Using routine programmatic data to measure HIV incidence among pregnant women in Botswana.

INTRODUCTION: Pregnant women in sub-Saharan Africa have high risk of HIV acquisition, yet approaches for measuring maternal HIV incidence using routine surveillance systems are undefined. We used programmatic data from routine antenatal care (ANC) HIV testing in Botswana to measure real-world HIV incidence during pregnancy. METHODS: From January 2018 to September 2019, the Botswana Ministry of Health and Wellness implemented an HIV testing program at 139 ANC clinics. The program captured information on testers' age, testing date and result, and antiretroviral treatment (ART) initiation. In our analysis, we excluded individuals who previously tested HIV-positive prior to their first ANC visit. We defined incident HIV infection as testing HIV-positive at an ANC visit after a prior HIV-negative result within ANC. RESULTS: Overall, 29,570 pregnant women (median age 26 years, IQR 22-31) tested for HIV at ANC clinics: 3% (836) tested HIV-positive at their first recorded ANC visit and 97% tested HIV-negative (28,734). Of those who tested HIV-negative, 28% (7940/28,734) had a repeat HIV test recorded at ANC. The median time to HIV re-testing was 92 days (IQR 70-112). In total, 17 previously undiagnosed HIV infections were detected (HIV incidence 8 per 1000 person-years, 95% CI 0.5-1.3). ART initiation among women newly diagnosed with HIV at ANC (853) was 88% (671/762). CONCLUSIONS: In Botswana, real-world HIV incidence among pregnant women at ANC remains above levels of HIV epidemic control (≤ 1 per 1000 person-years). This study shows how HIV programmatic data can answer timely population-level epidemiological questions and inform ongoing implementation of HIV prevention and treatment programs.

HIV testing criteria to reduce testing volume and increase positivity in Botswana.

OBJECTIVE: We used data from a routine HIV testing program to develop risk scores to identify patients with undiagnosed HIV infection while reducing the number of total tests performed. DESIGN: Multivariate logistic regression. METHODS: We included demographic factors from HIV testing data collected in 134 Botswana Ministry of Health & Wellness facilities during two periods (1 October 2018- 19 August 2019 and 1 December 2019 to 30 March 2020). In period 2, the program collected additional demographic and risk factors. We randomly split each period into prediction/validation datasets and used multivariate logistic regression to identify factors associated with positivity; factors with adjusted odds ratios at least 1.5 were included in the risk score with weights equal to their coefficient. We applied a range of risk score cutoffs to validation datasets to determine tests averted, test positivity, positives missed, and costs averted. RESULTS: In period 1, three factors were significantly associated with HIV positivity (coefficients range 0.44-0.87). In period 2, 12 such factors were identified (coefficients range 0.44-1.37). In period 1, application of risk score cutoff at least 1.0 would result in 50% fewer tests performed and capture 61% of positives. In period 2, a cutoff at least 1.0 would result in 13% fewer tests and capture 96% of positives; a cutoff at least 2.0 would result in 40% fewer tests and capture 83% of positives. Costs averted ranged from 12.1 to 52.3%. CONCLUSION: Botswana's testing program could decrease testing volume but may delay diagnosis of some positive patients. Whether this trade-off is worthwhile depends on operational considerations, impact of testing volume on program costs, and implications of delayed diagnoses.