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Cluster randomized trials (CRTs) often enroll large numbers of participants; yet due to resource constraints, only a subset of participants may be selected for outcome assessment, and those sampled may not be representative of all cluster members. Missing data also present a challenge: if sampled individuals with measured outcomes are dissimilar from those with missing outcomes, unadjusted estimates of arm-specific endpoints and the intervention effect may be biased. Further, CRTs often enroll and randomize few clusters, limiting statistical power and raising concerns about finite sample performance. Motivated by SEARCH-TB, a CRT aimed at reducing incident tuberculosis infection, we demonstrate interlocking methods to handle these challenges. First, we extend Two-Stage targeted minimum loss-based estimation to account for three sources of missingness: (i) subsampling; (ii) measurement of baseline status among those sampled; and (iii) measurement of final status among those in the incidence cohort (persons known to be at risk at baseline). Second, we critically evaluate the assumptions under which subunits of the cluster can be considered the conditionally independent unit, improving precision and statistical power but also causing the CRT to behave like an observational study. Our application to SEARCH-TB highlights the real-world impact of different assumptions on measurement and dependence; estimates relying on unrealistic assumptions suggested the intervention increased the incidence of TB infection by 18% (risk ratio [RR]=1.18, 95% confidence interval [CI]: 0.85-1.63), while estimates accounting for the sampling scheme, missingness, and within community dependence found the intervention decreased the incident TB by 27% (RR=0.73, 95% CI: 0.57-0.92).

IntroductionIdentifying the optimal approaches to offering HIV prevention to meet the needs of those at risk is a high priority, particularly given the expanding toolkit of biomedical HIV prevention options. An ongoing study in rural East African communities evaluated the uptake of choices in product, testing mode and location of care delivery through a structured patient-centred HIV prevention delivery model. In this qualitative study, we sought to understand clients' experiences of this "dynamic choice prevention model" (DCP) and highlight pathways of action to inform HIV prevention delivery models.MethodsIn-depth semi-structured interviews were conducted from November 2021 through March 2022 with a purposively selected sample of n = 56 participants in DCP trials (across outpatient departments, antenatal clinics and community settings), and n = 21 healthcare providers (total n = 77). A seven-person multi-regional team translated and inductively coded transcript data. We used a framework analysis approach to identify emergent themes.ResultsIndividuals taking up HIV pre-exposure prophylaxis (PrEP) reported feelings of relief, liberation from fears of acquiring HIV and satisfaction with being able to take action despite partners' behaviours. Couples used a range of approaches afforded by the study to persuade partners to get tested and opt for PrEP. Post-exposure prophylaxis (PEP) use was less common, although women welcomed it in the event of sexual coercion or assault. Participants discussed switching from PEP to PrEP after familiarizing themselves with usage and ascertaining ongoing risk. Participants felt respected by providers, trusted them and appreciated being able to contact them directly for telephone support. Prevention uptake was hindered by stigma, limited experience with and knowledge of prevention methods, gendered and generational power dynamics within intimate partnerships and families, and negative perceptions of methods due to the products themselves. Participants anticipated long-acting injectable PrEP could solve their challenges regarding pill size, daily pill burden and the likelihood of unwanted disclosure.ConclusionsDiverse preferences and barriers to uptake of prevention require a choice of HIV prevention options, locations and delivery modalities-but in addition, flexible, competent and friendly care provision is crucial to promote uptake. Helping clients feel valued, and addressing their unique needs and challenges, enables their agency to prioritize their health.

BackgroundPregnant and postpartum women in Sub-Saharan Africa are at high risk of HIV acquisition. We evaluated a person-centered dynamic choice intervention for HIV prevention (DCP) among women attending antenatal and postnatal care.SettingRural Kenya and Uganda.MethodsWomen (aged 15 years or older) at risk of HIV acquisition seen at antenatal and postnatal care clinics were individually randomized to DCP vs. standard of care (SEARCH; NCT04810650). The DCP intervention included structured client choice of product (daily oral pre-exposure prophylaxis or postexposure prophylaxis), service location (clinic or out of facility), and HIV testing modality (self-test or provider-administered), with option to switch over time and person-centered care (phone access to clinician, structured barrier assessment and counseling, and provider training). The primary outcome was biomedical prevention coverage-proportion of 48-week follow-up with self-reported pre-exposure prophylaxis or postexposure prophylaxis use, compared between arms using targeted maximum likelihood estimation.ResultsBetween April and July 2021, we enrolled 400 women (203 intervention and 197 control); 38% were pregnant, 52% were aged 15-24 years, and 94% reported no pre-exposure prophylaxis or postexposure prophylaxis use for ≥6 months before baseline. Among 384/400 participants (96%) with outcome ascertained, DCP increased biomedical prevention coverage 40% (95% CI: 34% to 47%; P < 0.001); the coverage was 70% in intervention vs. 29% in control. DCP also increased coverage during months at risk of HIV (81% in intervention, 43% in control; 38% absolute increase; 95% CI: 31% to 45%; P < 0.001).ConclusionA person-centered dynamic choice intervention that provided flexibility in product, testing, and service location more than doubled biomedical HIV prevention coverage in a high-risk population already routinely offered access to biomedical prevention options.

Benkeser et al. demonstrate how adjustment for baseline covariates in randomized trials can meaningfully improve precision for a variety of outcome types. Their findings build on a long history, starting in 1932 with R.A. Fisher and including more recent endorsements by the U.S. Food and Drug Administration and the European Medicines Agency. Here, we address an important practical consideration: how to select the adjustment approach-which variables and in which form-to maximize precision, while maintaining Type-I error control. Balzer et al. previously proposed Adaptive Pre-specification within TMLE to flexibly and automatically select, from a prespecified set, the approach that maximizes empirical efficiency in small trials (N < 40). To avoid overfitting with few randomized units, selection was previously limited to working generalized linear models, adjusting for a single covariate. Now, we tailor Adaptive Pre-specification to trials with many randomized units. Using V-fold cross-validation and the estimated influence curve-squared as the loss function, we select from an expanded set of candidates, including modern machine learning methods adjusting for multiple covariates. As assessed in simulations exploring a variety of data-generating processes, our approach maintains Type-I error control (under the null) and offers substantial gains in precision-equivalent to 20%-43% reductions in sample size for the same statistical power. When applied to real data from ACTG Study 175, we also see meaningful efficiency improvements overall and within subgroups.

BackgroundPersons with HIV (PWH) with high mobility face obstacles to HIV care engagement and viral suppression. We sought to understand whether a patient-centered intervention for mobile PWH would improve viral suppression and retention in care, and if so, which subgroups would benefit most.MethodsIn a randomized trial, we evaluated the effect of an intervention designed to address barriers to care among mobile (≥2 weeks out of community in previous year) PWH with viral nonsuppression or recent missed visits in Kenya and Uganda (NCT04810650). The intervention included dynamic choice of a "travel pack" (emergency antiretroviral therapy [ART] supply, discrete ART packaging, and travel checklist), multimonth and offsite refills, facilitated transfer to out-of-community clinics, and hotline access to a mobility coordinator. The primary outcome was viral suppression (

IntroductionOptimizing HIV prevention may require structured approaches for providing client-centred choices as well as community-based entry points and delivery. We evaluated the effect of a dynamic choice model for HIV prevention, delivered by community health workers (CHWs) with clinician support, on the use of biomedical prevention among persons at risk of HIV in rural East Africa.MethodsWe conducted a cluster randomized trial among persons (≥15 years) with current or anticipated HIV risk in 16 villages in Uganda and Kenya (SEARCH; NCT04810650). The intervention was a client-centred HIV prevention model, including (1) structured client choice of product (pre-exposure prophylaxis [PrEP] or post-exposure prophylaxis [PEP]), service location (clinic or out-of-clinic) and HIV testing modality (self-test or rapid test), with the ability to switch over time; (2) a structured assessment of patient barriers and development of a personalized support plan; and (3) phone access to a clinician 24/7. The intervention was delivered by CHWs and supported by clinicians who oversaw PrEP and PEP initiation and monitoring. Participants in control villages were referred to local health facilities for HIV prevention services, delivered by Ministry of Health staff. The primary outcome was biomedical prevention coverage: a proportion of 48-week follow-up with self-reported PrEP or PEP use.ResultsFrom May to July 2021, we enrolled 429 people (212 intervention; 217 control): 57% women and 35% aged 15-24 years. Among intervention participants, 58% chose PrEP and 58% chose PEP at least once over follow-up; self-testing increased from 52% (baseline) to 71% (week 48); ≥98% chose out-of-facility service delivery. Among 413 (96%) participants with the primary outcome ascertained, average biomedical prevention coverage was 28.0% in the intervention versus 0.5% in the control: a difference of 27.5% (95% CI: 23.0-31.9%, p

IntroductionUnhealthy alcohol use significantly contributes to viral non-suppression among persons with HIV (PWH). It is unknown whether brief behavioural interventions to reduce alcohol use can improve viral suppression among PWH with unhealthy alcohol use in sub-Saharan Africa (SSA).MethodsAs part of the SEARCH study (NCT04810650), we conducted an individually randomized trial in Kenya and Uganda of a brief, skills-based alcohol intervention among PWH with self-reported unhealthy alcohol use (Alcohol Use Disorders Identification Test-Consumption [AUDIT-C], prior 3 months, ≥3/female; ≥4/male) and at risk of viral non-suppression, defined as either recent HIV viral non-suppression (≥400 copies/ml), missed visits, out of care or new diagnosis. The intervention included baseline and 3-month in-person counselling sessions with interim booster phone calls every 3 weeks. The primary outcome was HIV viral suppression (200 ng/ml (RR 0.97, 95% CI: 0.92-1.02).ConclusionsIn a randomized trial of 401 PWH with unhealthy alcohol use and risk for viral non-suppression, a brief alcohol intervention reduced unhealthy alcohol use but did not affect viral suppression at 24 weeks. Brief alcohol interventions have the potential to improve the health of PWH in SSA by reducing alcohol use, a significant driver of HIV-associated co-morbidities.

Across research disciplines, cluster randomized trials (CRTs) are commonly implemented to evaluate interventions delivered to groups of participants, such as communities and clinics. Despite advances in the design and analysis of CRTs, several challenges remain. First, there are many possible ways to specify the causal effect of interest (eg, at the individual-level or at the cluster-level). Second, the theoretical and practical performance of common methods for CRT analysis remain poorly understood. Here, we present a general framework to formally define an array of causal effects in terms of summary measures of counterfactual outcomes. Next, we provide a comprehensive overview of CRT estimators, including the t-test, generalized estimating equations (GEE), augmented-GEE, and targeted maximum likelihood estimation (TMLE). Using finite sample simulations, we illustrate the practical performance of these estimators for different causal effects and when, as commonly occurs, there are limited numbers of clusters of different sizes. Finally, our application to data from the Preterm Birth Initiative (PTBi) study demonstrates the real-world impact of varying cluster sizes and targeting effects at the cluster-level or at the individual-level. Specifically, the relative effect of the PTBi intervention was 0.81 at the cluster-level, corresponding to a 19% reduction in outcome incidence, and was 0.66 at the individual-level, corresponding to a 34% reduction in outcome risk. Given its flexibility to estimate a variety of user-specified effects and ability to adaptively adjust for covariates for precision gains while maintaining Type-I error control, we conclude TMLE is a promising tool for CRT analysis.

IntroductionPerson-centred HIV prevention delivery models that offer structured choices in product, testing and visit location may increase coverage. However, data are lacking on the actual uptake of choices among persons at risk of HIV in southern Africa. In an ongoing randomized study (SEARCH; NCT04810650) in rural East Africa, we evaluated the uptake of choices made when offered in a person-centred, dynamic choice model for HIV prevention.MethodsUsing the PRECEDE framework, we developed a persont-centred, Dynamic Choice HIV Prevention (DCP) intervention for persons at risk of HIV in three settings in rural Kenya and Uganda: antenatal clinic (ANC), outpatient department (OPD) and in the community. Components include: provider training on product choice (predisposing); flexibility and responsiveness to client desires and choices (pre-exposure prophylaxis [PrEP]/post-exposure prophylaxis [PEP], clinic vs. off-site visits and self- or clinician-based HIV testing) (enabling); and client and staff feedback (reinforcing). All clients received a structured assessment of barriers with personalized plans to address them, mobile phone access to clinicians (24 hours/7 days/week) and integrated reproductive health services. In this interim analysis, we describe the uptake of choices of product, location and testing during the first 24 weeks of follow-up (April 2021-March 2022).ResultsA total of 612 (203 ANC, 197 OPD and 212 community) participants were randomized to the person-centred DCP intervention. We delivered the DCP intervention in all three settings with diverse populations: ANC: 39% pregnant; median age: 24 years; OPD: 39% male, median age 27 years; and community: 42% male, median age: 29 years. Baseline choice of PrEP was highest in ANC (98%) vs. OPD (84%) and community (40%); whereas the proportion of adults selecting PEP was higher in the community (46%) vs. OPD (8%) and ANC (1%). Personal preference for off-site visits increased over time (65% at week 24 vs. 35% at baseline). Interest in alternative HIV testing modalities grew over time (38% baseline self-testing vs. 58% at week 24).ConclusionsA person-centred model incorporating structured choice in biomedical prevention and care delivery options in settings with demographically diverse groups, in rural Kenya and Uganda, was responsive to varying personal preferences over time in HIV prevention programmes.

IntroductionSwitch to dolutegravir (DTG) in treatment-experienced people living with HIV (PLH) is associated with excess weight gain in some settings; data are limited from rural low-income settings with low obesity prevalence.MethodsIn rural Kenya, we conducted a retrospective cohort study at 8 HIV clinics and a single-site prospective cohort study including adults switching to DTG during countrywide transition to DTG/tenofovir DF(TDF)/emtricitabine as first-line HIV treatment. In the retrospective analysis, we used preswitch data to model postswitch weight trajectory had each participant not switched to DTG and contrasted observed vs. predicted postswitch weight. In the prospective analysis, we measured weight post-DTG switch and evaluated predictors of 6-month weight change.ResultsOur retrospective cohort included 4445 PLH who switched to DTG between 2018 and 2020. Mean 12-month weight change was 0.6 kg preswitch and 0.8 kg postswitch. Among those on TDF throughout (n = 3374; 83% on efavirenz preswitch), 12-month postswitch weight was 0.7 kg more than predicted for women (95% CI: 0.4, 1.0) and similar among men (0.04 kg; 95% CI -0.3, 0.4). In our prospective cohort (n = 135, 100% female), mean 6-month weight change was +0.4 kg (IQR -1.1, 2.0 kg). Predicted gain varied by baseline food insecurity: +1.1 kg (95% CI: 0.34, 1.87) among food secure, -0.09 kg (95% CI -0.71, 0.54) among moderate insecure, and +0.27 kg (95% CI -0.82, 1.36) among severe insecurity.ConclusionIn contrast to some reports of large weight gain following switch to DTG, we observed small weight increases in women and no weight change in men following DTG switch when on TDF throughout. Weight gain may be attenuated by food insecurity, though was modest even among food secure.

Cluster randomized trials (CRTs) randomly assign an intervention to groups of individuals (e.g., clinics or communities) and measure outcomes on individuals in those groups. While offering many advantages, this experimental design introduces challenges that are only partially addressed by existing analytic approaches. First, outcomes are often missing for some individuals within clusters. Failing to appropriately adjust for differential outcome measurement can result in biased estimates and inference. Second, CRTs often randomize limited numbers of clusters, resulting in chance imbalances on baseline outcome predictors between arms. Failing to adaptively adjust for these imbalances and other predictive covariates can result in efficiency losses. To address these methodological gaps, we propose and evaluate a novel two-stage targeted minimum loss-based estimator to adjust for baseline covariates in a manner that optimizes precision, after controlling for baseline and postbaseline causes of missing outcomes. Finite sample simulations illustrate that our approach can nearly eliminate bias due to differential outcome measurement, while existing CRT estimators yield misleading results and inferences. Application to real data from the SEARCH community randomized trial demonstrates the gains in efficiency afforded through adaptive adjustment for baseline covariates, after controlling for missingness on individual-level outcomes.

BackgroundSocial network analysis can elucidate tuberculosis transmission dynamics outside the home and may inform novel network-based case-finding strategies.MethodsWe assessed the association between social network characteristics and prevalent tuberculosis infection among residents (aged ≥15 years) of 9 rural communities in Eastern Uganda. Social contacts named during a census were used to create community-specific nonhousehold social networks. We evaluated whether social network structure and characteristics of first-degree contacts (sex, human immunodeficiency virus [HIV] status, tuberculosis infection) were associated with revalent tuberculosis infection (positive tuberculin skin test [TST] result) after adjusting for individual-level risk factors (age, sex, HIV status, tuberculosis contact, wealth, occupation, and Bacillus Calmette-Guérin [BCG] vaccination) with targeted maximum likelihood estimation.ResultsAmong 3 335 residents sampled for TST, 32% had a positive TST results and 4% reported a tuberculosis contact. The social network contained 15 328 first-degree contacts. Persons with the most network centrality (top 10%) (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.1]) and the most (top 10%) male contacts (1.5 [1.3-1.9]) had a higher risk of prevalent tuberculosis, than those in the remaining 90%. People with ≥1 contact with HIV (adjusted risk ratio, 1.3 [95% confidence interval, 1.1-1.6]) and ≥2 contacts with tuberculosis infection were more likely to have tuberculosis themselves (2.6 [ 95% confidence interval: 2.2-2.9]).ConclusionsSocial networks with higher centrality, more men, contacts with HIV, and tuberculosis infection were positively associated with tuberculosis infection. Tuberculosis transmission within measurable social networks may explain prevalent tuberculosis not associated with a household contact. Further study on network-informed tuberculosis case finding interventions is warranted.

Youth living with HIV in sub-Saharan Africa have poor HIV care outcomes. We determined the association of recent significant life-events with HIV antiretroviral treatment (ART) initiation and HIV viral suppression in youth aged 15-24 years living with HIV in rural Kenya and Uganda. This was a cross-sectional analysis of 995 youth enrolled in the SEARCH Youth study. At baseline, providers assessed recent (within 6 months) life-events, defined as changes in schooling/employment, residence, partnerships, sickness, incarceration status, family strife or death, and birth/pregnancy, self-reported alcohol use, being a parent, and HIV-status disclosure. We examined the frequencies of events and their association with ART status and HIV viral suppression (2 significant life-events (aOR = 0.61, 95% CI:0.45-0.85) and consuming alcohol (aOR = 0.61, 95% CI:0.43-0.87) were associated with a lower odds of HIV viral suppression, while disclosure of HIV-status to partner (aOR = 2.39, 95% CI:1.6-3.5) or to family (aOR = 1.86, 95% CI:1.3-2.7), being a parent (aOR = 1.8, 95% CI:1.2-2.5), and being single (aOR = 1.6, 95% CI:1.3-2.1) had a higher odds. This suggest that two or more recent life-events and alcohol use are key barriers to ART initiation and achievement of viral suppression among youth living with HIV in rural East Africa.Trial registration: ClinicalTrials.gov identifier: NCT03848728..

BackgroundDespite longstanding guidelines endorsing isoniazid preventive therapy (IPT) for people with HIV, uptake is low across sub-Saharan Africa. Mid-level health managers oversee IPT programmes nationally; interventions aimed at this group have not been tested. We aimed to establish whether providing structured leadership and management training and facilitating subregional collaboration and routine data feedback to mid-level managers could increase IPT initiation among people with HIV compared with standard practice.MethodsWe conducted a cluster randomised trial in Uganda among district-level health managers. We randomly assigned clusters of between four and seven managers in a 1:1 ratio to intervention or control groups. Our intervention convened managers into mini-collaboratives facilitated by Ugandan experts in tuberculosis and HIV, and provided business leadership and management training, SMS platform access, and data feedback. The control was standard practice. Participants were not masked to trial group, but study statisticians were masked until trial completion. The primary outcome was IPT initiation rates among adults with HIV in facilities overseen by participants over a period of 2 years (2019-21). We conducted prespecified analyses that excluded the third quarter of 2019 (Q3-2019) to understand intervention effects independent of a national 100-day IPT push tied to a financial contingency during Q3-2019. This trial is registered with ClinicalTrials.gov (NCT03315962), and is ongoing.FindingsBetween Nov 15, 2017, and March 14, 2018, managers from 82 of 82 eligible districts (61% of Uganda's 135 districts) were enrolled and randomised: 43 districts to intervention, 39 to control. Intervention delivery took place between Dec 6, 2017, and Feb 2, 2022. Over 2 years, IPT initiation rates were 0·74 versus 0·65 starts per person-year in intervention versus control groups (incidence rate ratio [IRR] 1·14, 95% CI 0·88-1·46; p=0·16). Excluding Q3-2019, IPT initiation was higher in the intervention group versus the control group: 0·32 versus 0·25 starts per person-year (IRR 1·27, 95% CI 1·00-1·61; p=0·026).InterpretationFollowing an intervention targeting managers in more than 60% of Uganda's districts, IPT initiation rates were not significantly higher in intervention than control groups. After accounting for large increases in IPT from a 100-day push in both groups, the intervention led to significantly increased IPT rates, sustained after the push and during the COVID-19 pandemic. Our findings suggest that interventions centred on mid-level health managers can improve IPT implementation on a large, subnational scale, and merit further exploration to address key public health challenges for which strong evidence exists but implementation remains suboptimal.FundingNational Institute of Allergy and Infectious Diseases.

Study questionIs sperm epigenetic aging (SEA) associated with probability of pregnancy among couples in the general population?Summary answerWe observed a 17% lower cumulative probability at 12 months for couples with male partners in the older compared to the younger SEA categories.What is known alreadyThe strong relation between chronological age and DNA methylation profiles has enabled the estimation of biological age as epigenetic 'clock' metrics in most somatic tissue. Such clocks in male germ cells are less developed and lack clinical relevance in terms of their utility to predict reproductive outcomes.Study design, size, durationThis was a population-based prospective cohort study of couples discontinuing contraception to become pregnant recruited from 16 US counties from 2005 to 2009 and followed for up to 12 months.Participants/materials, setting, methodsSperm DNA methylation from 379 semen samples was assessed via a beadchip array. A state-of-the-art ensemble machine learning algorithm was employed to predict age from the sperm DNA methylation data. SEA was estimated from clocks derived from individual CpGs (SEACpG) and differentially methylated regions (SEADMR). Probability of pregnancy within 1 year was compared by SEA, and discrete-time proportional hazards models were used to evaluate the relations with time-to-pregnancy (TTP) with adjustment for covariates.Main results and the role of chanceOur SEACpG clock had the highest predictive performance with correlation between chronological and predicted age (r = 0.91). In adjusted discrete Cox models, SEACpG was negatively associated with TTP (fecundability odds ratios (FORs)=0.83; 95% CI: 0.76, 0.90; P = 1.2×10-5), indicating a longer TTP with advanced SEACpG. For subsequent birth outcomes, advanced SEACpG was associated with shorter gestational age (n = 192; -2.13 days; 95% CI: -3.67, -0.59; P = 0.007). Current smokers also displayed advanced SEACpG (P

BackgroundApproaches that allow easy access to pre-exposure prophylaxis (PrEP), such as over-the-counter provision at pharmacies, could facilitate risk-informed PrEP use and lead to lower HIV incidence, but their cost-effectiveness is unknown. We aimed to evaluate conditions under which risk-informed PrEP use is cost-effective.MethodsWe applied a mathematical model of HIV transmission to simulate 3000 setting-scenarios reflecting a range of epidemiological characteristics of communities in sub-Saharan Africa. The prevalence of HIV viral load greater than 1000 copies per mL among all adults (HIV positive and negative) varied from 1·1% to 7·4% (90% range). We hypothesised that if PrEP was made easily available without restriction and with education regarding its use, women and men would use PrEP, with sufficient daily adherence, during so-called seasons of risk (ie, periods in which individuals are at risk of acquiring infection). We refer to this as risk-informed PrEP. For each setting-scenario, we considered the situation in mid-2021 and performed a pairwise comparison of the outcomes of two policies: immediate PrEP scale-up and then continuation for 50 years, and no PrEP. We estimated the relationship between epidemic and programme characteristics and cost-effectiveness of PrEP availability to all during seasons of risk. For our base-case analysis, we assumed a 3-monthly PrEP cost of US$29 (drug $11, HIV test $4, and $14 for additional costs necessary to facilitate education and access), a cost-effectiveness threshold of $500 per disability-adjusted life-year (DALY) averted, an annual discount rate of 3%, and a time horizon of 50 years. In sensitivity analyses, we considered a cost-effectiveness threshold of $100 per DALY averted, a discount rate of 7% per annum, the use of PrEP outside of seasons of risk, and reduced uptake of risk-informed PrEP.FindingsIn the context of PrEP scale-up such that 66% (90% range across setting-scenarios 46-81) of HIV-negative people with at least one non-primary condomless sex partner take PrEP in any given period, resulting in 2·6% (0·9-6·0) of all HIV negative adults taking PrEP at any given time, risk-informed PrEP was predicted to reduce HIV incidence by 49% (23-78) over 50 years compared with no PrEP. PrEP was cost-effective in 71% of all setting-scenarios, and cost-effective in 76% of setting-scenarios with prevalence of HIV viral load greater than 1000 copies per mL among all adults higher than 2%. In sensitivity analyses with a $100 per DALY averted cost-effectiveness threshold, a 7% per year discount rate, or with PrEP use that was less well risk-informed than in our base case, PrEP was less likely to be cost-effective, but generally remained cost-effective if the prevalence of HIV viral load greater than 1000 copies per mL among all adults was higher than 3%. In sensitivity analyses based on additional setting-scenarios in which risk-informed PrEP was less extensively used, the HIV incidence reduction was smaller, but the cost-effectiveness of risk-informed PrEP was undiminished.InterpretationUnder the assumption that making PrEP easily accessible for all adults in sub-Saharan Africa in the context of community education leads to risk-informed use, PrEP is likely to be cost-effective in settings with prevalence of HIV viral load greater than 1000 copies per mL among all adults higher than 2%, suggesting the need for implementation of such approaches, with ongoing evaluation.FundingUS Agency for International Development, US President's Emergency Plan for AIDS Relief, and Bill & Melinda Gates Foundation.

BackgroundFewer than 10% of people with hypertension in sub-Saharan Africa are diagnosed, linked to care, and achieve hypertension control. We hypothesized that a one-time financial incentive and phone call reminder for missed appointments would increase linkage to hypertension care following community-based screening in rural Uganda and Kenya.MethodsIn a randomized controlled trial, we conducted community-based hypertension screening and enrolled adults ≥25 years with blood pressure ≥140/90 mmHg on three measures; we excluded participants with known hypertension or hypertensive emergency. The intervention was transportation reimbursement upon linkage (~$5 USD) and up to three reminder phone calls for those not linking within seven days. Control participants received a clinic referral only. Outcomes were linkage to hypertension care within 30 days (primary) and hypertension control

BackgroundWe tested the hypothesis that patient-centered, streamlined human immunodeficiency virus (HIV) care would achieve lower mortality than the standard treatment model for persons with HIV and CD4 ≤ 350/uL in the setting of population-wide HIV testing.MethodsIn the SEARCH (Sustainable East Africa Research in Community Health) Study (NCT01864603), 32 communities in rural Uganda and Kenya were randomized to country-guided antiretroviral therapy (ART) versus streamlined ART care that included rapid ART start, visit spacing, flexible clinic hours, and welcoming environment. We assessed persons with HIV and CD4 ≤ 350/uL, ART eligible in both arms, and estimated the effect of streamlined care on ART initiation and mortality at 3 years. Comparisons between study arms used a cluster-level analysis with survival estimates from Kaplan-Meier; estimates of ART start among ART-naive persons treated death as a competing risk.ResultsAmong 13 266 adults with HIV, 2973 (22.4%) had CD4 ≤ 350/uL. Of these, 33% were new diagnoses, and 10% were diagnosed but ART-naive. Men with HIV were almost twice as likely as women with HIV to have CD4 ≤ 350/uL and be untreated (15% vs 8%, respectively). Streamlined care reduced mortality by 28% versus control (risk ratio [RR] = 0.72; 95% confidence interval [CI]: .56, .93; P = .02). Despite eligibility in both arms, persons with CD4 ≤ 350/uL started ART faster under streamlined care versus control (76% vs 43% by 12 months, respectively; P

BackgroundHypertension treatment reduces morbidity and mortality yet has not been broadly implemented in many low-resource settings, including sub-Saharan Africa (SSA). We hypothesized that a patient-centered integrated chronic disease model that included hypertension treatment and leveraged the HIV care system would reduce mortality among adults with uncontrolled hypertension in rural Kenya and Uganda.Methods and findingsThis is a secondary analysis of the SEARCH trial (NCT:01864603), in which 32 communities underwent baseline population-based multidisease testing, including hypertension screening, and were randomized to standard country-guided treatment or to a patient-centered integrated chronic care model including treatment for hypertension, diabetes, and HIV. Patient-centered care included on-site introduction to clinic staff at screening, nursing triage to expedite visits, reduced visit frequency, flexible clinic hours, and a welcoming clinic environment. The analytic population included nonpregnant adults (≥18 years) with baseline uncontrolled hypertension (blood pressure ≥140/90 mm Hg). The primary outcome was 3-year all-cause mortality with comprehensive population-level assessment. Secondary outcomes included hypertension control assessed at a population level at year 3 (defined per country guidelines as at least 1 blood pressure measure

Background Human immunodeficiency virus (HIV) treatment reduces tuberculosis (TB) disease and mortality; however, the population-level impact of universal HIV-test-and-treat interventions on TB infection and transmission remain unclear. Methods In a sub-study nested in the SEARCH trial, a community cluster-randomized trial (NCT01864603), we assessed whether a universal HIV-test-and-treat intervention reduced population-level incident TB infection in rural Uganda. Intervention communities received annual, population-level HIV testing and patient-centered linkage. Control communities received population-level HIV testing at baseline and endline. We compared estimated incident TB infection by arms, defined by tuberculin skin test conversion in a cohort of persons aged 5 and older, adjusting for participation and predictors of infection, and accounting for clustering. Results Of the 32 trial communities, 9 were included, comprising 90 801 participants (43 127 intervention and 47 674 control). One-year cumulative incidence of TB infection was 16% in the intervention and 22% in the control; SEARCH reduced the population-level risk of incident TB infection by 27% (adjusted risk ratio = 0.73; 95% confidence interval [CI]:.57–.92, P =.005). In pre-specified analyses, the effect was largest among children aged 5–11 years and males. Conclusions A universal HIV-test-and-treat intervention reduced incident TB infection, a marker of population-level TB transmission. Investments in community-level HIV interventions have broader population-level benefits, including TB reductions. [ABSTRACT FROM AUTHOR]

In this issue, Naimi et al. (Am J Epidemiol. 2023;192(9):1536–1544) discuss a critical topic in public health and beyond: obtaining valid statistical inference when using machine learning in causal research. In doing so, the authors review recent prominent methodological work and recommend: 1) doubly robust estimators, such as targeted maximum likelihood estimation (TMLE); 2) ensemble methods, such as Super Learner, to combine predictions from a diverse library of algorithms; and 3) sample splitting to reduce bias and improve inference. We largely agree with these recommendations. In this commentary, we highlight the critical importance of the Super Learner library. Specifically, in both simulation settings considered by the authors, we demonstrate that reductions in bias and improvements in confidence-interval coverage can be achieved using TMLE without sample splitting and with a Super Learner library that excludes tree-based methods but includes regression splines. Whether extremely data-adaptive algorithms and sample splitting are needed depends on the specific problem and should be informed by simulations reflecting the specific application. More research is needed on practical recommendations for selecting among these options in common situations arising in epidemiology. [ABSTRACT FROM AUTHOR]

Gaussian graphical models (GGMs) are a popular form of network model in which nodes represent features in multivariate normal data and edges reflect conditional dependencies between these features. GGM estimation is an active area of research. Currently available tools for GGM estimation require investigators to make several choices regarding algorithms, scoring criteria, and tuning parameters. An estimated GGM may be highly sensitive to these choices, and the accuracy of each method can vary based on structural characteristics of the network such as topology, degree distribution, and density. Because these characteristics are a priori unknown, it is not straightforward to establish universal guidelines for choosing a GGM estimation method. We address this problem by introducing SpiderLearner, an ensemble method that constructs a consensus network from multiple estimated GGMs. Given a set of candidate methods, SpiderLearner estimates the optimal convex combination of results from each method using a likelihood‐based loss function. K$$ K $$‐fold cross‐validation is applied in this process, reducing the risk of overfitting. In simulations, SpiderLearner performs better than or comparably to the best candidate methods according to a variety of metrics, including relative Frobenius norm and out‐of‐sample likelihood. We apply SpiderLearner to publicly available ovarian cancer gene expression data including 2013 participants from 13 diverse studies, demonstrating our tool's potential to identify biomarkers of complex disease. SpiderLearner is implemented as flexible, extensible, open‐source code in the R package ensembleGGM at https://github.com/katehoffshutta/ensembleGGM. [ABSTRACT FROM AUTHOR]