Faculty of Health Sciences (Research Outputs)
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Item Group-based trajectory modeling to describe the geographical distribution of tuberculosis notifcations(Springer Nature, 2025-02) Martinson, Neil A.; Lebina, Limakatso; Dagnew, Alemnew F.; Hanrahan, Colleen F.; Dowdy, David W.; Nonyane, Bareng A. S.Background Tuberculosis (TB) is a major public health problem, and understanding the geographic distribution of the disease is critical in planning and evaluating intervention strategies. This manuscript illustrates the application of Group-Based Trajectory Modeling (GBTM), a statistical method that analyzes the evolution of an outcome over time to identify groups with similar trajectories. Specifically, we apply GBTM to identify the evolution of the number of TB notifications over time across various geographic locations, aiming to identify groups of locations with similar trajectories. Locations sharing the same trajectory may be considered geographic TB clusters, indicating areas with similar TB notifications. We used data abstracted from clinic records in Limpopo province, South Africa, treating the clinics as a proxy for the spatial location of their respective catchment areas. Methods Data for this analysis were obtained as part of a cluster-randomized trial involving 56 clinics to evaluate two active TB patient-funding strategies in South Africa. We utilized GBTM to identify groups of clinics with similar trajectories of the number of TB patients. Results We identified three trajectory groups: Groups 1, comprising 57.8% of clinics; Group 2, 33.9%; and Group 3, 8.3%. These groups accounted for 30.8%, 44.4%, and 24.8% of total TB-diagnosed patients, respectively. The estimated mean number of TB-diagnosed patients was highest in trajectory group 3 followed by trajectory group 2 across the 12 months, with no overlap in the corresponding 95% confidence intervals. The estimated mean number of TB-diagnosed patients over time was fairly constant for trajectory groups 1 and 2 with exponentiated slopes of 0.979 (95% CI: 0.950, 1.004) and 1.004 (95% CI: 0.977, 1.044), respectively. In contrast, there was a statistically significant 3.8% decrease in the number of TB patients per month for trajectory group 3 with an exponentiated slope of 0.962 (95% CI: 0.901, 0.985) per month. Conclusions GBTM is a powerful tool for identifying geographic clusters of varying levels of TB notification when longitudinal data on the number of TB diagnoses are available. This analysis can inform the planning and evaluation of intervention strategies.Item Improving poor outcomes of children with Biliary Atresia in South Africa by early referral to centralized units(Wolters Kluwer., 2021) van der Schyff, Francisca; Terblanche, Alberta J.; Botha, Jean F.Objectives: Biliary atresia (BA) is a progressive fibrosing cholangiopathy of infancy, the most common cause of cholestatic jaundice in infants and the top indication for liver transplantation in children. Kasai portoenterostomy (KPE) when successful may delay the requirement for liver transplantation, which in the majority offers the only cure. Good outcomes demand early surgical intervention, appropriate management of liver cirrhosis, and in most cases, liver transplantation. These parameters were audited of children with BA treated at the Steve Biko Academic Hospital (SBAH) in Pretoria, South Africa. Methods: All children with BA who were managed at SBAH between June 2007 and July 2018 were included. Parameters measured centered on patient demographics, timing of referral and surgical intervention, immediate and long-term outcomes of surgery, and follow-up management. Results: Of 104 children treated, 94 (90%) were KPE naive. Only 23/86 (26%) of children were referred before 60 days of life and 42/86 (49%) after 120 days. Median time to surgical assessment and surgery was 4 (IQR 1–70) and 5 (IQR 1–27) days post presentation, respectively. The median age at KPE was 91 days (IQR 28–165), with only 4/41 (12%) of KPEs performed before 60 days of life. Of those with recorded outcomes, 12/33 (36%) achieved resolution of jaundice. Only a third of the cohort were referred for transplantation. Conclusion: Children with BA have poor outcomes in the public health sector in South Africa. Late referrals, delayed diagnostics, advanced age at KPE with low drainage rates, poor follow–up, and low transplant rates account for low survival. Early referral to units offering expert intervention at all stages of care, including transplantation, would offer the best outcomes.Item A qualitative analysis of community health worker perspectives on the implementation of the preconception and pregnancy phases of the Bukhali randomised controlled trial(Public Library of Science, 2024) Norris, Shane A.; Soepnel, Larske M.; Mabetha, Khuthala; Motlhatlhedi, Molebogeng; Nkosi, Nokuthula; Lye, Stephen; Draper, Catherine E.Community health workers (CHWs) play an important role in health systems in low- and middle- income countries, including South Africa. Bukhali is a CHW-delivered intervention as part of a randomised controlled trial, to improve the health trajectories of young women in Soweto, South Africa. This study aimed to qualitatively explore factors influencing implementation of the preconception and pregnancy phases of Bukhali, from the perspective of the CHWs (Health Helpers, HHs) delivering the intervention. As part of the Bukhali trial process evaluation, three focus group discussions were conducted with the 13 HHs employed by the trial. A thematic approach was used to analyse the data, drawing on elements of a reflexive thematic and codebook approach. The following six themes were developed, representing factors impacting implementation of the HH roles: interaction with the existing public healthcare sector; participant perceptions of health; health literacy and language barriers; participants’ socioeconomic constraints; family, partner, and community views of trial components; and the HH-participant relationship. HHs reported uses of several trial-based tools to overcome implementation challenges, increasing their ability to implement their roles as planned. The relationship of trust between the HH and participants seemed to function as one important mechanism for impact. The findings supported a number of adaptations to the implementation of Bukhali, such as intensified trial-based follow-up of referrals that do not receive management at clinics, continued HH training and community engagement parallel to trial implementation, with an increased emphasis on health-related stigma and education. HH perspectives on intervention implementation highlighted adaptations across three broad strategic areas: navigating and bridging healthcare systems, adaptability to individual participant needs, and navigating stigma around disease. These findings provide recommendations for the next phases of Bukhali, for other CHW-delivered preconception and pregnancy trials, and for the strengthening of CHW roles in clinical settings with similar implementation challenges.