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Introduction: Antiretroviral therapy (ART) and tuberculosis preventive treatment (TPT) both prevent tuberculosis (TB) disease and deaths among people living with HIV. Differentiated care models, including community‐based care, can increase the uptake of ART and TPT to prevent TB in settings with a high burden of HIV‐associated TB, particularly among men. Methods: We developed a gender‐stratified dynamic model of TB and HIV transmission and disease progression among 100,000 adults ages 15−59 in KwaZulu‐Natal, South Africa. We drew model parameters from a community‐based ART initiation and resupply trial in sub‐Saharan Africa (Delivery Optimization for Antiretroviral Therapy, DO ART) and other scientific literature. We simulated the impacts of community‐based ART and TPT care programmes during 2018−2027, assuming that community‐based ART and TPT care were scaled up to similar levels as in the DO ART trial (i.e. ART coverage increasing from 49% to 82% among men and from 69% to 83% among women) and sustained for 10 years. We projected the number of TB cases, deaths and disability‐adjusted life years (DALYs) averted relative to standard, clinic‐based care. We calculated programme costs and incremental cost‐effectiveness ratios from the provider perspective. Results: If community‐based ART care could be implemented with similar effectiveness to the DO ART trial, increased ART coverage could reduce TB incidence by 27.0% (range 21.3%−34.1%) and TB mortality by 34.6% (range 24.8%–42.2%) after 10 years. Increasing both ART and TPT uptake through community‐based ART with TPT care could reduce TB incidence by 29.7% (range 23.9%−36.0%) and TB mortality by 36.0% (range 26.9%−43.8%). Community‐based ART with TPT care reduced gender disparities in TB mortality rates, with a projected 54 more deaths annually among men than women (range 11–103) after 10 years of community‐based care versus 109 (range 41–182) in standard care. Over 10 years, the mean cost per DALY averted by community‐based ART with TPT care was $846 USD (range $709–$1012). Conclusions: By substantially increasing coverage of ART and TPT, community‐based care for people living with HIV could reduce TB incidence and mortality in settings with high burdens of HIV‐associated TB and reduce TB gender disparities. [ABSTRACT FROM AUTHOR]

Background: Chest X-ray offers high sensitivity and acceptable specificity as a tuberculosis screening tool, but in areas with a high burden of tuberculosis, there is often a lack of radiological expertise to interpret chest X-ray. Computer-aided detection systems based on artificial intelligence are therefore increasingly used to screen for tuberculosis-related abnormalities on digital chest radiographies. The CAD4TB software has previously been shown to demonstrate high sensitivity for chest X-ray tuberculosis-related abnormalities, but it is not yet calibrated for the detection of non-tuberculosis abnormalities. When screening for tuberculosis, users of computer-aided detection need to be aware that other chest pathologies are likely to be as prevalent as, or more prevalent than, active tuberculosis. However, non--tuberculosis chest X-ray abnormalities detected during chest X-ray screening for tuberculosis remain poorly characterized in the sub-Saharan African setting, with only minimal literature. Case presentation: In this case series, we report on four cases with non-tuberculosis abnormalities detected on CXR in TB TRIAGE + ACCURACY (ClinicalTrials.gov Identifier: NCT04666311), a study in adult presumptive tuberculosis cases at health facilities in Lesotho and South Africa to determine the diagnostic accuracy of two potential tuberculosis triage tests: computer-aided detection (CAD4TB v7, Delft, the Netherlands) and C-reactive protein (Alere Afinion, USA). The four Black African participants presented with the following chest X-ray abnormalities: a 59-year-old woman with pulmonary arteriovenous malformation, a 28-year-old man with pneumothorax, a 20-year-old man with massive bronchiectasis, and a 47-year-old woman with aspergilloma. Conclusions: Solely using chest X-ray computer-aided detection systems based on artificial intelligence as a tuberculosis screening strategy in sub-Saharan Africa comes with benefits, but also risks. Due to the limitation of CAD4TB for non-tuberculosis-abnormality identification, the computer-aided detection software may miss significant chest X-ray abnormalities that require treatment, as exemplified in our four cases. Increased data collection, characterization of non-tuberculosis anomalies and research on the implications of these diseases for individuals and health systems in sub-Saharan Africa is needed to help improve existing artificial intelligence software programs and their use in countries with high tuberculosis burden. [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]