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Direct measures of HIV incidence are needed to assess the population-level impact of prevention programs but are scarcely available in the subnational epidemic hotspots of sub-Saharan Africa. We created a sentinel HIV incidence cohort within a community-based program that provided home-based HIV testing to all residents of Namibia’s Zambezi region, where approximately 24% of the adult population was estimated to be living with HIV.
The aim of this study was to estimate HIV incidence, detect correlates of HIV acquisition, and assess the feasibility of the sentinel, community-based approach to HIV incidence surveillance in a subnational epidemic hotspot.
Following the program’s initial home-based testing (December 2014-July 2015), we purposefully selected 10 clusters of 60 to 70 households each and invited residents who were HIV negative and aged ≥15 years to participate in the cohort. Consenting participants completed behavioral interviews and a second HIV test approximately 1 year later (March-September 2016). We used Poisson models to calculate HIV incidence rates between baseline and follow-up and multivariable Cox proportional hazard models to assess the correlates of seroconversion.
Among 1742 HIV-negative participants, 1624 (93.23%) completed follow-up. We observed 26 seroconversions in 1954 person-years (PY) of follow-up, equating to an overall incidence rate of 1.33 per 100 PY (95% CI 0.91-1.95). Among women, the incidence was 1.55 per 100 PY (95% CI 1.12-2.17) and significantly higher among those aged 15 to 24 years and residing in rural areas (adjusted hazard ratio [aHR] 4.26, 95% CI 1.39-13.13;
Nearly three decades into Namibia’s generalized HIV epidemic, these are the first estimates of HIV incidence for its highest prevalence region. By creating a sentinel incidence cohort from the infrastructure of an existing community-based testing program, we were able to characterize current transmission patterns, corroborate known risk factors for HIV acquisition, and provide insight into the efficacy of prevention interventions in a subnational epidemic hotspot. This study demonstrates an efficient and scalable framework for longitudinal HIV incidence surveillance that can be implemented in diverse sentinel sites and populations.
Namibia has a generalized epidemic with 237,000 adults (13.3%) living with HIV [
Namibia, like most countries with generalized epidemics, has limited ability to assess the impact of prevention interventions and monitor HIV incidence over time. The gold standard for measuring HIV incidence is a longitudinal cohort study, which entails enrolling persons uninfected at baseline and following them over time with repeated testing to detect acquisition of infection. Owing to the perceived high cost and logistical complexity, few surveillance cohort studies have been conducted around the world in recent years [
A pragmatic method for tracking HIV incidence may be found in the sentinel approach to surveillance [
We conducted a sentinel HIV incidence cohort study by adding behavioral measurements and repeated testing to an existing community-based program offering home testing in Namibia’s Zambezi region. Our objectives were to estimate HIV incidence, detect new or confirm known risk and preventive factors for HIV acquisition, and assess the feasibility of the sentinel approach to HIV incidence surveillance in a subnational epidemic hotspot.
The study was a prospective cohort implemented in households in Namibia’s Zambezi region, situated in the northeast bordering Angola, Botswana, Zambia, and Zimbabwe. Zambezi was chosen because it has the highest prevalence of HIV in the country (23.7%) [
TCE mapped all households in the Zambezi region and divided them into 60 programmatic
TCE staff approached all households in the sites to offer home-based HIV testing to all residents from December 2015 to July 2016. Residents were identified by the head of the household and assigned unique testing codes. GPS coordinates were recorded at each household to facilitate household identification. Residents aged ≥15 years who received the TCE program were invited to complete a baseline interview. Clients who tested negative for HIV were invited to participate in the cohort.
Data on exposure to prevention interventions (eg, HIV testing outside the study, ART use in serodiscordant partnerships, and medical male circumcision), HIV-related risk and preventive behaviors (eg, multiple partners and transactional sex), and demographic characteristics (eg, sex, age, and marital status) were obtained in face-to-face interviews.
Rapid HIV testing was done in the participant’s household by TCE staff following the national parallel algorithm, including Alere Determine HIV-1/2 (Abbott Diagnostic Division) and Uni-Gold Recombigen HIV-1/2 (Trinity Biotech) with Clearview Complete HIV-1/2 (Inverness Medical) to resolve discrepant results. Results from the rapid testing algorithm were immediately returned to participants with posttest counseling.
TCE staff collected dried blood spot (DBS) specimens from participants by finger prick on Whatman 903 filter paper. DBS were dried and packaged according to the manufacturer’s instructions and shipped weekly to the National Institute of Pathology reference laboratory in Windhoek and stored at −70°C to −80°C. A fourth-generation enzyme-linked immunosorbent assay (Vironostika Uniform II bioMérieux-Diagnostics) was used on DBS for quality assurance to confirm every 10th HIV-negative and all HIV-positive rapid test results at baseline and follow-up. Quality assurance results were not returned to the participants. Additional quality assurance was performed according to national standards, including proficiency panels for counselors throughout the study.
Cohort participants were recontacted approximately 12 months after enrollment to complete a follow-up interview and HIV test using the same procedures.
Proportions and 95% CIs were calculated to describe the characteristics of the cohort. We used baseline interview data for demographic characteristics, prior testing history, partner’s HIV status, and male circumcision. We used follow-up interview data for variables that may have changed from baseline to follow-up, including seeking testing for HIV outside of the study, transactional sex, sex with partners residing outside of the study sites, condom use, and multiple sex partners. We used generalized linear models to assess baseline correlates of cohort participation and completion of follow-up.
Rates of HIV incidence were calculated as the number of seroconversions per 100 person-years (PY) of follow-up. PY was calculated as the number of days between baseline and follow-up/365 for participants who did not seroconvert and one-half the number of days between baseline and follow-up/365 for participants who seroconverted, which is a commonly used technique when the exact date of seroconversion is unknown [
Participants gave verbal informed consent at baseline and again at follow-up. Participants aged 15 to 17 years gave their assent and were required to have consent from a parent or guardian. No monetary or material incentives were provided. The study was approved by the Institutional Review Boards of the Ministry of Health and Social Services in Namibia and the University of California, San Francisco. The study was reviewed in accordance with the Centers for Disease Control and Prevention (CDC) human research protection procedures and determined to be research, although CDC investigators did not interact with human subjects or have access to identifiable data or specimens for research purposes. All procedures were implemented in accordance with the ethical standards of the abovementioned ethics committees and the Helsinki Declaration of 1975, as revised in 2000.
The TCE program offered home-based testing to 1004 households across the 5 sites (
Flow diagram of household listing, receipt of home-based HIV testing, participation in the cohort study and follow-up measurements among adults age ≥ 15 years in five community-based sites of the Zambezi region of Namibia, 2014-2016.
Demographic characteristics and HIV-related risk behaviors of the cohort participants who completed the follow-up are shown in
Demographic and behavioral characteristics of HIV-negative participants who completed baseline and follow-up measurements—household cohort study of adults aged ≥15 years in the Zambezi region of Namibia, 2014 to 2016 (N=1624).
Variable | Total, n (%) | Women (n=914), n (%) | Men (n=710), n (%) | |
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15-19 | 301 (18.53) | 176 (19.3) | 125 (17.6) |
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20-24 | 379 (23.34) | 222 (24.3) | 157 (22.1) |
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25-29 | 253 (15.58) | 134 (14.7) | 119 (16.8) |
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30-34 | 195 (12.01) | 107 (11.7) | 88 (12.4) |
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35-39 | 152 (9.36) | 69 (7.5) | 83 (11.7) |
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40-44 | 92 (5.67) | 50 (5.5) | 42 (5.9) |
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45-49 | 63 (3.88) | 30 (3.3) | 33 (4.6) |
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50-64 | 189 (11.64) | 126 (13.8) | 63 (8.9) |
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Ngweze urban | 384 (23.65) | 230 (25.2) | 154 (21.7) |
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Mavuluma urban | 356 (21.92) | 217 (23.7) | 139 (19.6) |
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Bukalo rural | 368 (22.66) | 175 (19.1) | 193 (27.2) |
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Ngoma rural | 201 (12.38) | 101 (11.1) | 100 (14.1) |
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Sibbinda rural | 315 (19.40) | 191 (20.9) | 124 (17.5) |
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Rural | 887 (54.62) | 468 (51.2) | 419 (59.0) |
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Urban | 737 (45.38) | 446 (48.8) | 291 (41.0) |
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15-24, rural | 328 (20.20) | 169 (18.5) | 159 (22.4) |
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15-24, urban | 354 (21.80) | 229 (25.1) | 125 (17.6) |
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≥25, rural | 559 (34.42) | 299 (32.7) | 260 (36.6) |
|
≥25, urban | 383 (23.58) | 217 (23.7) | 166 (23.4) |
Currently marrieda | 644 (39.66) | 381 (41.7) | 263 (37.0) | |
Tested for HIV in the 12 months before enrollmenta | 485 (29.86) | 315 (34.5) | 170 (23.9) | |
Tested with a partner at enrollmenta | 463 (28.51) | 264 (28.9) | 199 (28.0) | |
Had a serodiscordant positive partner (among those tested with a partner at enrollment)a | 40 (8.6) | 13 (4.9) | 27 (13.6) | |
Partner on antiretroviral treatment (among those with serodiscordant positive testing partner)a,b | 11 (27.5) | 4 (30.8) | 7 (25.9) | |
Circumcised (among men only)a | N/Ac | N/A | 32 (4.6) | |
Sought HIV testing outside the study in past 12 monthsd | 212 (13.05) | 133 (14.6) | 79 (11.1) | |
Had sex partner residing outside study area in the past 12 monthsb,d | 144 (11.70) | 84 (12.4) | 60 (10.8) | |
Engaged in transactional sex in the past 12 monthsd | 44 (2.71) | 8 (0.9) | 36 (5.1) | |
Used a condom at the last sexual encounterb,d | 677 (54.82) | 381 (56.0) | 296 (53.3) | |
Used condoms consistently with all sex partners in past the 12 monthsb,d | 119 (9.64) | 58 (8.5) | 61 (11.0) | |
Had multiple sex partners in the past 12 monthsd | 38 (2.34) | 12 (1.3) | 26 (3.7) |
aData collected at baseline.
bAmong participants who reported having any sex partners between baseline and follow-up (n=1235, including 680 women and 555 men).
cN/A: not applicable.
dData collected at follow-up.
There were 26 seroconversions in 1954 PY among the 1624 baseline HIV-negative participants who completed the follow-up (
HIV incidence per 100 person-years by sex and demographic and behavioral characteristics—household cohort study of adults aged ≥15 years in the Zambezi region of Namibia, 2014 to 2016 (N=1624).
Variable | Women | Men | |||||
|
Incident infections | Rate per 100 person, years (CI)a | Incident infections | Rate per 100 person, years (CI) | |||
Overall | 17 | 1.55 (1.12-2.17) | .29 | 9 | 1.05 (0.54-2.31) | Refb | |
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15-19 | 5 | 2.42 (0.97-7.34) | .42 | 0 | 0.00 (0.00-2.44) | —d |
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20-24 | 5 | 1.88 (1.05-3.57) | .68 | 1 | 0.53 (0.01-2.93) | Ref |
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25-29 | 2 | 1.23 (0.31-8.52) | Ref | 1 | 0.69 (0.02-3.87) | .80 |
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30-34 | 4 | 3.09 (1.68-6.61) | .40 | 2 | 1.86 (0.50-12.51) | .25 |
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35-39 | 0 | 0.00 (0.00-4.53) | — | 1 | 1.00 (0.03-5.57) | .60 |
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40-44 | 0 | 0.00 (0.00-6.25) | — | 4 | 8.21 (3.76-21.14) | <.001 |
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45-49 | 1 | 2.89 (0.07-16.10) | .61 | 0 | 0.00 (0.00-9.23) | — |
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50-64 | 0 | 0.00 (0.00-2.34) | — | 0 | 0.00 (0.00-4.95) | — |
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No | 14 | 2.20 (1.38-3.49) | .03 | 6 | 1.12 (0.49-2.87) | .79 |
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Yes | 3 | 0.65 (0.25-2.21) | Ref | 3 | 0.94 (0.38-3.08) | Ref |
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Ngweze urban | 5 | 1.88 (1.23-3.02) | <.001 | 1 | 0.58 (0.01-3.21) | Ref |
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Mavuluma urban | 3 | 1.17 (0.41-3.86) | Ref | 2 | 1.29 (0.16-4.64) | .75 |
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Bukalo rural | 3 | 1.47 (0.41-5.40) | .36 | 3 | 1.31 (0.27-3.84) | .58 |
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Ngoma rural | 2 | 1.59 (1.46-1.76) | .005 | 2 | 1.61 (1.34-1.96) | .34 |
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Sibbinda rural | 4 | 1.81 (0.75-5.83) | .11 | 1 | 0.70 (0.02-3.89) | .94 |
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Rural | 9 | 1.62 (0.99-2.76) | .53 | 6 | 1.20 (0.51-3.60) | .54 |
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Urban | 8 | 1.47 (0.91-2.48) | Ref | 3 | 0.85 (0.23-5.36) | Ref |
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15-24 and rural | 7 | 3.59 (1.60-8.69) | .04 | 0 | 0.00 (0.00-1.94) | — |
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15-24 and urban | 3 | 1.08 (0.66-1.93) | .58 | 1 | 0.65 (0.02-3.64) | Ref |
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≥25 and rural | 2 | 0.56 (0.14-3.59) | Ref | 6 | 1.93 (0.94-5.01) | .08 |
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≥25 and urban | 5 | 1.88 (0.83-4.92) | .18 | 2 | 0.99 (0.31-4.48) | .36 |
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No | 14 | 1.97 (1.32-2.95) | .05 | 5 | 0.77 (0.32-2.31) | .11 |
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Yes | 3 | 0.78 (0.33-2.41) | Ref | 4 | 1.95 (1.03-4.24) | Ref |
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No | 16 | 2.05 (1.41-2.98) | .05 | 7 | 1.15 (0.54-2.75) | .57 |
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Yes | 1 | 0.30 (0.01-1.69) | Ref | 2 | 0.82 (0.22-5.47) | Ref |
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No | 0 | 0.00 (0.00-1.18) | — | 1 | 0.47 (0.01-2.63) | Ref |
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Yes | 1 | 6.82 (0.17-38.01) | Ref | 1 | 3.06 (0.08-17.03) | .23 |
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No | 1 | 9.94 (0.25-55.38) | Ref | 1 | 4.07 (0.10-22.68) | Ref |
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Yes | 0 | 0.00 (0.00-80.02) | — | 0 | 0.00 (0.00-45.26) | — |
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No | N/Ae | N/A | — | 9 | 1.13 (0.58-2.49) | Ref |
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Yes | N/A | N/A | — | 0 | 0.00 (0.00-9.78) | — |
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No | 11 | 1.17 (0.68-2.12) | .14 | 4 | 0.53 (0.17-2.42) | .03 |
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Yes | 6 | 3.72 (1.64-9.27) | Ref | 5 | 5.23 (1.99-16.65) | Ref |
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No | 13 | 1.82 (1.31-2.57) | .13 | 4 | 0.67 (0.30-1.73) | .05 |
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Yes | 3 | 2.98 (1.62-6.71) | Ref | 2 | 2.79 (0.34-10.07) | Ref |
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No | 15 | 1.38 (0.88-2.24) | .01 | 9 | 1.11 (0.55-2.51) | Ref |
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Yes | 2 | 22.75 (3.79-100) | Ref | 0 | 0.00 (0.00-8.52) | — |
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No | 9 | 2.52 (1.15-5.08) | .37 | 1 | 0.32 (0.08-1.76) | .23 |
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Yes | 7 | 1.53 (0.84-3.03) | Ref | 5 | 1.41 (0.45-7.42) | Ref |
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No | 14 | 1.88 (1.45-2.48) | .98 | 7 | 1.21 (0.62-2.72) | .64 |
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Yes | 2 | 2.82 (0.67-20.52) | Ref | 1 | 0.87 (0.02-4.60) | Ref |
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No | 15 | 1.38 (0.89-2.25) | .02 | 9 | 1.09 (0.56-2.41) | Ref |
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Yes | 2 | 14.78 (3.81-94.41) | Ref | 0 | 0.00 (0.00-12.07) | — |
aCIs are cluster-robust unless there are 1 or 0 seroconversions, in which case the CI is Poisson exact. CI is 2-sided 95% except when there are 0 seroconversions, in which cases CI is 1-sided 97.5%.
b
cData collected at baseline.
d
eN/A: not applicable.
fData collected at follow-up.
HIV incidence per 100 person-years by age, residence, and sex; household cohort of adults age ≥ 15 years in the Zambezi region of Namibia, 2014-2016 (N=1624). Error bars in the figure represent two-sided 95% CI, except when there were 0 seroconversions, in which case CI are one-sided and 97.5%.
In the multivariable model for women (
Correlates of HIV seroconversion among women and men, multivariable Cox proportional hazards models, and household cohort study of adults aged ≥15 years in the Zambezi region of Namibia, 2014 to 2016 (N=1624).
Variable | Full model, adjusted hazards ratio (95% CI)a | Final model, adjusted hazards ratio (95% CI)a | |||
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15-24 years old and resident of rural site (vs other age and residential groups)b | 4.17 (1.37-12.65) | .01 | 4.26 (1.39- 13.13) | .01 |
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Resident of Ngoma rural (vs residents of other sites)b | 0.55 (0.05-5.70) | .62 | —c | — |
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Resident of Ngweze urban (vs residents of other sites)b | 2.13 (1.08-4.18) | .03 | 2.34 (1.25- 4.40) | .01 |
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Not currently married (vs married)b | 1.34 (0.58-3.07) | .49 | — | — |
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Not tested with partner at enrollment (vs tested with partner)b | 5.95 (0.65-54.3) | .13 | — | — |
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Not tested for HIV in the 12 months before enrollment (vs tested)b | 3.12 (0.91-10.68) | .07 | 3.38 (1.04-10.95) | .05 |
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Engaged in transactional sex (vs did not engage in transactional sex)d | 10.33 (2.48- 42.95) | .001 | 17.64 (2.88-108.14) | .02 |
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Had multiple sex partners in the past 12 months (vs did not have multiple partners)d | 3.17 (0.58-17.48) | .19 | — | — |
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Age 40-44 years (vs other age groups)b | 6.90 (2.75-17.34) | <.001 | 13.04 (5.98-28.41) | <.001 |
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Older and residing in a rural site (vs other age and residential groups)b | 7.90 (0.65-96.49) | .11 | — | — |
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Sought testing for HIV outside the study in the past 12 months (vs did not seek testing)d | 35.23 (12.40-100.06) | <.001 | 8.28 (1.39-49.38) | .02 |
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Had a sex partner residing outside the study area (vs did not have partner outside study area)d | 2.31 (0.68-7.88) | .18 | — | — |
aAll CIs are 2-sided 95% and cluster robust.
b Data collected at baseline.
cVariables at
dData collected at follow-up.
Our longitudinal, sentinel cohort study reports the first directly observed measure of HIV incidence in the adult population of Zambezi, Namibia. Nearly three decades into Namibia’s epidemic, this is the first estimate of incidence for its most severely affected region. Our measure of 1.33 per 100 PY, compared with modeled HIV incidence for all Namibia during this period (0.78 per annum) [
We were able to detect significant correlates of HIV seroconversion that can be used to understand the extent to which existing HIV prevention interventions are working and where additional interventions should be delivered. These include where to prioritize the deployment and scale-up of effective biomedical interventions such as enhanced test and treatment strategies and PrEP. AGYW living in rural areas had more than four times the likelihood of acquiring HIV infection compared with other women. HIV incidence among men was highest in the 40- to 44-year-old group and among older men in rural areas. These findings are consistent with a pattern of intergenerational, heterosexual transmission observed across sub-Saharan Africa [
Few recent direct measures of HIV incidence are available from longitudinal studies elsewhere in sub-Saharan Africa. HIV incidence was 2.4 per 100 PY (95% CI 2.00-2.54) in a national population-based cohort in Eswatini from 2010 to 2011 [
Our longitudinal sentinel incidence surveillance study points to moderately high internal validity (eg, the robustness of correlates of HIV acquisition within the sentinel population). Nearly three-fourths (3261/4490, 72.63%) of residents accepted home-based testing by TCE, of whom 68.02% (2218/3261) participated in our cohort. Participation was lower than that observed in the Eswatini (73.8%) [
Although our results are encouraging that sentinel surveillance integrated within existing testing programs can track HIV incidence and demonstrate prevention impact, we recognize limitations. First, the sample size and few incident infections resulted in low precision for HIV incidence in subgroups, low statistical power to detect smaller effects for HIV acquisition, and an increased chance that some correlates may be because of chance. As the incidence is declining in the current era, larger sample sizes are needed to measure the impact of prevention programs. Nonetheless, the sentinel incidence surveillance approach has two advantages for increasing statistical power: purposely choosing populations with high HIV incidence and leveraging programs already testing large numbers of persons at risk. If community-based testing programs are already in place, the sentinel approach can be scaled up to include more sites with minimal additional resources, forming an integrated national system similar to antenatal clinic sentinel surveillance for HIV prevalence [
By design, we deliberately chose the sentinel population within the most severely affected region of Namibia and purposively selected a limited number of clusters for the sake of efficiency. Unlike the studies in Eswatini [
We tested an efficient method to obtain a directly observed, longitudinal measure of HIV incidence in a high-prevalence region of Namibia. Nearly three decades into Namibia’s epidemic, this is the first estimate of the incidence for this region. With the achievement of its target sample, high retention, and ability to detect correlates of seroconversion, our approach appears to be a viable community-based surveillance method that could be replicated in other settings serviced by similar testing programs. We believe this approach can strike a reasonable balance between the additional resources required and the ability to generate direct measures of prevention impact. As HIV testing becomes increasingly accessible and frequent, more opportunities to measure incidence through active and passive repeat testing will arise. Longitudinal sentinel incidence surveillance can be integrated into other community-based programs or facilities conducting high numbers of repeat HIV tests, such as antenatal and sexually transmitted infection clinics [
adolescent girls and young women
adjusted hazard ratio
antiretroviral treatment
Centers for Disease Control and Prevention
dried blood spot
men who have sex with men
people living with HIV
pre-exposure prophylaxis
person-years
Total Control of the Epidemic
For their hard work and dedication to the study, the authors thank the field officers and other staff of TCE Zambezi, including Beauty Muyoba, Beauty Mumbela, Catherine Milinga, Cecilia Mantanyani, Charity Ntema, Charity Silengano, Christopher Mayumbelo, Dorcus Mubiana, Grace Sinvula, Josephine Sombelo, Kabende Frederick, Kaela Alpha, Kwala Ednah, Matengu Musohwa, Melody Katangu, Mildred Mwilima, Nalisa Norrister, Namatama Phoustinah, Nicky Kakwena, Petronah Munzie Mubonda, Raphael Siyanga, Sarriety Bushihu, Simon M. Mukena, Progress Muzamai, Namasiku Fellyster, Moderia Mafulata, Viona Chenjekwa, and Doctrine Mukelebai. This study was funded by the President’s Emergency Plan for AIDS Relief through the CDC under the terms of cooperative agreement no. U2GGH000977. The findings and conclusions in this manuscript are those of the authors and do not necessarily represent the official position of the funding agency. Internal review was required by the finding agency before authorization for submission.
None declared.