Regression discontinuity analysis demonstrated varied effect of Treat-All on CD4 testing among Southern African countries.

OBJECTIVE: To determine whether Treat-All policy impacted laboratory testing practices of antiretroviral therapy (ART) programs in Southern Africa. STUDY DESIGN AND SETTING: We used HIV cohort data from Lesotho, Malawi, Mozambique, South Africa, Zambia and Zimbabwe in a regression discontinuity design to estimate changes in pre-ART CD4 testing and viral load monitoring following national Treat-all adoption that occurred during 2016 to 2017. This study included more than 230,000 ART-naïve people living with HIV (PLHIV) aged five years or older who started ART within two years of national Treat-All adoption. RESULTS: We found pre-ART CD4 testing decreased following adoption of Treat-All recommendations in Malawi (-21.4 percentage points (pp), 95% confidence interval, CI: -26.8, -16.0) and in Mozambique (-8.8pp, 95% CI: -14.9, -2.8), but increased in Zambia (+2.7pp, 95% CI: +0.4, +5.1). Treat-All policy had no effect on viral load monitoring, except among females in South Africa (+7.1pp, 95% CI: +1.1, +13.0). CONCLUSION: Treat-All policy expanded ART eligibility, but led to reductions in pre-ART CD4 testing in some countries that may weaken advanced HIV disease management. Continued and expanded support of CD4 and viral load laboratory capacity is needed to further improve treatment successes and allow for uniform evaluation of ART implementation across Southern Africa.

Cost-effectiveness of PrEP in HIV/AIDS control in Zambia: a stochastic league approach.

BACKGROUND: Earlier antiretroviral therapy initiation and pre-exposure prophylaxis (PrEP) prevent HIV, although at a substantial cost. We use mathematical modeling to compare the cost-effectiveness and economic affordability of antiretroviral-based prevention strategies in rural Macha, Zambia. METHODS: We compare the epidemiological impact and cost-effectiveness over 40 years of a baseline scenario (treatment initiation at CD4 <350 cells/µL) with treatment initiation at CD4 <500 cells per microliter, and PrEP (prioritized to the most sexually active, or nonprioritized). A strategy is cost effective when the incremental cost-effectiveness ratio (ICER) is <$3480 (<3 times Zambian per capita GDP). Stochastic league tables then predict the optimal intervention per budget level. RESULTS: All scenarios will reduce the prevalence from 6.2% (interquartile range, 5.8%-6.6%) in 2014 to about 1% after 40 years. Compared with the baseline, 16% of infections will be averted with prioritized PrEP plus treatment at CD4 <350, 34% with treatment at CD4 <500, and 59% with nonprioritized PrEP plus treatment at CD4 <500. Only treating at CD4 <500 is cost effective: ICER of $62 ($46-$75). Nonprioritized PrEP plus treating at CD4 <500 is borderline cost effective: ICER of $5861 ($3959-$8483). Initiating treatment at CD4 <500 requires a budget increase from $20 million to $25 million over 40 years, with a 96.7% probability of being the optimal intervention. PrEP should only be considered when the budget exceeds $180 million. CONCLUSIONS: Treatment initiation at CD4 <500 is a cost-effective HIV prevention approach that will require a modest increase in budget. Although adding PrEP will avert more infections, it is not economically feasible, as it requires a 10-fold increase in budget.

Hospitalizations and costs incurred at the facility level after scale-up of malaria control: pre-post comparisons from two hospitals in Zambia.

There is little evidence on the impact of malaria control on the health system, particularly at the facility level. Using retrospective, longitudinal facility-level and patient record data from two hospitals in Zambia, we report a pre-post comparison of hospital admissions and outpatient visits for malaria and estimated costs incurred for malaria admissions before and after malaria control scale-up. The results show a substantial reduction in inpatient admissions and outpatient visits for malaria at both hospitals after the scale-up, and malaria cases accounted for a smaller proportion of total hospital visits over time. Hospital spending on malaria admissions also decreased. In one hospital, malaria accounted for 11% of total hospital spending before large-scale malaria control compared with < 1% after malaria control. The findings demonstrate that facility-level resources are freed up as malaria is controlled, potentially making these resources available for other diseases and conditions.

Cost-effectiveness of pre-exposure prophylaxis (PrEP) in preventing HIV-1 infections in rural Zambia: a modeling study.

BACKGROUND: Pre-exposure prophylaxis (PrEP) with tenofovir and emtricitabine effectively prevents new HIV infections. The optimal scenario for implementing PrEP where most infections are averted at the lowest cost is unknown. We determined the impact of different PrEP strategies on averting new infections, prevalence, drug resistance and cost-effectiveness in Macha, a rural setting in Zambia. METHODS: A deterministic mathematical model of HIV transmission was constructed using data from the Macha epidemic (antenatal prevalence 7.7%). Antiretroviral therapy is started at CD4<350 cells/mm(3). We compared the number of infections averted, cost-effectiveness, and potential emergence of drug resistance of two ends of the prioritization spectrum: prioritizing PrEP to half of the most sexually active individuals (5-15% of the total population), versus randomly putting 40-60% of the total population on PrEP. RESULTS: Prioritizing PrEP to individuals with the highest sexual activity resulted in more infections averted than a non-prioritized strategy over ten years (31% and 23% reduction in new infections respectively), and also a lower HIV prevalence after ten years (5.7%, 6.4% respectively). The strategy was very cost-effective at $323 per quality adjusted life year gained and appeared to be both less costly and more effective than the non-prioritized strategy. The prevalence of drug resistance due to PrEP was as high as 11.6% when all assumed breakthrough infections resulted in resistance, and as low as 1.3% when 10% of breakthrough infections resulted in resistance in both our prioritized and non-prioritized scenarios. CONCLUSIONS: Even in settings with low test rates and treatment retention, the use of PrEP can still be a useful strategy in averting infections. Our model has shown that PrEP is a cost-effective strategy for reducing HIV incidence, even when adherence is suboptimal and prioritization is imperfect.