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ABSTRACT There are limited options to estimate the treatment effects of variables which are continuous and measured at multiple time points, particularly if the true dose–response curve should be estimated as closely as possible. However, these situations may be of relevance: in pharmacology, one may be interested in how outcomes of people living with—and treated for—HIV, such as viral failure, would vary for time‐varying interventions such as different drug concentration trajectories. A challenge for doing causal inference with continuous interventions is that the positivity assumption is typically violated. To address positivity violations, we develop projection functions, which reweigh and redefine the estimand of interest based on functions of the conditional support for the respective interventions. With these functions, we obtain the desired dose–response curve in areas of enough support, and otherwise a meaningful estimand that does not require the positivity assumption. We develop g$$ g $$‐computation type plug‐in estimators for this case. Those are contrasted with g‐computation estimators which are applied to continuous interventions without specifically addressing positivity violations, which we propose to be presented with diagnostics. The ideas are illustrated with longitudinal data from HIV positive children treated with an efavirenz‐based regimen as part of the CHAPAS‐3 trial, which enrolled children <13$$ <13 $$ years in Zambia/Uganda. Simulations show in which situations a standard g‐computation approach is appropriate, and in which it leads to bias and how the proposed weighted estimation approach then recovers the alternative estimand of interest. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this study is to assess the outcomes of children, adolescents and young adults with HIV reported as lost to follow‐up, correct mortality estimates for children, adolescents and young adults with HIV for unascertained outcomes in those loss to follow‐up (LTFU) based on tracing and linkage data separately using data from the International epidemiology Databases to Evaluate AIDS in Southern Africa. Methods: We included data from two different populations of children, adolescents and young adults with HIV; (1) clinical data from children, adolescents and young adults with HIV aged ≤24 years from Lesotho, Malawi, Mozambique, Zambia and Zimbabwe; (2) clinical data from children, adolescents and young adults with HIV aged ≤14 years from the Western Cape (WC) in South Africa. Outcomes of patients lost to follow‐up were available from (1) a tracing study and (2) linkage to a health information exchange. For both populations, we compared six methods for correcting mortality estimates for all children, adolescents and young adults with HIV. Results: We found substantial variations of mortality estimates among children, adolescents and young adults with HIV reported as lost to follow‐up versus those retained in care. Ascertained mortality was higher among lost and traceable children, adolescents and young adults with HIV and lower among lost and linkable than those retained in care (mortality: 13.4% [traced] vs. 12.6% [retained‐other Southern Africa countries]; 3.4% [linked] vs. 9.4% [retained‐WC]). A high proportion of lost to follow‐up children, adolescents and young adults with HIV had self‐transferred (21.0% and 47.0%) in the traced and linked samples, respectively. The uncorrected method of non‐informative censoring yielded the lowest mortality estimates among all methods for both tracing (6.0%) and linkage (4.0%) approaches at 2 years from ART start. Among corrected methods using ascertained data, multiple imputation, incorporating ascertained data (MI(asc.)) and inverse probability weighting with logistic weights were most robust for the tracing approach. In contrast, for the linkage approach, MI(asc.) was the most robust. Conclusions: Our findings emphasise that lost to follow‐up is non‐ignorable and both tracing and linkage improved outcome ascertainment: tracing identified substantial mortality in those reported as lost to follow‐up, whereas linkage did not identify out‐of‐facility deaths, but showed that a large proportion of those reported as lost to follow‐up were self‐transfers. [ABSTRACT FROM AUTHOR]

Objectives: Despite declining TB notifications in Southern Africa, TB‐related deaths remain high. We describe patient‐ and population‐level trends in TB‐related deaths in Eswatini over a period of 11 years. Methods: Patient‐level (retrospective cohort, from 2009 to 2019) and population‐level (ecological analysis, 2009–2017) predictors and rates of TB‐related deaths were analysed in HIV‐negative and HIV‐coinfected first‐line TB treatment cases and the population of the Shiselweni region. Patient‐level TB treatment data, and population and HIV prevalence estimates were combined to obtain stratified annual mortality rates. Multivariable Poisson regressions models were fitted to identify patient‐level and population‐level predictors of deaths. Results: Of 11,883 TB treatment cases, 1302 (11.0%) patients died during treatment: 210/2798 (7.5%) HIV‐negative patients, 984/8443 (11.7%) people living with HIV (PLHIV), and 108/642 (16.8%) patients with unknown HIV‐status. The treatment case fatality ratio remained above 10% in most years. At patient‐level, fatality risk was higher in PLHIV (aRR 1.74, 1.51–2.02), and for older age and extra‐pulmonary TB irrespective of HIV‐status. For PLHIV, fatality risk was higher for TB retreatment cases (aRR 1.38, 1.18–1.61) and patients without antiretroviral therapy (aRR 1.70, 1.47–1.97). It decreases with increasing higher CD4 strata and the programmatic availability of TB‐LAM testing (aRR 0.65, 0.35–0.90). At population‐level, mortality rates decreased 6.4‐fold (−147/100,000 population) between 2009 (174/100,000) and 2017 (27/100,000), coinciding with a decline in TB treatment cases (2785 in 2009 to 497 in 2017). Although the absolute decline in mortality rates was most pronounced in PLHIV (−826/100,000 vs. HIV‐negative: −23/100,000), the relative population‐level mortality risk remained higher in PLHIV (aRR 4.68, 3.25–6.72) compared to the HIV‐negative population. Conclusions: TB‐related mortality rapidly decreased at population‐level and most pronounced in PLHIV. However, case fatality among TB treatment cases remained high. Further strategies to reduce active TB disease and introduce improved TB therapies are warranted. [ABSTRACT FROM AUTHOR]