The importance of implementation strategy in scaling up Xpert MTB/RIF for diagnosis of tuberculosis in the Indian health-care system: a transmission model

Assessing potential insights of an imperfect testing strategy: Parameter estimation and practical identifiability using early COVID-19 data in India

A deterministic model with testing of infected individuals has been proposed to investigate the potential consequences of the impact of testing strategy. The model exhibits global dynamics concerning the disease-free and a unique endemic equilibrium depending on the basic reproduction number when the recruitment of infected individuals is zero; otherwise, the model does not have a disease-free equilibrium, and disease never dies out in the community. Model parameters have been estimated using the maximum likelihood method with respect to the data of early COVID-19 outbreak in India. The practical identifiability analysis shows that the model parameters are estimated uniquely. The consequences of the testing rate for the weekly new cases of early COVID-19 data in India tell that if the testing rate is increased by 20% and 30% from its baseline value, the weekly new cases at the peak are decreased by 37.63% and 52.90%; and it also delayed the peak time by four and fourteen weeks, respectively. Similar findings are obtained for the testing efficacy that if it is increased by 12.67% from its baseline value, the weekly new cases at the peak are decreased by 59.05% and delayed the peak by 15 weeks. Therefore, a higher testing rate and efficacy reduce the disease burden by tumbling the new cases, representing a real scenario. It is also obtained that the testing rate and efficacy reduce the epidemic's severity by increasing the final size of the susceptible population. The testing rate is found more significant if testing efficacy is high. Global sensitivity analysis using partial rank correlation coefficients (PRCCs) and Latin hypercube sampling (LHS) determine the key parameters that must be targeted to worsen/contain the epidemic.

Impact of molecular diagnostic tests on diagnostic and treatment delays in tuberculosis: a systematic review and meta-analysis

BACKGROUND

Countries with high TB burden have expanded access to molecular diagnostic tests. However, their impact on reducing delays in TB diagnosis and treatment has not been assessed. Our primary aim was to summarize the quantitative evidence on the impact of nucleic acid amplification tests (NAAT) on diagnostic and treatment delays compared to that of the standard of care for drug-sensitive and drug-resistant tuberculosis (DS-TB and DR-TB).

METHODS

We searched MEDLINE, EMBASE, Web of Science, and the Global Health databases (from their inception to October 12, 2020) and extracted time delay data for each test. We then analysed the diagnostic and treatment initiation delay separately for DS-TB and DR-TB by comparing smear vs Xpert for DS-TB and culture drug sensitivity testing (DST) vs line probe assay (LPA) for DR-TB. We conducted random effects meta-analyses of differences of the medians to quantify the difference in diagnostic and treatment initiation delay, and we investigated heterogeneity in effect estimates based on the period the test was used in, empiric treatment rate, HIV prevalence, healthcare level, and study design. We also evaluated methodological differences in assessing time delays.

RESULTS

A total of 45 studies were included in this review (DS = 26; DR = 20). We found considerable heterogeneity in the definition and reporting of time delays across the studies. For DS-TB, the use of Xpert reduced diagnostic delay by 1.79 days (95% CI - 0.27 to 3.85) and treatment initiation delay by 2.55 days (95% CI 0.54-4.56) in comparison to sputum microscopy. For DR-TB, use of LPAs reduced diagnostic delay by 40.09 days (95% CI 26.82-53.37) and treatment initiation delay by 45.32 days (95% CI 30.27-60.37) in comparison to any culture DST methods.

CONCLUSIONS

Our findings indicate that the use of World Health Organization recommended diagnostics for TB reduced delays in diagnosing and initiating TB treatment. Future studies evaluating performance and impact of diagnostics should consider reporting time delay estimates based on the standardized reporting framework.

Costs and cost-effectiveness of a comprehensive tuberculosis case finding strategy in Zambia

Introduction

Active-case finding (ACF) programs have an important role in addressing case detection gaps and halting tuberculosis (TB) transmission. Evidence is limited on the cost-effectiveness of ACF interventions, particularly on how their value is impacted by different operational, epidemiological and patient care-seeking patterns.

Methods

We evaluated the costs and cost-effectiveness of a combined facility and community-based ACF intervention in Zambia that utilized mobile chest X-ray with computer-aided reading/interpretation software and laboratory-based Xpert MTB/RIF testing. Programmatic costs (in 2018 US dollars) were assessed from the health system perspective using prospectively collected cost and operational data. Cost-effectiveness of the ACF intervention was assessed as the incremental cost per TB death averted over a five-year time horizon using a multi-stage Markov state-transition model reflecting patient symptom-associated care-seeking and TB care under ACF compared to passive care.

Results

Over 18 months of field operations, the ACF intervention costed $435 to diagnose and initiate treatment for one person with TB. After accounting for patient symptom-associated care-seeking patterns in Zambia, we estimate that this one-time ACF intervention would incrementally diagnose 407 (7,207 versus 6,800) TB patients and avert 502 (611 versus 1,113) TB-associated deaths compared to the status quo (passive case finding), at an incremental cost of $2,284 per death averted over the next five-year period. HIV/TB mortality rate, patient symptom-associated care-seeking probabilities in the absence of ACF, and the costs of ACF patient screening were key drivers of cost-effectiveness.

Conclusions

A one-time comprehensive ACF intervention simultaneously operating in public health clinics and corresponding catchment communities can have important medium-term impact on case-finding and be cost-effective in Zambia. The value of such interventions increases if targeted to populations with high HIV/TB mortality, substantial barriers (both behavioral and physical) to care-seeking exist, and when ACF interventions can optimize screening by achieving operational efficiency.

Field sales force model to increase adoption of a novel tuberculosis diagnostic test among private providers: evidence from India

Background

Impact of novel high-quality tuberculosis (TB) tests such as Xpert MTB/RIF has been limited due to low uptake among private providers in high-burden countries including India. Our objective was to assess the impact of a demand generation intervention comprising field sales force on the uptake of high-quality TB tests by providers and its financial sustainability for private labs in the long run.

Methods

We implemented a demand generation intervention across five Indian cities between October 2014 and June 2016 and compared the change in the quantity of Xpert cartridges ordered by labs in these cities from before (February 2013–September 2014) to after intervention (October 2014–December 2015) to corresponding change in labs in comparable non-intervention cities. We embedded this difference-in-differences estimate within a financial model to calculate the internal rate of return (IRR) if the labs were to invest in an Xpert machine with or without the demand generation intervention.

Results

The intervention resulted in an estimated 60 additional Xpert cartridges ordered per lab-month in the intervention group, which yielded an estimated increase of 11 500 tests over the post-intervention period, at an additional cost of US$13.3–US$17.63 per test. Further, we found that investing in this intervention would increase the IRR from 4.8% to 5.5% for hospital labs but yield a negative IRR for standalone labs.

Conclusions

Field sales force model can generate additional demand for Xpert at private labs, but additional strategies may be needed to ensure its financial sustainability.

Predicting the impact of patient and private provider behavior on diagnostic delay for pulmonary tuberculosis patients in India: A simulation modeling study

BACKGROUND

Tuberculosis (TB) incidence in India continues to be high due, in large part, to long delays experienced by patients before successful diagnosis and treatment initiation, especially in the private sector. This diagnostic delay is driven by patients' inclination to switch between different types of providers and providers' inclination to delay ordering of accurate diagnostic tests relevant to TB. Our objective is to quantify the impact of changes in these behavioral characteristics of providers and patients on diagnostic delay experienced by pulmonary TB patients.

METHODS AND FINDINGS

We developed a discrete event simulation model of patients' diagnostic pathways that captures key behavioral characteristics of providers (time to order a test) and patients (time to switch to another provider). We used an expectation-maximization algorithm to estimate the parameters underlying these behavioral characteristics, with quantitative data encoded from detailed interviews of 76 and 64 pulmonary TB patients in the 2 Indian cities of Mumbai and Patna, respectively, which were conducted between April and August 2014. We employed the estimated model to simulate different counterfactual scenarios of diagnostic pathways under altered behavioral characteristics of providers and patients to predict their potential impact on the diagnostic delay. Private healthcare providers including chemists were the first point of contact for the majority of TB patients in Mumbai (70%) and Patna (94%). In Mumbai, 45% of TB patients first approached less-than-fully-qualified providers (LTFQs), who take 28.71 days on average for diagnosis. About 61% of these patients switched to other providers without a diagnosis. Our model estimates that immediate testing for TB by LTFQs at the first visit (at the current level of diagnostic accuracy) could reduce the average diagnostic delay from 35.53 days (95% CI: 34.60, 36.46) to 18.72 days (95% CI: 18.01, 19.43). In Patna, 61% of TB patients first approached fully qualified providers (FQs), who take 9.74 days on average for diagnosis. Similarly, immediate testing by FQs at the first visit (at the current level of diagnostic accuracy) could reduce the average diagnostic delay from 23.39 days (95% CI: 22.77, 24.02) to 11.16 days (95% CI: 10.52, 11.81). Improving the diagnostic accuracy of providers per se, without reducing the time to testing, was not predicted to lead to any reduction in diagnostic delay. Our study was limited because of its restricted geographic scope, small sample size, and possible recall bias, which are typically associated with studies of patient pathways using patient interviews.

CONCLUSIONS

In this study, we found that encouraging private providers to order definitive TB diagnostic tests earlier during patient consultation may have substantial impact on reducing diagnostic delay in these urban Indian settings. These results should be combined with disease transmission models to predict the impact of changes in provider behavior on TB incidence.

Closing gaps in the tuberculosis care cascade: an action-oriented research agenda

The care cascade-which evaluates outcomes across stages of patient engagement in a health system-is an important framework for assessing quality of tuberculosis (TB) care. In recent years, there has been progress in measuring care cascades in high TB burden countries; however, there are still shortcomings in our knowledge of how to reduce poor patient outcomes. In this paper, we outline a research agenda for understanding why patients fall through the cracks in the care cascade. The pathway for evidence generation will require new systematic reviews, observational cohort studies, intervention development and testing, and continuous quality improvement initiatives embedded within national TB programs. Certain gaps, such as pretreatment loss to follow-up and post-treatment disease recurrence, should be a priority given a relative paucity of high-quality research to understand and address poor outcomes. Research on interventions to reduce death and loss to follow-up during treatment should move beyond a focus on monitoring (or observation) strategies, to address patient needs including psychosocial and nutritional support. While key research questions vary for each gap, some patient populations may experience disparities across multiple stages of care and should be a priority for research, including men, individuals with a prior treatment history, and individuals with drug-resistant TB. Closing gaps in the care cascade will require investments in a bold and innovative action-oriented research agenda.

Heterogeneous infectiousness in mathematical models of tuberculosis: A systematic review

TB mathematical models employ various assumptions and approaches in dealing with the heterogeneous infectiousness of persons with active TB. We reviewed existing approaches and considered the relationship between them and existing epidemiological evidence. We searched the following electronic bibliographic databases from inception to 9 October 2018: MEDLINE, EMBASE, Biosis, Global Health and Scopus. Two investigators extracted data using a standardised data extraction tool. We included in the review any transmission dynamic model of M. tuberculosis transmission explicitly simulating heterogeneous infectiousness of person with active TB. We extracted information including: study objective, model structure, number of active TB compartments, factors used to stratify the active TB compartment, relative infectiousness of each active TB compartment and any intervention evaluated in the model. Our search returned 1899 unique references, of which the full text of 454 records were assessed for eligibility, and 99 studies met the inclusion criteria. Of these, 89 used compartmental models implemented with ordinary differential equations, while the most common approach to stratification of the active TB compartment was to incorporate two levels of infectiousness. However, various clinical characteristics were used to stratify the active TB compartments, and models differed as to whether they permitted transition between these states. Thirty-four models stratified the infectious compartment according to sputum smear status or pulmonary involvement, while 18 models stratified based on health care-related factors. Variation in infectiousness associated with drug-resistant M. tuberculosis was the rationale for stratifying active TB in 33 models, with these models consistently assuming that drug-resistant active TB cases were less infectious. Given the evidence of extensive heterogeneity in infectiousness of individuals with active TB, an argument exists for incorporating heterogeneous infectiousness, although this should be considered in light of the objectives of the study and the research question. PROSPERO Registration: CRD42019111936.

Informing decision-making for universal access to quality tuberculosis diagnosis in India: an economic-epidemiological model

BACKGROUND

India and many other high-burden countries have committed to providing universal access to high-quality diagnosis and drug susceptibility testing (DST) for tuberculosis (TB), but the most cost-effective approach to achieve this goal remains uncertain. Centralized testing at district-level hub facilities with a supporting sample transport network can generate economies of scale, but decentralization to the peripheral level may provide faster diagnosis and reduce losses to follow-up (LTFU).

METHODS

We generated functions to evaluate the costs of centralized and decentralized molecular testing for tuberculosis with Xpert MTB/RIF (Xpert), a WHO-endorsed test which can be performed at centralized and decentralized levels. We merged the cost estimates with an agent-based simulation of TB transmission in a hypothetical representative region in India to assess the impact and cost-effectiveness of each strategy.

RESULTS

Compared against centralized Xpert testing, decentralization was most favorable when testing volume at decentralized facilities and pre-treatment LTFU were high, and specimen transport network was exclusively established for TB. Assuming equal quality of centralized and decentralized testing, decentralization was cost-saving, saving a median $338,000 (interquartile simulation range [IQR] - $222,000; $889,000) per 20 million people over 10 years, in the most cost-favorable scenario. In the most cost-unfavorable scenario, decentralized testing would cost a median $3161 [IQR $2412; $4731] per disability-adjusted life year averted relative to centralized testing.

CONCLUSIONS

Decentralization of Xpert testing is likely to be cost-saving or cost-effective in most settings to which these simulation results might generalize. More decentralized testing is more cost-effective in settings with moderate-to-high peripheral testing volumes, high existing clinical LTFU, inability to share specimen transport costs with other disease entities, and ability to ensure high-quality peripheral Xpert testing. Decision-makers should assess these factors when deciding whether to decentralize molecular testing for tuberculosis.

Introducing risk inequality metrics in tuberculosis policy development

Global stakeholders including the World Health Organization rely on predictive models for developing strategies and setting targets for tuberculosis care and control programs. Failure to account for variation in individual risk leads to substantial biases that impair data interpretation and policy decisions. Anticipated impediments to estimating heterogeneity for each parameter are discouraging despite considerable technical progress in recent years. Here we identify acquisition of infection as the single process where heterogeneity most fundamentally impacts model outputs, due to selection imposed by dynamic forces of infection. We introduce concrete metrics of risk inequality, demonstrate their utility in mathematical models, and pack the information into a risk inequality coefficient (RIC) which can be calculated and reported by national tuberculosis programs for use in policy development and modeling.

Failure to account for heterogeneity in TB risk can mislead model-based evaluation of proposed interventions. Here, the authors introduce a metric to estimate the distribution of risk in populations from routinely collected data and find that variation in infection acquisition is the most impactful.

Modelling the impact of effective private provider engagement on tuberculosis control in urban India

In India, the country with the world’s largest burden of tuberculosis (TB), most patients first seek care in the private healthcare sector, which is fragmented and unregulated. Ongoing initiatives are demonstrating effective approaches for engaging with this sector, and form a central part of India’s recent National Strategic Plan: here we aimed to address their potential impact on TB transmission in urban settings, when taken to scale. We developed a mathematical model of TB transmission dynamics, calibrated to urban populations in Mumbai and Patna, two major cities in India where pilot interventions are currently ongoing. We found that, when taken to sufficient scale to capture 75% of patient-provider interactions, the intervention could reduce incidence by upto 21.3% (95% Bayesian credible interval (CrI) 13.0–32.5%) and 15.8% (95% CrI 7.8–28.2%) in Mumbai and Patna respectively, between 2018 and 2025. There is a stronger impact on TB mortality, with a reduction of up to 38.1% (95% CrI 20.0–55.1%) in the example of Mumbai. The incidence impact of this intervention alone may be limited by the amount of transmission that has already occurred by the time a patient first presents for care: model estimates suggest an initial patient delay of 4–5 months before first seeking care, followed by a diagnostic delay of 1–2 months before ultimately initiating TB treatment. Our results suggest that the transmission impact of such interventions could be maximised by additional measures to encourage early uptake of TB services.

Constructing care cascades for active tuberculosis: A strategy for program monitoring and identifying gaps in quality of care

The cascade of care is a model for evaluating patient retention across sequential stages of care required to achieve a successful treatment outcome. This approach was first used to evaluate HIV care and has since been applied to other diseases. The tuberculosis (TB) community has only recently started using care cascade analyses to quantify gaps in quality of care. In this article, we describe methods for estimating gaps (patient losses) and steps (patients retained) in the care cascade for active TB disease. We highlight approaches for overcoming challenges in constructing the TB care cascade, which include difficulties in estimating the population-level burden of disease and the diagnostic gap due to the limited sensitivity of TB diagnostic tests. We also describe potential uses of this model for evaluating the impact of interventions to improve case finding, diagnosis, linkage to care, retention in care, and post-treatment monitoring of TB patients.

Impact of involvement of non-formal health providers on TB case notification among migrant slum-dwelling populations in Odisha, India

BACKGROUND

Migrant labourers living in the slums of urban and industrial patches across India make up a key sub-population so far controlling Tuberculosis (TB) in the country is concerned. This is because many TB patients from these communities- remain under reached by the Revised National Tuberculosis Control Programme (RNTCP) of India. This marginalized community usually seeks early-stage healthcare from "friendly neighbourhood" non-formal health providers (NFHPs). Because, RNTCP has limited capacity to involve the NFHPs, an implementation research project was conceived, whereby an external partner would engage with the NFHPs to enable them to identify early TB symptomatics from this key sub-population who would be then tested using Xpert MTB/RIF technology. Diagnosed TB cases among them would be referred promptly to RNTCP for treatment. This paper aimed to describe the project and its impact.

METHODS

Adopting a quasi-experimental before-after design, four RNTCP units from two major urban-industrial areas of Odisha were selected for intervention, which spanned five quarters and covered 151,400 people, of which 30% were slum-dwelling migrants. Two similar units comprised the control population. The hypothesis was, reaching the under reached in the intervention area through NFHPs would increase TB notification from these traditionally under-notifying units. RNTCP notification data during intervention was compared with pre-intervention era, adjusted for contemporaneous changes in control population.

RESULTS

The project detected 488 Xpert+ TB cases, of whom 466 were administered RNTCP treatment. This translated into notification of additional 198 new bacteriologically positive cases to RNTCP, a 30% notification surge, after adjustment for 2% decline in control. This meant an average quarterly increase in notification of 41.20(20.08, 62.31; p<0.001) cases. The increase was immediate, evident from the rise in level in the time series analysis by 50.42(10.28, 90.55; p = 0.02) cases.

CONCLUSION

Engagement with NFHPs contributed to an increase in TB notification to RNTCP from key under reached, slum-dwelling migrant populations.

Higher cost of implementing Xpert(®) MTB/RIF in Ugandan peripheral settings: implications for cost-effectiveness

SETTING

Initial cost-effectiveness evaluations of Xpert(®) MTB/RIF for tuberculosis (TB) diagnosis have not fully accounted for the realities of implementation in peripheral settings.

OBJECTIVE

To evaluate costs and diagnostic outcomes of Xpert testing implemented at various health care levels in Uganda.

DESIGN

We collected empirical cost data from five health centers utilizing Xpert for TB diagnosis, using an ingredients approach. We reviewed laboratory and patient records to assess outcomes at these sites and10 sites without Xpert. We also estimated incremental cost-effectiveness of Xpert testing; our primary outcome was the incremental cost of Xpert testing per newly detected TB case.

RESULTS

The mean unit cost of an Xpert test was US$21 based on a mean monthly volume of 54 tests per site, although unit cost varied widely (US$16-58) and was primarily determined by testing volume. Total diagnostic costs were 2.4-fold higher in Xpert clinics than in non-Xpert clinics; however, Xpert only increased diagnoses by 12%. The diagnostic costs of Xpert averaged US$119 per newly detected TB case, but were as high as US$885 at the center with the lowest volume of tests.

CONCLUSION

Xpert testing can detect TB cases at reasonable cost, but may double diagnostic budgets for relatively small gains, with cost-effectiveness deteriorating with lower testing volumes.

Designing and Evaluating Interventions to Halt the Transmission of Tuberculosis

To reduce the incidence of tuberculosis, it is insufficient to simply understand the dynamics of tuberculosis transmission. Rather, we must design and rigorously evaluate interventions to halt transmission, prioritizing those interventions most likely to achieve population-level impact. Synergy in reducing tuberculosis transmission may be attainable by combining interventions that shrink the reservoir of latent Mycobacterium tuberculosis infection (preventive therapy), shorten the time between disease onset and treatment initiation (case finding and diagnosis), and prevent transmission in key settings, such as the built environment (infection control). In evaluating efficacy and estimating population-level impact, cluster-randomized trials and mechanistic models play particularly prominent roles. Historical and contemporary evidence suggests that effective public health interventions can halt tuberculosis transmission, but an evidence-based approach based on knowledge of local epidemiology is necessary for success. We provide a roadmap for designing, evaluating, and modeling interventions to interrupt the process of transmission that fuels a diverse array of tuberculosis epidemics worldwide.

Optimal timing of drug sensitivity testing for patients on first-line tuberculosis treatment

Effective treatment for tuberculosis (TB) patients on first-line treatment involves triaging those with drug-resistant (DR) TB to appropriate treatment alternatives. Patients likely to have DR TB are identified using results from repeated inexpensive sputum-smear (SS) tests and expensive but definitive drug sensitivity tests (DST). Early DST may lead to high costs and unnecessary testing; late DST may lead to poor health outcomes and disease transmission. We use a partially observable Markov decision process (POMDP) framework to determine optimal DST timing. We develop policy-relevant structural properties of the POMDP model. We apply our model to TB in India to identify the patterns of SS test results that should prompt DST if transmission costs remain at status-quo levels. Unlike previous analyses of personalized treatment policies, we take a societal perspective and consider the effects of disease transmission. The inclusion of such effects can significantly alter the optimal policy. We find that an optimal DST policy could save India approximately $1.9 billion annually.

The epidemiology, pathogenesis, transmission, diagnosis, and management of multidrug-resistant, extensively drug-resistant, and incurable tuberculosis

Global tuberculosis incidence has declined marginally over the past decade, and tuberculosis remains out of control in several parts of the world including Africa and Asia. Although tuberculosis control has been effective in some regions of the world, these gains are threatened by the increasing burden of multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis. XDR tuberculosis has evolved in several tuberculosis-endemic countries to drug-incurable or programmatically incurable tuberculosis (totally drug-resistant tuberculosis). This poses several challenges similar to those encountered in the pre-chemotherapy era, including the inability to cure tuberculosis, high mortality, and the need for alternative methods to prevent disease transmission. This phenomenon mirrors the worldwide increase in antimicrobial resistance and the emergence of other MDR pathogens, such as malaria, HIV, and Gram-negative bacteria. MDR and XDR tuberculosis are associated with high morbidity and substantial mortality, are a threat to health-care workers, prohibitively expensive to treat, and are therefore a serious public health problem. In this Commission, we examine several aspects of drug-resistant tuberculosis. The traditional view that acquired resistance to antituberculous drugs is driven by poor compliance and programmatic failure is now being questioned, and several lines of evidence suggest that alternative mechanisms-including pharmacokinetic variability, induction of efflux pumps that transport the drug out of cells, and suboptimal drug penetration into tuberculosis lesions-are likely crucial to the pathogenesis of drug-resistant tuberculosis. These factors have implications for the design of new interventions, drug delivery and dosing mechanisms, and public health policy. We discuss epidemiology and transmission dynamics, including new insights into the fundamental biology of transmission, and we review the utility of newer diagnostic tools, including molecular tests and next-generation whole-genome sequencing, and their potential for clinical effectiveness. Relevant research priorities are highlighted, including optimal medical and surgical management, the role of newer and repurposed drugs (including bedaquiline, delamanid, and linezolid), pharmacokinetic and pharmacodynamic considerations, preventive strategies (such as prophylaxis in MDR and XDR contacts), palliative and patient-orientated care aspects, and medicolegal and ethical issues.

Impact of the GeneXpert MTB/RIF Technology on Tuberculosis Control

Molecular technology revolutionized the diagnosis of tuberculosis (TB) with a paradigm shift to faster, more sensitive, clinically relevant patient care. The most recent molecular leader is the GeneXpert MTB/RIF assay (Xpert) (Cepheid, Sunnyvale, CA), which was endorsed by the World Health Organization with unprecedented speed in December 2010 as the initial diagnostic for detection of HIV-associated TB and for where high rates of drug resistance are suspected. South Africa elected to take an aggressive smear replacement approach to facilitate earlier diagnosis and treatment through the decision to implement the Xpert assay nationally in March 2011, against the backdrop of approximately 6.3 million HIV-infected individuals, one of highest global TB and HIV coinfection rates, no available implementation models, uncertainties around field performance and program costs, and lack of guidance on how to operationalize the assay into existing complex clinical algorithms. South Africa's national implementation was conducted as a phased, forecasted, and managed approach (March 2011 to September 2013), through political will and both treasury-funded and donor-funded support. Today there are 314 GeneXperts across 207 microscopy centers; over 8 million assays have been conducted, and South Africa accounts for over half the global test cartridge usage. As with any implementation of new technology, challenges were encountered, both predicted and unexpected. This chapter discusses the challenges and consequences of such large-scale implementation efforts, the opportunities for new innovations, and the need to strengthen health systems, as well as the impact of the Xpert assay on rifampin-sensitive and multidrug-resistant TB patient care that translated into global TB control as we move toward the sustainable development goals.

Development, roll-out and impact of Xpert MTB/RIF for tuberculosis: what lessons have we learnt and how can we do better?

The global roll-out of Xpert MTB/RIF (Cepheid Inc., Sunnyvale, CA, USA) has changed the diagnostic landscape of tuberculosis (TB). More than 16 million tests have been performed in 122 countries since 2011, and detection of multidrug-resistant TB has increased three- to eight-fold compared to conventional testing. The roll-out has galvanised stakeholders, from donors to civil society, and paved the way for universal drug susceptibility testing. It has attracted new product developers to TB, resulting in a robust molecular diagnostics pipeline. However, the roll-out has also highlighted gaps that have constrained scale-up and limited impact on patient outcomes. The roll-out has been hampered by high costs for under-funded programmes, unavailability of a complete solution package (notably comprehensive training, quality assurance, implementation plans, inadequate service and maintenance support) and lack of impact assessment. Insufficient focus has been afforded to effective linkage to care of diagnosed patients, and clinical impact has been blunted by weak health systems. In many countries the private sector plays a dominant role in TB control, yet this sector has limited access to subsidised pricing. In light of these lessons, we advocate for a comprehensive diagnostics implementation approach, including increased engagement of in-country stakeholders for product launch and roll-out, broader systems strengthening in preparation for new technologies, as well as quality impact data from programmatic settings.

A comprehensive diagnostic solution approach including systems strengthening is essential for TB diagnostics impacthttp://ow.ly/uWSy300CfJT

Use of Rapid, Point-of-Care Assays by Private Practitioners in Chennai, India: Priorities for Tuberculosis Diagnostic Testing

SETTING

Private practitioners are frequently the first point of healthcare contact for patients with tuberculosis (TB) in India. As new molecular tests are developed for point-of-care (POC) diagnosis of TB, it is imperative to understand these individuals' practices and preferences for POC testing.

OBJECTIVE

To evaluate rapid testing practices and identify priorities for novel POC TB tests among private practitioners in Chennai.

DESIGN

We conducted a cross-sectional survey of 228 practitioners practicing in the private sector from January 2014 to February 2015 who saw at least one TB patient in the previous year. Practitioners were randomly selected from both the general community and a list of practitioners who referred patients to a public-private mix program for TB treatment. We used standardized questionnaires to collect data on current practices related to point-of-care diagnosis and interest in hypothetical POC tests. We used multivariable Poisson regression with robust estimates of standard error to calculate measures of association.

RESULTS

Among 228 private practitioners, about half (48%) utilized any rapid testing in their current practice, most commonly for glucose (43%), pregnancy (21%), and malaria (5%). Providers using POC tests were more likely to work in hospitals (56% vs. 43%, P = 0.05) and less likely to be chest specialists (21% vs. 54%, P<0.001). Only half (51%) of providers would use a hypothetical POC test for TB that was accurate, equipment-free, and took 20 minutes to complete. Chest specialists were half as likely to express interest in performing the hypothetical POC TB test in-house as other practitioners (aPR 0.5, 95%CI: 0.2-0.9). Key challenges to performing POC testing for TB in this study included time constraints, easy access to local private labs and lack of an attached lab facility.

CONCLUSION

As novel POC tests for TB are developed and scaled up, attention must be paid to integrating these diagnostics into healthcare providers' routine practice and addressing barriers for POC testing.

How Do Urban Indian Private Practitioners Diagnose and Treat Tuberculosis? A Cross-Sectional Study in Chennai

Setting

Private practitioners are frequently the first point of healthcare contact for patients with tuberculosis (TB) in India. Inappropriate TB management practices among private practitioners may contribute to delayed TB diagnosis and generate drug resistance. However, these practices are not well understood. We evaluated diagnostic and treatment practices for active TB and benchmarked practices against International Standards for TB Care (ISTC) among private medical practitioners in Chennai.

Design

A cross-sectional survey of 228 practitioners practicing in the private sector from January 2014 to February 2015 in Chennai city who saw at least one TB patient in the previous year. Practitioners were randomly selected from both the general community and a list of practitioners who referred patients to a public-private mix program for TB treatment in Chennai. Practitioners were interviewed using standardized questionnaires.

Results

Among 228 private practitioners, a median of 12 (IQR 4–28) patients with TB were seen per year. Of 10 ISTC standards evaluated, the median of standards adhered to was 4.0 (IQR 3.0–6.0). Chest physicians reported greater median ISTC adherence than other MD and MS practitioners (score 7.0 vs. 4.0, P<0.001), or MBBS practitioners (score 7.0 vs. 4.0, P<0.001). Only 52% of all practitioners sent >5% of patients with cough for TB testing, 83% used smear microscopy for diagnosis, 33% monitored treatment response, and 22% notified TB cases to authorities. Of 228 practitioners, 68 reported referring all patients with new pulmonary TB for treatment, while 160 listed 27 different regimens; 78% (125/160) prescribed a regimen classified as consistent with ISTC. Appropriate treatment practices differed significantly between chest physicians and other MD and MS practitioners (54% vs. 87%, P<0.001).

Conclusion

TB management practices in India’s urban private sector are heterogeneous and often suboptimal. Private providers must be better engaged to improve diagnostic capacity and decrease TB transmission in the community.

Transmission modeling and health systems: the case of TB in India

BACKGROUND

TB in India presents the challenges of a complex disease in a complex healthcare system. Mathematical models, offering a framework for capturing such complexities, have proven useful in exploring strategies for the control of TB. As the use of such techniques develops in future, it is important to understand what aspects of the healthcare system are most critical for models to faithfully capture.

METHODS

We ask what type of intervention should be prioritized for the control of TB, amongst: improved diagnosis of TB per visit to a healthcare provider; improved treatment success; and increased identification of TB cases in the community? Using simple mathematical models, calibrated to the national TB epidemic in India, we explore how the relative importance of each of these interventions is affected by different assumptions for the patient pathway in careseeking, thus outlining aspects of the healthcare system that may matter most for the transmission dynamics of TB.

RESULTS

We illustrate that, under a range of plausible parameter assumptions, it is possible to generate conditions under which a case-finding intervention would be prioritized over improvement of diagnosis and treatment, and vice versa. Key data needs include: the proportion of patients not contacting the healthcare system, and the mean patient delay before first seeking care.

CONCLUSIONS

For mathematical models addressing strategic priorities for TB control, it is important to adequately quantify the dynamics of careseeking. We outline ways in which these data gaps may be addressed, and questions for future work.

Cost-effectiveness of improvements in diagnosis and treatment accessibility for tuberculosis control in India

SETTING

Inaccurate diagnosis and inaccessibility of care undercut the effectiveness of high-quality anti-tuberculosis treatment and select for resistance. Rapid diagnostic systems, such as Xpert(®) MTB/RIF for tuberculosis (TB) diagnosis and drug susceptibility testing (DST), and programs that provide high-quality DOTS anti-tuberculosis treatment to patients in the unregulated private sector (public-private mix [PPM]), may help address these challenges, albeit at increased cost.

OBJECTIVE/DESIGN

We extended a microsimulation model of TB in India calibrated to demographic, epidemiologic, and care trends to evaluate 1) replacing DST with Xpert; 2) replacing microscopy and culture with Xpert to diagnose multidrug-resistant TB (MDR-TB) and non-MDR-TB; 3) implementing nationwide PPM; and combinations of (3) with (1) or (2).

RESULTS

PPM (assuming costs of $38/person) and Xpert improved health and increase costs relative to the status quo. PPM alone or with Xpert cost <1 gross domestic product/capita per quality-adjusted life-year gained relative to the next best intervention, and dominated Xpert interventions excluding PPM.

CONCLUSIONS

While both PPM and Xpert are promising tools for combatting TB in India, PPM should be prioritized over Xpert, as private sector engagement is more cost-effective than Xpert alone and, if sufficient resources are available, would substantially increase the value of Xpert if both interventions are implemented together.

Identifying Hotspots of Multidrug-Resistant Tuberculosis Transmission Using Spatial and Molecular Genetic Data

BACKGROUND

We aimed to identify and determine the etiology of "hotspots" of concentrated multidrug-resistant tuberculosis (MDR-tuberculosis) risk in Lima, Peru.

METHODS

From 2009 to 2012, we conducted a prospective cohort study among households of tuberculosis cases from 106 health center (HC) areas in Lima, Peru. All notified tuberculosis cases and their household contacts were followed for 1 year. Symptomatic individuals were screened by microscopy and culture; positive cultures were tested for drug susceptibility (DST) and genotyped by 24-loci mycobacterial interspersed repetitive units-variable-number tandem repeats (MIRU-VNTR).

RESULTS

3286 individuals with culture-confirmed disease, DST, and 24-loci MIRU-VNTR were included in our analysis. Our analysis reveals: (1) heterogeneity in annual per-capita incidence of tuberculosis and MDR-tuberculosis by HC, with a rate of MDR-tuberculosis 89 times greater (95% confidence interval [CI], 54,185) in the most-affected versus the least-affected HC; (2) high risk for MDR-tuberculosis in a region spanning several HCs (odds ratio = 3.19, 95% CI, 2.33, 4.36); and (3) spatial aggregation of MDR-tuberculosis genotypes, suggesting localized transmission.

CONCLUSIONS

These findings reveal that localized transmission is an important driver of the epidemic of MDR-tuberculosis in Lima. Efforts to interrupt transmission may be most effective if targeted to this area of the city.

The Potential Impact of Up-Front Drug Sensitivity Testing on India's Epidemic of Multi-Drug Resistant Tuberculosis

Background

In India as elsewhere, multi-drug resistance (MDR) poses a serious challenge in the control of tuberculosis (TB). The End TB strategy, recently approved by the world health assembly, aims to reduce TB deaths by 95% and new cases by 90% between 2015 and 2035. A key pillar of this approach is early diagnosis of tuberculosis, including use of higher-sensitivity diagnostic testing and universal rapid drug susceptibility testing (DST). Despite limitations of current laboratory assays, universal access to rapid DST could become more feasible with the advent of new and emerging technologies. Here we use a mathematical model of TB transmission, calibrated to the TB epidemic in India, to explore the potential impact of a major national scale-up of rapid DST. To inform key parameters in a clinical setting, we take GeneXpert as an example of a technology that could enable such scale-up. We draw from a recent multi-centric demonstration study conducted in India that involved upfront Xpert MTB/RIF testing of all TB suspects.

Results

We find that widespread, public-sector deployment of high-sensitivity diagnostic testing and universal DST appropriately linked with treatment could substantially impact MDR-TB in India. Achieving 75% access over 3 years amongst all cases being diagnosed for TB in the public sector alone could avert over 180,000 cases of MDR-TB (95% CI 44187 – 317077 cases) between 2015 and 2025. Sufficiently wide deployment of Xpert could, moreover, turn an increasing MDR epidemic into a diminishing one. Synergistic effects were observed with assumptions of simultaneously improving MDR-TB treatment outcomes. Our results illustrate the potential impact of new and emerging technologies that enable widespread, timely DST, and the important effect that universal rapid DST in the public sector can have on the MDR-TB epidemic in India.

Achieving Systemic and Scalable Private Sector Engagement in Tuberculosis Care and Prevention in Asia

William Wells and colleagues describe opportunities for improving public-private health provider partnerships to tackle TB.

Target product profile of a molecular drug-susceptibility test for use in microscopy centers

BACKGROUND

Current phenotypic testing for drug resistance in patients with tuberculosis is inadequate primarily with respect to turnaround time. Molecular tests hold the promise of an improved time to diagnosis.

METHODS

A target product profile for a molecular drug-susceptibility test (DST) was developed on the basis of a collaborative effort that included opinions gathered from researchers, clinicians, policy makers, and test developers on optimal clinical and operational characteristics in settings of intended use. In addition, the current diagnostic ecosystem and the diagnostic development landscape were mapped.

RESULTS

Molecular DSTs for detecting tuberculosis in microscopy centers should ideally evaluate for resistance to rifampin, fluoroquinolones, isoniazid, and pyrazinamide and enable the selection of the most appropriate treatment regimen. Performance characteristics of DSTs need to be optimized, but compromises can be made that depend on the trade-off between a false-positive result and a false-negative result. The operational requirements of a test will vary depending on the site of implementation. However, the most-important considerations pertain to quality control, maintenance and calibration, and the ability to export data.

CONCLUSION

This target product profile defines the needs as perceived by the tuberculosis stakeholder community and attempts to provide a means of communication with test developers to ensure that fit-for-purpose DSTs are being developed.

Costs and Consequences of Using Interferon-γ Release Assays for the Diagnosis of Active Tuberculosis in India

Background

There is growing concern that interferon-γ release assays (IGRAs) are being used off-label for the diagnosis of active tuberculosis (TB) disease in many high-burden settings, including India, where the background prevalence of latent TB infection is high. We analyzed the costs and consequences of using IGRAs for the diagnosis of active TB in India from the perspective of the Indian TB control sector.

Methods and Findings

We constructed a decision analytic model to estimate the incremental cost and effectiveness of IGRAs for the diagnosis of active TB in India. We compared a reference scenario of clinical examination and non-microbiological tests against scenarios in which clinical diagnosis was augmented by the addition of either sputum smear microscopy, IGRA, or Xpert MTB/RIF. We examined costs (in 2013 US dollars) and consequences from the perspective of the Indian healthcare sector. Relative to sputum smear microscopy, use of IGRA for active TB resulted in 23,700 (95% uncertainty range, UR: 3,800 – 38,300) additional true-positive diagnoses, but at the expense of 315,700 (95% UR: 118,300 – 388,400) additional false-positive diagnoses and an incremental cost of US$49.3 million (95% UR: $34.9 – $58.0 million) (2.9 billion Indian Rupees). Relative to Xpert MTB/RIF (including the cost of treatment for drug resistant TB), use of IGRA led to 400 additional TB cases treated (95% UR: [-8,000] – 16,200), 370,600 (95% UR: 252,200 – 441,700) more false-positive diagnoses, 70,400 (95% UR: [-7,900] – 247,200) fewer disability-adjusted life years averted, and US$14.6 million (95%UR: [-$7.2] – $28.7 million) (854 million Indian Rupees) in additional costs.

Conclusion

Using IGRAs for diagnosis of active TB in a setting like India results in tremendous overtreatment of people without TB, and substantial incremental cost with little gain in health. These results support the policies by WHO and Standards for TB Care in India, which discourage the use of IGRAs for the diagnosis of active TB in India and similar settings.

Testing and treating the missing millions with tuberculosis

In a Guest Editorial on World TB Day, Madhukar Pai and Puneet Dewan identify programmatic and policy changes needed to end TB by 2035.