Intimate partner violence and HIV: embracing complexity

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

Standard Measures are Inadequate to Monitor Pediatric Adherence in a Resource-Limited Setting

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

No Association between HIV and Intimate Partner Violence among Women in 10 Developing Countries

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

Predicting Subnational Ebola Virus Disease Epidemic Dynamics from Sociodemographic Indicators

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