National HIV Prevalence in Kenya The National AIDS Control Council and the National AIDS and STD Control Programme Nairobi, Kenya June 2007
Background Each year the National AIDS and STD Control Programme (NASCOP) conducts sentinel surveillance for HIV infections at ante-natal clinics throughout the country. These data provide information on trends in HIV prevalence. In 2003 a national household survey (2003 KDHS) provided a good estimate of HIV prevalence in the adult population aged 15-49. This paper describes the use of the sentinel surveillance data and the KDHS to estimate national prevalence in Kenya and the implications of that estimate for other indicators of interest, such as the number of people infected and the number of people in need of ART.
Sentinel surveillance for HIV prevalence among pregnant women Sentinel surveillance for HIV is designed to provide information on trends in prevalence over time by geographic region. The HIV sentinel surveillance system in Kenya is implemented by the National AIDS and STD Control Programme (NASCOP). Data are collected for both ante-natal clinic (ANC) clients and for STD clinic clients. The STD data are primarily designed to represent high-risk populations while the ANC data represent the general population. Therefore, only the ANC data are used to estimate national prevalence. The sentinel surveillance system has been in operation since 1990. It started with 13 sites and has expanded over time to include 44 sites today. The surveillance data for all sites are shown in Appendix 1. HIV Prevalence among all adults 15-49 HIV prevalence is the percentage of the adult population between the ages of 15 and 49 that is infected with HIV. Although ANC attendees are generally representative of the adult population 15-49, there are some differences between the two groups. For example, the age distribution of pregnant women is different from all women 15-49, all pregnant women are sexually active while some women 15-49 are not sexually active, the fertility of HIV+ women is lower than for HIV- women, and ANC surveillance only measures prevalence among women whereas the total adult population also includes men. As a result the prevalence data from ANC sites need to be adjusted to estimate total adult 1
prevalence. This adjustment is made using the estimate of national adult prevalence (for men and women) for 2003 from the KDHS. The adjustment is calculated for 2003 and applied to the ANC-based estimate for all other years. Methodology for estimating national HIV prevalence among adults 15-49 There are eight steps in the preparation of the national estimate based on surveillance data. 1. Curve fitting. Surveillance data are available for 17 years for some sites and for 6 years for sites added in 2001. Individual estimates are subject to some error due to small sample sizes. The average sample size is about 300 for rural sites and 400 for urban sites. To smooth the year-to-year fluctuations, epidemic curves are fit to the data from each site using the Estimation and Projection Package (EPP) developed by the UNAIDS Reference Group on Estimates, Model and Projections1. The curve indicates the trend through the available data points. Values from these curves (rather than the actual sentinel site point estimates) are used to estimate national prevalence. An example is shown in Figure 1. In this figure the boxes represent the point prevalence estimate, the bars extending above and below these points show the 95% confidence limits around each point and the solid line is the best-fitting curve to these points. For the 24 sites with 8 years or more of data, the EPP curve fitting package usually determines a reasonable curve fit. However, for many sites the curve fit does vary depending on the initial assumption as to whether prevalence is declining or not. Among the sites with many data points almost all show clear signs of declining prevalence. As a result, the starting assumption for all curve fits was that prevalence is declining. For the sites with five years of data or less, the curve fitting program cannot be expected to produce useful results. Therefore, curve fits were done by province by aggregating all the surveillance data into urban and rural data sets for each province. Separate curves were fit to the urban and rural data sets for each province. The parameters of these curves were then used as the starting values for each rural site in each province.
1
Ghys PD, Brown T, Grassly NC, Garnett G, Stanecki KA, Stover J, Walker N. The UNAIDS Estimation and Projection Package: a software package to estimate and project national HIV epidemics. Sex Transm Inf 2004, 80 (suppl 1): i5-i9.
2
Figure 1. Curve fit to annual measurements of prevalence among pregnant women at the ante-natal surveillance clinic in Kitale 25%
20%
15%
10%
5%
0% 1980
1985
1990
1995
2000
2005
2. Adjusting for geographic distribution. It would be very expensive to establish a sentinel site in each district. Therefore, the districts are represented by the available sites. The assignment of sites to districts was done by a technical working group based on similarities in urbanization, ethnic groups, economic activity and geographic proximity. One site is assigned to represent the urban population of each district and one site to represent the rural population. Table 1 shows the sentinel sites and the districts that they represent. Table 1. Districts represented by each sentinel site Province
District
Urban Site
Rural Site
Central
Kiambu Kirinyaga Maragua Muranga Nyandarua Nyeri Thika Kilifi Kwale Lamu Malindi Mombasa Taita-Taveta
Fatima Nyeri Nyeri Thika Nyeri Nyeri Thika Kilifi Tiwi Tiwi Kilifi Mombasa Kitui
Njambini Maragua Maragua Maragua Njambini Maragua Maragua Bamba Wesu/Wundanyi Bamba Tiwi Tiwi Wesu/Wundanyi
Coast
3
Province Eastern
Nairobi North Eastern
Nyanza
Nyanza
Rift Valley
Western
District
Urban Site
Rural Site
Tana River Embu Isiolo Kitui Machakos Makueni Marsabit Mbeere Meru Central Meru North Meru South Moyale Mwingi Nithi Tharaka Nairobi Garissa Mandera Wajir Bondo Gucha Homa Bay Kisii Central Kisii North Kisumu Kuria Migori Nyando Rachuonyo Siaya Suba Baringo Bomet Buret Kajiado Keiyo Kericho Koibatek Laikipia Marakwet Nakuru Nandi Narok Samburu Trans Mara Trans Nzoia Turkana Uasin Gishu West Pokot Bungoma
Garissa Nyeri Kitui Kitui Thika Kitui Garissa Meru Meru Meru Meru Garissa Kitui Meru Meru Nairobi Garissa Garissa Garissa Kisumu Kisii Suba Kisii Kisii Kisumu Kisii Kisumu Kisumu Kisumu Kisumu Suba Baringo Baringo Baringo Kajiado Baringo Nakuru Baringo Nakuru Baringo Nakuru Baringo Kajiado Maralal Kajiado Kitale Lodwar Kitale Kajiado Mt. Elgon
Wesu/Wundanyi Karurumo Mutomo Mutomo Kangudo Mutomo Mutomo Karurumo Karurumo Karurumo Karurumo Mutomo Kangudo Karurumo Karurumo Garissa Garissa Garissa Chulaimbo Tabaka Suba Tabaka Tabaka Chulaimbo Tabaka Chulaimbo Chulaimbo Chulaimbo Chulaimbo Suba Sirikwa/Turbo Kaplong Kaplong Kajiado Sirikwa/Turbo Kaplong Sirikwa/Turbo Njambini Mosoriot Njambini Mosoriot Kajiado Maralal Sirikwa/Turbo Mosoriot Sirikwa/Turbo Sirikwa/Turbo Sirikwa/Turbo Teso
4
Province
District
Urban Site
Rural Site
Busia Butere/Mumias Kakamega Lugari Mt. Elgon Teso Vihiga
Busia Kakamega Kakamega Kakamega Mt. Elgon Mbale Kakamega
Mbale Mbale Mbale Mbale Mt. Elgon Mbale Mbale
3. Estimating the size of the adult population. The total population for each district is estimated for all years from 1990 to 1999 by interpolating between the population at the time of the 1989 census and the population at the time of the 1999 census. The adult population 15-49 by district and urban/rural residence for the 1989 and 1999 censuses are based on special tabulations provided by the Central Bureau of Statistics. Urban and rural populations for each district are projected beyond 1999 at the 19891999 growth rates for that district. Growth rates are limited to 11.5% per year in order to avoid continuing the very high growth rates that occurred for some districts with small urban populations in 1999. The result is an adult population that is growing at about 4% per year after 1999. 4. Estimating the number of HIV infections. The number of adults between the ages of 15 and 49 infected with HIV is estimated by multiplying the number of urban adults in each district by the HIV prevalence in the urban site associated with that district and the number of rural adults by the HIV prevalence in the rural site associated with that district. 5. Estimating national adult prevalence. National prevalence is estimated by summing the number of infected adults 15-49 for all districts and dividing by the total population 15-49. 6. Adjusting adult prevalence. The estimate for 2003 is compared with the KDHS estimate for 2003. The ratio of these two estimates is an adjustment factor which is applied to all years in order to adjust ANC prevalence to represent prevalence among all adults. 7. Direct estimate of national prevalence. A second method of estimating national prevalence was also implemented. In this approach the actual site prevalence values are used rather than the smooth curves. This approach can only be used for the period 2001 – 2006 when the number of sites has been constant. When the actual site prevalence values are weighted by the population they represent, an estimate of national prevalence is produced. An estimate produced in this manner is subject to more year-to-year variation than when smooth curves are used, but it may also provide a better estimate when prevalence is changing quickly. 8. Estimating the uncertainty range around the prevalence estimate. The Estimates and Projections Package (EPP) includes procedures to estimate the uncertainty associated with the curve fits through the application of a procedure known as 5
Bayesian Melding. This approach determines the uncertainty associated with the error around each data point and the different types of curves that might be fit to the data for each sentinel site. The uncertainties associated with the curve fits for each site are combined to estimate the plausibility bounds around the national estimate. 9. Calculate the consequences of the prevalence estimate. Once the prevalence estimate is prepared it is used in the Spectrum software package2 to estimate to consequences including the number of child infections, new infections, AIDS deaths and the need for ART. Spectrum also includes a Monte Carlo technique to estimate the ranges around key indicators.
2
Stover J. Projecting the demographic consequences of adult HIV prevalence trends: the Spectrum Projection Package. Sex Transm Infect 2004; 80 (Suppl 1): i14–i18.
6
Results Prevalence among all adults 15-49 The method of fitting smooth curves to the data from each surveillance site yields an estimated adult HIV prevalence of 5.1% (4.6%-5.8%) in 2006, a reduction of 1.6% from 2003, as shown in Figure 2. It indicates that national prevalence peaked at around 9% in 1997/1998. The current estimate of urban prevalence is about 8.3% (7.3%-9.1%) and rural prevalence is 4.0% (3.3%-4.7%). Figure 2. HIV Prevalence Among Adults 15-49, 1980-2006 12%
10%
8%
6%
4%
2%
0% 1980
1985
1990
1995
2000
2005
The direct estimate, using the actual site data for 2001 – 2006, produces a somewhat lower figure for 2006 of 4.6%, as shown in Figure 3. The direct estimate is within the plausibility bounds of the trend estimate. Since the direct estimate does fluctuate from year to year the smooth trend may represent a better estimate. However, the trend does show a slower rate of decline over the past few years than the direct estimate and may under-estimate the true rate of decline.
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Figure 3. HIV Prevalence Among Adults 15-49 10% 9% 8% 7% 6% 5.1% 4.6%
5% 4% 3% 2% 1% 0% 2001
2002
2003 Weighted ANC
2004
2005
2006
Trend
The decline in prevalence since the late 1990s does not mean that the problem of HIV/AIDS is over. The number of people infected declines when the number of AIDS deaths exceeds the number of new infections. New infections occur every day, especially among young people. In 2006 there were about 55,000 new adult infections. The number of AIDS deaths had been increasing rapidly as a result of the rise in new infection in the mid-1990s. The annual number of adult AIDS deaths reached a peak of about 120,000 in 2003. It would have stayed at roughly that level for the next three years but the increasing number of people receiving anti-retroviral therapy (ART) has reduced the annual number of AIDS deaths to about 85,000 in 2006 as shown in Figure 4. This implies that ART programs have averted about 57,000 deaths since 2001
8
Figure 4. Number of New Infections and AIDS Deaths Among Adults, 1980-2006 250,000
200,000
150,000
100,000
50,000
0 1980
1985
1990 AIDS Deaths
1995
2000
2005
New Infections
The estimated adult prevalence and number of adults infected by region and sex for 2006 is shown in Table 2. It indicates that about one million adults, 15-49 are living with HIV. There are also almost 100,000 people over the age of 49 living with HIV and 156,000 children, for a total of almost 1.3 million people infected with HIV. Estimates of infection and prevalence among youth between the ages of 15 and 24 are shown in table 3. Estimates of HIV infection by province are shown in Table 4. Table 2. National HIV estimates for 2006 Prevalence Adults 15-49 Total (Range) Male Female Urban Rural Adults 50+ Children 0-14 Total
5.1% (4.6%-5.8%) 3.5% 6.7% 8.3% 4.0%
Number HIV+ 930,000 (700,000 – 1,200,000 320,000 615,000 400,000 530,000 55,000 100,000 1,100,000
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Table 3. Prevalence estimates for youth aged 15-24 in 2006 Male Female Total
Prevalence 1.4% 4.0% 2.7%
Number HIV+ 55,000 160,000 215,000
Table 4. Adult HIV prevalence by province in 2006 Province Nairobi Central Coast Eastern North Eastern Nyanza Rift Valley Western Total
Number HIV+ 197,000 96,000 93,000 72,000 9,000 183,000 171,000 112,000 934,000
Total 10.1% 4.1% 5.9% 2.8% 1.4% 7.8% 3.8% 5.3% 5.1%
Prevalence Male Female 8.0% 12.3% 1.7% 6.5% 5.0% 6.9% 1.1% 4.4% 0.9% 1.8% 6.1% 9.6% 2.6% 4.9% 4.2% 6.4% 3.5% 6.7%
The national and provincial estimates are produced by summing the district estimates. These are shown in Appendix 2. The estimates of HIV infection among adults are used to calculate the number of children that become infected through mother-to-child transmission. In 2006 there were about 100,000 children living with HIV and 19,000 new infections. The transmission of HIV from mother-to-child can be greatly reduced through PMTCT programs that provide counseling and testing to all pregnant women and treatment for those women who are HIV+. As Table 5 shows, the total number of pregnant women needing counseling and testing each year is almost 1.5 million. About 850,000 pregnant women received counseling and testing in 2006. About 70,000 pregnant women were HIV+ and could benefit from treatment to prevent transmitting the virus to their babies. HIV+ children can benefit from cotrimoxazole prophylaxis and ART. Cotrimoxazole is recommended for all children born to HIV+ mothers until their own HIV status can be determined, usually at about 18 months of age, and then for all HIV+ children. About 200,000 children are in need of cotrimoxazole and 23,000 are in need of ART. Table 5. Need for PMTCT and child treatment, 2006 Number of births Births to HIV+ women HIV+ births Child AIDS deaths Children needing ART Children need cotrimoxazole
1,460,000 68,000 19,000 20,000 23,000 200,000
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When adults die from AIDS their children become orphans. In 2006 there were an estimated 2.4 million orphans as shown in Table 6. The definition of an orphan used here is a child under the age of 18 who has lost at least one parent. Forty-five percent of these children, just over one million, have lost a parent to AIDS. Table 6. Number of orphans by type, 2005 Maternal Orphans AIDS Non-AIDS Paternal Orphans AIDS Non-AIDS Doublel Orphans AIDS Non-AIDS Total Orphans All AIDS orphans
1,282,000 692,000 590,000 1,591,000 750,000 841,000 443,000 349,000 94,000 2,430,000 1,149,000
These figures illustrate the magnitude of the task to provide prevention, care and treatment, and support services for all who need them. They indicate that: • • • • •
1.5 million pregnant women need counseling and testing each year to determine their HIV status 68,000 need treatment to prevent mother-to-child transmission of HIV 23,000 children need ART and 200,000 need cotrimoxazole prophylaxis 430,000 adults need ART 2.4 million orphans need care and support from their extended families and communities
These figures describe the national needs. Since services are organized at the local level there is also a need for estimates by district. Precise district-level estimates require detailed analysis of the demographic and epidemiological trends in each district. For this report approximations of the district-level indicators have been prepared by distributing the national needs according to the number of people infected by district. These figures are only approximations but should provide an indication of the magnitude of need by district. The figures are given in Appendix 3.
National response Much has been done to address the HIV/AIDS epidemic and its consequences. A comprehensive response requires many things, including service provision, community mobilization, strong leadership, appropriate policies, coordination and management, research, support to people living with and affected by HIV/AIDS, programs to protect human rights and fight stigma and discrimination, resource mobilization, evaluation and 11
monitoring, etc. Indicators have been developed to monitor progress in most of these areas. In this report, we focus on small number of indicators for which data are readily available and which are directly related to the epidemiological estimates. These include the coverage of VCT, PMTCT, and ART services, condom distribution, and financial resources. Table 7 compares the latest information on service provision with the estimated needs and the targets from the Kenya National HIV/AIDS Strategic Plan (KNASP) 2005-2010. Table 7. Coverage of essential services Service Voluntary counseling and testing (VCT) Prevention of mother-to-child transmission (PMTCT) Condoms (millions) Anti-retroviral therapy (ART)
Number provided 800,000+ 850,000
Estimated Need 500,000 1,423,000
Coverage 80% 26%
KNASP Target 500,000 713,000
93 120,000
160 430,000
58% 28%
160 186,000
Notes 1. The target for VCT assumes 2 million people tested annually with 500,000 tested at VCT sites and 1.5 million receiving clinical testing including pregnant women 2. The target for PMTCT is based on the assumptions that 80% of pregnant women will attend an ANC facility at least once, 80% of facilities will offer PMTCT and 80% of women will accept. The resources required for the HIV/AIDS program were estimated by the KNASP at KSh 178 billion. The details by year and intervention are shown in Table 8. The resources available to the program have increased dramatically over the past several years as shown in Table 9. While the resources available were nearly equal to the needs in 2004, the needs increase rapidly as programs as expected to expand to meet the 2009/10 targets.
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Table 8. KNASP 2005-2010 estimated resources required (KSh millions)
PREVENTION Youth focused interventions Sex workers and clients Workplace Harm reduction programmes Uniform Services Other vulnerable populations Condom provision STI management VCT PMTCT Behaviour change communication Blood safety Post-exposure prophylaxis Total: Prevention IMPROVING OF QUALITY OF LIFE Home-based care Palliative care Diagnostic testing Treatment of opportunistic infections OI prophylaxis Lab HAART ARV therapy Training Nutritional support Protection of Human Rights Total: Improving of Quality of Life MITIGATION OF SOCIO-ECONOMIC IMPACT Mitigation policy Mitigation advocacy Livelihood and social security Mitigation programmes Community empowerment Human resource planning Total: Mitigation of Socio – Economic Impact PROVISION OF SUPPORT SERVICES Financing and procurement Communication, coordination & networking Monitoring and evaluation Research Institutional capacity building Total: Support Services OVERALL TOTAL (Ksh. million) OVERALL TOTAL (US$ million)
2005/06
2006/07
2007/08
2008/09
2009/10
TOTAL
1,017 35 210 14 59 118 2,181 422 740 953 240 365 40 6,395
1,416 37 278 20 83 166 2,426 466 789 1,363 240 426 55 7,765
1,853 38 349 24 109 217 2,747 513 777 1,357 120 487 70 8,661
2,341 39 425 27 135 271 3,095 561 830 1,351 80 548 85 9,788
2,883 41 503 31 164 327 3,472 612 886 1,450 40 656 108 11,173
9,509 190 1,765 116 550 1,099 13,921 2,575 4,021 6,476 720 2,482 360 43,782
265 163 78 1,668 117 55 4,000 27 133 723 7,228
323 217 95 1,712 163 93 5,231 39 164 795 8,833
345 116 113 1,364 212 139 7,458 57 259 835 10,897
380 158 130 1,384 261 173 8,352 69 299 835 12,041
423 176 147 1,249 314 216 9,357 81 357 835 13,156
1,737 830 563 7,376 1,067 677 34,397 273 1,212 4,022 52,154
883 1,261 1,261 3,153 757 252 7,568
1,076 1,537 1,537 3,842 922 307 9,221
724 1,087 1,087 6,881 724 362 10,865
808 808 1,213 8,287 808 202 12,127
1,352 451 1,352 9,236 901 225 13,516
4,843 5,144 6,449 31,400 4,113 1,349 53,298
770 1,514 2,018 505 505 5,311 25,226 315
770 1,844 2,459 615 615 6,303 30,737 384
770 1,811 2,173 724 724 6,203 36,218 453
770 2,021 1,617 808 808 6,025 40,424 505
770 2,253 1,802 901 901 6,627 45,054 563
3,850 9,443 10,069 3,553 3,553 30,469 177,659 2,221
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Table 9: Total HIV/AIDS Resources by Source of Funding 2000/2001 - 2004/2005 (Kshs Million) 2000/2001 2001/2002 2002/2003 2003/2004 2004/2005 All years 2000– 2005 GOK Donors budgetary Donors non-budget NGOs Households Total
70 302 1,760 10 2,142
10 1,165 3,539 26 4 4,744
120 1,796 4,136 19
40 2,685 5,487 22
156 6,794 11,961 52
6,071
8,234
18,963
396 12,742 26,884 129 4 40,155
Source: HIV/AIDS 2005 Public Expenditure Review, Ministry of Health.
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Appendix 1. HIV prevalence among pregnant women at sentinel surveillance sites, 1990 – 2006 Bamba Baringo Busia Chulaimbo Fatima Garissa Kajiado Kakamega Kangudo Kaplong Karurumo Kilifi Kisii Kisumu Kitale Kitui Lodwar Maragua Maralal Mbale Meru Mombasa Mosoriot Mt. Elgon Mutomo Nairobi Nakuru
Clients Rural Mixed Urban Rural Rural Mixed Mixed Mixed Mixed Rural Rural Mixed Urban Urban Mixed Mixed Urban Rural Mixed Rural Mixed Urban Rural Mixed Rural Urban Urban
1990
1991
1992
1993
1994
1995
1996 1%
1997
1998
1999
2000
16%
9%
29%
21%
22%
21% 20%
27% 26%
28%
28% 35%
32% 24%
20% 29%
4%
3%
14%
8%
13%
4% 6% 9%
7% 9% 9%
4% 6% 14%
4%
14%
5% 5% 11%
3% 1%
9%
5% 26%
8% 29% 10% 19%
3% 24% 9% 3%
15% 26% 11% 3%
4% 4%
1% 18% 2% 0%
2% 9%
5% 9%
12%
3% 18% 5% 4%
16%
12% 12%
0% 19% 20% 1%
10%
13% 12%
2% 19% 7% 7%
1% 16%
17% 22%
11% 10% 10% 1%
10% 8% 15% 12%
15% 11%
15%
16% 26%
16% 10%
10%
10%
4% 10%
4%
2%
15% 32% 12% 5%
13% 27% 8% 8%
11% 25% 16% 7%
14% 33% 15% 12%
10%
5%
15% 13% 16% 8%
10% 21% 14% 1%
24%
23%
8% 11% 28% 1%
23% 23% 10% 5%
17% 25%
17% 9%
2001 9% 10% 15% 25% 22% 9% 8% 11% 14% 9% 6% 10% 17% 29% 13% 17% 16% 8% 15% 11% 10% 14% 4% 21% 2% 14% 12%
2002 5% 6% 16% 22% 8% 4% 5% 14% 7% 6% 4% 5% 14% 26% 16% 6% 18% 8% 13% 11% 5% 15% 3% 6% 5% 13% 12%
2003 1% 4% 16% 22% 10% 2% 4% 13% 4% 3% 7% 8% 9% 26% 11% 6% 13% 5% 18% 8% 8% 16% 3% 5% 4% 11% 10%
2004 2% 6% 16% 14% 7% 1% 2% 9% 5% 3% 3% 4% 6% 11% 7% 6% 6% 8% 10% 3% 10% 5% 5% 5% 10% 7%
2005 2% 4% 14% 8% 4% 1% 3% 9% 5% 4% 3% 5% 7% 15% 5% 8% 7% 5% 4% 10% 5% 11% 4% 5% 3% 10% 7%
15
2006 3% 6% 8% 8% 7% 1% 4% 8% 4% 5% 4% 3% 2% 18% 5% 10% 9% 4% 7% 5% 4% 6% 4% 5% 4% 10% 11%
Njambini Nyeri SirikwaTurbo Suba Tabaka Teso Thika Tiwi WesuWundanyi
Clients Rural Mixed Rural Rural Rural Rural Mixed Mixed Rural
1990
1991
1992
1993
1994
1995
1996
2%
3%
8%
2%
5%
20%
8%
2%
9%
2%
27%
39% 16%
12% 23%
1997 4% 6%
18%
1998 2% 15%
31% 31%
1999
16% 21%
2000 7% 12%
19% 12%
2001 6% 11% 5%
2002 6% 8% 5%
2003 10% 8% 4%
2004 10% 6% 5%
2005 7% 5% 4%
2006 4% 5% 4%
31% 11%
34% 4% 6% 7% 7% 5%
41% 9%
30% 3% 4% 8% 7% 3%
33% 3% 4% 8% 7% 2%
26% 1% 4% 5% 8% 6%
11% 10% 7%
8% 10% 3%
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Appendix 2. HIV prevalence, number infected, and AIDS deaths among adults by district in 2006 Province Central Central Central Central Central Central Central Coast Coast Coast Coast Coast Coast Coast Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Nairobi North Eastern North Eastern North Eastern Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Western Western Western Western Western Western Western
District Kiambu Kirinyaga Maragua Muranga Nyandarua Nyeri Thika Kilifi Kwale Lamu Malindi Mombasa Taita-Taveta Tana River Embu Isiolo Kitui Machakos Makueni Marsabit Mbeere Meru Central Meru North Meru South Moyale Mwingi Nithi Tharaka Nairobi Garissa Mandera Wajir Bondo Gucha Homa Bay Kisii Central Kisii North Kisumu Kuria Migori Nyando Rachuonyo Siaya Suba Baringo Bomet Buret Kajiado Keiyo Kericho Koibatek Laikipia Marakwet Nakuru Nandi Narok Samburu Trans Mara Trans Nzoia Turkana Uasin Gishu West Pokot Bungoma Busia Butere/Mumias Kakamega Lugari Mt. Elgon Teso
Urban Rural Total HIV+ HIV+ HIV+ 1,126 21,526 22,653 1,255 10,646 11,901 280 8,528 8,808 471 7,440 7,911 914 11,879 12,794 2,275 12,438 14,713 8,355 9,186 17,541 1,723 4,327 6,050 2,062 6,842 8,904 393 519 912 1,919 3,898 5,816 62,214 62,214 1,878 3,879 5,757 81 3,311 3,393 1,926 2,717 4,643 1,496 1,503 2,999 1,473 8,125 9,598 1,968 12,544 14,512 843 11,591 12,434 97 1,549 1,646 55 1,846 1,902 3,530 5,329 8,859 334 6,572 6,906 290 1,472 1,763 174 517 691 995 4,464 5,459 726 726 196,917 196,917 726 2,273 2,999 392 1,951 2,343 242 3,649 3,890 1,313 5,214 6,527 585 5,619 6,203 7,660 32,392 40,052 2,088 9,428 11,516 968 6,031 6,999 16,537 5,923 22,459 791 2,316 3,107 8,438 20,081 28,519 1,059 7,066 8,126 1,324 13,578 14,902 1,878 10,070 11,948 1,923 20,941 22,863 699 7,177 7,876 69 8,549 8,618 35 3,011 3,045 2,169 5,807 7,976 206 4,253 4,458 2,468 10,161 12,629 928 3,486 4,414 4,390 6,809 11,199 3,406 3,406 17,243 22,797 40,040 862 8,481 9,343 790 3,831 4,621 1,299 3,192 4,492 166 2,184 2,350 2,426 8,384 10,809 2,674 9,285 11,959 9,774 8,363 18,137 206 4,928 5,134 3,616 37,945 41,561 1,783 6,644 8,428 3,855 11,777 15,632 3,019 9,219 12,237 412 6,177 6,589 170 4,376 4,545 1,173 7,650 8,822
Total Prevalence Male Female AIDS prevalence Range prevalence prevalence deaths 4.6% 1.9%-13.3% 1.9% 7.3% 2,542 3.9% 1.3%-9.0% 1.6% 6.2% 1,335 3.9% 1.6% 6.1% 988 3.8% 1.6% 6.1% 888 4.5% 1.9% 7.2% 1,436 3.9% 1.6% 6.2% 1,651 3.7% 1.6% 5.9% 1,968 1.9% 1.6% 2.2% 679 3.4% 2.8% 3.9% 999 2.2% 1.8% 2.5% 102 3.4% 2.8% 3.9% 653 11.7% 9.9% 13.6% 6,981 4.1% 3.4% 4.7% 646 3.2% 2.7% 3.7% 381 2.1% 0.8% 3.4% 521 4.9% 1.9% 7.9% 337 3.9% 1.5% 6.3% 1,077 3.4% 1.4% 5.5% 1,628 3.7% 1.5% 5.9% 1,395 3.3% 1.3% 5.2% 185 1.6% 0.6% 2.6% 213 2.2% 0.9% 3.5% 994 1.6% 0.6% 2.6% 775 1.8% 0.7% 2.8% 198 2.5% 1.0% 4.1% 78 3.8% 1.5% 6.1% 613 1.6% 0.6% 2.5% 81 0.0% 0.0% 0.0% 10.1% 4.0% 16.3% 22,095 1.4% 0.9% 1.8% 337 1.4% 0.9% 1.8% 263 1.4% 0.9% 1.8% 437 7.8% 6.0% 9.5% 732 2.8% 2.2% 3.5% 696 21.0% 16.3% 25.7% 4,494 3.0% 2.3% 3.7% 1,292 2.9% 2.3% 3.6% 785 10.8% 8.4% 13.3% 2,520 3.1% 2.4% 3.8% 349 8.2% 6.4% 10.0% 3,200 7.5% 5.8% 9.2% 912 7.3% 5.7% 9.0% 1,672 7.6% 5.9% 9.3% 1,341 21.0% 16.3% 25.7% 2,565 3.3% 2.2% 4.3% 884 3.2% 2.2% 4.3% 967 3.2% 2.2% 4.3% 342 2.8% 1.9% 3.7% 895 3.2% 2.2% 4.2% 500 3.5% 2.4% 4.7% 1,417 3.3% 2.3% 4.3% 495 5.0% 3.4% 6.6% 1,257 2.7% 1.8% 3.5% 382 5.0% 3.5% 6.6% 4,493 2.7% 1.9% 3.6% 1,048 2.8% 1.9% 3.7% 519 6.1% 4.2% 8.0% 504 3.2% 2.2% 4.2% 264 3.1% 2.1% 4.1% 1,213 3.8% 2.6% 4.9% 1,342 4.5% 3.1% 5.9% 2,035 3.2% 2.2% 4.2% 576 5.1% 4.0% 6.2% 4,663 5.9% 4.7% 7.1% 946 5.7% 4.5% 6.9% 1,754 5.7% 4.5% 6.9% 1,373 5.4% 4.3% 6.5% 739 3.7% 2.9% 4.5% 510 5.3% 4.2% 6.4% 990
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Appendix 3. Needs for treatment and support by district in 2005 Province Central Central Central Central Central Central Central Coast Coast Coast Coast Coast Coast Coast Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Eastern Nairobi North Eastern North Eastern North Eastern Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Nyanza Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Rift Valley Western Western Western Western Western Western Western
District Kiambu Kirinyaga Maragua Muranga Nyandarua Nyeri Thika Kilifi Kwale Lamu Malindi Mombasa Taita-Taveta Tana River Embu Isiolo Kitui Machakos Makueni Marsabit Mbeere Meru Central Meru North Meru South Moyale Mwingi Nithi Tharaka Nairobi Garissa Mandera Wajir Bondo Gucha Homa Bay Kisii Central Kisii North Kisumu Kuria Migori Nyando Rachuonyo Siaya Suba Baringo Bomet Buret Kajiado Keiyo Kericho Koibatek Laikipia Marakwet Nakuru Nandi Narok Samburu Trans Mara Trans Nzoia Turkana Uasin Gishu West Pokot Bungoma Busia Butere/Mumias Kakamega Lugari Mt. Elgon Teso
Adults requiring ART 6,284 3,046 2,195 2,106 3,610 3,874 6,875 1,691 2,346 336 2,403 17,118 1,160 677 1,728 630 2,077 5,064 2,781 386 779 3,180 2,808 737 176 1,554 320 50,665 1,030 814 1,307 2,344 1,975 10,438 3,429 2,229 7,587 940 9,332 2,971 4,977 4,336 5,949 1,727 1,627 660 1,616 984 2,650 956 3,173 776 11,624 2,254 974 1,259 571 2,707 2,883 4,650 1,223 12,171 2,815 5,007 4,218 2,096 1,281 2,593
Children requiring ART 942 457 329 316 541 581 1,031 253 352 50 360 2,566 174 102 259 94 311 759 417 58 117 477 421 110 26 233 48 7,595 154 122 196 351 296 1,565 514 334 1,137 141 1,399 445 746 650 892 259 244 99 242 148 397 143 476 116 1,743 338 146 189 86 406 432 697 183 1,825 422 751 632 314 192 389
Children requiring cotrimoxazole 5,476 2,654 1,913 1,835 3,146 3,375 5,990 1,473 2,044 293 2,094 14,915 1,010 590 1,505 549 1,809 4,412 2,423 336 679 2,770 2,447 642 153 1,354 279 44,143 897 710 1,139 2,043 1,721 9,095 2,988 1,942 6,611 819 8,131 2,589 4,336 3,778 5,183 1,505 1,417 575 1,408 858 2,309 833 2,765 676 10,128 1,964 848 1,097 498 2,359 2,512 4,052 1,066 10,604 2,452 4,363 3,675 1,827 1,116 2,259
Number of orphans 58,448 28,328 20,418 19,587 33,577 36,028 63,939 15,723 21,821 3,124 22,352 159,208 10,786 6,298 16,069 5,856 19,315 47,094 25,866 3,589 7,248 29,573 26,120 6,852 1,634 14,449 2,974 471,204 9,575 7,574 12,160 21,804 18,366 97,082 31,895 20,730 70,566 8,747 86,789 27,632 46,287 40,330 55,328 16,065 15,128 6,139 15,032 9,154 24,647 8,889 29,510 7,218 108,109 20,967 9,054 11,707 5,313 25,177 26,814 43,249 11,374 113,192 26,178 46,569 39,233 19,498 11,915 24,117
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