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K A I S 2 0 0 7 C o l l a b o r a t i n g I n s t i t u t i o n sNational AIDS and STI Control Programme, Ministry of Health, Kenya (NASCOP)
National AIDS Control Council (NACC)Kenya National Bureau of Statistics (KNBS)National Public Health Laboratory Services (NPHLS)National Coordinating Agency for Population and Development (NCAPD)Kenya Medical Research Institute (KEMRI)U.S. Centers for Disease Control and Prevention, Atlanta/Kenya (CDC)U.S. Agency for International Development (USAID-Kenya)United Nations (UNAIDS and WHO)
Donor SupportKAIS 2007 was made possible through technical and financial support provided by the U.S.Presidents Emergency Plan for AIDS Relief (PEPFAR) through the U.S. Centers for Disease
Control and Prevention (CDC) and the United States Agency for International Development(USAID) and through technical and financial support provided by United Nations through UNAIDSand World Health Organization (WHO).
Suggested CitationNational AIDS and STI Control Programme, Ministry of Health, Kenya. July 2008. Kenya AIDS
Indicator Survey 2007: Preliminary Report. Nairobi, Kenya.
Contact InformationNational AIDS and STI Control Programme, Ministry of Health, Kenya. (NASCOP)P.O. Box: 9361 Code: 00202 Nairobi, KenyaTelephone: +254.(0)20.729.502, +254.(0)20.729.549 Fax: +254.(0)20.710.518
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E-mail: [email protected] Website: http://www.aidskenya.org
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K E N Y A A I D S I N D I C A T O R S U R V E Y
K A I S 2 0 0 7
P R E L I M I N A R Y R E P O R T
NATIONAL AIDS AND STI CONTROL PROGRAMME
Min i s t ry o f Hea l th , Kenya
J U L Y 2 0 0 8
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CONTENTS
L i s t o f A b b r e v i a t i o n s 2
I n t r o d u c t i o n
1.1 Background 3
1.2 Overview of KAIS 2007 4
1.3 Specific objectives 4
1.4 Timeline 5
D e s i g n & M e t h o d s
2.1 Geographic coverage and target population 6
2.2 Sampling frame and design 6
2.3 Data collection tools 7
2.4 Survey implementation
Training 7
Community sensitization 8
Fieldwork 8
Supervision 8
2.5 Laboratory logistics 8
2.6 Data processing and analysis 9
2.7 Return of test rsults 10
P r e l i m i n a r y R e s u l t s
3.1 Response rates 11
3.2 Prevalence of HIV
Overall estimates 12
Estimates stratified by key demographic characteristics 12
Prevalence of HSV-2 and co-infection with HIV 20
3.3 Coverage of HIV testing, care and treatment services
HIV testing 21
Reasons for not testing for HIV 21Knowledge of status among person with HIV 22
Coverage of cotrimoxazole 23
Coverage of antiretroviral therapy based on CD4 distribution 24
N e x t S t e p s
4.1 Dissemination of final results 26
4.2 National programmatic response 26
G l o s s a r y o f T e r m s 27
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L IST OF ABBREV IAT IONS
AIDS Acquired immunodeficiency syndrome
AIS AIDS indicator survey
ANC Antenatal care
ART Antiretroviral therapy
ARV Antiretroviral
CD4 CD4 T-lymphocyte
CSPro Census and Survey Processing System
CTX Cotrimoxazole
DASCO District AIDS/STI Coordinator
DBS Dried blood spot
GoK Government of Kenya
HIV Human immunodeficiency virus
HSV-2 Herpes simplex virus-2
IEC Information, education, and communication
KAIS Kenya AIDS Indicator Survey
KDHS Kenya Demographic and Health Survey
KNASP Kenya National HIV/AIDS Strategic Plan (KNASP)
NASSEP National Sample Survey and Evaluation Programme
PASCO Provincial AIDS/STI Coordinator
PMCT Prevention of mother to child transmission
SAS Statistical Analysis Software
STI Sexually transmitted infection
VCT Voluntary counselling and testing
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INTRODUCT ION
1.1 Background
HIV/AIDS remains a major challenge in Kenya. Substantial regional variations in HIV
infection, low levels of HIV testing, couple HIV discordance, and ongoing epidemics of
sexually transmitted infections (STI) are important challenges in the control and
management of the HIV epidemic in Kenya.
The first identified case of HIV in Kenya was recorded in 1986. Since then, the epidemic and
the governments mechanisms to monitor it have expanded greatly. While the highest rates
of infection were initially concentrated in marginalized and special risk groups, for more
than a decade Kenya has faced a mixed HIV/AIDS epidemic; new infections are occurring in
both the general population and vulnerable, high-risk groups. In 1999, the Government of
Kenya (GoK) declared the HIV epidemic a national disaster and established the National AIDS
Control Council (NACC) to coordinate the multisectoral response to HIV/AIDS.
Since 1990, Kenya has conducted yearly sentinel surveillance in pregnant women attending
ANC sites and patients attending STI clinics. Other sources of information on HIV/AIDS
include programmatic data from voluntary counselling and testing (VCT), blood donations,
antenatal clinics and tuberculosis clinics, and population-based data from the 2003 Kenya
Demographic and Health Survey (KDHS). In the past four years, Kenya has witnessed
considerable growth in funding of its HIV/AIDS national program from major global
initiatives. The growth and diversification in HIV/AIDS services in Kenya call for an
expansion of HIV and STI surveillance systems. UNAIDS and WHO recommend that arepresentative sample of the general population be included in HIV surveillance systems in
countries with generalized epidemics to provide a) reliable measures of HIV prevalence for
women and men and b) information to calibrate the data resulting from the routine HIV
surveillance systems. The HIV epidemic is complex and dynamic, and a number of factors
can impact how prevalence rises and falls, including new infections, mortality due to HIV-
related illness, and availability of care and treatment.
KE Y F E A T U R E S O F K A I S 2 0 0 7 Provides nationally-representative information about the HIV/AIDS epidemic
Almost 18,000 individuals from nearly 10,000 households participated
Includes older adults ages 50-64 for the first time in a national HIV survey
Prevalence of HIV, HSV-2 and syphilis; CD4 count in those with HIV
Reports coverage of HIV services including HIV testing and HIV care and treatment
Allows comparison of 2007 HIV prevalence with KDHS 2003 estimates
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1.2 Overv iew of KAIS 2007
The AIDS Indicator Survey (AIS) was developed to provide countries with a standardized tool
for monitoring nationally-representative HIV/AIDS indicators in the general population. The
KAIS 2007 was the first AIS for Kenya and provides the most up-to-date information on HIV
and other sexually transmitted infections. The methods and findings build upon previouspopulation-based HIV estimates from KDHS 2003.
KAIS data collection included questionnaires, including a household survey and an individual
survey; biological testing based on venous blood samples; and return of test results to
respondents. Incorporating blood testing for HIV and other sexually transmitted infections
in the KAIS makes it possible to link socio-demographic, behavioural characteristics and
household-level indicators to biological outcomes. For the first time, KAIS provides
population-based information about CD4 cell counts among people with HIV. This
information helps to determine HIV/AIDS care and treatment needs. KAIS also partnered
with health facilities and health workers throughout the country to return results to KAISparticipants approximately 6 weeks after blood specimen collection. Participants were
counselled on the meaning of their test results and referred appropriately for follow-up
testing and care at local facilities.
Data from KAIS will be used to evaluate the national response to HIV/AIDS. It will also inform
HIV prevention and treatment efforts coordinated through the GoK.
1.3 Speci f ic Object ives
Determine the magnitude and distribution of HIV, HSV-2, syphilis and in adults ages
15-64
Estimate HIV incidence through laboratory testing
Determine access to and unmet need for HIV/AIDS services
Describe socio-demographic and behavioural risk factors related to HIV and other STI
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Marc hJune '07 July Aug FebJan '08Sept Oc t Nov Dec
Kenya AIDS Indicator Survey 2007 - TimeKAIS study protocol
approved by relevant
scientific and ethical
review boards
Training of interviewers, field
lab staff, field supervisors and
core lab staff
Launch of
KAIS data
collection
Successful completion of
data collection (interview
and blood draw)
Begin returning test
results to KAIS
participants
Complete data en
data cleaning, me
weighting
Figure 1. Timeline of KAIS 2007 activities, June 2007-July 2008.
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DES IGN & METHODS
2.1 Geographic coverage and target populat ion
The survey was conducted on a representative sample of households selected from the all 8provinces and covered both urban and rural areas. Sampled, occupied households with a
consenting head of household of were eligible for the household questionnaire. Females and
males ages 15 to 64 who were usual residents of sampled residential households or visitors
present in the sampled households on the night before the survey were eligible to
participate in the study provided they gave informed consent. Potential participants could
consent to the interview and the blood draw or to the interview alone.
2.2 Sampl ing f rame and des ign
The sampling frame for KAIS was the National Sample Survey and Evaluation Programme IV
(NASSEP IV) created and maintained by Kenya National Bureau of Statistics (KNBS). The
NASSEP IV frame was developed in 2002 and based on the 1999 Kenya Household and
Population Census. The frame has 1800 clusters, comprised of 1260 rural and 540 urban
clusters; of these, 294 rural and 141 urban clusters were sampled for KAIS. The sample
enables calculation of estimates of key indicators for each of the eight provinces, as well as
for urban and rural areas.
The overall design for KAIS 2007 was a stratified, two-stage cluster sample design for
comparability to the KDHS 2003. The first stage involved selecting clusters from NASSEP IV,and the second stage involved the selection of households for KAIS with equal probability in
the urban-rural strata within the districts. A sample of 415 clusters and 10,375 households
were systematically selected for KAIS in order to achieve the power necessary to make the
estimates at the level of estimation desired by KAIS partners. A uniform sample of 25
households per cluster was selected using an equal probability systematic sampling method.
The sample size took in to consideration the level of non-response in the 2003 Kenya DHS.
Table 1 indicates the sample distribution for KAIS.
Table 1: Distribution of sampled clusters and households by province, KAIS 2007
Clusters Households
Province Rural Urban Total Rural Urban Total
Nairobi 0 58 58 0 1,450 1,450
Central 48 7 55 1,200 175 1,375
Coast 24 22 46 600 550 1,150
Eastern 50 5 55 1,250 125 1,375
North Eastern 23 5 28 575 125 700
Nyanza 54 7 61 1,350 175 1,525
Rift Valley 51 12 63 1,275 300 1,575
Western 44 5 49 1,100 125 1,225Total 294 121 415 7,350 3,025 10,375
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2.3 Data col lect ion tools
HOUSEHOLD QUESTIONNAIRE
Household census
Parental survivorship
Household characteristics
Mosquito net use
Support for sick persons
INDIVIDUAL QUESTIONNAIRE
Socio-demographic characteristics
Reproduction, fertility, and familyplanning
Marriage and sexual partnerships
HIV/STI knowledge, attitude, behaviours
Uptake of HIV prevention, care andtreatment services
BLOOD DRAW
Venous blood:HIV, HSV-2, syphilis testing;CD4 for those with HIV
Dried blood spot:HIV testing only
RETURN OF RESULTS FORM
Specific test results retrieved
Individual or couple counselling
Minors with or without parents
Referrals provided
2.4 Survey implementat ion
Tra in ing Over 200 skilled interviewers, laboratorytechnicians and scientists, and field supervisors were
recruited in July 2007 and trained for 2 weeks. Thetraining involved both lecture-based and interactive,
with practical applications, mock interviews, and small
group discussions.
INTERVIEWER TRAINING
Interview technique
Interview informed consent
Explaining KAIS diseases
Administering questionnaires
Interviewers were trained in interview techniques,
identifying eligible households and individuals, obtaining
LAB TECHNICIAN TRAINING
Blood draw informed consent
Universal precautions Sample collection
Sample processing
Return of results vouchers
informed consent, educating participants about HIV,
HSV-2 and syphilis, and administering the household
and individual questionnaires. Field laboratory
technicians and scientists were trained in preparingrespondents for the blood draw, and specimen
collection, processing, storage and transportation to
the central laboratory. Trainers emphasized ways to
minimize risks in handling biological specimens. Lab
technicians were also trained to issue the return of results vouchers.
In September 2007, the Ministry of Health/NASCOP conducted intensive trainings for
counsellors/health workers involved in the return of test results. All counsellors/health
workers, regardless of their health care experience, attended. Nearly 200 counsellors were
trained for 1 week in educating participants about HIV, HSV-2, syphilis, and CD4 counts,
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counselling them on their results and referring them and their partners for follow-up testing
and care.
Communi ty sens i t i za t ion The launch of KAIS was launched on August 1, 2007marked the start of the national television, radio and print media campaign to educate
Kenyans about KAIS and the importance of broad participation. Mobilization efforts soon
shifted to interpersonal communications at the village level to raise awareness of KAIS as a
major GoK initiative.
MOBILIZATION AT THE COMMUNITY LEVEL WAS CRITICAL FOR ENSURING HIGHSURVEY PARTICIPATION RATES AND THUS A REPRESENTATIVE SURVEY SAMPLE.
Fie ldwork A total of 29 field teams each consisting of 6 primary data collectors(interviewers and laboratory technicians), 1 supervisor and 1 driver throughout Kenya
conducted fieldwork over a period of 4 months from August to December 2007. Teams were
given local language questionnaires in addition to instruments in Kiswahili and English to
accommodate respondents not conversant in local languages. Completed questionnaires for
each cluster were packed and delivered to KNBS headquarters through secured courier
services for data processing.
The household questionnaire was first administered to the household heads or the most
knowledgeable members followed by interviews and blood draws among all eligible and
consenting individuals in participating households. Participants received an informational
brochure in two languages on HIV, HSV-2 and syphilis, the association between the diseases
and the value of knowing ones HIV status.
Superv is ion Data collection teams were constantly supervised by teams ofcoordinators representing KAIS partner agencies. These teams travelled the country to visit
with teams and deliver survey supplies, perform quality checks on questionnaires, assess
mobilization efforts and help address challenges to data collection. Supervision reports were
circulated among KAIS leadership and key issues were attended to immediately.
2.5 Laboratory logis t ics
Specimens were collected by the field laboratory teams working in different parts of the
country and shipped by secured courier services to the National Public Health Laboratory
(NPHL), three times a week. Each week, more than 600 samples from across the eight
provinces were received at the NPHL, logged into an electronic laboratory information
management database and then screened for HIV, HSV-2 and syphilis. All samples reading
positive for these infections as well as select negative samples were retested for qualityassurance at the KEMRI/CDC laboratory (Kenya Medical Research Institute/U.S. Centers for
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Disease Control and Prevention, Nairobi, Kenya). NPHL quantified CD4 cell counts for all HIV
seropositive serum samples. Results between the two laboratories were cross-checked and
verified to ensure accurate results were dispatched to the field to share with participants. To
ensure samples collected in remote areas would be delivered to NPHL in a timely fashion,
KAIS partnered with a local airline to fly blood samples from the North Eastern province tolaboratory headquarters in Nairobi. Overall, 98.9 percent of whole blood samples and 99.8
percent of serum samples were of good quality for testing. Only 1.1 percent of whole blood
samples (used for CD4 counts) and 0.2 percent of serum samples (used for determining HIV,
HSV-2 and syphilis status) were rejected for testing.
2.6 Data processing and analys is
Data processing included a number of important steps to prepare the raw KAIS data for
analysis. The initial steps in data processing included: editing questionnaires, both in the
field and at KNBS headquarters, prior to data entry, and complete double-data entry of all
questionnaire responses to minimize error. Data were entered using Census and Survey
Processing System (CSPro) version 3.3. Once all survey responses were transferred to
electronic format, data cleaning began. The first step was to ensure 100 percent verification
between the two data entry databases, using paper questionnaires to resolve any
discrepancies. Next, a series of consistency and range checks were used to identify any
unreasonable responses and to verify that responses adhered to skip patterns. Data cleaning
programs were written in Stata version 8.0 and corrections were entered directly in CSPro.
As the survey data were cleaned at KNBS, a concurrent process of cleaning the raw
laboratory data by laboratory information management specialists was ongoing. The final
cleaned, combined questionnaire database was merged with the laboratory results database
using unique barcodes and study identification numbers to ensure the greatest accuracy.
All results presented in the report are based on weighted data. The weights were used to
correct for unequal probability of selection, to produce results that are representative of the
larger population from which the sample was drawn, and to adjust for nonresponse. The
final weights were derived from the design weights of NASSEP IV frame and adjusted for
non-response. Three weights were calculated for KAIS analysis: a household weight, an
individual survey weight, and a blood draw weight.
Preliminary analyses were conducted using SAS software version 9.0. SUDAAN and SAS have
procedures to account for the KAIS multi-stage stratified sampling design, and were used to
produce reliable standard errors and confidence intervals. Some data analyses of interest
were verified in Stata version 8.2, to ensure reproducibility across software programs.
Limited preliminary analyses covered response rates, overall prevalence estimates for HIV,
syphilis and HSV-2 (genital herpes); CD4 distribution; HIV testing and correct knowledge of
HIV status; and antiretroviral therapy and cotrimoxazole usage.
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2.7 Return of test resul ts Returning test results to the field involved careful coordination between NPHL, NASCOP
officers across Kenya (PASCOs and DASCOs), local health facilities and individual
counsellors. At the time of specimen collection, participants were given vouchers that listed
facilities in the area where they could receive their test results six weeks after the blood
draw. Retrieving results was not required for participation in KAIS, but interviewers and lab
technicians were trained to educate participants on the benefits of knowing ones disease
status. Results counsellors shared and explained results and also referred respondents who
required follow up to testing and treatment facilities. Tools were developed to capture the
number of participants who came for results and counselling.
Kenya
HIV/AIDS
IndicatorSurvey
KAISKAIS 2007
Thank you for participating in the 2007 Kenya HIV/AIDS indicator survey
Your results will be ready for collection at:
1.
2.
Between: &
Today's Date
Cluster No.
Affix Matching
KAIS Barcode
Here
123456
Male Female
To ensure confidentiality of your test results, please keep this card in a safeplace. You are encouraged to come with your partner to receive your test results.
Weekdays: 9am 5pm | Saturdays: 9am 1pm | Sundays: 2pm 5pmTime:
Kenya
HIV/AIDS
IndicatorSurvey
KAISKAIS 2007
Thank you for participating in the 2007 Kenya HIV/AIDS indicator survey
Your results will be ready for collection at:
1.
2.
Between: &
Today's DateToday's Date
Cluster No.Cluster No.
Affix Matching
KAIS Barcode
Here
123456
Male FemaleMale Female
To ensure confidentiality of your test results, please keep this card in a safeplace. You are encouraged to come with your partner to receive your test results.
To ensure confidentiality of your test results, please keep this card in a safeplace. You are encouraged to come with your partner to receive your test results.
Weekdays: 9am 5pm | Saturdays: 9am 1pm | Sundays: 2pm 5pmTime:
Figure 2. Examples of mobilization and educational materials and the return of results voucherutilized during KAIS 2007.
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PREL IM INARY RESULTS
3.1 Response Rates
Overall, participation rates in KAIS 2007 were high. Household response rates were
calculated as the number households consenting to the household interview out of the total
households occupied. Vacant, destroyed, or missing households were excluded from the
study. Individual interview response rates were calculated as the number of completed
interviews out of those eligible for the survey based on the household census. Only those
consenting to an interview could participate in the blood draw component of KAIS. Blood
draw coverage was calculated as the number of blood draws completed out of all eligible
individuals based on the household schedule. Blood draw response rates indicate the
number of successful blood draws out of those completing individual interview.
Blood draw coverage increased from 2003, by 7 percentage points among males andfemales, by 4 percent points in rural areas and by 12 percentage points in urban areas. Thehousehold and individual response rates in KAIS are similar to KDHS 2003.
Table 2: KAIS response rates by residence, Kenya, 2007.
Urban Rural Total
Eligible (occupied) households 2,198 7,107 10,025
Eligible individuals 5,367 14,483 19,840
Household interview response rate 95% 97% 97%Individual interview response rate 86% 92% 91%
Blood draw covera e out of eli ibles 74% 83% 80%
Blood draw response rate (out of interviewees) 86% 90% 88%
Participation in the rural areas was higher than in urban areas by an average of 5 percentage
points. This was in part due to a greater proportion of urban residents being absent during
the survey. This pattern is similar to what was observed in KDHS 2003.
Table 3: KAIS response rates by sex, Kenya, 2007.
Females Males Total
Eligible individuals 10,957 8,883 19,840
Individual interview response rate 94% 87% 91%
Blood draw coverage (out of eligibles) 83% 77% 80%
Blood draw response rate (out of interviewees) 88% 88% 88%
Participation among females was higher than among males by 6-7 percentage points. This
was in part due to a greater proportion of males being absent during the survey. This
pattern is similar to what was observed in KDHS 2003.
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3.2 Preva lence of HIV
Prevalence is a measure of the total burden of disease, including new and old infections.
Prevalence can increase and decrease based on several factors including rate of new
infections, the mortality from a disease and the length of time people are able to survive a
disease based on available treatments. Results from KAIS indicate that 7.4 percent of Kenyan
adults age 15-64 are infected with HIV, the virus that causes AIDS.
According to the survey, more than 1.4 million Kenyans are living with HIV/AIDS.In 2003, KDHS estimated a prevalence of 6.7 percent among 15-49 year olds. For the same
age group, KAIS estimates that 7.8 percent are infected.
Sex A higher proportion of women age 15-64 (8.7 percent) than men (5.6 percent) are
infected with HIV according to KAIS 2007. This pattern is similar to what was observed in2003. This means that 3 out of 5 HIV-infected Kenyans are female.
The HIV prevalence rates among both women and men are higher than the rates observed in
2003. There is overlap in 95 percent confidence intervals (95% CI) for both women and men
as indicated below in Figure 3; the overlap is less striking among men, suggesting the
higher rate among men in 2007 may indicate a real increase since 2003. Additionally, in
2003, there were 1.9 infections among women for every one infection among men. The
current ratio according to KAIS is 1.6. (Note: Confidence intervals and other terms can be found in
the glossary on page 27.)
4.6
(3.6, 5.5)
8.7
(7.4, 9.9)
5.8(5.1, 6.5)
9.2
(8.3, 10.1)
Female Male
HIVPrevalence%
2003 KDHS
2007 KAIS
Figure 3. HIV prevalence among females and males age 15-49 in KAIS 2007 and KDHS2003 with 95% CI.
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Age and sex For both females and males, HIV is occurring in all age groups. Thereare, however, some differences in prevalence across the life span. Among youth age 15-24,
women are 4 times more likely to be infected than men (6.1 percent compared to 1.5
percent). A higher proportion of Kenyans ages 30-34 are currently infected with HIV than in
any other age category. The decline in prevalence among women after age 34, and amongmen after age 44 could represent a decline in new infections in older age groups or an
increase in HIV-related deaths in these age groups. The burden of infections is statistically
higher among females than males until age 35 after which the ratio of male to female
infections starts to approach 1 to 1.
KAIS interviewed and tested women age 50-64 and men age 55-64 who have not been
included in past HIV serosurveys. This addition gives us new insight into the epidemic
among older Kenyan adults who have previously been considered low risk. Prevalence
among Kenyans age 50 and older is greater than among the youngest Kenyans; this may
reflect cumulative lifetime exposure to HIV.
0
4
8
12
16
20
15
-19
20
-24
25
-29
30
-34
35
-39
40
-44
45
-49
50
-54
55
-59
60
-64
Age (years)
HIVPrevalence(%)
Females
Males
Total
Figure 4. HIV prevalence and 95% CI among participants 15-64 years old by sex and 5-year age categories, KAIS 2007.
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Geography The distribution of HIV infections varies greatly across Kenya. Prevalence
remains the highest in Nyanza at 15.3 percent, more than double the national prevalence
estimate. Other provinces with rates similar to or higher than the national level are Nairobi
(9.0 percent), Coast (7.9 percent), and Rift Valley (7.0 percent). Prevalence in Eastern is 4.7
percent and in Central, 3.8 percent of the adult population is infected. North Easternprovince has the lowest adult HIV prevalence at 1 percent.
Kenya: 7.4%
Figure 5. HIV prevalence inKenya by province, KAIS 2007.
Because of different population sizes across provinces, prevalence estimates may not
provide the complete picture of HIV burden in a province. Though the proportion of infectedadults in the Coast and Nairobi is higher than the proportion in Rift Valley, the number of
infected adults in Rift Valley (estimated 322,000) was greater than in Coast (estimated
135,000) or Nairobi (estimated 176,000). Together, Nyanza and Rift Valley are home to halfof all HIV-infected adults.The provincial estimates for HIV prevalence among 15-49 year olds in 2007 were similar
(within 1 percent) to estimates from KDHS 2003 for Nairobi, Central, Eastern and Western
Provinces. In 2003, no cases of HIV were detected in Northeastern province; in 2007 1.3
percent of participants (n=7) tested positive for HIV, though the figures are too small to
draw conclusions. The Coast experienced a striking increase in the proportion of adultsliving with HIV; the proportion of HIV infected adults was 2.3 percentage points higher in
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2007 than in 2003, representing a 40 percent increase in HIV prevalence. Similarly in Rift
Valley, the increase in HIV prevalence of 2.1 percentage points represents a 40 percent
increase since 2003.
4.0
5.84.9
9.9
15.1
5.3 4.9
6.7
0.0
4.9
1.3
8.1
4.2
9.3
15.4
7.4
5.7
7.8
0.0
4.0
8.0
12.0
16.0
Nairobi Central Coast Eastern NE Nyanza RV Western TOTAL
HIVPrevalence(%)
20.0
2003 KDHS
2007 KAIS
Figure 6. HIV prevalence among participants 15-49 years old in KAIS 2007 and KDHS2003 by province.
Below in Figure 7, HIV prevalence estimates for Coast and Rift Valley Provinces are stratified
by sex to better understand the increases since 2003. Point estimates for HIV prevalence
increased from 2003 to 2007 in both provinces among women and men though the
increases were not statistically significant at the p
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Res idence About three quarters of Kenyans live in rural areas of the country. Among
those ages 15-64, 7 percent are infected with HIV. In urban areas, the prevalence is 9
percent.
Infected
7%
Infected
9%
About 400,000 urbanadults infected with HIV -
30% of all HIV infections
About 1 million ruraladults infected with HIV
70% of all HIV infections
MORE THAN 1.4 MILLION ADULTS ARE LIVING WITH HIV/AIDS.
7 out of 10 HIV infected adults are rural residents.
Though the prevalence in rural areas is lower in urban areas, the greatestburden of disease is in rural areas since most Ken ans live in rural areas.
Women age 15-64 are more likely to be infected than men in both urban and rural areas,with 10.8 percent of urban females compared to 6.2 percent of urban males, and 8.2
percent of rural women infected compared to 5.5 percent of rural men.
Below in Figure 8, HIV prevalence rates among women and men age 15-49 are presented
based on data from KDHS 2003 and KAIS 2007. There appears to be a trend of declining HIV
prevalence among urban residents, though the declines are not statistically significant.
In contract, rural HIV prevalence appears to be on the rise among women and men.
The increase in HIV prevalence among rural males from 2003 to 2007 is statisticallysignificant (p-value
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7.5
10.07.5
12.3
5.6
3.6
8.7
5.7
9.2
6.4
11.1
7.4
0
4
8
12
16
Female Male Total Female Male Total
HIVPrevalence(%) 2003 KDHS
2007 KAIS
7.5
10.07.5
12.3
5.6
3.6
8.7
5.7
9.2
6.4
11.1
7.4
0
4
8
12
16
Female Male Total Female Male Total
HIVPrevalence(%) 2003 KDHS
2007 KAIS
Urban Rural
Figure 8. HIV prevalence among participants 15-49 years old in KAIS 2007 and KDHS2003 by sex and residence, with 95% CI.
Educat ion Women age 15-64 with higher educational levels have significantly lower
HIV prevalence than those with less education. Those with primary education have a
prevalence of 10 percent compared to 7 percent with secondary education and 4 percent
with tertiary education. Prevalence among women who have never attended school is 7
percent. For men, there is also a decrease in HIV prevalence with higher levels of education
but the differences are less pronounced and not statistically significant.
Mar i ta l s ta tus Marital status can be an important risk factor when exploring patterns
of HIV transmission in a population. In Kenya, nearly 2 out of 3 Kenyans ages 15-64 are in a
union (married or cohabitating). Two findings from the KAIS 2007 stand out (Table x below).
Kenyans in polygynous unions (one man, more than one woman) are more likely to be HIV
infected (11 percent) than those in monogamous unions (7 percent). Also, women who have
ever been widowed and women who are currently divorced or separated have high HIV
prevalence at 17-21 percent. This is especially relevant since the proportion of Kenyans
(both women and men) currently widowed has more than tripled since 2003. One hypothesis
is that the deceased partners of women respondents are likely to have died from HIV-relatedillness after years of infection, since HIV is the leading adult cause of death among Kenyans
age 15-49. These women were potentially exposed to HIV for several years before their
partners died. The pattern is the same among men, though the number of reporting they
were currently widowed was too small to draw conclusions (n
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Table 4. HIV prevalence among Kenyans age 15-64 who were tested, by sex andmarital status, KAIS 2007.
Female Male Total
Marital Status % HIV infected % HIV infected % HIV infected
Currently in union 7.8 7.4 7.6Monogamous 7.1 7.0 7.1
Polygynous 11.2 11.4 11.3
Currently not in union 10.3 3.2 7.1
Currently widowed 20.7 19.3** 20.5
Currently divorced/separated
17.1 6.4* 13.7
Never in union 4.7 2.2 3.3
Ever had sex 7.3 2.8 4.6
Never had sex 1.8** 1.1** 1.5**
Ever widowed 21.2 NA*** 21.0
*Married or living with partner ** n
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Table 5. HIV prevalence women age 15-49, by reported pregnancy status and recentmotherhood. Kenya 2007
*Not exclusive from other categories ** n
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Preva lence of HSV-2 and co- in fec t ion wi th H IV HSV-2 is a virus that
causes genital herpes. As with HIV, not everyone with HSV-2 has symptoms. There is no
cure for HSV-2; infection is life-long but usually not life-threatening. The presence of
genital herpes in a HIV-uninfected person increases his or her chances of acquiring HIV. In a
HIV-infected person, genital herpes increases his or her chances of transmitting HIV.
Overall, one-third (35 percent) of Kenyans age 15-64 are infected with HSV-2. Women are
more likely to be infected compared to men (42 and 26 percent, respectively). By age 25, 1
in 5 women are infected with HSV-2; half of all individuals age 35-64 are infected.
Among those with HSV-2, HIV prevalence is 17 percent.Among those who do not have HSV-2, HIV prevalence is 2 percent.
Table 6. HSV-2 prevalence among women and men age 15-64 who were tested
TOTAL FEMALES MALES
% HSV-2 infected % HSV-2 infected % HSV-2 infected
Total 35.4 42.3 26.1
15-24 15.3 21.6 7.1
15-19 9.0 13.0 4.5
20-24 21.4 29.1 10.2
25-29 33.1 41.3 19.9
30-34 42.9 51.6 30.1
35-39 48.7 56.9 36.7
40-44 54.2 59.8 46.7
45-49 51.9 56.2 46.0
50-54 48.3 53.6 41.5
55-59 48.8 57.1 39.8
60-64 43.1 49.8 38.2
Urban 40.1 47.4 29.9
Rural 34.2 41.0 25.2
Nairobi 37.8 43.4 29.2
Central 28.0 34.0 19.9
Coast 39.7 49.9 29.3
Eastern 28.6 36.6 18.4
North Eastern 6.4 6.3 6.7
Nyanza 49.7 58.2 37.9
Rift Valley 32.9 39.3 24.7
Western 38.3 44.2 30.4
HIV-infected 81.0 84.2 74.5HIV-uninfected 31.7 38.3 23.2
32% OF ADULTS WHO DO NOT HAVE HIV HAVE GENITAL HERPESAND ARE AT INCREASED RISK OF ACQUIRING HIV
81% OF ADULTS WITH HIV ALSO HAVE GENITAL HERPES
AND ARE AT INCREASED RISK OF TRANSMITTING HIV.
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3.3 Coverage of HIV Test ing, Care and Treatment Serv ices
HIV tes t ing HIV testing uptake has tripled among women age 15-49 since 2003and nearly doubled among men.
13 14 14
43
25
36
0
10
20
30
40
50
Females Males TotalEverTestedan
dReceivedResutls(%)
2003 KDHS
2007 KAIS
Figure 9. HIV testing uptake among Kenyans ages 15-49, by sex. KDHS 2003 and KAIS2007.
Overall, 36 percent of Kenyans adults ages 15-64 have tested at least once for HIV and
received results. Nearly two-thirds of Kenyans report never having been tested for HIV, and
are therefore unaware of their status and may not access appropriate services for
prevention, care and treatment of HIV. Testing is particularly low among older Kenyans age
50-64; among this cohort, only 17.5 percent have tested for HIV. The disparity between
urban and rural areas is substantial: 50 percent of urban residents have tested for HIV at
least once compared to only 30 percent of rural residents. The increase in HIV testing
among women is in part due to PMCT services and testing in antenatal clinics. Nearly one-
third of women who reported having ever tested said they were tested at an antenatal clinic.
Reasons for never tes t ing for H IV Among those who have never been
tested for HIV, the most common reason for not testing among both sexes was low
perception of risk (61 percent). This underscores the importance of ongoing campaigns to
improve knowledge about risk factors for HIV transmission and attitudes toward testing.
Sixteen percent have never tested because they did not want to know their test results or
were afraid others would know the results. A small but notable proportion of respondents
(14 percent) said they were unaware that there was a test for HIV or did not know how to
access testing. Five percent cited distance to the nearest known testing site as the major
barrier, which may suggest that mobile testing services should be given more consideration.
The cost of the test or the lack of access to or availability of treatment were veryinfrequently cited as barriers to testing (
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Knowledge of s ta tus among persons wi th H IV Testing for HIV is an
important step toward knowing ones status but does not guarantee it. Repeated exposure
to HIV through unprotected sex or other modes of transmission means that repeat testing
for HIV is needed for accurate knowledge of ones current HIV status.
Among laboratory-confirmed HIV-infected individuals in KAIS, 57 percent reported that they
had never tested for HIV. Another 26 percent reported themselves as negative based on
their last HIV test, but tested positive for HIV. It is possible that some of these individuals
knew their true HIV-infected status but were not prepared to share the result with the
interviewer. Together, these two groups (never tested for HIV, and tested but misreported
as HIV-uninfected) did not have correct knowledge of their HIV status and comprised about
80 percent of all HIV-infected participants.
Figure 10. Knowledge of HIV status among HIV-infected individuals age 15-64. Kenya
2007.
2% missing
AS MANY AS 4 OUT OF 5HIV-INFECTED PERSONS DO
NOT KNOW THEIR STATUS.
26% reported
themselvesuninfected but
tested positive57% never
tested for HIV
16% correctly reported
HIV status
*2 percent missing represents those who were laboratory-confirmed HIV infected but did not reportwhether they had ever tested, or what the result of the HIV test was.
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Coverage of cot r imoxazole The Ministry of Health recommends that everyone
diagnosed with HIV take cotrimoxazole (also known as Septrin), an antibiotic that reduces
the risk of early mortality by 25-46 percent as well as rates of hospitalization, malaria,
diarrhoea, and pneumonia.
The KAIS 2007 shows a large unmet need for cotrimoxazole. The great majority of unmet
need can be attributed to low level of awareness of HIV status among those infected with
HIV, as shown in Figure x below.
12% Need CTX, know
status, on CTX (8%-16%)
4% Need CTX, knowstatus, not on CTX
(2-6%)
84% Need CTX but donot know their status
(80-88%)
Figure 11. Cotrimoxazole coverage among HIV-infected Kenyans age 15-64, Kenya2007. Due to the small proportion of HIV-infected survey participants who know their status,the number of persons answering the care and treatment module of the questionnaire wassmall (n
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Coverage of ant i re t rov i ra l therapy based on CD4 d is t r ibut ion
The measurement of CD4 cell counts is critical for planning current and future needs for HIV
treatment. The KAIS 2007 was the first ever national, population-based survey to measure
CD4 counts among people with HIV. The following results are based on CD4 testing done as
part of KAIS.
Table 7. CD4 count distribution among adults with HIV not on ART according to KAIS 2007.
Unweighted n Weighted % Projected populationestimate
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As with cotrimoxazole, the majority of unmet need for ART can be attributed to not knowing
ones HIV status. The figure above indicates that two-thirds of those eligible for treatment
cannot access it since they do not know their status. Of the estimated number of adults age15-64 eligible for ART at the time of the survey (approximately 390,000), 35 percent
(approximately 140,000 persons) ) were taking ART. Of those eligible and not taking ART,
97 percent reported they had never tested for HIV or had a tested negative for HIV. Among
HIV-infected adults who knew their status, ART services appeared to be equitably reaching
the population in need, with few differences across socio-demographic characteristics.
The information presented here reflects coverage of ARVs among HIV-infected adults 15-64
at the time of the KAIS 2007 survey. At the end of June 2008, preliminary service statistics
reports indicated that approximately 190,000 HIV-infected Kenyan adults were receiving
ARVs. In addition to the number currently receiving treatment, the number of those in needof treatment has also increased since the time of the survey. More up to date estimates of
ARV coverage are available through NASCOP.
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NEXT STEPS
The preliminary results of KAIS 2007 presented here are only highlights of the complex HIV
and AIDS epidemic. In-depth analysis of KAIS data is ongoing and more comprehensive
results will be presented in the final report anticipated in January 2009.
4.1 Disseminat ion of f ina l resul ts
In addition to the information in this preliminary report, the main report will offer a broader
picture of the status of HIV/AIDS and related diseases in Kenya through a comprehensive
look at the all indicators included in the KAIS questionnaires. These include:
HIV prevalence and incidence estimates and relevant comparisons to KDHS 2003
Uptake and unmet need for HIV testing
Risk of acquiring HIV among the HIV-
uninfected
Uptake and unmet need for care and
treatment among the HIV-infected
Co-infection with STI
Impact of HIV on households
The report will be released to the public and
institutional stakeholders through a series of
national and regional dissemination events. Soonafter the report, fact sheets and policy briefs about each province and selected target
groups, such as youths and older adults, will be available through GoK partners and online
at www.aidskenya.org; www.health.go.ke; and www.nacc.or.ke.
KAIS FINDINGS PROVIDE THE
GOVERNMENT OF KENYA AN
OPPORTUNITY TO IMPROVE THE
WAY IT ALLOCATES RESOURCES AND
PROVIDES HIV/AIDS PREVENTION,
CARE AND TREATMENT SERVICES.
4.2 Nat ional programmatic response
KAIS 2007 findings provide the strategic information the GoK needs to improve the way it
allocates resources and provides HIV and AIDS prevention, care and treatment services. A
key conclusion from these preliminary findings is that prevention efforts must be intensifiedsimultaneously with care and treatment scale-up. The GoK intends to respond to the low
awareness of HIV status among adult Kenyans with a series of intensified, rapid HIV testing
campaigns. Additionally, NACC is coordinating a review of the Kenya National HIV/AIDS
Strategic Plan (KNASP) and organizing a second HIV Prevention Summit at which an HIV
Prevention Task Force will be launched. Acknowledging the particular vulnerability of youth
to HIV and the opportunity to instil norms of safer sex practices early, NACC and other key
stakeholders have developed a Youth Strategy for HIV Prevention.
The 2007 KAIS is the first in a series of AIDS Indicator Surveys in Kenya. The next KAIS is
planned for 2011. The KDHS survey is scheduled to begin in late 2008.
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GLOSSARY OF TERMS
Human Immunodeficiency Virus (HIV): HIV isthe virus that causes AIDS (Acquired
Immunodeficiency Syndrome. The virus is
passed from person to person through blood,
semen, vaginal fluids, and breast milk. HIV
replicates slowly; most of the time, several
years pass between initial infection and the
onset of symptoms. HIV attacks the human
immune system and leaves infected persons
very vulnerable to illnesses that are normally
eliminated by healthy immune systems.
Acquired Immune Deficiency Syndrome (AIDS):AIDS is the final stage of HIV infection. It
represents the late disease stage of HIV
infection which usually results in damage to
the immune and other organ systems, leaving
the body very vulnerable to life-threatening
conditions such as infections and cancer.
CD4 cells: A CD4 lymphocyte cell is a cell ofthe immune system that carries the CD4
surface protein. CD4 cells are very important
to a normal health immune system. CD4 cellsattract HIV. HIV infects and kills CD4 cells,
leading to a weakened immune system.
HSV-2: Herpes simplex virus-2 or genitalherpes is a common, sexually transmitted viral
infection characterized by lesions (cuts) and
ulcers in genital areas. HSV-2 can be treated
but cannot be cured.
Syphilis: Syphilis is a curable sexuallytransmitted disease. 3 weeks after exposure to
syphilis, a lesion appears on the genital area.
Secondary syphilis is characterized by a rash
on the body, arms and legs.Some people canhave latent syphilis which means they are
infected with syphilis but do not show signs or
symptoms of disease.
Antiretroviral therapy (ART): Medications thatstop or slow down viruses (like HIV) from
multiplying in the body and therefore extends
the length of a persons life. ART is given to
patients with HIV who have low counts of CD4
cells to help them fight HIV disease.
Cotrimoxazole: Also known as septrin. Anantibiotic used in the treatment of a variety of
bacterial infections. Kenya policy recommends
that Cotrimoxazole be given as prevention to
all people HIV to help avoid some
opportunistic infections and therefore extend
the length of a persons life.
Prevalence: The number of cases of a givendisease (or other health conditions), in a givenpopulation, at a designated time, expressed as
a percentage of all persons who can have the
disease. Prevalence can increase or decrease
over time depending on the number of new
infections, the rate of mortality, the availability
of treatment, and surveillance methods.
Incidence: The number of new cases of adisease in a defined population, within a
specified period of time, expressed as a
percentage among all person who can acquirethe disease. Incident cases make up a portion
of all prevalent cases.
Statistical significance: The probability that theresults observed during the study (or more
extreme results) was not likely to be due
to chance alone. The threshold for statistical
significance is an arbitrary value called a p
value which is usually set at 0.05 or 5%. If the
probability that the observed result was due to
chance is that less than the set p value, the
result is considered statistically significant.
95% confidence interval (95% CI): A confidenceinterval gives a range of possible values (using
an upper and lower bound) within which the
true population value of a variable (e.g. the
mean, proportion, or rate) will fall 95 times out
of 100. It is a measure of certainty and
precision around the sample estimate when
estimating the true population value.
http://en.wikipedia.org/wiki/Sexually_transmitted_diseasehttp://en.wikipedia.org/wiki/Sexually_transmitted_diseasehttp://en.wikipedia.org/wiki/Sexually_transmitted_diseasehttp://en.wikipedia.org/wiki/Sexually_transmitted_disease -
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