Person:

Harling, Guy

This study aims to compare the use and cost of objective and subjective measures of adherence to pediatric antiretroviral treatment in a primary care facility in South Africa. In a 1-month longitudinal study of 53 caregiver-child dyads, pharmacy refill (PR), measurement of returned syrups (RS), caregiver self-report (3DR) and Visual Analogue Scale (VAS) were compared to Medication Event Monitoring System (MEMS). Adherence was 100% for both VAS and 3DR; by PR and RS 100% and 103%, respectively. MEMS showed that 92% of prescribed doses were administered, but only 66% of these within the correct 12-hourly interval. None of the four measures correlated significantly with MEMS. MEMS data suggest that timing of doses is often more deviant from prescribed than expected and should be better addressed when monitoring adherence. Of all, MEMS was by far the most expensive measure. Alternative, cheaper electronic devices need to be more accessible in resource-limited settings.

BACKGROUND: Intimate Partner Violence (IPV) has been reported to be a determinant of women's risk for HIV. We examined the relationship between women's self-reported experiences of IPV in their most recent relationship and their laboratory-confirmed HIV serostatus in ten low- to middle-income countries. METHODOLOGY/PRINCIPAL FINDINGS: Data for the study came from the most recent Demographic and Health Surveys conducted in Dominican Republic, Haiti, India, Kenya, Liberia, Malawi, Mali, Rwanda, Zambia and Zimbabwe. Each survey population was a cross-sectional sample of women aged 15-49 years. Information on IPV was obtained by a face-to-face interview with the mother with an 81.1% response rate; information on HIV serostatus was obtained from blood samples with an 85.3% response rate. Demographic and socioeconomic variables were considered as potentially confounding covariates. Logistic regression models accounting for multi-stage survey design were estimated individually for each country and as a pooled total with country fixed effects (n = 60,114). Country-specific adjusted odds ratios (OR) for physical or sexual IPV compared to neither ranged from 0.45 [95% confidence interval (CI): 0.23-0.90] in Haiti to 1.35 [95% CI: 0.95-1.90] in India; the pooled association was 1.03 [95% CI: 0.94-1.13]. Country-specific adjusted ORs for physical and sexual IPV compared to no sexual IPV ranged from 0.41 [95% CI: 0.12-1.36] in Haiti to 1.41 [95% CI: 0.26-7.77] in Mali; the pooled association was 1.05 [95% CI: 0.90-1.22]. CONCLUSIONS: IPV and HIV were not found to be consistently associated amongst ever-married women in national population samples in these lower income countries, suggesting that IPV is not consistently associated with HIV prevalence worldwide. More research is needed to understand the circumstances in which IPV and HIV are and are not associated with one another.

Objectives: This study evaluated the validity of using respondents’ reports of age disparity in their sexual relationships (perceived disparity), compared to age disparity based on each partner's report of their own date of birth (actual disparity). Setting: The study was conducted using data from a longitudinal population-based cohort in rural KwaZulu-Natal, South Africa, between 2005 and 2012. Participants: The study used 13 831 reports of partner age disparity within 7337 unique conjugal relationships. 10 012 (72.4%) reports were made by women. Primary and secondary outcome measures The primary outcome was the Lin concordance correlation of perceived and actual age disparities. Secondary outcomes included the sensitivity/specificity of perceived disparities to assess whether the man in the relationship was more than five or more than 10 years older than the woman. Results: Mean relationship age disparity was 6 years. On average, respondents slightly underestimated their partners’ ages (male respondents: 0.50 years; female respondents: 0.85 years). Almost three-quarters (72.3%) of age disparity estimates fell within 2 years of the true values, although a small minority of reports were far from correct. The Lin concordance correlation of perceived and actual age disparities (men: ρ=0.61; women: ρ=0.78), and assessments of whether the man in the relationship was more than five, or more than 10 years older than the woman (sensitivity >60%; specificity >75%), were relatively high. Accuracy was higher for spouses and people living in the same household, but was not affected by relationship duration. Conclusions: Rural South Africans reported their sexual partners’ ages imperfectly, but with less error than in some other African settings. Further research is required to determine how generalisable these findings are. Self-reported data on age disparity in sexual relationships can be used with caution for research, intervention design, and targeting in this and similar settings.

Background

The recent Ebola virus disease (EVD) outbreak in West Africa has spread wider than any previous human EVD epidemic. While individual-level risk factors that contribute to the spread of EVD have been studied, the population-level attributes of subnational regions associated with outbreak severity have not yet been considered.

Methods

To investigate the area-level predictors of EVD dynamics, we integrated time series data on cumulative reported cases of EVD from the World Health Organization and covariate data from the Demographic and Health Surveys. We first estimated the early growth rates of epidemics in each second-level administrative district (ADM2) in Guinea, Sierra Leone and Liberia using exponential, logistic and polynomial growth models. We then evaluated how these growth rates, as well as epidemic size within ADM2s, were ecologically associated with several demographic and socio-economic characteristics of the ADM2, using bivariate correlations and multivariable regression models.

Results

The polynomial growth model appeared to best fit the ADM2 epidemic curves, displaying the lowest residual standard error. Each outcome was associated with various regional characteristics in bivariate models, however in stepwise multivariable models only mean education levels were consistently associated with a worse local epidemic.

Discussion

By combining two common methods—estimation of epidemic parameters using mathematical models, and estimation of associations using ecological regression models—we identified some factors predicting rapid and severe EVD epidemics in West African subnational regions. While care should be taken interpreting such results as anything more than correlational, we suggest that our approach of using data sources that were publicly available in advance of the epidemic or in real-time provides an analytic framework that may assist countries in understanding the dynamics of future outbreaks as they occur.

Introduction: Individuals’ educational attainment has long been considered as a risk factor for HIV. However, little attention has been paid to the association between partner educational attainment and HIV infection. Methods: We conducted cross-sectional analysis of young women (aged 15–34) in 14 Demographic and Health Surveys from seven sub-Saharan Africa (SSA) countries with generalized HIV epidemics. We measured the degree of similarity in educational attainment (partner homophily) in 75,373 partnerships and evaluated the correlation between homophily and female HIV prevalence at the survey cluster level. We then used logistic regression to assess whether own and partner educational attainment was associated with HIV serostatus amongst 38,791 women. Results: Educational attainment was positively correlated within partnerships in both urban and rural areas of every survey (Newman assortativity coefficients between 0.09 and 0.44), but this correlation was not ecologically associated with HIV prevalence. At the individual level, larger absolute differences between own and partner educational attainment were associated with significantly higher HIV prevalence amongst women. This association was heterogeneous across countries, but not between survey waves. In contrast to other women, for those aged 25–34 who had secondary or higher education, a more-educated partner was associated with lower HIV prevalence. Conclusions: HIV prevalence amongst women in SSA is associated not only with one's own education but also with that of one's partner. These findings highlight the importance of understanding how partners place individuals at risk of infection and suggest that HIV prevention efforts may benefit from considering partner characteristics.

Dick Durevall and Annika Lindskog (January, 2015) explore the association between intimate partner violence (IPV) and HIV infection in Demographic and Health Survey (DHS) data.1 We welcome Durevall and Lindskog's examination of the confluence of risk factors that might place women at risk of HIV infection, building from our earlier analysis of an overlapping set of DHS datasets,2 and their careful interpretation of the results they find. However, we believe that Sunita Kishor's interpretation of their study,3 in relation to our earlier study on the same question,2 necessitates some elaboration to ensure an accurate interpretation of this analysis.

Background List randomization (LR), a survey method intended to mitigate biases related to sensitive true/false questions, has received recent attention from researchers. However, tests of its validity are limited, with no study comparing LR-elicited results with individually known truths. We conducted a test of LR for HIV-related responses in a high HIV prevalence setting in KwaZulu-Natal. By using researcher-known HIV serostatus and HIV test refusal data, we were able to assess how LR and direct questionnaires perform against individual known truth.

Methods Participants were recruited from the participation list from the 2016 round of the Africa Health Research Institute demographic surveillance system, oversampling individuals who were HIV positive. Participants were randomized to two study arms. In Arm A, participants were presented five true/false statements, one of which was the sensitive item, the others non-sensitive. Participants were then asked how many of the five statements they believed were true. In Arm B, participants were asked about each statement individually. LR estimates used data from both arms, while direct estimates were generated from Arm B alone. We compared elicited responses to HIV testing and serostatus data collected through the demographic surveillance system.

Results We enrolled 483 participants, 262 (54%) were randomly assigned to Arm A, and 221 (46%) to Arm B. LR estimated 56% (95% CI: 40 to 72%) of the population to be HIV-negative, compared to 47% (95% CI: 39 to 54%) using direct estimates; the population-estimate of the true value was 32% (95% CI: 28 to 36%). LR estimates yielded HIV test refusal percentages of 55% (95% CI: 37 to 73%) compared to 13% (95% CI: 8 to 17%) by direct estimation, and 15% (95% CI: 12 to 18%) based on observed past behavior.

Conclusions In this context, LR performed poorly when compared to known truth, and did not improve estimates over direct questioning methods when comparing with known truth. These results may reflect difficulties in implementation or comprehension of the LR approach, which is inherently complex. Adjustments to delivery procedures may improve LR’s usefulness. Further investigation of the cognitive processes of participants in answering LR surveys is warranted.

Objectives: To assess the effect of two health system approaches to distribute HIV self-tests on the number of female sex workers’ client and nonclient sexual partners. Design: Cluster randomized controlled trial. Methods: Peer educators recruited 965 participants. Peer educator–participant groups were randomized 1 : 1 : 1 to one of three arms: delivery of HIV self-tests directly from a peer educator, free facility-based delivery of HIV self-tests in exchange for coupons, or referral to standard-of-care HIV testing. Participants in all three arms completed four peer educator intervention sessions, which included counseling and condom distribution. Participants were asked the average number of client partners they had per night at baseline, 1 and 4 months, and the number of nonclient partners they had in the past 12 months (at baseline) and in the past month (at 1 month and 4 months). Results: At 4 months, participants reported significantly fewer clients per night in the direct delivery arm (mean difference −0.78 clients, 95% CI −1.28 to −0.28, P = 0.002) and the coupon arm (−0.71, 95% CI −1.21 to −0.21, P = 0.005) compared with standard of care. Similarly, they reported fewer nonclient partners in the direct delivery arm (−3.19, 95% CI −5.18 to −1.21, P = 0.002) and in the coupon arm (−1.84, 95% CI −3.81 to 0.14, P = 0.07) arm compared with standard of care. Conclusion: Expansion of HIV self-testing may have positive behavioral effects enhancing other HIV prevention efforts among female sex workers in Zambia. Trial Registration: ClinicalTrials.gov NCT02827240.