Literature DB >> 26223900

Risk factors for service use and trends in coverage of different HIV testing and counselling models in northwest Tanzania between 2003 and 2010.

Caoimhe Cawley1, Alison Wringe1, Jim Todd1,2, Annabelle Gourlay1, Benjamin Clark1,2, Clemens Masesa2, Richard Machemba2, Georges Reniers1, Mark Urassa2, Basia Zaba1.   

Abstract

OBJECTIVES: To investigate the relative effectiveness of different HIV testing and counselling (HTC) services in improving HIV diagnosis rates and increasing HTC coverage in African settings.
METHODS: Patient records from three HTC services [community outreach HTC during cohort study rounds (CO-HTC), walk-in HTC at the local health centre (WI-HTC) and antenatal HIV testing (ANC-HTC)] were linked to records from a community cohort study using a probabilistic record linkage algorithm. Characteristics of linked users of each HTC service were compared to those of cohort participants who did not use the HTC service using logistic regression. Data from three cohort study rounds between 2003 and 2010 were used to assess trends in the proportion of persons testing at different service types.
RESULTS: The adjusted odds ratios for HTC use among men with increasing numbers of sexual partners in the past year, and among HIV-positive men and women compared to HIV-negative men and women, were higher at WI-HTC than at CO-HTC and ANC-HTC. Among sero-survey participants, the largest numbers of HIV-positive men and women learned their status via CO-HTC. However, we are likely to have underestimated the numbers diagnosed at WI-HTC and ANC-HTC, due to low sensitivity of the probabilistic record linkage algorithm.
CONCLUSIONS: Compared to CO-HTC or ANC-HTC, WI-HTC was most likely to attract HIV-positive men and women, and to attract men with greater numbers of sexual partners. Further research should aim to optimise probabilistic record linkage techniques, and to investigate which types of HTC services most effectively link HIV-positive people to treatment services relative to the total cost per diagnosis made.
© 2015 The Authors. Tropical Medicine & International Health Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  HIV prevention; HIV testing and counselling; Tanzania; Tanzanie; asesoramiento y pruebas de VIH; conseil et dépistage du VIH; prevención del VIH; prévention du VIH

Year:  2015        PMID: 26223900      PMCID: PMC4832370          DOI: 10.1111/tmi.12578

Source DB:  PubMed          Journal:  Trop Med Int Health        ISSN: 1360-2276            Impact factor:   2.622


Introduction

The traditional model of HIV testing and counselling (HTC) service delivery in many countries in sub‐Saharan Africa has been at voluntary counselling and testing (VCT) centres, provided either as stand‐alone services or at clinics attached to health facilities. However, in response to a need to increase HTC uptake in sub‐Saharan Africa 1 and in recognition that alternative models of service delivery may help to reach different population groups, there has been a drive to diversify strategies for HTC service provision 2, 3, 4. These include HTC services offered routinely to pregnant women at antenatal clinics (ANC), or to attendees of outpatient departments such as sexually transmitted infection or tuberculosis clinics (provider‐initiated testing and counselling or PITC) 2, 5. Additional options for service provision include door‐to‐door testing provided to people in their homes, or temporary or mobile outreach HTC units provided to individuals within their communities or places of work 6, 7, 8, 9. In Tanzania, little is known regarding the relative effectiveness of different HTC models in attracting people with risky behaviours or HIV infection, or in identifying the greatest absolute numbers of HIV‐positive individuals at an early stage of infection – the latter group being particularly important to identify for the treatment as prevention programmes 10. We used community cohort data linked to facility records from three different HTC services in northwest Tanzania [community outreach testing (CO‐HTC), a walk‐in HTC centre at a health facility (WI‐HTC) and an antenatal testing service (ANC‐HTC)], to compare socio‐demographic, behavioural and clinical factors associated with HTC service use. We also assessed trends in the proportion of persons tested at different service types between 2003 and 2010, by HIV status and socio‐demographic characteristics.

Methods

Study setting

The Kisesa HIV community cohort study includes seven villages (adult population approximately 15 000 in 2012) and has conducted 28 approximately half‐yearly rounds of demographic surveillance since 1994, collecting information on residence and survival status of household members, pregnancy, births and migration. Seven rounds of serological and behavioural surveillance (sero‐surveys) have been completed every two‐three years over the same period, with eligibility defined as being resident at the last demographic surveillance round and aged 15 or older at the time of the sero‐survey. Participants were invited to a central location in each village to give finger‐prick blood samples for HIV‐research testing without results disclosure, completed an interview questionnaire on health‐ and HIV‐related knowledge and behaviours, and were offered VCT and free medical treatment for health problems 14, 15. Participation in sero‐surveys has declined over time and was 67% (8008/11 946) at the Sero6 round in 2010. HIV prevalence in the study area was estimated at 6.5% in 2010.

HIV testing and counselling services in the study area

Three HTC services are available in the study area: (i) a community outreach HTC (CO‐HTC) service operates within each village for approximately one month during sero‐surveys, since the fourth round in 2003/4; (ii) a walk‐in HTC (WI‐HTC) clinic has been permanently available at the study area's only health centre (located within the trading centre – approximately 70% of clients are from within the study area) since 2005; and (iii) PITC has been routinely offered to pregnant women attending the health centre ANC since the roll‐out of a prevention to mother‐to‐child transmission (PMTCT) programme in 2008. Antenatal testing (ANC‐HTC) may be carried out in the ANC or WI‐HTC building, dependant on the availability of staff and test‐kit supplies. All HTC services are provided free of charge.

Data sources – cohort data

During three sero‐surveys in 2003–2004 (Sero4), 2006–2007 (Sero5) and 2010 (Sero6), data on participants’ socio‐demographic characteristics, sexual and health‐seeking behaviours and reported prior use of any HTC services were collected and were used to investigate factors associated with CO‐HTC, WI‐HTC or ANC‐HTC use. HIV status for all study participants was determined using research test results. Area of residence is defined as rural (located away from the main road and between 5 and 10 km from the trading centre containing the health centre offering WI‐HTC and ANC‐HTC), roadside (villages located along the main tarmac road which runs through the study area), or within the trading centre.

Data sources – HTC data

Data on CO‐HTC use were obtained by deterministically linking unique anonymous identifiers assigned to those using the service to their research study record. Data from the WI‐HTC, including data on ANC‐HTC which occurred within the WI‐HTC building, were double‐entered for the period 2005–2012 (partial data for 2012). A probabilistic record linkage algorithm was developed to match users of the clinic HTC services (WI‐HTC and ANC‐HTC) to cohort study participants, based on measures of similarity (‘match‐scores’) between personal identifiers (name, sex, year of birth, village, sub‐village) in the two data sets 13. The CO‐HTC data set was used as a gold standard to train the record linkage algorithm. All possible cohort matches for each clinic ID were de‐duplicated and trimmed to select the most likely match for each clinic record (see Data S1). The final linked data set available for analyses contained 4046 clinic IDs matched to a cohort participant (linkage rate of 36.8% – 4046/10 994 WI‐HTC and ANC‐HTC clients matched), 1955 of whom (48.3%) were sero‐survey attendees. The final linked data set had low sensitivity (estimated at 17.8% based on the proportion of correctly matched gold‐standard links) but a positive predictive value (PPV) of 68.9%.

Statistical methods

The investigation of risk factors for CO‐HTC was a cross‐sectional analysis comparing the characteristics of all those who used the service compared to all those who did not use the service during Sero6 (Figure 1). For the analysis of WI‐HTC and ANC‐HTC use, a large proportion of cohort participants who were matched to a WI‐HTC or ANC‐HTC client with a low match likelihood were dropped from the data set, because the accuracy of the matches could not be confidently ascertained. The analyses assessing risk factors for WI‐HTC and ANC‐HTC use therefore used a restricted data set (i.e. did not include all sero‐survey participants) and employed case–control methods (Figure 1). For WI‐HTC use, cases were defined as Sero6 participants who were linked to a WI‐HTC client in the final linked data set, with a clinic visit occurring within 2 years of participation in Sero6. For cases with repeat WI‐HTC (18/187), only the first testing visit was used. Controls were selected from among those Sero6 participants who were not included in the final linked data set.
Figure 1

Flow diagram showing participation in Sero6 and individuals included in analyses of CO‐HTC, WI‐HTC and ANC‐HTC use. *This number includes some visitors (non‐residents in the study area) who are not included when calculating the eligible population. Therefore, the total number (and proportion) of eligible (i.e. Kisesa resident) individuals who used CO‐HTC is somewhat smaller than this.

Flow diagram showing participation in Sero6 and individuals included in analyses of CO‐HTC, WI‐HTC and ANC‐HTC use. *This number includes some visitors (non‐residents in the study area) who are not included when calculating the eligible population. Therefore, the total number (and proportion) of eligible (i.e. Kisesa resident) individuals who used CO‐HTC is somewhat smaller than this. For the analysis of risk factors associated with ANC‐HTC use, women attending either Sero5 or Sero6 were included to increase sample size (Figure 1). Cases were defined as women who participated in Sero5, reported a pregnancy between 2007 and 2010 and were linked to an ANC‐HTC client in the final linked data set with a testing visit within three years of Sero5, or women who participated in Sero6, reported a pregnancy between 2010 and 2012 and were linked to an ANC‐HTC client in the final linked data set with a testing visit within 2 years of Sero6. For cases with repeat ANC‐HTC (3/153), only the first testing visit was used. Controls were selected from Sero5 and Sero6 participants who were not included in the final linked data set and were defined as women who participated in either Sero5 or Sero6, and who reported a pregnancy between 2007 and 2010 (Sero5 attendees) or 2010 and 2012 (Sero6 attendees). A proportion of controls (11/78) (but no cases) participated in both Sero5 and Sero6; these were randomly assigned as a control for one or other round. Logistic regression models were fitted separately for men and women to identify characteristics independently associated with CO‐HTC, WI‐HTC or ANC‐HTC, using a forward‐fitting approach and including all variables significant in univariable analyses at the P ≤ 0.10 level. Likelihood ratio tests were used to assess the inclusion of variables in multivariable models (variable retained if it significantly improved model fit at P ≤ 0.10 level). Interactions were explored between HIV status and other characteristics previously found to be strongly associated with HTC use in this setting (area of residence, level of education and previous HTC use) 14, 15. Trends in the proportion of persons testing at different service types were assessed using data on actual or reported HTC use among participants of Sero4, Sero5 and Sero6, by HIV status and socio‐demographic characteristics. All statistical analyses were carried out in Stata 12 (StataCorp, TX, USA).

Ethical statement

Ethical approval for the activities carried out as part of the Kisesa cohort study, including linkage of WI‐HTC and ANC‐HTC clinic data to the research study data set, was granted by the Tanzanian Medical Research Coordinating Committee and the Ethics Committee of the London School of Hygiene and Tropical Medicine. Participation in sero‐surveys is based on informed consent without disclosure of HIV‐research test results, with a free CO‐HTC service available since Sero4 in 2003–2004 (just prior to the start of the Tanzanian national antiretroviral therapy programme). Verbal consent was obtained during Sero4, due to low literacy rates among the study population. This was witnessed and documented for each participant on their study questionnaire, by a member of the sero‐survey team. During Sero5 and Sero6, written consent was introduced (either a signature or a thumbprint, depending on the participant's writing ability).

Results

The analysis of CO‐HTC use among Sero6 attendees included 812 men and 1227 women who used HTC, and 2319 men and 3650 women who did not use HTC. For WI‐HTC, there were 75 male and 112 female Sero6 participants who were linked to a WI‐HTC client (cases), and 425 men and 390 women who were controls. For ANC‐HTC, 153 pregnant women were tested and linked to a Sero5 (85) or Sero6 (68) participant, and 76 pregnant women were controls (58 in Sero5 and 31 in Sero6).

Characteristics of HTC users

In adjusted analyses, men and women aged ≥55 had significantly lower odds of using CO‐HTC and WI‐HTC than those aged 15–24 (Tables 1 and 2). Among women, increasing educational attainment was significantly associated with both CO‐HTC and WI‐HTC but not with ANC‐HTC (Tables 2 and 3). Men and women living in roadside villages or in the trading centre had significantly higher odds of using all types of testing services compared to those living in rural villages, with the exception of WI‐HTC use among women, where the association did not quite reach statistical significance (Tables 1, 2, 3).
Table 1

Risk factors for community outreach HTC or walk‐in HTC among men attending Sero6 in 2010¶,⌂

Community outreach HTC (CO‐HTC)$ Walk‐in HTC (WI‐HTC)+
N % usingcOR95% CIaOR95% CI N % usingcOR95% CIaOR95% CI
Total313125.950015.0
Age
15–24149419.71116716.811
25–3445837.62.451.95–3.081.140.84–1.544323.31.50.67–3.400.580.21–1.61
35–4441735.72.271.79–2.88 1.140.83–1.586035.02.671.37–5.211.30.54–3.11
45–5431332.61.971.51–2.581.030.73–1.474812.50.710.28–1.830.40.13–1.22
>5544721.31.10.85–1.43 0.670.48–0.941825.50.290.14–0.610.240.10–0.59
Area of residence
Rural177215.81127811.211
Roadside76336.33.042.50–3.69 2.612.09–3.2612420.22.011.13–3.5821.04–3.85
Trading Centre59642.83.983.24–4.90 3.432.72–4.339819.41.921.03–3.581.270.62–2.61
Education
None45318.111386.51
Primary 1–432425.31.531.08–2.17606.71.020.30–3.46
Primary 5–7 1563 26.7 1.65 1.26–2.14 213 22.1 4.06 1.92–8.59
Secondary or higher77729.11.861.40–2.478916.92.911.21–6.97
Religion
Catholic110728.2117118.11
Other Christian141627.00.940.79–1.1319317.60.970.56–1.65
Traditional53015.80.480.37–0.631215.80.280.12–0.65
Muslim7544.021.25–3.221520.01.130.30–4.24
Marital status
Never married146620.10.550.46–0.6517616.51.410.82–2.44
Married monogamous132531.5125312.31
Married polygamous 128 37.5 1.3 0.89–1.90 26 34.6 3.79 1.56–9.24
Widowed4613.00.330.14–0.77238.70.680.15–3.05
Separated/divorced9733.01.070.69–1.661816.71.430.39–5.23
HIV status
Negative294725.9147214.21
<3 years since first positive research test11129.71.210.80–1.841827.82.320.80–6.73
>3 years since first positive research test5024.00.910.47–1.74540.04.030.66–24.57
Reported any previous HCT
No200519.2113868.811
Yes86345.53.522.96–4.192.131.74–2.6111136.96.063.60–10.225.152.79–9.50
Has an HIV‐positive relative
No213324.31133715.41
Yes47938.81.971.60–2.431.281.00–1.626021.71.520.77–3.00
Don't know27429.21.280.97–1.69 1.250.92–1.711039.70.590.29–1.21
Spouse HIV & VCT use status at Sero6
No spouse identified244424.91135417.01
Spouse HIV‐neg no VCT48419.40.730.57–0.930.560.42–0.751126.30.330.14–0.74
Spouse HIV‐pos no VCT2931.01.360.62–3.000.720.30–1.72728.61.960.37–10.34
Spouse HIV‐neg used VCT 16358.34.223.05–5.842.261.55–3.282321.71.360.49–3.81
Spouse HIV‐pos used VCT 1060.04.531.27–16.102.820.73–10.88333.32.450.22–27.45
Age at first sex
<1525621.50.540.40–0.740.640.44–0.924515.60.820.35–1.92
≥15178233.51129318.41
Never had sexγ 82511.20.250.20–0.320.320.23–0.44
Don't knowγ 23727.40.750.55–1.010.820.58–1.161588.90.430.23–0.80
Number of sexual partners in last year
None32221.10.580.43–0.780.650.46–0.915910.20.850.34–2.15 1.170.41–3.34
One131531.61124711.711
Two or more64036.21.231.01–1.501.120.89–1.429131.93.521.96–6.32 2.771.41–5.46
Never had sexγ 82511.20.270.21–0.35**
Don't knowγ 9811.20.950.45–1.99 0.870.33–2.28
Had a casual partner in last year
No179930.4134614.71
Yes47635.31.251.01–1.555424.11.830.92–3.66
Never had sexγ 82511.20.290.23–0.37
Don't knowγ 9811.20.730.37–1.46
Frequency of condom use with spouseα
Consistent450.02.10.30–14.981100.0
Inconsistent10643.41.611.08–2.411250.06.481.97–21.30
Never124132.2124713.41
No spouse83030.20.910.75–1.1011319.51.570.87–2.84
Never had sexγ 82511.20.260.21–0.34
Don't knowγ 9811.20.820.40–1.70
Frequency of condom use with regular partnerβ
Consistent3933.31.120.57–2.190.620.30–1.28633.32.940.52–16.42
Inconsistent5349.12.161.25–3.731.981.05–3.73540.03.910.64–23.97
Never11630.20.970.64–1.451.20.75–1.911540.03.911.34–11.44
No regular partner204430.91137114.61
Never had sex82511.20.280.22–0.36**
Don't know9811.20.740.37–1.48

¶, All characteristics as reported at Sero6 in 2010; cOR, crude OR; CI, confidence interval; aOR, adjusted OR; $, cross‐sectional analysis; +, case–control analysis.

⌂, Missing small proportions of data (<5%) for all variables with the exception of area of residence (no missing data), reported any previous HTC (8% missing), has an HIV‐positive relative (8% missing).

γ, Participants reporting ‘never had sex’ at Sero6 reassigned to ‘don't know’ category for WI‐HTC analysis, because these testing visits happened after the time of data collection.

*, Omitted because of colinearity; α, First/main spouse among men with more than one spouse; β, First reported regular partner among those with more than one.

Table 2

Risk factors for community outreach HTC or walk‐in HTC among women attending Sero6 in 2010¶,⌂

Community outreach HTC (CO‐HTC)$ Walk‐in HTC (WI‐HTC)+
N % usingcOR95% CIaOR95% CI N % usingcOR95% CIaOR95% CI
Total487725.250222.3
Age
15–24168923.3117837.211
25–34 113232.61.59 1.35–1.89 0.98 0.79–1.22 58 58.6 2.39 1.19–4.80 1.76 0.64–4.84
35–4481931.31.51.25–1.810.990.77–1.255255.82.131.04–4.352.50.87–7.21
45–5451626.71.20.96–1.510.90.67–1.215923.70.530.25–1.120.970.32–2.92
>557209.90.360.28–0.470.340.23–0.502552.40.040.02–0.100.430.11–1.61
Area of residence
Rural249314.01125820.21
Roadside 128434.7 3.27 2.78–3.84 2.96 2.47–3.55129 27.1 1.48 0.90–2.42
Trading Centre110039.54.023.40–4.743.813.14–4.6111521.71.10.64–1.88
Education
None182917.71132410.511
Primary 1–4 31428.3 1.84 1.40–2.411.330.98–1.802729.6 3.591.46–8.834.421.31–14.95
Primary 5–7221430.1 21.72–2.32 1.41.17–1.6912149.6 8.39 5.07–13.882.83 1.33–6.01
Secondary or higher51028.61.861.49–2.341.61.18–2.163033.34.261.84–9.862.310.74–7.27
Religion
Catholic206226.01120624.31
Other Christian243325.00.950.83–1.081.020.88–1.1920725.61.070.69–1.68
Traditional 25312.3 0.4 0 27–0 580.89 0.57–1.3967 4.5 0.15 0.04–0.49
Muslim11742.72.121.45–3.101.571.02–2.412025.01.040.36–3.01
Marital status
Never married100818.30.540.45–0.640.720.50–1.044932.70.920.47–1.810.420.07–2.44
Married monogamous 244829.4 11180 34.4 1 1
Married polygamous40229.61.010 80–1 271.110.86–1.444445.51.590.81–3.091.490.66–3.36
Widowed51213.10.360.28–0.470.570.36–0.891522.00.040.01–0.131.710.23–12.50
Separated/divorced46428.00.940.75–1.170.970.67–1.407414.90.330.16–0.684.350.75–25.30
HIV status
Negative450225.51147420.511
<3 years since first24624.00.920.68–1.240.590.42–0.822157.15.182.12–12.654.141.27–13.52
>3 years since first positive research test11314.20.480.28–0.820.260.15–0.46650.03.890.77–19.5611.60.68–198.17
Reported any previous HCT
No291117.51139615.211
Yes189437.32.822.47–3.221.491.27–1.7510348.55.283.29–8.491.890 95–3 79
Has an HIV‐positive relative
No3478 22.61137819.81
Yes114834.2 1.79 1.54–2.071.22 1.03–1.4592 33.7 2.05 1.24–3.39
Don't know19924.11.090.78–1.520.860.59–1.253218.80.930.37–2.35
Spouse HIV & VCT use status at Sero6
No spouse identified418025.31142521.91
Spouse HIV‐neg no VCT45014.00.480.37–0.630.550.41–0.756224.21.140.61–2.13
Spouse HIV‐pos no VCT3716.20.570.24–1.380.650.26–1.65540.02.380.39–14.45
Spouse HIV‐neg used VCT19649.52.92.17–3.872.171.57–3.00825.01.190.24–5.99
Spouse HIV‐pos used VCT944.42.370.63–8.832.490.59–10.41
Age at first sex
<1546720.60.60.48–0.770.750.57–0.977821.80.860.47–1.55
≥15343130.01131824.5 1
Never had sexγ 6128.70.220.17–0.300.250.16–0.39
Don't knowγ 33713.90.380.28–0.520.670.47–0.9510216.70.620.34–1.10
Number of sexual partners in last year
None85816.60.460.38–0.561.090.75–1.582251.80.03 0.01–0.07 0.03 0.00–0.22
One 3261 30.1 1 1 231 40.7 1 1
Two or more 100 44.0 1.83 1.22–2.73 1.81 1.15–2.86 4 50.0 1.46 0.20–10.53 0.2 0.01–4.04
Never had sexγ 612 8.7 0.22 0.16–0.29 * *
Don't knowγ 36 33.3 0.73 0.35–1.53 2.51 0.42–14.95
Had a casual partner in last year
No 4007 27.3 1 457 20.4 1 1
Yes 211 33.6 1.35 1.01–1.81 9 77.8 13.7 2.80–67.03 10.3 0.72–146.02
Never had sexγ 612 8.7 0.25 0.19–0.34
Don't knowγ 36 33.3 1.96 0.94–4.06 * *
Frequency of condom use with spouse
Consistent 0 0
Inconsistent 309 39.5 1.65 1.30–2.11 18 77.8 43 12.81–144.19 3.13 0.88–11.07
Never 2458 28.3 1 192 35.4 6.73 3.83–11.84 * *
No spouse1389 23.8 0.79 0.68–0.92 239 7.5 11
Never had sexγ 612 8.7 0.24 0.18–0.32
Don't knowγ 36 33.3 6.14 2.64–14.27 * *
Frequency of condom use with regular partnerβ
Consistent 39 33.3 1.38 0.71–2.69 0.93 0.43–1.99 3 33.3 1.94 0.17–21.62
Inconsistent 153 45.8 2.33 1.68–3.22 1.64 1.06–2.55 8 62.5 6.46 1.52–27.55
Never 206 32.0 1.3 0.96–1.76 1.4 0.93–2.12 11 36.4 2.22 0.63–7.74
No regular partner3814 26.6 1 1 439 20.5 1
Never had sexγ 612 8.7 0.26 0.20–0.35 * *
Don't knowγ 36 33.3 1.94 0.93–4.03

¶, All characteristics as reported at Sero6 in 2010; cOR, crude OR; CI, confidence interval; aOR, adjusted OR; $, cross‐sectional analysis; +, case–control analysis.

⌂, Missing small proportions of data (<3%) for all variables with the exception of area of residence (no missing data).

γ, Participants reporting ‘never had sex’ at Sero6 reassigned to ‘don't know’ category for WI‐HTC analysis, because these testing visits happened after the time of data collection.

*, Omitted because of colinearity; β, First reported regular partner among those with more than one.

Table 3

Risk factors for ANC‐HTC among women attending Sero5 or Sero6 and reporting pregnancies between 2007 and 2010 (Sero5 attendees) or 2010 and 2012 (Sero6 attendees)¶,⌂,+

N % usingcOR95% CIaOR95% CI
Total22966.8
Age
15–24 58 60.3 1
25–3411771.81.670.86–3.24
35–444468.21.410.62–3.21
45–541040.00.440.11–1.72
Area of residence
Rural 11453.51 1
Roadside7386.35.472.55–11.736.252.66–14.58
Trading Centre4269.11.940.91–4.112.390.97–5.86
Education
None 78 65.4 1
Primary 1–41478.61.940.50–7.56
Primary 5–712268.91.170.64–2.14
Secondary or higher1442.90.40.12–1.26
Religion
Catholic 82 65.9 1
Other Christian12268.01.10.61–2.00
Traditional1752.90.580.20–1.68
Muslim887.53.630.43–30.99
Marital status
Never married 25 48.00.35 0.15–0.83
Married monogamous16672.31
Married polygamous2657.70.520.22–1.22
Widowed2 0.0
Separated/divorced1060.00.580.16–2.13
HIV status
Negative 22066.8 1
<3 years since first positive research test560.00.740.12–4.56
>3 years since first positive research test366.70.990.09–11.13
Reported any previous HCT
No162 60.511
Yes6681.82.941.46–5.922.351.07–5.13
Spouse HIV & VCT use status at Sero6
No spouse identified16761.7 11
Spouse HIV‐neg, no VCT3482.42.91.14–7.396.582.11–20.57
Spouse HIV‐pos, no VCT250.00.620.04–10.110.530.02–11.91
Spouse HIV‐neg, used VCT2580.02.490.89–6.954.081.13–14.80
Spouse HIV‐pos, used VCT
Has an HIV‐positive relative
No 16670.5 11
Yes4271.41.050.50–2.21 0.730.30–1.78
Don't know2128.60.170.06–0.460.180.06–0.60
Age at first sex
<151163.6 0.79 0.22–2.78
≥1520069.01
Don't know1844.40.360.14–0.95
Number of sexual partners in last year
None666.70.88 0.16–4.93
One20369.51
Two or more1050.00.440.12–1.57
Don't know1030.00.190.05–0.75
Had a casual partner in last year
No 205 67.3 1 1
Yes1485.72.910.63–13.393.370.59–19.19
Don't know1030.00.210.05–0.830.340.07–1.51

¶, Pooled analysis – characteristics as reported at either Sero5 (2006/7) or Sero6 (2010).

⌂, Missing small proportions of data (<1%) for the following variables: education, HIV status, reported any previous HTC, spouse HIV & VCT use status at Sero6.

+, case–control analysis; cOR, crude OR; CI, confidence interval; aOR adjusted OR.

Risk factors for community outreach HTC or walk‐in HTC among men attending Sero6 in 2010¶,⌂ ¶, All characteristics as reported at Sero6 in 2010; cOR, crude OR; CI, confidence interval; aOR, adjusted OR; $, cross‐sectional analysis; +, case–control analysis. ⌂, Missing small proportions of data (<5%) for all variables with the exception of area of residence (no missing data), reported any previous HTC (8% missing), has an HIV‐positive relative (8% missing). γ, Participants reporting ‘never had sex’ at Sero6 reassigned to ‘don't know’ category for WI‐HTC analysis, because these testing visits happened after the time of data collection. *, Omitted because of colinearity; α, First/main spouse among men with more than one spouse; β, First reported regular partner among those with more than one. Risk factors for community outreach HTC or walk‐in HTC among women attending Sero6 in 2010¶,⌂ ¶, All characteristics as reported at Sero6 in 2010; cOR, crude OR; CI, confidence interval; aOR, adjusted OR; $, cross‐sectional analysis; +, case–control analysis. ⌂, Missing small proportions of data (<3%) for all variables with the exception of area of residence (no missing data). γ, Participants reporting ‘never had sex’ at Sero6 reassigned to ‘don't know’ category for WI‐HTC analysis, because these testing visits happened after the time of data collection. *, Omitted because of colinearity; β, First reported regular partner among those with more than one. Risk factors for ANC‐HTC among women attending Sero5 or Sero6 and reporting pregnancies between 2007 and 2010 (Sero5 attendees) or 2010 and 2012 (Sero6 attendees)¶,⌂,+ ¶, Pooled analysis – characteristics as reported at either Sero5 (2006/7) or Sero6 (2010). ⌂, Missing small proportions of data (<1%) for the following variables: education, HIV status, reported any previous HTC, spouse HIV & VCT use status at Sero6. +, case–control analysis; cOR, crude OR; CI, confidence interval; aOR adjusted OR. Self‐reported prior HTC was strongly associated with the use of all three testing service types. Men with two or more sexual partners in the last year were significantly more likely to use WI‐HTC compared to men with one partner (aOR: 2.77, 95% CI: 1.41–5.46; Table 1). While a similar trend for was seen for CO‐HTC use, the measure of effect was not as strong nor was the result statistically significant (aOR for men with two or more partners in the last year compared to those with one partner: 1.12, 95% CI: 0.89–1.42; Table 1). Although a larger proportion of women with two or more partners in the last year used WI‐HTC compared to those with one partner (50% vs. 41%), this was not statistically significant, likely due to the small number reporting two or more sexual partners (n = 4; Table 2). For the analysis of CO‐HTC use, women with two or more sexual partners in the last year were statistically significantly more likely to test compared to those with one partner (aOR: 1.81, 95% CI: 1.15–2.86; Table 2). In adjusted analyses, there was weak evidence (based on a small sample size of nine women, resulting in wide confidence intervals) for an association between having a casual partner in the last year and WI‐HTC use (aOR: 10.25, 95% CI: 0.72–146.02; Table 2), but a similar finding was not observed among CO‐HTC users. There was some evidence that HIV‐positive individuals were more likely to use WI‐HTC than HIV‐negatives. Among men, the results did not quite reach statistical significance (Table 1); however, women who were HIV‐positive <3 years since first positive research test had higher odds of using WI‐HTC than HIV‐negatives (aOR: 4.14, 95% CI: 1.27–13.52; Table 2). The result was just short of reaching statistical significance for women HIV‐positive ≥3 years since first positive research test, although the trend was in the same direction. In contrast, HIV‐positive men and women were not more likely to use CO‐HTC or ANC‐HTC compared to HIV‐negative individuals (Tables 1, 2, 3). For CO‐HTC use, there was an interaction between HIV status and previous HTC use. Men and women HIV‐positive ≥3 years since first positive research test who reported previous HTC were significantly less likely to use CO‐HTC than HIV‐negative individuals (men: OR: 0.30, 95% CI: 0.12–0.74; women: aOR: 0.18, 95% CI: 0.09–0.36). However, these individuals were not significantly more or less likely to use CO‐HTC if they reported no prior HTC (men: OR: 1.98, 95% CI: 0.75–5.24; women: aOR: 0.68, 95% CI: 0.27–1.72; P values for interaction: men: P = 0.01, women: P = 0.06).

HIV prevalence by service type

Based on sero‐survey research test results, HIV prevalence was highest among WI‐HTC users (men: 9.5%, women: 13.4%) compared to CO‐HTC users (men: 5.6%, women: 6.1%) or ANC‐HTC users (4.9%) (Figure 2). Among HIV‐positive individuals, differences in the proportions testing at an early stage of infection (<3 years since first positive research test) by testing service type were not statistically significant, but sample sizes were small for WI‐HTC (men: seven positive individuals, women: 15 positive individuals) and ANC‐HTC (five positive women), so results should be interpreted with caution (men: CO‐HTC: 72.1%, WI‐HTC: 71.4%, chi‐square test P = 0.9; women: CO‐HTC: 79.5%, WI‐HTC: 80.0%, ANC‐HTC: 40%, chi‐square test P = 0.12; Figure 2).
Figure 2

Proportion testing HIV‐positive (based on sero‐survey research test results) by time since first positive research test and HTC service type. N represents total sample size, with bars showing percentage of who tested HIV‐positive.

Proportion testing HIV‐positive (based on sero‐survey research test results) by time since first positive research test and HTC service type. N represents total sample size, with bars showing percentage of who tested HIV‐positive.

Trends in the proportion of persons ever tested by HIV status

The proportion of HIV‐negative individuals receiving their first test at WI‐HTC or ANC‐HTC has grown over time, particularly among women and those aged 25–44 (Figure 3a). By Sero6, similar proportions of HIV‐negative women had first tested at CO‐HTC (18.6%) or WI‐HTC (18.1%), while the greatest proportion of HIV‐negative men had first tested at CO‐HTC (23.9%, vs. 7.9% first testing at WI‐HTC). The greatest proportions of HIV‐positive individuals were diagnosed at CO‐HTC. However, we are likely to have underestimated the proportions of HIV‐positive individuals diagnosed at WI‐HTC and ANC‐HTC due to the low sensitivity of the final linked data set, and reliance on reports of previous HTC use for which we did not know the test result. At the later sero‐survey rounds in particular, increasing proportions of HIV‐positive individuals reported previous HTC (at the WI‐HTC, ANC‐HTC or elsewhere – 9.5% of all HIV‐positive individuals at Sero5 and 30.2% of all HIV‐positive individuals at Sero6), but it was unknown whether testing occurred before or after seroconversion (Figure 3b).
Figure 3

Location of (a) first test for HIV‐negative individuals, (b) diagnosis for previously undiagnosed HIV‐positive individuals (actual or reported HTC use), among attendees of Seros 4, 5 and 6 by sex, age group and area of residence.

Location of (a) first test for HIV‐negative individuals, (b) diagnosis for previously undiagnosed HIV‐positive individuals (actual or reported HTC use), among attendees of Seros 4, 5 and 6 by sex, age group and area of residence.

Discussion

Our results revealed that WI‐HTC was more likely to attract men with greater numbers of sexual partners in the last year than CO‐HTC. A similar pattern was not observed among women, although the numbers of women reporting two or more sexual partners in the last year were small, particularly among WI‐HTC users, possibly as a result of social desirability biases 16. This may have affected our ability to detect any association between numbers of sexual partners and WI‐HTC use among women. There was also evidence that WI‐HTC was more likely to attract HIV‐positive men and women than the other testing modalities. This is in agreement with other studies which found that stand‐alone or clinic‐based HTC identified larger proportions of HIV‐positive patients than mobile or outreach testing services 8, 17, 18. Users of client‐initiated WI‐HTC may be motivated by recent exposures or by suspicions that they are HIV‐infected, due to symptoms or death of a partner. Conversely, CO‐HTC and ANC‐HTC represent more passive opportunities to test and therefore may attract relatively fewer high‐risk individuals. However, the aforementioned studies found that outreach testing services were better at facilitating earlier HIV diagnosis clinic‐based services, which tended to diagnose patients at a later stage of infection. We did not find evidence for significant differences in HIV diagnoses by stage of infection by testing service type (Figure 2), but our analyses were limited by small sample sizes, particularly for users of WI‐HTC and ANC‐HTC. Among sero‐survey participants, the largest numbers of HIV‐positive men and women learned their status via CO‐HTC. However, this may not be true in the wider population, if we had been able to take account of WI‐HTC and/or ANC‐HTC use among individuals who did not attend sero‐surveys. We are also likely to have underestimated the numbers diagnosed at WI‐HTC and ANC‐HTC, due to low linkage sensitivity and reliance on reports of HTC use in the past for which we did not know test results (for 4% of HIV‐positive individuals at Sero4, 10% of HIV‐positive individuals at Sero5 and 30% of HIV‐positive individuals at Sero6). Nevertheless, CO‐HTC is likely to represent an efficient model of service delivery in which large numbers of people were reached in a short period of time. Achieving high HTC coverage is an important objective of HIV prevention programmes in sub‐Saharan Africa, and a number of studies have found that uptake rates are highest when testing is provided as an outreach service 6, 8, 9, 17, 19. One meta‐analysis reported that in 14 studies, most of which were conducted in sub‐Saharan Africa, 87% of individuals accepted mobile outreach HTC when it was offered 9. This is considerably higher than the uptake of CO‐HTC in Kisesa, which was 25% at Sero6. Differences in uptake of outreach HTC between settings may relate to the way in which services are provided, for example whether services are offered independently or as part of a research activity, levels of community mobilisation, and/or differences in the prevalence of HIV‐related stigma between settings. In terms of treatment as prevention, it will be important that HTC services can be regularly accessed, and to understand which services most effectively link HIV‐positive individuals to care and treatment 20. The three main HTC services in this setting attracted users with different socio‐demographic profiles. Overall, WI‐HTC attracted a greater proportion of women than men, while the proportions of women and men using CO‐HTC were more even (Figure 3). By Sero6 in 2010, a larger proportion of women had ever tested at any HTC service compared to men. These findings concur with other studies which found that men were less likely to use health facility‐based HTC compared to women 18, 21 and that larger numbers of women had ever tested overall 5, 22 In adjusted analyses, WI‐HTC was less likely to attract individuals aged ≥55 compared to those aged 15–24, and less likely to recruit women with no education compared to those with primary education. While similar patterns for age group and level of education were seen for CO‐HTC, the measures of effect were not as strong. A number of studies have shown that outreach testing and some types of PITC reach proportionately older and less educated clients compared to walk‐in HTC 18, 23, 24, and we similarly found that access to CO‐HTC and ANC‐HTC appeared more equitable in terms of these socio‐demographic characteristics compared to WI‐HTC. However, there were inequities in access by area of residence for all testing service types, with the exception of WI‐HTC use among women. It was somewhat surprising that men and women living in rural areas were considerably less likely to use CO‐HTC seeing as this service was provided within the village. Larger distances to the health centre (where HIV care services are available), perceived lack of need, stigma or residual confounding by unmeasured socio‐economic factors may be some of the reasons explaining this finding. Policies that aim to promote and normalise HTC in rural villages may help to increase the uptake of testing in these areas. Unlike many studies relying on data collected at HTC clinics, a key strength of our analysis was the linkage of community cohort and clinic data, allowing comparison of factors associated with uptake of three different HTC services at the community level. Nevertheless, the final linked data set had low sensitivity (17.8% – many clinic records were dropped during the validation procedures), and this may have introduced some biases which need consideration. Linked individuals included in the WI‐HTC analyses were less likely to be male compared to records not included (33%% vs. 37%%, P = 0.004). This may have led us to underestimate the proportions of men using WI‐HTC. Linked individuals included in the WI‐HTC and ANC‐HTC analyses were also more likely to be older (P < 0.001) and less likely to have secondary education (P = 0.002) compared to those not included, which may have led us to underestimate the strength of associations between age and/or educational attainment and WI‐HTC or ANC‐HTC use. WI‐HTC and ANC‐HTC clients included in analyses may also have differed from those not included in other ways which we were unable to measure, and small sample sizes may have prevented us from detecting weaker effects for some risk factors. Nevertheless, our results are broadly in line with previous studies that compared the characteristics of users of similar types of HTC services at other sites in sub‐Saharan Africa 18, 23, 24, giving confidence in our study findings. We have seen a declining participation in sero‐surveys over time. Declines in participation have been greatest among young men, likely as a result of migration for work. Previous research has shown that migration is associated with a higher risk of HIV infection 25 and also that HIV‐positive individuals are less likely to participate in population‐based research 26, 27, 28. This may have resulted in underestimates of the strength of the associations between HIV status, sexual risk behaviours (numbers of sexual partners, condom use, etc.) and CO‐HTC, WI‐HTC and ANC‐HTC use, particularly among men. However, previous analyses have shown similar factors to be associated with CO‐HTC use over successive rounds of the Kisesa cohort study 14, 15, suggesting that the bias introduced by declining participation is likely to be small. The proportions of individuals who used the CO‐HTC service offered at Sero6 but who did not consent to completing the questionnaire were small (estimated at <4% of all those eligible), and so this is unlikely to have biased the estimates of risk factors associated with CO‐HTC use. Sensitivity analyses were explored which increased the PPV of the linked WI‐HTC and ANC‐HTC clinic‐cohort data sets from 68.9% to 85.0%. These did not change the overall direction of any of our findings, although in some cases they strengthened associations (as expected given that random error should be reduced in higher PPV data sets), giving confidence in our findings. An additional strength of our study was the ability to explore associations between HIV status and HTC use due to knowledge of HIV status among both testers and non‐testers.

Conclusions

Of the three services available, the odds of attracting high‐risk men, and HIV‐positive men and women, was greatest at WI‐HTC. Among sero‐survey participants, the largest numbers of HIV‐positive men and women learned their status via CO‐HTC. However, we are likely to have underestimated the numbers diagnosed at WI‐HTC and ANC‐HTC due to low sensitivity of the probabilistic record linkage algorithm. Further research should aim to optimise probabilistic record linkage techniques in order to maximise their sensitivity and positive predictive value and should investigate which types of HTC services most effectively link HIV‐positive people to treatment services relative to the total cost per diagnosis made. Data S1. Development and validation of the probabilistic record linkage algorithm. Click here for additional data file.
  26 in total

1.  Increasing access to HIV counseling and testing through mobile services in Kenya: strategies, utilization, and cost-effectiveness.

Authors:  Kristina L Grabbe; Nick Menzies; Miriam Taegtmeyer; Gideon Emukule; Patrick Angala; Irene Mwega; Geraldine Musango; Elizabeth Marum
Journal:  J Acquir Immune Defic Syndr       Date:  2010-07       Impact factor: 3.731

2.  Unfinished business--expanding HIV testing in developing countries.

Authors:  Kevin M De Cock; Rebecca Bunnell; Jonathan Mermin
Journal:  N Engl J Med       Date:  2006-02-02       Impact factor: 91.245

3.  Client characteristics and gender-specific correlates of testing HIV positive: a comparison of standalone center versus mobile outreach HIV testing and counseling in Botswana.

Authors:  Julia E Hood; Duncan MacKellar; Anne Spaulding; Rob Nelson; Boingotlo Mosiakgabo; Bangwato Sikwa; Innocentia Puso; Jan Raats; Peter Loeto; Mary Grace Alwano; Blessed Monyatsi
Journal:  AIDS Behav       Date:  2012-10

4.  Secretive females or swaggering males? An assessment of the quality of sexual partnership reporting in rural Tanzania.

Authors:  Soori Nnko; J Ties Boerma; Mark Urassa; Gabriel Mwaluko; Basia Zaba
Journal:  Soc Sci Med       Date:  2004-07       Impact factor: 4.634

5.  Trends and measurement of HIV prevalence in northern Malawi.

Authors:  Amelia C Crampin; Judith R Glynn; Bagrey M Ngwira; Frank D Mwaungulu; Jörg M Pönnighaus; David K Warndorff; Paul E Fine
Journal:  AIDS       Date:  2003-08-15       Impact factor: 4.177

6.  Increasing the acceptability of HIV counseling and testing with three C's: convenience, confidentiality and credibility.

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Journal:  Soc Sci Med       Date:  2009-04-15       Impact factor: 4.634

Review 7.  From caution to urgency: the evolution of HIV testing and counselling in Africa.

Authors:  R Baggaley; B Hensen; O Ajose; K L Grabbe; V J Wong; A Schilsky; Y-R Lo; F Lule; R Granich; J Hargreaves
Journal:  Bull World Health Organ       Date:  2012-06-27       Impact factor: 9.408

8.  Socio-economic determinants of HIV testing and counselling: a comparative study in four African countries.

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Journal:  Trop Med Int Health       Date:  2013-09       Impact factor: 2.622

Review 9.  Uptake of home-based voluntary HIV testing in sub-Saharan Africa: a systematic review and meta-analysis.

Authors:  Kalpana Sabapathy; Rafael Van den Bergh; Sarah Fidler; Richard Hayes; Nathan Ford
Journal:  PLoS Med       Date:  2012-12-04       Impact factor: 11.069

10.  Trends in the uptake of voluntary counselling and testing for HIV in rural Tanzania in the context of the scale up of antiretroviral therapy.

Authors:  Raphael Isingo; Alison Wringe; Jim Todd; Mark Urassa; Doris Mbata; Griter Maiseli; Rose Manyalla; John Changalucha; Julius Mngara; Ester Mwinuka; Basia Zaba
Journal:  Trop Med Int Health       Date:  2012-08       Impact factor: 2.622

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1.  Bottlenecks to HIV care and treatment in sub-Saharan Africa: a multi-country qualitative study.

Authors:  Alison Wringe; Jenny Renju; Janet Seeley; Mosa Moshabela; Morten Skovdal
Journal:  Sex Transm Infect       Date:  2017-07       Impact factor: 3.519

2.  Impact of linkage quality on inferences drawn from analyses using data with high rates of linkage errors in rural Tanzania.

Authors:  Christopher T Rentsch; Katie Harron; Mark Urassa; Jim Todd; Georges Reniers; Basia Zaba
Journal:  BMC Med Res Methodol       Date:  2018-12-10       Impact factor: 4.615

3.  Point-of-contact interactive record linkage (PIRL) between demographic surveillance and health facility data in rural Tanzania.

Authors:  Christopher T Rentsch; Georges Reniers; Chodziwadziwa Kabudula; Richard Machemba; Baltazar Mtenga; Katie Harron; Paul Mee; Denna Michael; Redempta Natalis; Mark Urassa; Jim Todd; Basia Zaba
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4.  Processes and dynamics of linkage to care from mobile/outreach and facility-based HIV testing models in hard-to-reach settings in rural Tanzania. Qualitative findings of a mixed methods study.

Authors:  Erica S Sanga; Ferdinand C Mukumbang; Adiel K Mushi; Willyhelmina Olomi; Wondwossen Lerebo; Christina Zarowsky
Journal:  AIDS Res Ther       Date:  2018-11-20       Impact factor: 2.250

5.  Linkage to care and antiretroviral therapy initiation by testing modality among individuals newly diagnosed with HIV in Tanzania, 2014-2017.

Authors:  Christopher T Rentsch; Alison Wringe; Richard Machemba; Denna Michael; Mark Urassa; Jim Todd; Georges Reniers; Basia Zaba
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