Tanzania HIV/AIDS and Malaria Indicator Survey ... - Measure DHS

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HIV PREVALENCE 99.1 INTRODUCTIONPrior to the 2003-04 Tanzania HIV/AIDS Indicator Survey (THIS), national HIV prevalencewas estimated using prevalence from blood donors and sentinel surveillance among pregnant womenattending selected antenatal care (ANC) services. Prevalence estimates really began in 1990 when 24ANC sites were established for HIV surveillance in 11 regions. In 2005-06, surveillance of HIVamong ANC attendees had increased to 90 ANC sites in 15 regions. Results from that round of ANCsurveillance data were analysed and used together with data from the 2003-04 THIS to estimate theprevalence of HIV among the Tanzania population. The 2008 round of sentinel surveillance of HIVamong pregnant women is being collected from 134 ANC sites in all 21 regions in MainlandTanzania.Another source of information that was sometimes used in estimating HIV prevalence rates inthe general population was data collected from blood donations. As a matter of policy, there ismandatory screening of blood that is used for blood transfusion. Data from this source were availablethroughout the country. Because for some years this was the only information available at the subnationallevel, it has been used as a proxy for HIV infection rates in those areas.From July 2007 to April 2008, Tanzania carried out the National Voluntary HIV TestingCampaign in all parts of the country. During this period, over 4 million Tanzanians were tested forHIV and results were made available to those tested. In some regions and districts, HIV test resultsfrom this campaign are being used to estimate the rate of HIV infection in those localities.While the rates of HIV infection from the above-mentioned sources are important and arebeing used in various settings, they cannot be used as a reliable estimate of the HIV prevalence ratefor the Tanzania population. The ANC data do not capture information on HIV prevalence in nonpregnantwomen, nor in women who do not attend clinics for ANC. Pregnant women are more at riskfor HIV infection than women who may be avoiding both HIV and pregnancy through the use ofcondoms or women who are less sexually active and therefore less likely to become pregnant orexpose themselves to HIV. In addition, there may be biases in the ANC surveillance data becauseHIV infection reduces fertility and knowledge of HIV status may influence fertility choices.Moreover, ANC data do not include socio-economic characteristics that may facilitate HIV infection.Finally, ANC data are sex selective; therefore, the rates among pregnant women are not a proxy formale HIV rates.Although blood donor data have been used widely in various areas, they have limitations.First, before the introduction of the National Blood Transfusion Services (NTS) in Tanzania, mostblood donors were relatives of the patient and hence were not representative of the general population.Secondly, it is likely that those who suspect that they might have contracted HIV do not volunteer todonate blood for fear of being tested and/or potentially infecting the patient. While the introduction ofthe NTS eliminated dependence on relatives of patients for blood donations, data from this sourceshould not be used to estimate the prevalence of HIV in the general population. This is because NTSaims at obtaining blood of the highest quality and does a lot of screening during recruitment ofdonors; hence, NTS has a very low rate of HIV infection, which underestimates the actual prevalencein the general population.The National Voluntary HIV Testing Campaign, which took place throughout the country,was voluntary. People came for testing by choice and no scientific methods were applied to obtaininformation about the clients.HIV Prevalence | 109
Thus, although the information from the ANC surveillance system and blood donor data havebeen useful for monitoring trends in HIV infection in Tanzania, and the national testing campaignprovided some prevalence data from different geographical locations of Tanzania, the HIV trendsobserved from the 2003-04 THIS and the 2007-08 THMIS give a clearer understanding of themagnitude and pattern of HIV infection in both Mainland Tanzania and Zanzibar. By usinginformation obtained from the two surveys, it is possible to see the trends in HIV infection throughoutTanzania.9.2 COVERAGE OF HIV TESTINGAll women and men age 15-49 living in the households selected for the 2007-08 THMIS wereeligible for the HIV testing component. Table 9.1 presents the coverage rates for HIV testing foreligible men and women by geographic location, while Table 9.2 presents coverage of HIV testing byselected background characteristics. Both tables are based on respondents who were eligible to betested. They show the proportion of people who were interviewed and consented to HIV testing, theproportion who were interviewed and refused to provide blood when asked, the proportion who wereabsent at the time of blood collection, and the proportion who were not tested for other reasons, suchas mismatch of questionnaires and blood samples, or technical problems in taking blood.A total of 17,670 adults (9,735 women and 7,935 men) were eligible for HIV testing. Overall,85 percent (90 percent of eligible women and 80 percent of eligible men) agreed to provide a bloodsample for HIV testing. The response rate was higher in rural than in urban areas (87 percent and 79percent respectively). Table 9.1 also shows that the response rate was higher among women thanamong men in both rural and urban areas.Overall, the proportion of eligible adults who provided a blood sample for HIV testing was 84percent for Mainland Tanzania and 89 percent for Zanzibar. Coverage of HIV testing by region rangesfrom 69 percent among adults in Dar es Salaam to 93 percent in Kagera. Rates are lower for men thanfor women in every region, mainly because of the higher proportion of men who were not interviewed.110 | HIV Prevalence
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TanzaniaHIV/AIDS and MalariaIndicat
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The 2007-08 Tanzania HIV/AIDS and M
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3.5 Access to Mass Media ..........
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12.2 Orphans and Vulnerable Childre
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Table 4.3Table 4.4Table 4.5Table 4.
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Figure 9.2 HIV Prevlence by Region/
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FOREWORDThis report presents the ma
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SUMMARY OF FINDINGSThe 2007-08 Tanz
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HIV prevalence among youth (women a
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xxii | Map of Tanzania
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1.2 NATIONAL POLICY ON HIV/AIDSIn r
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To assess levels and trends in know
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1.8 FIELDWORKData collection was ca
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Table 1.1 Results of the household
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Figure 2.1 presents a graphic pictu
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Table 2.3.1 Educational attainment
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Educational attainment is higher in
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2.5.1 Energy SourcesTable 2.5 prese
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The most common items are agricultu
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The 2007-08 THMIS included aquestio
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Table 3.1—ContinuedBackgroundchar
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Education is positively related to
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Table 3.3.2 Employment status: MenP
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Table 3.4.1 Exposure to mass media:
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3.6 CURRENT MARITAL STATUSMarriage
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Polygyny also varies by household w
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Four in ten women age 20-49 marry b
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There is a positive relationship be
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FERTILITY AND REPRODUCTIVE HEALTH 4
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Table 4.2 Fertility by background c
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infertility, 1 or the inability to
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4.3 ADOLESCENT FERTILITYAdolescent
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Table 4.7 Antenatal carePercent dis
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Table 4.8 Place of antenatal carePe
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Table 5.1 Knowledge of AIDSPercenta
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The use of condoms as an effective
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Table 5.3.2 Comprehensive knowledge
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Page 83 and 84: Table 5.5.1 Exposure to HIV educati
Page 85 and 86: 5.6 KNOWLEDGE AND ATTITUDE CONCERNI
Page 87 and 88: Table 5.6.2 Knowledge and attitudes
Page 89 and 90: Table 6.1.1 Accepting attitudes tow
Page 91 and 92: Stigma is also found to vary with l
Page 93 and 94: 6.3 ATTITUDES OF ADULTS TOWARDS EDU
Page 96 and 97: HIV/AIDS-RELATED BEHAVIOUR 77.1 INT
Page 98 and 99: Table 7.2.1 Recent sexual activity:
Page 100 and 101: Figure 7.1 Recent Sexual Intercours
Page 102 and 103: Table 7.3.2 Multiple sexual partner
Page 104 and 105: Table 7.4 Payment for sexual interc
Page 106 and 107: Table 7.5.1 Coverage of prior HIV t
Page 108 and 109: Figure 7.2 Prior HIV Testing by Edu
Page 110 and 111: 7.7 PREVALENCE OF SEXUALLY TRANSMIT
Page 112 and 113: Figure 7.3 Prevalence of STIs and S
Page 114: Table 7.8 Prevalence of medical inj
Page 117 and 118: Table 8.1 Comprehensive knowledge a
Page 119 and 120: Table 8.2 Age at first sexual inter
Page 121 and 122: Never-married women and men age 15-
Page 123 and 124: Figure 8.3 Condom Use at Premarital
Page 125 and 126: Table 8.5.2 Higher-risk sexual inte
Page 127 and 128: Table 8.6 Age-mixing in sexual rela
Page 129 and 130: 8.9 HIV TESTING AMONG YOUNG PEOPLEK
Page 134 and 135: Table 9.1 Coverage of HIV testing b
Page 136 and 137: Table 9.1—ContinuedBackgroundchar
Page 138 and 139: Table 9.3 HIV prevalence by ageAmon
Page 140 and 141: There are large variations in HIV p
Page 142 and 143: Table 9.5 shows that men who are cu
Page 144 and 145: Women who said they had higher-risk
Page 146 and 147: Table 9.8 shows data on HIV prevale
Page 148 and 149: Table 9.11 HIV prevalence by male c
Page 150 and 151: INFANT AND CHILD MORTALITY 1010.1 I
Page 152 and 153: As expected, the level of infant an
Page 154: category (1.41) is 41 percent highe
Page 157 and 158: 11.1 OWNERSHIP AND USE OF MOSQUITO
Page 159 and 160: carrying mosquitoes. Much of the fi
Page 161 and 162: 11.2 USE OF ANTIMALARIAL DRUGS DURI
Page 163 and 164: 11.3 TREATMENT OF CHILDREN WITH FEV
Page 165 and 166: 11.4.1 Type and Timing of Antimalar
Page 167 and 168: 11.4.2 Availability of Drug at Home
Page 169 and 170: 11.6 SOURCE OF MOSQUITO NETSUntil l
Page 171 and 172: In spite of steady increases in ITN
Page 174 and 175: ORPHANS AND VULNERABLE CHILDREN 12P
Page 176 and 177: 12.2 ORPHANS AND VULNERABLE CHILDRE
Page 178 and 179: 12.3.1 School Attendance by Survivo
Page 180 and 181: While there are no differences in p
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Table 12.7 Widows dispossessed of p
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Table 12.9 External support for orp
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REFERENCESAgot, K.E., J.O. Ndinya-A
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SAMPLE IMPLEMENTATIONAPPENDIX AAppe
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Table A.2 Sample implementation: Me
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Table A.4 Coverage of HIV testing a
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Table A.6 Coverage of HIV testing a
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where h represents the stratum whic
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Table B.2 Sampling errors for Natio
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Table B.4 Sampling errors for Rural
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Table B.6 Sampling errors for Mainl
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Table B.8 Sampling errors for Mainl
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Table B.10 Sampling errors for Zanz
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Table B.12 Sampling errors for Nort
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Table B.14 Sampling errors for Sout
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Table B.16 Sampling errors for East
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Table B.18 Sampling errors for Dodo
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Table B.20 Sampling errors for Kili
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Table B.22 Sampling errors for Moro
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Table B.24 Sampling errors for Dar
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Table B.26 Sampling errors for Mtwa
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Table B.28 Sampling errors for Irin
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Table B.30 Sampling errors for Sing
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Table B.32 Sampling errors for Rukw
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Table B.34 Sampling errors for Shin
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Table B.36 Sampling errors for Mwan
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Table B.38 Sampling errors for Many
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Table B.40 Sampling errors for Pemb
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216 | Appendix B
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Joyce MbambaYulitha MwakasoleRemigi
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QUESTIONNAIRESAppendix DAppendix D
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HOUSEHOLD SCHEDULEIntroduction and
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IF AGE 0-17 YEARSIF AGE 5 YEARS OR
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IF AGE 0-17 YEARSLINE SICK CARE SUR
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HOUSEHOLD CHARACTERISTICSNO. QUESTI
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NO. QUESTIONS AND FILTERS CODING CA
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SUPPORT FOR SICK PEOPLENO. QUESTION
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NO.QUESTIONS AND FILTERSSUPPORT FOR
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NO.QUESTIONS AND FILTERSCODING CATE
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CHILD 4 CHILD 5 CHILD 6502 LINE NUM
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515 CHECK 509:NUMBER OF CHILDREN WI
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UNITED REPUBLIC OF TANZANIATANZANIA
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213 214 215 216217 218219 220221222
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LAST BIRTH NEXT-TO-LAST BIRTH SECON
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LASTSEXUAL PARTNERSECOND-TO-LASTSEX
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SECTION 7 - HIV TESTTHIS PAGE TO BE
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