Correction: Early mortality in tuberculosis patients initially lost to follow up following diagnosis in provincial hospitals and primary health care facilities in Western Cape, South Africa.

[This corrects the article DOI: 10.1371/journal.pone.0252084.].

Reducing Initial Loss to Follow-up Among People With Bacteriologically Confirmed Tuberculosis: LINKEDin, a Quasi-experimental Study in South Africa.

Every person diagnosed with tuberculosis (TB) needs to initiate treatment. The World Health Organization estimated that 61% of people who developed TB in 2021 were included in a TB treatment registration system. Initial loss to follow-up (ILTFU) is the loss of persons to care between diagnosis and treatment initiation/registration. LINKEDin, a quasi-experimental study, evaluated the effect of 2 interventions (hospital recording and an alert-and-response patient management intervention) in 6 subdistricts across 3 high-TB burden provinces of South Africa. Using integrated electronic reports, we identified all persons diagnosed with TB (Xpert MTB/RIF positive) in the hospital and at primary health care facilities. We prospectively determined linkage to care at 30 days after TB diagnosis. We calculated the risk of ILTFU during the baseline and intervention periods and the relative risk reduction in ILTFU between these periods. We found a relative reduction in ILTFU of 42.4% (95% CI, 28.5%-53.7%) in KwaZulu Natal (KZN) and 22.3% (95% CI, 13.3%-30.4%) in the Western Cape (WC), with no significant change in Gauteng. In KZN and the WC, the relative reduction in ILTFU appeared greater in subdistricts where the alert-and-response patient management intervention was implemented (KZN: 49.3%; 95% CI, 32.4%-62%; vs 32.2%; 95% CI, 5.4%-51.4%; and WC: 34.2%; 95% CI, 20.9%-45.3%; vs 13.4%; 95% CI, 0.7%-24.4%). We reported a notable reduction in ILTFU in 2 provinces using existing routine health service data and applying a simple intervention to trace and recall those not linked to care. TB programs need to consider ILTFU a priority and develop interventions specific to their context to ensure improved linkage to care.

Acceptability of using the medication monitor and experience of a differentiated care approach for TB treatment adherence among people living with TB in South Africa.

BACKGROUND: The introduction of digital adherence technologies (DATs) such as medication monitors in tuberculosis (TB) programmes supports treatment adherence among people with tuberculosis (PWTB). We evaluated the acceptability of using medication monitors (Wisepill evriMED) prompting a stepwise differentiated care approach (DCA), involving short message service (SMS), phone calls, home visits and motivational counselling, among PWTB in South Africa. METHODS: We conducted 62 in-depth interviews with participants in local languages across three provinces (January-October 2020), purposively selected by treatment month, adherence history and gender. Interviews were audio recorded, transcribed verbatim and translated. Using a deductive approach and the Theoretical Framework for Acceptability (TFA), we explored acceptability across the sample attributes. RESULTS: PWTB across adherence histories showed a positive attitude to using the evriMED device and receiving the DCA support. PWTB described the SMS reminders and phone calls as effective reminders, though home visits were less acceptable, due to perceived stigma. Despite willingness to participate in the intervention, the large size of the monitor and sound of the alarm drew attention, potentially causing embarrassment and stigma. Due to perceived stigma, some PWTB adapted the intervention by leaving the monitor at home after removing the pills to ensure that someone else tracked usage, while the PWTB used alternative reminders such as cell phones to take their medication. CONCLUSION: Although PWTB showed a positive attitude towards the intervention, perceived stigma contributed to participants adapting their lifestyle to meet treatment adherence requirements without using the monitor. However, the medication monitor was a tool that seemed to prompt this personal change in behaviour. Achieving people-centered TB care, including the introduction of DATs, will require that TB programmes incorporate PWTB insights to maximize their use and effectiveness.

Improving measurement of tuberculosis care cascades to enhance people-centred care.

Care cascades represent the proportion of people reaching milestones in care for a disease and are widely used to track progress towards global targets for HIV and other diseases. Despite recent progress in estimating care cascades for tuberculosis (TB) disease, they have not been routinely applied at national and subnational levels, representing a lost opportunity for public health impact. As researchers who have estimated TB care cascades in high-incidence countries (India, Madagascar, Nigeria, Peru, South Africa, and Zambia), we describe the utility of care cascades and identify measurement challenges, including the lack of population-based disease burden data and electronic data capture, the under-reporting of people with TB navigating fragmented and privatised health systems, the heterogeneity of TB tests, and the lack of post-treatment follow-up. We outline an agenda for rectifying these gaps and argue that improving care cascade measurement is crucial to enhancing people-centred care and achieving the End TB goals.

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.

Qualitative study exploring the feasibility of using medication monitors and a differentiated care approach to support adherence among people receiving TB treatment in South Africa.

OBJECTIVES: The tuberculosis (TB) MATE study evaluated whether a differentiated care approach (DCA) based on tablet-taking data from Wisepill evriMED digital adherence technology could improve TB treatment adherence. The DCA entailed a stepwise increase in adherence support starting from short message service (SMS) to phone calls, followed by home visits and motivational counselling. We explored feasibility of this approach with providers in implementing clinics. DESIGN: Between June 2020 and February 2021, in-depth interviews were conducted in the provider's preferred language, audiorecorded, transcribed verbatim and translated. The interview guide included three categories: feasibility, system-level challenges and sustainability of the intervention. We assessed saturation and used thematic analysis. SETTING: Primary healthcare clinics in three provinces of South Africa. PARTICIPANTS: We conducted 25 interviews with 18 staff and 7 stakeholders. RESULTS: Three major themes emerged: First, providers were supportive of the intervention being integrated into the TB programme and were eager to be trained on the device as it helped to monitor treatment adherence. Second, there were challenges in the adoption system such as shortage of human resources which could serve as a barrier to information provision once the intervention is scaled up. Healthcare workers reported that some patients received incorrect SMS's due to delays in the system that contributed to distrust. Third, DCA was considered as a key aspect of the intervention by some staff and stakeholders since it allowed for support based on individual needs. CONCLUSIONS: It was feasible to monitor TB treatment adherence using the evriMED device and DCA. To ensure successful scale-up of the adherence support system, emphasis will need to be placed on ensuring that the device and the network operate optimally and continued support on adhering to treatment which will enable people with TB to take ownership of their treatment journey and help overcome TB-related stigma. TRIAL REGISTRATION NUMBER: Pan African Trial Registry PACTR201902681157721.

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.

Who is more likely to return for TB test results? A survey at three high-burden primary healthcare facilities in Cape Town, South Africa.

BACKGROUND: In low- and middle-income countries with a high burden of tuberculosis (TB), a large proportion of people who are tested for TB do not return to the health facility to collect their test results and initiate treatment, thus putting themselves at increased risk of adverse outcomes. METHODS: This prospective study aimed to identify predictors of returning to the primary health care (PHC) facility to collect TB test results. From 15 August to 15 December 2017, 1105 people who tested for pulmonary TB at three Cape Town PHC facilities were surveyed. Using multi-variate logistic regressions on an analysis sample of 1097 people, three groups of predictors were considered: (i) demographics, health and socio-economic status; (ii) costs and benefits; and (iii) behavioural factors. RESULTS: Forty-four percent of people tested returned to the PHC facility to collect their test results within the stipulated 2 days, and 68% returned before the end of the study period. Return was strongly and positively correlated with expecting a TB-positive result, cognitive avoidance and postponement behaviour. CONCLUSION: Interventions to improve pre-treatment loss to follow-up should target patients who think they do not have TB, and those with a history of postponement behaviour and cognitive avoidance.

Mortality during tuberculosis treatment in South Africa using an 8-year analysis of the national tuberculosis treatment register.

In 2011, the South African HIV treatment eligibility criteria were expanded to allow all tuberculosis (TB) patients lifelong ART. The impact of this change on TB mortality in South Africa is not known. We evaluated mortality in all adults (≥ 15 years old) treated for drug-susceptible TB in South Africa between 2009 and 2016. Using a Cox regression model, we quantified risk factors for mortality during TB treatment and present standardised mortality ratios (SMR) stratified by year, age, sex, and HIV status. During the study period, 8.6% (219,618/2,551,058) of adults on TB treatment died. Older age, male sex, previous TB treatment and HIV infection (with or without the use of ART) were associated with increased hazard of mortality. There was a 19% reduction in hazard of mortality amongst all TB patients between 2009 and 2016 (adjusted hazard ratio: 0.81 95%CI 0.80-0.83). The highest SMR was in 15-24-year-old women, more than double that of men (42.3 in 2016). Between 2009 and 2016, the SMR for HIV-positive TB patients increased, from 9.0 to 19.6 in women, and 7.0 to 10.6 in men. In South Africa, case fatality during TB treatment is decreasing and further interventions to address specific risk factors for TB mortality are required. Young women (15-24-year-olds) with TB experience a disproportionate burden of mortality and interventions targeting this age-group are needed.

Evaluation of adherence monitoring system using evriMED with a differentiated response compared to standard of care among drug-sensitive TB patients in three provinces in South Africa: a protocol for a cluster randomised control trial.

BACKGROUND: South Africa has achieved drug-susceptible TB (DS-TB) treatment success of only 77% among people with new and previously treated TB. Alternative approaches are required to improve medication adherence and treatment completion to limit transmission, TB relapse and the development of resistance. This study aims to implement and evaluate the use of adherence medication monitors (Wisepill evriMED 1000) with a differentiated response to patient care, among DS-TB patients in three provinces of South Africa. METHODS: In total, 18 public health clinics across three provinces were selected. Clinics were randomised to intervention or standard of care clinics. In each clinic, approximately 145 DS-TB patients are being enrolled to reach a total of 2610. All patients have their daily adherence monitored using medication monitors. In the intervention arm, patients are receiving medication monitor reminders and differentiated care in response to adherence data. This weekly review of daily real-time monitoring will be undertaken from a central database. The differentiated care model includes automated SMS reminders with a missed dose, research staff-initiated phone call to the patient with a second or third missed dose, a home visit if four or more doses are missed, and motivational counselling if four or more doses are missed repeatedly. Fidelity of the intervention will be measured through process evaluation. Patients in control clinics will receive medication monitors for adherence tracking, standard of care TB education, and normal clinic follow-up procedures. The primary outcome is the proportion of patients by arm with >80% adherence, as measured by the medication monitor. The feasibility and acceptability of the intervention will be assessed by in-depth interviews with patients, stakeholders, and study staff. A cost effectiveness analysis of the intervention and standard of care clinics will be conducted. SIGNIFICANCE: This trial will provide evidence for the use of an intervention, including medication monitors and differentiated care package, to improve adherence to TB treatment. Improved adherence should also improve TB treatment completion rates, thus reducing loss to follow-up rates, and TB relapse among people with TB. The intervention is intended to ultimately improve overall TB control and reduce TB transmission in South Africa. TRIAL REGISTRATION: Pan African Trial Registry PACTR201902681157721 . Registered on 11 February 2019.

Early mortality in tuberculosis patients initially lost to follow up following diagnosis in provincial hospitals and primary health care facilities in Western Cape, South Africa.

In South Africa, low tuberculosis (TB) treatment coverage and high TB case fatality remain important challenges. Following TB diagnosis, patients must link with a primary health care (PHC) facility for initiation or continuation of antituberculosis treatment and TB registration. We aimed to evaluate mortality among TB patients who did not link to a TB treatment facility for TB treatment within 30 days of their TB diagnosis, i.e. who were "initial loss to follow-up (ILTFU)" in Cape Town, South Africa. We prospectively included all patients with a routine laboratory or clinical diagnosis of TB made at PHC or hospital level in Khayelitsha and Tygerberg sub-districts in Cape Town, using routine TB data from an integrated provincial health data centre between October 2018 and March 2020. Overall, 74% (10,208/13,736) of TB patients were diagnosed at PHC facilities and ILTFU was 20.0% (2,742/13,736). Of ILTFU patients, 17.1% (468/2,742) died, with 69.7% (326/468) of deaths occurring within 30 days of diagnosis. Most ILTFU deaths (85.5%; 400/468) occurred in patients diagnosed in hospital. Multivariable logistic regression identified increasing age, HIV positive status, and hospital-based TB diagnosis (higher in the absence of TB treatment initiation and being ILTFU) as predictors of mortality. Although hospitals account for a modest proportion of diagnosed TB patients they have high TB-associated mortality. A hospital-based TB diagnosis is a critical opportunity to identify those at high risk of early and overall mortality. Interventions to diagnose TB before hospital admission, improve linkage to TB treatment following diagnosis, and reduce mortality in hospital-diagnosed TB patients should be prioritised.

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.

Mortality in South African Children and Adolescents Routinely Treated for Tuberculosis.

BACKGROUND: In South Africa, tuberculosis (TB) is a leading cause of death among those <20 years of age. We describe changes in TB mortality among children and adolescents in South Africa over a 13-year period, identify risk factors for mortality, and estimate excess TB-related mortality. METHODS: Retrospective analysis of all patients <20 years of age routinely recorded in the national electronic drug-susceptible TB treatment register (2004-2016). We developed a multivariable Cox regression model for predictors of mortality and used estimates of mortality among the general population to calculate standardized mortality ratios (SMRs). RESULTS: Between 2004 and 2016, 729 463 children and adolescents were recorded on TB treatment; 84.0% had treatment outcomes and 2.5% (18 539) died during TB treatment. The case fatality ratio decreased from 3.3% in 2007 to 1.9% in 2016. In the multivariable Cox regression model, ages 0 to 4, 10 to 14, and 15 to 19 years (compared with ages 5 to 9 years) were associated with increased risk of mortality, as was HIV infection, previous TB treatment, and extrapulmonary involvement. The SMR of 15 to 19-year-old female patients was more than double that of male patients the same age (55.3 vs 26.2). Among 10 to 14-year-olds and those who were HIV-positive, SMRs increased over time. CONCLUSIONS: Mortality in South African children and adolescents treated for TB is declining but remains considerable, with 2% dying during 2016. Adolescents (10 to 19 years) and those people living with HIV have the highest risk of mortality and the greatest SMRs. Interventions to reduce mortality during TB treatment, specifically targeting those at highest risk, are urgently needed.

Tuberculosis in persons with sudden unexpected death, in Cape Town, South Africa.

BACKGROUND: Globally, tuberculosis (TB) remains one of the leading causes of death from a single infectious agent, but there has been little work to estimate mortality before the diagnosis of TB. We investigated the burden of diagnosed and undiagnosed TB in adult and child sudden unexpected deaths (SUDs) evaluated at Tygerberg Forensic Pathology Services, South Africa. METHODS: In a retrospective descriptive study spanning 2016, we identified all SUDs where active TB was detected at post-mortem and matched with routine health service data to differentiate decedents who were diagnosed or undiagnosed with TB before death. A patient pathway analysis of the health service activities preceding SUD in adults with active TB was conducted. RESULTS: Active TB was identified at post-mortem in 6.2% (48/770) of SUDs and was undiagnosed before death in 91.7% (44/48). The prevalence of active TB was 8.1% in adult SUDs (90.1% undiagnosed before SUD) and 1.8% in children (none diagnosed before SUD). Patient pathway analysis was possible for 15 adult SUDs, and this documented primary health care clinic attendances and hospital admissions in the six months preceding death and missed opportunities for TB investigations. CONCLUSION: The prevalence of TB among SUDs in the Eastern Metro of Cape Town is high. Most active TB at post-mortem was undiagnosed before death, and multiple missed opportunities for TB investigation and diagnosis were noted. The systematic evaluation of all SUDs for TB could improve the reporting of undiagnosed TB and support risk mitigation for healthcare workers involved with the post-mortem process.

The Impact of the Evolving Human Immunodeficiency Virus Response on the Epidemiology of Tuberculosis in South African Children and Adolescents.

BACKGROUND: Few studies have evaluated tuberculosis control in children and adolescents. We used routine tuberculosis surveillance data to quantify age- and human immunodeficiency virus (HIV)-stratified trends over time and investigate the relationship between tuberculosis, HIV, age, and sex. METHODS: All children and adolescents (0-19 years) routinely treated for drug-susceptible tuberculosis in South Africa and recorded in a de-duplicated national electronic tuberculosis treatment register (2004-2016) were included. Age- and HIV-stratified tuberculosis case notification rates (CNRs) were calculated in four age bands: 0-4, 5-9, 10-14, and 15-19 years. The association between HIV infection, age, and sex in children and adolescents with tuberculosis was evaluated using multivariable logistic regression. RESULTS: Of 719 400 children and adolescents included, 339 112 (47%) were 0-4 year olds. The overall tuberculosis CNR for 0-19 year olds declined by 54% between 2009 and 2016 (incidence rate ratio [IRR] = 0.46; 95% confidence interval [CI], .45-.47). Trends varied by age and HIV, with the smallest reductions (2013-2016) in HIV-positive 0-4 year olds (IRR = 0.90; 95% CI, .85-.95) and both HIV-positive (IRR = .84; 95% CI, .80-.88) and HIV-negative (IRR = 0.89; 95% CI, .86-.92) 15-19 year olds. Compared with 0- to 4-year-old males, odds of HIV coinfection among 15-19 year olds were nearly twice as high in females (adjusted odds ratio [aOR] = 2.49; 95% CI, 2.38-2.60) than in males (aOR = 1.35; 95% CI, 1.29-1.42). CONCLUSIONS: South Africa's national response to the HIV epidemic has made a substantial contribution to the observed declining trends in tuberculosis CNRs in children and adolescents. The slow decline of tuberculosis CNRs in adolescents and young HIV-positive children is concerning. Understanding how tuberculosis affects children and adolescents beyond conventional age bands and by sex can inform targeted tuberculosis control strategies.

Factors associated with linkage to HIV care and TB treatment at community-based HIV testing services in Cape Town, South Africa.

BACKGROUND: Diagnosing HIV and/or TB is not sufficient; linkage to care and treatment is conditional to reduce the burden of disease. This study aimed to determine factors associated with linkage to HIV care and TB treatment at community-based services in Cape Town, South Africa. METHODS: This retrospective cohort study utilized routinely collected data from clients who utilized stand-alone (fixed site not attached to a health facility) and mobile HIV testing services in eight communities in the City of Cape Town Metropolitan district, between January 2008 and June 2012. Clients were included in the analysis if they were ≥12 years and had a known HIV status. Generalized estimating equations (GEE) logistic regression models were used to assess the association between determinants (sex, age, HIV testing service and co-infection status) and self-reported linkage to HIV care and/or TB treatment. RESULTS: Linkage to HIV care was 3 738/5 929 (63.1%). Linkage to HIV care was associated with the type of HIV testing service. Clients diagnosed with HIV at mobile services had a significantly reduced odds of linking to HIV care (aOR 0.7 (CI 95%: 0.6-0.8), p<0.001. Linkage to TB treatment was 210/275 (76.4%). Linkage to TB treatment was not associated with sex and service type, but was associated with age. Clients in older age groups were less likely to link to TB treatment compared to clients in the age group 12-24 years (all, p-value<0.05). CONCLUSION: A large proportion of clients diagnosed with HIV at mobile services did not link to care. Almost a quarter of clients diagnosed with TB did not link to treatment. Integrated community-based HIV and TB testing services are efficient in diagnosing HIV and TB, but strategies to improve linkage to care are required to control these epidemics.

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.

Has universal screening with Xpert® MTB/RIF increased the proportion of multidrug-resistant tuberculosis cases diagnosed in a routine operational setting?

SETTING: Primary health services in Cape Town, South Africa where the introduction of Xpert® MTB/RIF (Xpert) enabled simultaneous screening for tuberculosis (TB) and drug susceptibility in all presumptive cases. STUDY AIM: To compare the proportion of TB cases with drug susceptibility tests undertaken and multidrug-resistant tuberculosis (MDR-TB) diagnosed pre-treatment and during the course of 1st line treatment in the previous smear/culture and the newly introduced Xpert-based algorithms. METHODS: TB cases identified in a previous stepped-wedge study of TB yield in five sub-districts over seven one-month time-points prior to, during and after the introduction of the Xpert-based algorithm were analysed. We used a combination of patient identifiers to identify all drug susceptibility tests undertaken from electronic laboratory records. Differences in the proportions of DST undertaken and MDR-TB cases diagnosed between algorithms were estimated using a binomial regression model. RESULTS: Pre-treatment, the probability of having a DST undertaken (RR = 1.82)(p<0.001) and being diagnosed with MDR-TB (RR = 1.42)(p<0.001) was higher in the Xpert-based algorithm than in the smear/culture-based algorithm. For cases evaluated during the course of 1st-line TB treatment, there was no significant difference in the proportion with DST undertaken (RR = 1.02)(p = 0.848) or MDR-TB diagnosed (RR = 1.12)(p = 0.678) between algorithms. CONCLUSION: Universal screening for drug susceptibility in all presumptive TB cases in the Xpert-based algorithm resulted in a higher overall proportion of MDR-TB cases being diagnosed and is an important strategy in reducing transmission. The previous strategy of only screening new TB cases when 1st line treatment failed did not compensate for cases missed pre-treatment.

Comparing Tuberculosis Diagnostic Yield in Smear/Culture and Xpert® MTB/RIF-Based Algorithms Using a Non-Randomised Stepped-Wedge Design.

SETTING: Primary health services in Cape Town, South Africa. STUDY AIM: To compare tuberculosis (TB) diagnostic yield in an existing smear/culture-based and a newly introduced Xpert® MTB/RIF-based algorithm. METHODS: TB diagnostic yield (the proportion of presumptive TB cases with a laboratory diagnosis of TB) was assessed using a non-randomised stepped-wedge design as sites transitioned to the Xpert® based algorithm. We identified the full sequence of sputum tests recorded in the electronic laboratory database for presumptive TB cases from 60 primary health sites during seven one-month time-points, six months apart. Differences in TB yield and temporal trends were estimated using a binomial regression model. RESULTS: TB yield was 20.9% (95% CI 19.9% to 22.0%) in the smear/culture-based algorithm compared to 17.9% (95%CI 16.4% to 19.5%) in the Xpert® based algorithm. There was a decline in TB yield over time with a mean risk difference of -0.9% (95% CI -1.2% to -0.6%) (p<0.001) per time-point. When estimates were adjusted for the temporal trend, TB yield was 19.1% (95% CI 17.6% to 20.5%) in the smear/culture-based algorithm compared to 19.3% (95% CI 17.7% to 20.9%) in the Xpert® based algorithm with a risk difference of 0.3% (95% CI -1.8% to 2.3%) (p = 0.796). Culture tests were undertaken for 35.5% of smear-negative compared to 17.9% of Xpert® negative low MDR-TB risk cases and for 82.6% of smear-negative compared to 40.5% of Xpert® negative high MDR-TB risk cases in respective algorithms. CONCLUSION: Introduction of an Xpert® based algorithm did not produce the expected increase in TB diagnostic yield. Studies are required to assess whether improving adherence to the Xpert® negative algorithm for HIV-infected individuals will increase yield. In light of the high cost of Xpert®, a review of its role as a screening test for all presumptive TB cases may be warranted.

Pathways to multidrug-resistant tuberculosis diagnosis and treatment initiation: a qualitative comparison of patients' experiences in the era of rapid molecular diagnostic tests.

BACKGROUND: Although new molecular diagnostic tests such as GenoType MTBDRplus and Xpert® MTB/RIF have reduced multidrug-resistant tuberculosis (MDR-TB) treatment initiation times, patients' experiences of diagnosis and treatment initiation are not known. This study aimed to explore and compare MDR-TB patients' experiences of their diagnostic and treatment initiation pathway in GenoType MTBDRplus and Xpert® MTB/RIF-based diagnostic algorithms. METHODS: The study was undertaken in Cape Town, South Africa where primary health-care services provided free TB diagnosis and treatment. A smear, culture and GenoType MTBDRplus diagnostic algorithm was used in 2010, with Xpert® MTB/RIF phased in from 2011-2013. Participants diagnosed in each algorithm at four facilities were purposively sampled, stratifying by age, gender and MDR-TB risk profiles. We conducted in-depth qualitative interviews using a semi-structured interview guide. Through constant comparative analysis we induced common and divergent themes related to symptom recognition, health-care access, testing for MDR-TB and treatment initiation within and between groups. Data were triangulated with clinical information and health visit data from a structured questionnaire. RESULTS: We identified both enablers and barriers to early MDR-TB diagnosis and treatment. Half the patients had previously been treated for TB; most recognised recurring symptoms and reported early health-seeking. Those who attributed symptoms to other causes delayed health-seeking. Perceptions of poor public sector services were prevalent and may have contributed both to deferred health-seeking and to patient's use of the private sector, contributing to delays. However, once on treatment, most patients expressed satisfaction with public sector care. Two patients in the Xpert® MTB/RIF-based algorithm exemplified its potential to reduce delays, commencing MDR-TB treatment within a week of their first health contact. However, most patients in both algorithms experienced substantial delays. Avoidable health system delays resulted from providers not testing for TB at initial health contact, non-adherence to testing algorithms, results not being available and failure to promptly recall patients with positive results. CONCLUSION: Whilst the introduction of rapid tests such as Xpert® MTB/RIF can expedite MDR-TB diagnosis and treatment initiation, the full benefits are unlikely to be realised without reducing delays in health-seeking and addressing the structural barriers present in the health-care system.