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Background: Estimation of prevalence and diagnostic test accuracy in tuberculosis (TB) prevalence surveys suffer from reference standard and verification biases. The former is attributed to the imperfect reference test used to bacteriologically confirm TB disease. The latter occurs when only the participants screening positive for any TB-compatible symptom or chest X-ray abnormality are selected for bacteriological testing (verification). Bayesian latent class analysis (LCA) alleviates the reference standard bias but suffers verification bias in TB prevalence surveys. This work aims to identify best-practice approaches to simultaneously alleviate the reference standard and verification biases in the estimates of pulmonary TB prevalence and diagnostic test performance in TB prevalence surveys. Methods: We performed a secondary analysis of 9869 participants aged ≥15 years from a community-based multimorbidity screening study in a rural district of KwaZulu-Natal, South Africa (Vukuzazi study). Participants were eligible for bacteriological testing using Xpert Ultra and culture if they reported any cardinal TB symptom or had an abnormal chest X-ray finding. We conducted Bayesian LCA in five ways to handle the unverified individuals: (i) complete-case analysis, (ii) analysis assuming the unverified individuals would be negative if bacteriologically tested, (iii) analysis of multiply-imputed datasets with imputation of the missing bacteriological test results for the unverified individuals using multivariate imputation via chained equations (MICE), and simultaneous imputation of the missing bacteriological test results in the analysis model assuming the missing bacteriological test results were (iv) missing at random (MAR), and (v) missing not at random (MNAR). We compared the results of (i)-(iii) to the analysis based on a composite reference standard (CRS) of Xpert Ultra and culture. Through simulation with an overall true prevalence of 2.0%, we evaluated the ability of the models to alleviate both biases simultaneously. Results: Based on simulation, Bayesian LCA with simultaneous imputation of the missing bacteriological test results under the assumption that the missing data are MAR and MNAR alleviate the reference standard and verification biases. CRS-based analysis and Bayesian LCA assuming the unverified are negative for TB alleviate the biases only when the true overall prevalence is <3.0%. Complete-case analysis produced biased estimates. In the Vukuzazi study, Bayesian LCA with simultaneous imputation of the missing bacteriological test results under the MAR and MNAR assumptions produced overall PTB prevalence of 0.9% (95% Credible Interval (CrI): 0.6–1.9) and 0.7% (95% CrI: 0.5–1.1) respectively alongside realistic estimates of overall diagnostic test sensitivity and specificity with substantially overlapping 95% CrI. The CRS-based analysis and Bayesian LCA assuming the unverified were negative for TB produced 0.7% (95% CrI: 0.5–0.9) and 0.7% (95% CrI: 0.5–1.2) overall PTB prevalence respectively with realistic estimates of overall diagnostic test sensitivity and specificity. Unlike CRS-based analysis, Bayesian LCA of multiply-imputed data using MICE mitigates both biases. Conclusion: The findings demonstrate the efficacy of these advanced techniques in alleviating the reference standard and verification biases, enhancing the robustness of community-based screening programs. Imputing missing values as negative for bacteriological tests is plausible under realistic assumptions. [ABSTRACT FROM AUTHOR]

During TB-case finding, we assessed the feasibility of implementing the advanced HIV disease (AHD) care package, including VISITECT CD4 Advanced Disease (VISITECT), a semiquantitative test to identify a CD4≤200cells/μl. Adult participants with tuberculosis symptoms, recruited near-facility in Lesotho and South-Africa between 2021–2022, were offered HIV testing (capillary blood), Xpert MTB/RIF and Ultra, and MGIT culture (sputum). People living with HIV (PLHIV) were offered VISITECT (venous blood) and Alere tuberculosis-lipoarabinomannan (AlereLAM, urine) testing. AHD was defined as a CD4≤200cells/μl on VISITECT or a positive tuberculosis test. A CD4≤200cells/μl on VISITECT triggered Immy cryptococcal antigen (Immy CrAg, plasma) testing. Participants were referred with test results. To evaluate feasibility, we assessed i) acceptability and ii) intervention delivery of point-of-care diagnostics among study staff using questionnaires and group discussions, iii) process compliance, and iv) early effectiveness (12-week survival and treatment status) in PLHIV. Predictors for 12-week survival were assessed with logistic regression. Thematic content analysis and triangulation were performed. Among PLHIV (N = 676, 48.6% of 1392 participants), 7.8% were newly diagnosed, 81.8% on ART, and 10.4% knew their HIV status but were not on ART. Among 676 PLHIV, 41.7% had AHD, 29.9% a CD4≤200cells/μl and 20.6% a tuberculosis diagnosis. Among 200 PLHIV tested with Immy CrAg, 4.0% were positive. The procedures were acceptable for study staff, despite intervention delivery challenges related to supply and the long procedural duration (median: 73 minutes). At 12 weeks, among 276 PLHIV with AHD and 328 without, 3.3% and 0.9% had died, 84.8% and 92.1% were alive and 12.0% and 7.0% had an unknown status, respectively. Neither AHD nor tuberculosis status were associated with survival. Implementing AHD care package diagnostics was feasible during tuberculosis-case finding. AHD was prevalent, and not associated with survival, which is likely explained by the low specificity of VISITECT. Challenges with CD4 testing and preventive treatment uptake require addressing. [ABSTRACT FROM AUTHOR]

Diagnostic accuracy studies in pulmonary tuberculosis (PTB) are complicated by the lack of a perfect reference standard. This limitation can be handled using latent class analysis (LCA), assuming independence between diagnostic test results conditional on the true unobserved PTB status. Test results could remain dependent, however, e.g. with diagnostic tests based on a similar biological basis. If ignored, this gives misleading inferences. Our secondary analysis of data collected during the first year (May 2018 –May 2019) of a community-based multi-morbidity screening program conducted in the rural uMkhanyakude district of KwaZulu Natal, South Africa, used Bayesian LCA. Residents of the catchment area, aged ≥15 years and eligible for microbiological testing, were analyzed. Probit regression methods for dependent binary data sequentially regressed each binary test outcome on other observed test results, measured covariates and the true unobserved PTB status. Unknown model parameters were assigned Gaussian priors to evaluate overall PTB prevalence and diagnostic accuracy of 6 tests used to screen for PTB: any TB symptom, radiologist conclusion, Computer Aided Detection for TB version 5 (CAD4TBv5≥53), CAD4TBv6≥53, Xpert Ultra (excluding trace) and culture. Before the application of our proposed model, we evaluated its performance using a previously published childhood pulmonary TB (CPTB) dataset. Standard LCA assuming conditional independence yielded an unrealistic prevalence estimate of 18.6% which was not resolved by accounting for conditional dependence among the true PTB cases only. Allowing, also, for conditional dependence among the true non-PTB cases produced a 1.1% plausible prevalence. After incorporating age, sex, and HIV status in the analysis, we obtained 0.9% (95% CrI: 0.6, 1.3) overall prevalence. Males had higher PTB prevalence compared to females (1.2% vs. 0.8%). Similarly, HIV+ had a higher PTB prevalence compared to HIV- (1.3% vs. 0.8%). The overall sensitivity for Xpert Ultra (excluding trace) and culture were 62.2% (95% CrI: 48.7, 74.4) and 75.9% (95% CrI: 61.9, 89.2), respectively. Any chest X-ray abnormality, CAD4TBv5≥53 and CAD4TBv6≥53 had similar overall sensitivity. Up to 73.3% (95% CrI: 61.4, 83.4) of all true PTB cases did not report TB symptoms. Our flexible modelling approach yields plausible, easy-to-interpret estimates of sensitivity, specificity and PTB prevalence under more realistic assumptions. Failure to fully account for diagnostic test dependence can yield misleading inferences. [ABSTRACT FROM AUTHOR]

The impacts of early pregnancy and young motherhood on everyday life, including interpersonal and individual behavior, are not well-known. Passive digital sensing on mobile technology including smartphones and passive Bluetooth beacons can yield information such as geographic movement, physical activity, and mother-infant proximity to illuminate behavioral patterns of a mother's everyday in Nepal. We contribute to mixed-methods research by triangulating passive sensing data (GPS, accelerometry, Bluetooth proximity) with multiple forms of qualitative data to characterize behavioral patterns and experiences of young motherhood in the first year postpartum. We triangulated this digital information in a constant comparative analysis with in-depth interviews, daily diaries, and fieldnotes. We reveal typical behavioral patterns of rural young mothers and highlight opportunities for integrating this information to improve health and well-being. [ABSTRACT FROM AUTHOR]

Introduction: To sustainably provide good quality care to increasing numbers of people living with HIV (PLHIV) receiving antiretroviral therapy (ART) in resource-limited settings, care delivery must shift from a "one-size-fits-all" approach to differentiated service delivery models. Such models should reallocate resources from PLHIV who are doing well to groups of PLHIV who may need more attention, such as those with treatment failure. The VIral load Triggered ART care Lesotho (VITAL) trial assesses a viral load (VL)-, participant's preference-informed, electronic health (eHealth)-supported, automated differentiated service delivery model (VITAL model). With VITAL, we aim to assess if the VITAL model is at least non-inferior to the standard of care in the proportion of participants engaged in care with viral suppression at 24 months follow-up and if it is cost-saving. Methods: The VITAL trial is a pragmatic, multicenter, cluster-randomized, non-blinded, non-inferiority trial with 1:1 allocation conducted at 18 nurse-led, rural health facilities in two districts of northern Lesotho, enrolling adult PLHIV taking ART. In intervention clinics, providers are trained to implement the VITAL model and are guided by a clinical decision support tool, the VITALapp. VITAL differentiates care according to VL results, clinical characteristics, sub-population and participants' and health care providers' preferences. Expected outcomes: Evidence on the effect of differentiated service delivery for PLHIV on treatment outcomes is still limited. This pragmatic cluster-randomized trial will assess if the VITAL model is at least non-inferior to the standard of care and if it is cost saving. Trial registration: The study has been registered with clinicaltrials.gov (Registration number NCT04527874; August 27, 2020). [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa has been heavily impacted by the HIV/AIDS epidemic. Social data (e.g., social media, internet search, wearable device, etc) show great promise assisting in public health and HIV surveillance. However, research on this topic has primarily focused in higher resource settings, such as the United States. It is especially important to study the prevalence and potential use of these data sources and tools in low- and middle-income countries (LMIC), such as Sub-Saharan Africa, which have been heavily impacted by the HIV epidemic, to determine the feasibility of using these technologies as surveillance and intervention tools. Accordingly, we 1) described the prevalence and characteristics of various social technologies within South Africa, 2) using Twitter, Instagram, and YouTube as a case study, analyzed the prevalence and patterns of social media use related to HIV risk in South Africa, and 3) mapped and statistically tested differences in HIV-related social media posts within regions of South Africa. Geocoded data were collected over a three-week period in 2018 (654,373 tweets, 90,410 Instagram posts and 14,133 YouTube videos with 1,121 comments). Of all tweets, 4,524 (0.7%) were found to related to HIV and AIDS. The percentage was similar for Instagram 95 (0.7%) but significantly lower for YouTube 18 (0.1%). We found regional differences in prevalence and use of social media related to HIV. We discuss the implication of data from these technologies in surveillance and interventions within South Africa and other LMICs. [ABSTRACT FROM AUTHOR]

Background: There is increased focus on HIV prevention with African men who report experiencing childhood sexual (CSA) or physical abuse (CPA). Objective: To better understand the effects of a community-based intervention (Project Accept HPTN 043) on HIV prevention behaviors among men who report CSA or CPA experiences. Methods: Project Accept compared a community-based voluntary mobile counseling and testing (CBVCT) intervention with standard VCT. The intervention employed individual HIV risk reduction planning with motivational interviewing in 34 African communities (16 communities at 2 sites in South Africa, 10 in Tanzania, and 8 in Zimbabwe). Communities were randomized unblinded in matched pairs to CBVCT or SVCT, delivered over 36 months. The post-intervention assessment was conducted using a single, cross-sectional random survey of 18-32 year-old community members (total N = 43,292). We analyzed the effect of the intervention on men with reported CSA or CPA across the African sites. Men were identified with a survey question asking about having experienced CSA or CPA across the lifespan. The effect of intervention on considered outcomes of the preventive behavior was statistically evaluated using the logistic regression models. Results: Across the sites, the rates of CSA or CPA among men indicated that African men reflected the global prevalence (20%) with a range of 13–24%. The statistically significant effect of the intervention among these men was seen in their increased effort to receive their HIV test results (OR 2.71; CI: (1.08, 6.82); P: 0.034). The intervention effect on the other designated HIV prevention behaviors was less pronounced. Conclusion: The effect of the intervention on these men showed increased motivation to receive their HIV test results. However, more research is needed to understand the effects of community-based interventions on this group, and such interventions need to integrate other keys predictors of HIV including trauma, coping strategies, and intimate partner violence. [ABSTRACT FROM AUTHOR]

Objective: We evaluate the effect of clinic-based support by HIV-positive Peer Mentors, in addition to standard clinic care, on maternal and infant well-being among Women Living with HIV (WLH) from pregnancy through the infant's first year of life. Methods: In a cluster randomized controlled trial in KwaZulu-Natal, South Africa, eight clinics were randomized for pregnant WLH to receive either: a Standard Care condition (SC; 4 clinics; n = 656 WLH); or an Enhanced Intervention (EI; 4 clinics; n = 544 WLH). WLH in the EI were invited to attend four antenatal and four postnatal meetings led by HIV-positive Peer Mentors, in addition to SC. WLH were recruited during pregnancy, and at least two post-birth assessment interviews were completed by 57% of WLH at 1.5, 6 or 12 months. EI's effect was ascertained on 19 measures of maternal and infant well-being using random effects regressions to control for clinic clustering. A binomial test for correlated outcomes evaluated EI's overall efficacy. Findings: WLH attended an average of 4.1 sessions (SD = 2.0); 13% did not attend any sessions. Significant overall benefits were found in EI compared to SC using the binomial test. Secondarily, over time, WLH in the EI reported significantly fewer depressive symptoms and fewer underweight infants than WLH in the SC condition. EI WLH were significantly more likely to use one feeding method for six months and exclusively breastfeed their infants for at least 6 months. Conclusions: WLH benefit by support from HIV-positive Peer Mentors, even though EI participation was partial, with incomplete follow-up rates from 6–12 months. Trial Registration: ClinicalTrials.gov NCT00972699 [ABSTRACT FROM AUTHOR]

Community-based delivery and monitoring of antiretroviral therapy (ART) for HIV has the potential to increase viral suppression for individual- and population-level health benefits. However, the cost-effectiveness and budget impact are needed for public health policy. We used a mathematical model of HIV transmission in KwaZulu-Natal, South Africa, to estimate population prevalence, incidence, mortality, and disability-adjusted life-years (DALYs) from 2020 to 2060 for two scenarios: 1) standard clinic-based HIV care and 2) five-yearly home testing campaigns with community ART for people not reached by clinic-based care. We parameterised model scenarios using observed community-based ART efficacy. Using a health system perspective, we evaluated incremental cost-effectiveness and net health benefits using a threshold of $750/DALY averted. In a sensitivity analysis, we varied the discount rate; time horizon; costs for clinic and community ART, hospitalisation, and testing; and the proportion of the population receiving community ART. Uncertainty ranges (URs) were estimated across 25 best-fitting parameter sets. By 2060, community ART following home testing averted 27.9% (UR: 24.3-31.5) of incident HIV infections, 27.8% (26.8-28.8) of HIV-related deaths, and 18.7% (17.9-19.7) of DALYs compared to standard of care. Adolescent girls and young women aged 15-24 years experienced the greatest reduction in incident HIV (30.7%, 27.1-34.7). In the first five years (2020-2024), community ART required an additional $44.9 million (35.8-50.1) annually, representing 14.3% (11.4-16.0) of the annual HIV budget. The cost per DALY averted was $102 (85-117) for community ART compared with standard of care. Providing six-monthly refills instead of quarterly refills further increased cost-effectiveness to $78.5 per DALY averted (62.9-92.8). Cost-effectiveness was robust to sensitivity analyses. In a high-prevalence setting, scale-up of decentralised ART dispensing and monitoring can provide large population health benefits and is cost-effective in preventing death and disability due to HIV., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: Maitreyi Sahu acknowledges payments to institution and salary support from the Bill & Melinda Gates Foundation, Gates Ventures, and the Peterson Center on Health Care. Cara J. Bayer acknowledges payments to institution and salary support from the National Cancer Institute (U01 CA199334). She also acknowledges payments to the Center for Studies in Demography & Ecology at the University of Washington. This funding supports the Hyak supercomputing system at the University of Washington, which facilitated the work presented in the present manuscript. Finally, after initial design, preparation and submission of this manuscript, Cara worked as a part-time Graduate Research Assistant for Merck & Co., Inc from 05/07/2022 to 08/14/2022 on a topic different from that covered in this manuscript. D. Allen Roberts acknowledges that he was paid by the Bill & Melinda Gates Foundation as a Research Assistant through the University of Washington. He also acknowledges a grant from the National Institutes of Mental Health. Maryam Shahmanesh acknowledges grant support from Wellcome Trust, the Bill and Melinda Gates Foundation, the National Institutes of Health, and National Institute for Health and Care Research. Kombi Sausi acknowledges grant support from the Wellcome Trust, Bill and Melinda Gates Foundation, National Insitutes of Health, and National Insitute for Health and Care Research. Darcy W. Rao acknowledges a career development award and salary support from the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number KL2 TR002317. She also acknowledges payments to institution and salary support from the National Cancer Institute (U01 CA199334), as well as salary support for work unrelated to the present manuscript from NIH, USAID, and the World Health Organization. Dr. Rao acknowledges payments to the Center for Studies in Demography & Ecology at the University of Washington. This funding supports the Hyak supercomputing system at the University of Washington, which facilitated the work presented in the present manuscript. Dr. Rao is now employed as a Senior Program Officer starting October 2022. Contributions to the enclosed manuscript proceeded employment at the Foundation, and her current scope of work is not related to the content of the manuscript. Adrienne E. Shapiro acknowledges payments to institution from BMGF. She is also supported in part by grant NIH K23AI140918 from NIH NIAID. Dr. Shapiro also sits on a DSMB for the DATURA clinical trial of TB treatment for persons with HIV (Sponsor: ANRS). Jared M. Baeten is an employee of Gilead Sciences and acknowledges grant support from the Bill and Melinda Gates Foundation and payments to institution from the National Institutes of Health. Connie Celum reports funding from USAID and consulting for Gilead Sciences and Merck. Paul Revill acknowledges a consultancy from UNAIDS to review HIV national strategic plans and investment cases. Ruanne V. Barnabas acknowledges grants from BMGF, NIH, and Francis and Dorothea Reed Endowed Chair in Infectious Diseases. She also receives an honorarium for serving on a Gilead Sciences DSMB, and acknowledges that Regeneron covered the cost of conference abstract and manuscript writing., (Copyright: © 2023 Sahu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)