A risk measurement tool for targeted HIV prevention measures amongst young pregnant and lactating women in South Africa

Background We aimed to develop and validate a tool to identify which pregnant/lactating young South African women (<= 24 years) are at risk of HIV infection. Methods Data from three national South African Prevention of Mother-to-Child Transmission (PMTCT) evaluations were used to internally validate three HIV acquisition risk models for young postpartum women. We used univariate and multivariable logistic regression analysis to determine which risk factors were significant. Model coefficients were rounded and stratified into risk groups and the area under the receiver operating curve (AUROC) was computed. Models were developed to determine which risk factors provided the most predictive accuracy whilst remining clinically meaningful. Results Data from 9 456 adult and 4 658 young pregnant and lactating women were included in the development and validation data sets, respectively. The optimal model included the following risk factors: age (20-24 years old), informal house structure, two or more pregnancies, mothers who had knowledge of when they received their last HIV test result, no knowledge of the infant's father's HIV status, no knowledge of breastfeeding as a mode of MTCT and knowledge of PMTCT programme. The mean AUROC was 0.71 and 0.72 in the development and validation datasets respectively. The optimum cut off score was >= 27, having 84% sensitivity, 44% specificity, and identifying 44% of high-risk women eligible for PrEP. Conclusion The optimal model to be used as a possible risk scoring tool to allow for early identification of those pregnant/lactating women most at-risk of HIV acquisition included both statistically as well as clinically meaningful risk factors. A field-based study is needed to test and validate the effectiveness of this targeted approach.

Automated summary

This study aimed to develop and validate a tool to identify pregnant/lactating young South African women at highest risk of HIV acquisition, identifying several key risk factors to consider.