kais - preliminary report_july 29

8/14/2019 KAIS - Preliminary Report_July 29

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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



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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http://www.aidskenya.org/http://www.health.go.ke/http://www.nacc.or.ke/http://www.nacc.or.ke/http://www.health.go.ke/http://www.aidskenya.org/


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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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