Risk factors for poor engagement in drug-resistant TB care in South Africa: a systematic review

The epidemiology, transmission, diagnosis, and management of drug-resistant tuberculosis-lessons from the South African experience

Drug-resistant tuberculosis (DR-TB) threatens to derail tuberculosis control efforts, particularly in Africa where the disease remains out of control. The dogma that DR-TB epidemics are fueled by unchecked rates of acquired resistance in inadequately treated or non-adherent individuals is no longer valid in most high DR-TB burden settings, where community transmission is now widespread. A large burden of DR-TB in Africa remains undiagnosed due to inadequate access to diagnostic tools that simultaneously detect tuberculosis and screen for resistance. Furthermore, acquisition of drug resistance to new and repurposed drugs, for which diagnostic solutions are not yet available, presents a major challenge for the implementation of novel, all-oral, shortened (6-9 months) treatment. Structural challenges including poverty, stigma, and social distress disrupt engagement in care, promote poor treatment outcomes, and reduce the quality of life for people with DR-TB. We reflect on the lessons learnt from the South African experience in implementing state-of-the-art advances in diagnostic solutions, deploying recent innovations in pharmacotherapeutic approaches for rapid cure, understanding local transmission dynamics and implementing interventions to curtail DR-TB transmission, and in mitigating the catastrophic socioeconomic costs of DR-TB. We also highlight globally relevant and locally responsive research priorities for achieving DR-TB control in South Africa.

Travel distance to rifampicin-resistant tuberculosis treatment and its impact on loss to follow-up: the importance of continued RR-TB treatment decentralization in South Africa

BACKGROUND

Understanding why patients experience loss to follow-up (LTFU) is essential for TB control. This analysis examines the impact of travel distance to RR-TB treatment on LTFU, which has yet to be analyzed within South Africa.

METHODS

We retrospectively analyzed 1436 patients treated for RR-TB at ten South African public hospitals. We linked patients to their residential ward using data reported to NHLS and maps available from the Municipal Demarcation Board. Travel distance was calculated from each patient's ward centroid to their RR-TB treatment site using the georoute command in Stata. The relationship between LTFU and travel distance was modeled using multivariable logistic regression.

RESULTS

Among 1436 participants, 75.6% successfully completed treatment and 24.4% were LTFU. The median travel distance was 40.96 km (IQR: 17.12, 63.49). A travel distance > 60 km increased odds of LTFU by 91% (p = 0.001) when adjusting for HIV status, age, sex, education level, employment status, residential locale, treatment regimen, and treatment site.

CONCLUSION

People living in KwaZulu-Natal and Eastern Cape travel long distances to receive RR-TB care, placing them at increased risk for LTFU. Policies that bring RR-TB treatment closer to patients, such as further decentralization to PHCs, are necessary to improve RR-TB outcomes.

A Comprehensive Review on Long vs. Short Regimens in Multidrug-Resistant Tuberculosis (MDR-TB) Under Programmatic Management of Drug-Resistant Tuberculosis (PMDT)

This comprehensive review delves into the intricate landscape of multidrug-resistant tuberculosis (MDR-TB) treatment within the programmatic management of drug-resistant tuberculosis (PMDT) framework. MDR-TB poses a substantial global health threat, necessitating targeted approaches for effective management. The analysis explores the historical evolution, efficacy, safety profiles, and implementation challenges associated with long and short regimens. The findings underscore the importance of individualized clinical practices, considering patient-specific factors, and the need for ongoing monitoring within PMDT programs. Recommendations advocate for integrating advanced diagnostics, continuous surveillance, and training for healthcare professionals. The review concludes with a nuanced outlook on long versus short regimens, emphasizing a balanced approach and the imperative role of collaborative efforts in shaping the future of MDR-TB treatment. This synthesis contributes to the ongoing discourse, providing valuable insights for healthcare practitioners, policymakers, and researchers working toward optimizing outcomes for individuals afflicted with MDR-TB.

Factors contributing to the high prevalence of multidrug-resistance/Rifampicin-resistance in patients with tuberculosis: an epidemiological cross sectional and qualitative study from Khabarovsk krai region of Russia

Background

Growing prevalence of multidrug-resistant/Rifampicin-resistant tuberculosis (MDR/RR-TB; resistance to Isoniazid and Rifampicin/Isolated resistance to Rifampicin) is putting in jeopardy the WHO End TB strategy. This study aimed to identify factors contributing to the high prevalence of MDR/RR-TB in Khabarovsk krai region of Russia.

Methods

A cross-sectional retrospective study was conducted, analyzing clinical, demographic, and drug susceptibility testing data on 1440 patients. As a source of raw data, the national electronic TB surveillance system was used. Anonymous data was collected on every patient diagnosed with TB in all healthcare facilities of the region from January 2018 to December 2019. Only patients with proven excretion of m. tuberculosis were included in the study. Factors associated with MDR/RR-TB were identified through logistic regression analysis, in conjunction with in-depth interviews with eight patients, five healthcare managers and five doctors.

Findings

2661 patients were identified with TB, 1440 were incorporated in the study based on inclusion criteria. Of these, 618 (42.9%) were identified with MDR/RR-TB. Patients with a history of imprisonment were 16.53 times (95% CI 5.37 to 50.88,) more likely to have MDR/RR-TB, whereas re-treatment patients were 2.82 times (95% CI 2.16 to 3.66) more likely to have MDR/RR-TB. Other influencing factors included presence of disability (AOR is 2.32, 95% CI 1.38 to 3.89), cavitary disease (AOR is 1.76, 95% CI 1.37 to 2.25), and retirement status (AOR 0.65, 95% CI 0.43 to 0.98, p = 0.042). Poor patient knowledge and understanding of the disease, progressive weariness of prolonged TB treatment, and inability hospitalize infectious patients without their consent were perceived by the interviewees as major influencing factors.

Conclusions

Incarceration and treatment history, regardless of outcome, were identified as major factors influencing MDR/RR-TB prevalence. It is essential for the TB care system to eliminate legal loopholes, which deprive doctors of means to enforce quarantine procedures and epidemiological surveillance on infected patients, former and current inmates. Increasing people’s awareness of TB, early detection and appropriate treatment of patients with TB are needed for successfully combating MDR/RR-TB.

Key factors influencing multidrug-resistant tuberculosis in patients under anti-tuberculosis treatment in two centres in Burundi: a mixed effect modelling study

Background

Despite the World Health Organization efforts to expand access to the tuberculosis treatment, multidrug resistant tuberculosis (MDR-TB) remains a major threat. MDR-TB represents a challenge for clinicians and staff operating in national tuberculosis (TB) programmes/centres. In sub-Saharan African countries including Burundi, MDR-TB coexists with high burden of other communicable and non-communicable diseases, creating a complex public health situation which is difficult to address. Tackling this will require targeted public health intervention based on evidence which well defines the at-risk population. In this study, using data from two referral anti-tuberculosis in Burundi, we model the key factors associated with MDR-TB in Burundi.

Methods

A case-control study was conducted from 1^stAugust 2019 to 15^th January 2020 in Kibumbu Sanatorium and Bujumbura anti-tuberculosis centres for cases and controls respectively. In all, 180 TB patients were selected, comprising of 60 cases and 120 controls using incidence density selection method. The associated factors were carried out by mixed effect logistic regression. Model performance was assessed by the Area under Curve (AUC). Model was internally validated via bootstrapping with 2000 replications. All analysis were done using R Statistical 3.5.0.

Results

MDR-TB was more identified among patients who lived in rural areas (51.3%), in patients’ residence (69.2%) and among those with a household size of six or more family members (59.5%).

Most of the MDR-TB cases had already been under TB treatment (86.4%), had previous contact with an MDR-TR case (85.0%), consumed tobacco (55.5%) and were diabetic (66.6 %). HIV prevalence was 32.3 % in controls and 67.7 % among cases. After modelling using mixed effects, Residence of patients (aOR= 1.31, 95%C: 1.12-1.80), living in houses with more than 6 family members (aOR= 4.15, 95% C: 3.06-5.39), previous close contact with MDR-TB (aOR= 6.03, 95% C: 4.01-8.12), history of TB treatment (aOR= 2.16, 95% C: 1.06-3.42), tobacco consumption (aOR = 3.17 ,95% C: 2.06-5.45) and underlying diabetes’ ( aOR= 4.09,95% CI = 2.01-16.79) were significantly associated with MDR-TB. With 2000 stratified bootstrap replicates, the model had an excellent predictive performance, accurately predicting 88.15% (95% C: 82.06%-92.8%) of all observations. The coexistence of risk factors to the same patients increases the risk of MDR-TB occurrence. TB patients with no any risk factors had 17.6% of risk to become MDR-TB. That probability was respectively three times and five times higher among diabetic and close contact MDR-TB patients.

Conclusion

The relatively high TB’s prevalence and MDR-TB occurrence in Burundi raises a cause for concern especially in this context where there exist an equally high burden of chronic diseases including malnutrition. Targeting interventions based on these identified risk factors will allow judicious channel of resources and effective public health planning.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-12233-2.