Tanyaradzwa Nicolette Dube

Mobile health (mHealth) technologies are increasingly used to support community-based healthcare. However, their real-world impact often remains unclear. Understanding implementation factors is essential for advancing their use and achieving meaningful health outcomes. We evaluated an mHealth tool (AitaHealth) after customising its modules and workflows for household Tuberculosis (TB) contact tracing and other community-based data collection by community health workers (CHWs). We describe the acceptability, feasibility, and implementation fidelity of this approach. We conducted a mixed-methods evaluation in two South African districts: uMkhanyakude and Ekurhuleni. We collected qualitative data through focus group discussions (FGDs) and in-depth interviews (IDIs) with CHWs, team leaders, and key stakeholders. We used deductive thematic analysis grounded in the Technology Acceptance Model (TAM) to assess the acceptability and implementation feasibility of the mHealth tool. We used quantitative data from the AitaHealth metadata to assess implementation fidelity. CHWs appreciated AitaHealth’s efficiency, data security, and credibility. Across the two districts, 103 CHWs recorded data for 2,452 households and 10,649 household members. However, they reported challenges in ease of use, with unreliable devices, weak support, and safety concerns hindering data collection. These issues led to inconsistent engagement, with 48.5% of CHWs logging in fewer than 15 times during implementation. Despite these challenges, when used, AitaHealth ensured high-quality data collection and household coverage, with TB-related fields completed in over 94% of households, demonstrating its potential under better conditions. AitaHealth`s limitations stemmed from system constraints rather than user resistance. To achieve full impact, mHealth tools require reliable infrastructure and supportive environments for both the tools and their implementers.

Background: Tuberculosis remains a leading cause of death globally, particularly in countries with high tuberculosis and HIV burdens. Disruptions caused by the COVID‐19 pandemic may have further impacted tuberculosis outcomes. This study examines on‐treatment mortality and associated risk factors in five countries. Method: We conducted a secondary analysis of data from ASCENT cluster‐randomised trials of digital adherence tools for improved adherence involving 23,799 adults with drug‐sensitive tuberculosis in South Africa, Tanzania, Ethiopia, the Philippines, and Ukraine. Analyses were conducted separately by country. Mortality rates were measured from treatment initiation to the earliest of 6 months, death, or loss to follow‐up. Cox regression models (with random effects or robust standard errors for clustering) assessed the associations between mortality and HIV status, ART use, tuberculosis diagnosis type, and calendar periods (COVID‐19 pandemic and conflict in Ukraine). Results: Mortality rates ranged from 7.6 (Ethiopia) to 23.2 (Tanzania) and 23.3 (Ukraine) per 100 person‐years. Higher mortality was associated with: older age in all countries (age < 30 versus ≥ 60 years, adjusted rate ratio [aRR] ranging from 2.38 to 6.57 by country); HIV status (positive versus negative, aRR ranging from 1.44 to 2.98 by country); tuberculosis diagnosis type (clinical vs. bacteriological, aRR 1.5–1.6 in Ethiopia, Tanzania and South Africa); extrapulmonary tuberculosis (aRR 1.44 to 1.60 in Ukraine and Tanzania). ART versus HIV‐positive not on ART was linked to lower mortality in South Africa and Ukraine but not in Tanzania. Analyses suggested possible mortality variations by calendar period. Conclusion: Our findings suggest variability in tuberculosis mortality across settings, influenced by HIV/ART and diagnosis type. The high mortality rates across countries may reflect underlying causes or potential misdiagnoses. Further investigation into these factors may be needed to improve tuberculosis outcomes globally.

Background: Tuberculosis (TB) remains a challenge in South Africa, with an estimated 280,000 new cases reported in 2022. Digital Adherence Technologies (DATs) may be important tools to improve adherence to TB treatment. However, there is limited knowledge about facilitators and barriers to implementing these technologies in South Africa. Methods: This qualitative study was embedded within the Adherence Support Coalition to End TB cluster-randomised trial which implemented the two technologies: a smart pillbox and/or a cell phone-based strategy similar to 99DOTS (labels), plus differentiated care, to support people with drug-sensitive TB (PWTB). In-depth interviews were conducted with purposively sampled participants comprising PWTB, Healthcare Workers (HCWs) and stakeholders. Inductive thematic analysis was used for data analysis, while the Unified Theory of Acceptance and Use of Technology (UTAUT) framework served as the overarching framework to synthesize and summarise the findings. Findings: Sixty-eight interviews were conducted: 35 with PWTB and 33 with HCWs and stakeholders. Facilitating factors for the pillbox were alarm reminder, storage, ease of use, not requiring a phone, social support, and portability. Barriers to the pillbox were that some found the box unportable and others experienced box malfunctioning. Facilitating factors for the labels were ease of use among the young, daily confirmation messages, social support, privacy, and portability. Barriers to implementing these DATs were older age, illiteracy, forgetting to send the SMS, lacking understanding, no cell phone access, power cuts, and unresolvable technical glitches. While differentiated care improved the client-provider relationship, some PWTB felt home visits were stigmatising. HCWs and stakeholders expressed willingness to scale up DATs because they improved their working conditions, and it was advantageous for the PWTB. Conclusions: Smart pillbox and labels had features which favoured their acceptability and there were also DAT specific barriers. DATs may improve person-centredness in TB care. Future guidelines should consider acceptability, differing situations, and allowing flexibility to possibly increase uptake and utilisation of DATs.

Background: HIV weakens the immune system, increasing the risk of tuberculosis (TB) in people with living HIV (PLHIV). People living with HIV and on antiretroviral treatment (ART) often experience physical body size changes. Studies have found a significant discrepancy between PLHIV’s self-reported weight loss and their measured weight loss when being screened for TB using the WHO tool. To understand this inconsistency, a qualitative sub-study was conducted to explore perceptions and attitudes towards weight change among adults attending HIV care, as well as health care workers in public clinics in Gauteng, South Africa. Methods: Our qualitative study was nested within the XPHACTOR study. A total of seven focus group discussions were conducted, five with adult participants attending for HIV care and two with health care workers and research staff in clinics around Gauteng. Inductive thematic analysis was used to analyse the data. Findings: The majority of PLHIV preferred to gain weight due to fear of stigma associated with weight loss. Weight loss is associated with HIV/AIDS, suggesting that people attending HIV care may underreport weight loss in the context of a TB symptoms screening tool because they fear stigma. Participants reported that weight changes impacted their daily lives and had psychological effects on them. Some PLHIV described lipodystrophy as disproportional weight gain. Culture and media have an influence on the perception of ideal body size and shape for both men and women. Conclusions: Underreporting weight loss might result in poor sensitivity of the WHO TB screening tool and suggests that we need either alternative ways to determine weight loss or screening tools for TB that are less dependent on reported symptoms.

Background: Digital adherence technologies (DATs) are promising tools for supporting tuberculosis (TB) treatment. DATs can serve as reminders for people with TB to take their medication and act as proxies for adherence monitoring. Strong engagement with DATs, from both the person with TB and health care provider (HCP) perspectives, is essential for ensuring intervention fidelity. The Adherence Support Coalition to End TB (ASCENT) project evaluated 2 types of DATs, pillboxes and medication labels (99DOTS), in cluster-randomized trials across 5 countries. Objective: This study aims to investigate participant and HCP engagement with DATs for TB treatment, stratified by DAT type and country. Methods: This study is a subanalysis of data generated through the ASCENT trials, which enrolled adults with drug-susceptible TB. A digital dose was defined as either a pillbox opening (for pillbox users) or a dosing confirmation SMS text message sent by the participant (for label users), both of which were recorded on the adherence platform. Descriptive analysis was used to provide an overview of dose-day outcomes. DAT engagement was assessed from both participant and HCP perspectives. To enhance participant engagement, we summarized the frequency of digital engagement overall and by treatment phase, as well as the frequency of consecutive days without engagement. For HCP engagement, we summarized the frequency of doses added manually, the number of days between the actual dose day and when a manual dose was added, and instances of consecutive manual dosing lasting more than 3 and more than 7 days, where doses were added more than 1 week after the dose day. Results: Of the 9511 participants included, 6719 (70.64%) were using the pillbox, 3544 (37.26%) were female, and the median age was 40 years. Across DAT types, there were 1,384,879 dose days, with 973,876 (70.32%) contributed by pillbox users. Of all dose days, 1,165,195 (84.14%) were recorded as digital, 156,664 (11.31%) as manual, 59,045 (4.26%) had no information, and 3975 (0.29%) were confirmed as missed. Digital dosing decreased slightly from the intensive to the continuation phase. The percentage of digital dose days was higher among pillbox users (851,496/973,876, 87.43%) compared with label users (313,699/411,003, 76.33%). Among label users, manual dosing was most common in the Philippines (37,919/171,786, 22.07%) and least common in Tanzania (11,108/76,231, 14.57%). Among pillbox users, manual dosing was most common in the Philippines (24,015/208,130, 11.54%) and Ukraine (13,209/111,901, 11.80%). Overall, 512 out of 2792 (18.34%) label users and 588 out of 6719 (8.75%) pillbox users experienced a run of more than 7 consecutive nondigital dose days that were resolved more than 1 week after the dose day. The highest occurrence was observed in the Philippines (368/1142, 32.22%, for label users and 224/1351, 16.58%, for pillbox users). Conclusions: There was considerable variation in DAT engagement across countries and DAT types, reflecting differences in how the intervention was implemented. Further refinement of the intervention and improvements in its delivery may be necessary to enhance outcomes.

Background: Digital adherence technologies (DATs) with associated differentiated care are potential tools to improve tuberculosis (TB) treatment outcomes and reduce associated costs for both patients and healthcare providers. However, the balance between epidemiological and economic benefits remains unclear. Here, we used data from the ASCENT trial to estimate the potential long-term epidemiological and economic impact of DAT interventions in Ethiopia. Methods: We developed a compartmental transmission model for TB, calibrated to Ethiopia and parameterised with patient and provider costs. We compared the epidemiological and economic impact of two DAT interventions, a digital pillbox and medication labels, to the current standard of care, assuming each was introduced at scale in 2023. We projected long-term TB incidence, mortality and costs to 2035 and conducted a threshold analysis to identify the maximum possible epidemiological impact of a DAT intervention by assuming 100% treatment completion for patients on DAT. Findings: We estimated small and uncertain epidemiological benefits of the pillbox intervention compared with the standard of care in Ethiopia, with a difference of −0.4% (95% uncertainty interval (UI) −1.1%; +2.0%) incident TB episodes and −0.7% (95% UI −2.2%; +3.6%) TB deaths. However, our analysis also found large total provider and patient cost savings (US$163 (95% UI US$118; US$211) and US$3 (95%UI: US$1; US$5), respectively, over 2023–2035), translating to a 50.2% (95% UI 35.9%; 65.2%) reduction in total cost of treatment. Results were similar for the medication label intervention. The maximum possible epidemiological impact a theoretical DAT intervention could achieve over the same timescale would be a 3% (95% UI 1.4%; 5.5%) reduction in incident TB and an 8.2% (95% UI 4.4%; 12.8%) reduction in TB deaths. Interpretation: DAT interventions, while showing limited epidemiological impact, could substantially reduce TB treatment costs for both patients and the healthcare provider.