Evaluating systematic targeted universal testing for tuberculosis in primary care clinics of South Africa: A cluster-randomized trial (The TUTT Trial).

BACKGROUND: The World Health Organization (WHO) recommends systematic symptom screening for tuberculosis (TB). However, TB prevalence surveys suggest that this strategy does not identify millions of TB patients, globally. Undiagnosed or delayed diagnosis of TB contribute to TB transmission and exacerbate morbidity and mortality. We conducted a cluster-randomized trial of large urban and rural primary healthcare clinics in 3 provinces of South Africa to evaluate whether a novel intervention of targeted universal testing for TB (TUTT) in high-risk groups diagnosed more patients with TB per month compared to current standard of care (SoC) symptom-directed TB testing. METHODS AND FINDINGS: Sixty-two clinics were randomized; with initiation of the intervention clinics over 6 months from March 2019. The study was prematurely stopped in March 2020 due to clinics restricting access to patients, and then a week later due to the Coronavirus Disease 2019 (COVID-19) national lockdown; by then, we had accrued a similar number of TB diagnoses to that of the power estimates and permanently stopped the trial. In intervention clinics, attendees living with HIV, those self-reporting a recent close contact with TB, or a prior episode of TB were all offered a sputum test for TB, irrespective of whether they reported symptoms of TB. We analyzed data abstracted from the national public sector laboratory database using Poisson regression models and compared the mean number of TB patients diagnosed per clinic per month between the study arms. Intervention clinics diagnosed 6,777 patients with TB, 20.7 patients with TB per clinic month (95% CI 16.7, 24.8) versus 6,750, 18.8 patients with TB per clinic month (95% CI 15.3, 22.2) in control clinics during study months. A direct comparison, adjusting for province and clinic TB case volume strata, did not show a significant difference in the number of TB cases between the 2 arms, incidence rate ratio (IRR) 1.14 (95% CI 0.94, 1.38, p = 0.46). However, prespecified difference-in-differences analyses showed that while the rate of TB diagnoses in control clinics decreased over time, intervention clinics had a 17% relative increase in TB patients diagnosed per month compared to the prior year, interaction IRR 1.17 (95% CI 1.14, 1.19, p < 0.001). Trial limitations were the premature stop due to COVID-19 lockdowns and the absence of between-arm comparisons of initiation and outcomes of TB treatment in those diagnosed with TB. CONCLUSIONS: Our trial suggests that the implementation of TUTT in these 3 groups at extreme risk of TB identified more TB patients than SoC and could assist in reducing undiagnosed TB patients in settings of high TB prevalence. TRIAL REGISTRATION: South African National Clinical Trials Registry DOH-27-092021-4901.

Yield of Facility-based Targeted Universal Testing for Tuberculosis With Xpert and Mycobacterial Culture in High-Risk Groups Attending Primary Care Facilities in South Africa.

BACKGROUND: We report the yield of targeted universal tuberculosis (TB) testing of clinic attendees in high-risk groups. METHODS: Clinic attendees in primary healthcare facilities in South Africa with one of the following risk factors underwent sputum testing for TB: human immunodeficiency virus (HIV), contact with a TB patient in the past year, and having had TB in the past 2 years. A single sample was collected for Xpert-Ultra (Xpert) and culture. We report the proportion positive for Mycobacterium tuberculosis. Data were analyzed descriptively. The unadjusted clinical and demographic factors' relative risk of TB detected by culture or Xpert were calculated and concordance between Xpert and culture is described. RESULTS: A total of 30 513 participants had a TB test result. Median age was 39 years, and 11 553 (38%) were men. The majority (n = 21734, 71%) had HIV, 12 492 (41%) reported close contact with a TB patient, and 1573 (5%) reported prior TB. Overall, 8.3% were positive for M. tuberculosis by culture and/or Xpert compared with 6.0% with trace-positive results excluded. In asymptomatic participants, the yield was 6.7% and 10.1% in symptomatic participants (with trace-positives excluded). Only 10% of trace-positive results were culture-positive. We found that 55% of clinic attendees with a sputum result positive for M. tuberculosis did not have a positive TB symptom screen. CONCLUSIONS: A high proportion of clinic attendees with specific risk factors (HIV, close TB contact, history of TB) test positive for M. tuberculosis when universal testing is implemented.

Telemedicine in the Western Cape Department of Health during the first peak of the COVID-19 pandemic: Leveraging data to save lives by activating a telemedicine response.

The pandemic caused by coronavirus disease 2019 (COVID-19) has put health systems across the globe under strain. There has been much suffering and loss, but a silver lining is emerging - a growing list of deeply contextualised, resource-light and patient-centric innovations that are showing the promise of reshaping health care delivery as we know it. Some of these innovations were lying latent in the system, waiting for the 'dots to be joined'. The Western Cape was the first province in South Africa to experience a COVID-19 wave from May 2020 to July 2020, with 60-70 deaths being reported daily. To bend the mortality curve during this crisis was not easy but was made possible using a rudimentary telehealth system. This project represents an exemplar of innovation, built out of necessity to save lives and may well become a staple component of the health service in a post-crisis era.

Health system determinants of tuberculosis mortality in South Africa: a causal loop model.

BACKGROUND: Tuberculosis (TB) is a major public health concern in South Africa and TB-related mortality remains unacceptably high. Numerous clinical studies have examined the direct causes of TB-related mortality, but its wider, systemic drivers are less well understood. Applying systems thinking, we aimed to identify factors underlying TB mortality in South Africa and describe their relationships. At a meeting organised by the 'Optimising TB Treatment Outcomes' task team of the National TB Think Tank, we drew on the wide expertise of attendees to identify factors underlying TB mortality in South Africa. We generated a causal loop diagram to illustrate how these factors relate to each other. RESULTS: Meeting attendees identified nine key variables: three 'drivers' (adequacy & availability of tools, implementation of guidelines, and the burden of bureaucracy); three 'links' (integration of health services, integration of data systems, and utilisation of prevention strategies); and three 'outcomes' (accessibility of services, patient empowerment, and socio-economic status). Through the development and refinement of the causal loop diagram, additional explanatory and linking variables were added and three important reinforcing loops identified. Loop 1, 'Leadership and management for outcomes' illustrated that poor leadership led to increased bureaucracy and reduced the accessibility of TB services, which increased TB-related mortality and reinforced poor leadership through patient empowerment. Loop 2, 'Prevention and structural determinants' describes the complex reinforcing loop between socio-economic status, patient empowerment, the poor uptake of TB and HIV prevention strategies and increasing TB mortality. Loop 3, 'System capacity' describes how fragmented leadership and limited resources compromise the workforce and the performance and accessibility of TB services, and how this negatively affects the demand for higher levels of stewardship. CONCLUSIONS: Strengthening leadership, reducing bureaucracy, improving integration across all levels of the system, increasing health care worker support, and using windows of opportunity to target points of leverage within the South African health system are needed to both strengthen the system and reduce TB mortality. Further refinement of this model may allow for the identification of additional areas of intervention.

Home delivery of medication during Coronavirus disease 2019, Cape Town, South Africa: Short report.

The public sector primary care facilities in Cape Town serve a large number of patients with chronic diseases such as human immunodeficiency virus, tuberculosis, diabetes, hypertension, asthma and chronic obstructive pulmonary disease. Prior to the Coronavirus disease 2019 (COVID-19) epidemic, stable patients with chronic conditions attended the facility or support groups to obtain their medication. During the COVID-19 epidemic, these patients would be put at risk if they had to travel and gather in groups to receive medication. The Metropolitan Health Services, therefore, decided to offer home delivery of medication. A system of home delivery was rapidly established by linking the existing chronic dispensing unit system with the emerging approach to community-orientated primary care in the Metro. Medication was delivered as usual to primary care pharmacies, but then a variety of means were used to disseminate the parcels to local non-profit organisations, where they could be delivered by a city-wide network of community health workers (CHWs). Innovations included various ways of delivering the parcels, including via Uber, bicycles and electric scooters, as well as Google forms to monitor the success of the initiative. It was estimated that up to 200 000 parcels per month could be delivered in this way via 2500 CHWs. The new system was established throughout the Metropole, and its strengths, weaknesses, opportunities and threats are further discussed. The initiative may prevent COVID-19 amongst people with comorbidities who would be at risk of more severe diseases. It may also have de-congested primary care facilities ahead of the expected surge in COVID-19 cases.

The South African Tuberculosis Care Cascade: Estimated Losses and Methodological Challenges.

Background: While tuberculosis incidence and mortality are declining in South Africa, meeting the goals of the End TB Strategy requires an invigorated programmatic response informed by accurate data. Enumerating the losses at each step in the care cascade enables appropriate targeting of interventions and resources. Methods: We estimated the tuberculosis burden; the number and proportion of individuals with tuberculosis who accessed tests, had tuberculosis diagnosed, initiated treatment, and successfully completed treatment for all tuberculosis cases, for those with drug-susceptible tuberculosis (including human immunodeficiency virus (HIV)-coinfected cases) and rifampicin-resistant tuberculosis. Estimates were derived from national electronic tuberculosis register data, laboratory data, and published studies. Results: The overall tuberculosis burden was estimated to be 532005 cases (range, 333760-764480 cases), with successful completion of treatment in 53% of cases. Losses occurred at multiple steps: 5% at test access, 13% at diagnosis, 12% at treatment initiation, and 17% at successful treatment completion. Overall losses were similar among all drug-susceptible cases and those with HIV coinfection (54% and 52%, respectively, successfully completed treatment). Losses were substantially higher among rifampicin- resistant cases, with only 22% successfully completing treatment. Conclusion: Although the vast majority of individuals with tuberculosis engaged the public health system, just over half were successfully treated. Urgent efforts are required to improve implementation of existing policies and protocols to close gaps in tuberculosis diagnosis, treatment initiation, and successful treatment completion.