This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate time-dependent covariates, and a possibly time-dependent outcome. The intervention nodes at each time point can include a binary treatment as well as a right-censoring indicator. Given a class of dynamic or static interventions, a marginal structural model is used to model the mean of the intervention-specific counterfactual outcome as a function of the intervention, time point, and possibly a subset of baseline covariates. Because the true shape of this function is rarely known, the marginal structural model is used as a working model. The causal quantity of interest is defined as the projection of the true function onto this working model. Iterated conditional expectation double robust estimators for marginal structural model parameters were previously proposed by Robins (2000, 2002) and Bang and Robins (2005). Here we build on this work and present a pooled TMLE for the parameters of marginal structural working models. We compare this pooled estimator to a stratified TMLE (Schnitzer et al. 2014) that is based on estimating the intervention-specific mean separately for each intervention of interest. The performance of the pooled TMLE is compared to the performance of the stratified TMLE and the performance of inverse probability weighted (IPW) estimators using simulations. Concepts are illustrated using an example in which the aim is to estimate the causal effect of delayed switch following immunological failure of first line antiretroviral therapy among HIV-infected patients. Data from the International Epidemiological Databases to Evaluate AIDS, Southern Africa are analyzed to investigate this question using both TML and IPW estimators. Our results demonstrate practical advantages of the pooled TMLE over an IPW estimator for working marginal structural models for survival, as well as cases in which the pooled TMLE is superior to its stratified counterpart.

Objectives: To determine magnitude and reasons of loss to program and poor antiretroviral prophylaxis coverage in prevention of mother-to-child transmission (PMTCT) programs in sub-Saharan Africa. Design: Systematic review and meta-analysis. Methods: We searched PubMed and Embase databases for PMTCT studies in sub-Saharan Africa published between January 2002 and March 2012. Outcomes were the percentage of pregnant women tested for HIV, initiating antiretroviral prophylaxis, having a CD4 cell count measured, and initiating antiretroviral combination therapy (cART) if eligible. In children outcomes were early infant diagnosis for HIV, and cART initiation. We combined data using random-effects meta-analysis and identified predictors of uptake of interventions. Results: Forty-four studies from 15 countries including 75 172 HIV-infected pregnant women were analyzed. HIV-testing uptake at antenatal care services was 94% [95% confidence intervals (CIs) 92–95%] for opt-out and 58% (95% CI 40–75%) for opt-in testing. Coverage with any antiretroviral prophylaxis was 70% (95% CI 64–76%) and 62% (95% CI 50–73%) of pregnant women eligible for cART received treatment. Sixty-four percent (95% CI 48–81%) of HIV exposed infants had early diagnosis performed and 55% (95% CI 36–74%) were tested between 12 and 18 months. Uptake of PMTCT interventions was improved if cART was provided at the antenatal clinic and if the male partner was involved. Conclusion: In sub-Saharan Africa, uptake of PMTCT interventions and early infant diagnosis is unsatisfactory. An integrated family-centered approach seems to improve retention.

The number of patients in need of second-line antiretroviral drugs is increasing in sub-Saharan Africa. We aimed to project the need of second-line antiretroviral therapy in adults in sub-Saharan Africa up to 2030. We developed a simulation model for HIV and applied it to each sub-Saharan African country. We used the WHO country intelligence database to estimate the number of adult patients receiving antiretroviral therapy from 2005 to 2014. We fitted the number of adult patients receiving antiretroviral therapy to observed estimates, and predicted first-line and second-line needs between 2015 and 2030. We present results for sub-Saharan Africa, and eight selected countries. We present 18 scenarios, combining the availability of viral load monitoring, speed of antiretroviral scale-up, and rates of retention and switching to second-line. HIV transmission was not included. Depending on the scenario, 8·7-25·6 million people are expected to receive antiretroviral therapy in 2020, of whom 0·5-3·0 million will be receiving second-line antiretroviral therapy. The proportion of patients on treatment receiving second-line therapy was highest (15·6%) in the scenario with perfect retention and immediate switching, no further scale-up, and universal routine viral load monitoring. In 2030, the estimated range of patients receiving antiretroviral therapy will remain constant, but the number of patients receiving second-line antiretroviral therapy will increase to 0·8-4·6 million (6·6-19·6%). The need for second-line antiretroviral therapy was two to three times higher if routine viral load monitoring was implemented throughout the region, compared with a scenario of no further viral load monitoring scale-up. For each monitoring strategy, the future proportion of patients receiving second-line antiretroviral therapy differed only minimally between countries. Donors and countries in sub-Saharan Africa should prepare for a substantial increase in the need for second-line drugs during the next few years as access to viral load monitoring improves. An urgent need exists to decrease the costs of second-line drugs. World Health Organization, Swiss National Science Foundation, National Institutes of Health.

Objectives: HIV ‘treatment as prevention’ (TasP) describes early treatment of HIV-infected patients intended to reduce viral load and transmission. Crucial assumptions for estimating TasP's effectiveness are the underlying estimates of transmission risk. We aimed to determine transmission risk during primary infection, and describe the relation of HIV transmission risk to viral load. Design: A systematic review and meta-analysis. Methods: We searched PubMed and Embase databases for studies that established a relationship between viral load and transmission risk, or primary infection and transmission risk, in serodiscordant couples. We analysed assumptions about the relationship between viral load and transmission risk, and between duration of primary infection and transmission risk. Results: We found 36 eligible articles, based on six different study populations. Studies consistently found that higher viral loads lead to higher HIV transmission rates, but assumptions about the shape of this increase varied from exponential increase to saturation. The assumed duration of primary infection ranged from 1.5 to 12 months; for each additional month, the log₁₀ transmission rate ratio between primary and asymptomatic infection decreased by 0.40. Conclusion: Assumptions and estimates of the relationship between viral load and transmission risk, and the relationship between primary infection and transmission risk, vary substantially and predictions of TasP's effectiveness should take this uncertainty into account.

Background WHO's 2013 revisions to its Consolidated Guidelines on antiretroviral drugs recommend routine viral load monitoring, rather than clinical or immunological monitoring, as the preferred monitoring approach on the basis of clinical evidence. However, HIV programmes in resource-limited settings require guidance on the most cost-effective use of resources in view of other competing priorities such as expansion of antiretroviral therapy coverage. We assessed the cost-effectiveness of alternative patient monitoring strategies. Methods We evaluated a range of monitoring strategies, including clinical, CD4 cell count, and viral load monitoring, alone and together, at different frequencies and with different criteria for switching to second-line therapies. We used three independently constructed and validated models simultaneously. We estimated costs on the basis of resource use projected in the models and associated unit costs; we quantified impact as disability-adjusted life years (DALYs) averted. We compared alternatives using incremental cost-effectiveness analysis. Findings All models show that clinical monitoring delivers significant benefit compared with a hypothetical baseline scenario with no monitoring or switching. Regular CD4 cell count monitoring confers a benefit over clinical monitoring alone, at an incremental cost that makes it affordable in more settings than viral load monitoring, which is currently more expensive. Viral load monitoring without CD4 cell count every 6–12 months provides the greatest reductions in morbidity and mortality, but incurs a high cost per DALY averted, resulting in lost opportunities to generate health gains if implemented instead of increasing antiretroviral therapy coverage or expanding antiretroviral therapy eligibility. Interpretation The priority for HIV programmes should be to expand antiretroviral therapy coverage, firstly at CD4 cell count lower than 350 cells per μL, and then at a CD4 cell count lower than 500 cells per μL, using lower-cost clinical or CD4 monitoring. At current costs, viral load monitoring should be considered only after high antiretroviral therapy coverage has been achieved. Point-of-care technologies and other factors reducing costs might make viral load monitoring more affordable in future. Funding Bill & Melinda Gates Foundation, WHO.