & write 92.7 4 66.4 Manya�a Runyenjes Gachoka Siakago

90
246
228
74
186 187
62

136
37 104
28 27

24

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


GARISSA COUNTY
General Information (2009) Garissa Rankᵅ Kenyaᵇ
Population 623,060 29 821,491
Surface area (km²) 44,175 4 12,368
- Garissa 116,317 16
- Masalani 14,012 107
- Daadab 5,723 160

Health and Education Outcomes Garissa Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Garissa Rankᵅ Kenyaᵇ
Access to Infrastructure Garissa Rankᵅ Kenyaᵇ

245
Paved roads (as % of total roads) Unavailable
97.0 9.4 190
Service Coverage Garissa Rankᵅ Kenyaᵇ
Delivered in a health centre 25.1 34 37.5 95 93
Can read & write 52.4 37 66.4 Lagdera Dujis Faﬁ Ijara

73 207
64
169 168 170

121
94

22
15
24
0 0
2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


HOMA BAY COUNTY
General Information (2009) Homa Bay Rankᵅ Kenyaᵇ
Population 958,791 13 821,491
Surface area (km²) 2,586 32 12,368
- Homa Bay 58,936 38
- Awendo 17,992 92
- Mbita Point 11,989 109
- Sindo 6,362 149

Health and Education Outcomes Homa Bay Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Homa Bay Rankᵅ Kenyaᵇ
Access to Infrastructure Homa Bay Rankᵅ Kenyaᵇ

221
194
162
Service Coverage Homa Bay Rankᵅ Kenyaᵇ 103
Can read & write 73.3 20 66.4 KASIPUL RONGO RANGWE NDHIWA GWASI KARACHUONYO
KABONDO

39 367
38
297 298 304

219
22 22
18 167

36
2

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


ISIOLO COUNTY
General Information (2009) Isiolo Rankᵅ Kenyaᵇ
Population 143,294 46 821,491
Surface area (km²) 25,336 8 12,368
- Isiolo 45,989 52
- Merti 6,532 147
- Kinna 4,867 173
- Garbatulla 3,774 185

Health and Education Outcomes Isiolo Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Isiolo Rankᵅ Kenyaᵇ
Rural Electrification Programme Fund - - 88 Constituency Population and County Voter Statistics
Total 1,013 7 725 County’s share of na�onally 0.4%
Access to Infrastructure Isiolo Rankᵅ Kenyaᵇ
Improved sanitation (% households 2009) 55.7 38 87.8 100

Service Coverage Isiolo Rankᵅ Kenyaᵇ 43
Can read & write 59.8 33 66.4 Isiolo North Isiolo South

141
96

78 79 79

57
44

33
12

0 0 0 0
2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


KAJIADO COUNTY
General Information (2009) Kajiado Rankᵅ Kenyaᵇ
Population 687,312 26 821,491
Surface area (km²) 21,901 9 12,368
- Ngong 107,188 19
- Kitengela 58,167 39
- Ongata Rongai 40,178 62
- Kiserian 18,096 91
- Kajiado 14,860 104
- Loitokitok 11,064 113
- Namanga 9,066 126
- Isinya 8,670 128
- Sultan Hamud 6,636 145
- Bissil 5,376 165

Health and Education Outcomes Kajiado Rankᵅ Kenyaᵇ
Funding Per Capita in Kshs. (2008/09) Kajiado Rankᵅ Kenyaᵇ
Access to Infrastructure Kajiado Rankᵅ Kenyaᵇ
388

Service Coverage Kajiado Rankᵅ Kenyaᵇ 162
Delivered in a health centre 39.7 18 37.5 137
Can read & write 55.4 36 66.4 Kajiado North Kajiado Central Kajiado South

89 167

78
136 137 137

55 98

75
37

22 40
17

2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2003/04 2004/05 2005/06 2006/07 2007/08 2008/09 2009/10


Kenya county fact_sheets_dec2011

Kenya county fact_sheets_dec2011

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