TB resistance is a ‘ticking time bomb’

Increasing resistance to tuberculosis drugs around the world is a “ticking time bomb”, says the World Health Organization (WHO).

It estimates almost 500,000 people around the world have a type of TB which is resistant to at least two of the main types of drugs used to treat the disease.

Ranjhu Zha with her 65 year old mother Parvati, who has extensively drug-resistant TB

But most are not diagnosed and are walking around spreading these more deadly strains.

More than half the cases are in China, Russia and India.

The WHO says the overall number of people developing the disease is falling, but 8.6 million people were diagnosed with TB last year, and more than a million people died from the disease.

Through the hot, winding, cramped streets of Mumbai’s sprawling Dharavi slum, we have come to meet Ranjhu Zha and her family.

The family of five is crammed into a space no more than about 2 sq m.

Ranjhu sits with her son and mother on the floor.

Her mother Parvati is wearing a surgical mask.

She has what is known as an extensively drug-resistant form of TB (XDR-TB).

It is not responding to most of the main drugs used to treat the disease.

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We’re just silently watching this epidemic unfold and spread before our eyes”

Dr Ruth Mcnerny TB Alert

She caught the disease from her 23-year-old grand-daughter Bharati, who died of TB in June.

She was resistant to two of the main drugs used to treat the condition.

“My daughter was as beautiful as a flower,” says Ranjhu.

“But slowly, slowly she wasted away. I remember her always.

“But what is the point in thinking about someone who is no more? She is never coming back.”

Tuberculosis is an airborne disease. It’s very contagious and can spread from person to person by breathing in an infected person’s germs.

The cramped conditions in places like the Dharavi slum create the perfect environment for the fast spread of TB and other diseases.

People are living cheek by jowl and there’s not much ventilation.

Ranjhu says her daughter wasn’t given the full course of treatment when she first developed TB, and that made her resistant to the two main types of TB drugs.

Ranjhu’s mother is now getting treatment from the medical charity Medecins Sans Frontieres.

She says she has not been able to get the right drugs from government schemes.

Rampant misuse of antibiotics

Her treatment includes painful injections every day and will last around two years.

MSF says her treatment costs somewhere in the region of $10,000 (£6,000). Standard TB treatment costs around $50.

Drug-resistant TB

  • Multidrug-resistant TB (MDR TB) is caused by an organism that is resistant to at least isoniazid and rifampin, the two most potent TB drugs.
  • Extensively drug resistant TB (XDR TB) is a rare type of MDR TB that is resistant to isoniazid and rifampin, plus any fluoroquinolone and at least one of three injectable second-line drugs, such as amikacin, kanamycin, or capreomycin).

“There are several drugs used to treat TB,” says Lorraine Rebello, medical services manager at the MSF TB and HIV clinic in Mumbai.

“But when two of the primary drugs that are essential to treating TB – rifampicin and isoniazid – are no longer killing the TB bacteria, then the patient has drug-resistant TB.”

The Indian government’s Revised National TB Control Program aims to provide free TB treatment to every tuberculosis patient in the country.

But the WHO says out of the estimated 64,000 drug-resistant cases in India in 2012, only 16,588 were diagnosed.

Lorraine Rebello puts the rise in cases she has seen down to a number of factors.

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What could happen is progressively multi-drug resistant TB takes over from normal tuberculosis”

Dr Mario Raviglione Director, Global TB programme at the World Health Organization

“We have a huge unregulated private sector,” she says.

“We have doctors who are not properly medically qualified, like Ayurvedic doctors who are treating drug-resistant TB.

“They probably don’t have the knowledge to treat the condition, but they prescribe a cocktail of drugs.

“Some patients are even going to pharmacies without prescription and buying drugs over the counter. So we are seeing a rampant misuse of antibiotics.”

Dr Mario Raviglione, director of the WHO’s Global TB programme, describes the situation as a public health crisis.

“What could happen is progressively multi-drug resistant TB takes over from normal tuberculosis.

“If this happens not only would millions of patients potentially die of this form of TB, but if I look at it from an economic perspective the cost of dealing with millions of potential cases is enormous.”

He describes the fact that 80% of multi-drug resistant TB cases around the world are not being treated as a “ticking time bomb”.

“Killing you slowly”

Dr Ruth Mcnerny, senior lecturer at the London School of Tropical Medicine, who works with TB charity TB Alert, says: “We’re just silently watching this epidemic unfold and spread before our eyes.

TB treatment in developing countries

  • Normal TB treatment takes at least six months to treat and costs around $50 (£30)
  • Multidrug-resistant TB treatment can take at least two years and costs around $2,500 (£1,500)
  • Extensively drug-resistant TB can cost many thousands of dollars to treat. Estimated 45,000 cases globally

“TB is very clever because it kills you very slowly. And while it’s killing you very slowly you’re walking around spreading it.

“The issue of TB is if you get someone on treatment, they’ll become non-infectious quite quickly.

“But if the treatment’s not working because it is a drug-resistant strain, then they stay infected and they stay spreading drug-resistant TB.

“The treatment for drug-resistant TB is very, very difficult and at some stage it becomes impossible.”

In India, the government says it is doing all it can to improve diagnoses and treatment.

Hanmant Chauhan heads the TB programme for the state of Maharashtra.

He says around 8,000 multi-drug resistant TB patients have been treated in the last three years.

“We are taking every step so that every TB affected person gets treatment as soon as possible,” he says.

Tuberculosis symptoms

  • A persistent cough, usually for more than three weeks
  • Night sweats for weeks or months
  • Weight loss
  • Fatigue
  • High temperature
  • Shortness of breath

“We are also trying to see that the disease doesn’t spread. We are trying to make people aware about the precautions and treatment, so that the patients get the treatment and TB gets eradicated soon.”

Back in Ranjhu’s slum her 16-year-old son Santosh is studying for exams.

He sleeps on the floor of his tiny home with his infected grandmother and three other relatives.

He knows he is at high risk of catching this particularly deadly form of TB.

“I do feel scared but what can we do, we only have this one place to stay all together,” he says.

“If she removes the mask which makes her so uncomfortable because it is so hot and stuffy here, there is always a danger we will also catch the disease.”

TB challenge over ‘missing’ millions

About three million people who developed tuberculosis in 2012 have been “missed” by health systems, the World Health Organization has said.

Finding these missed cases is one of the biggest challenges in TB care and control, the WHO’s report says.

Twelve countries including India, South Africa and Bangladesh account for the majority of undiagnosed individuals.

But the WHO says the target to halve the number of TB deaths by 2015 is still within reach.

Global TB programme director Dr Mario Raviglione said 56 million people had been cured and 22 million lives had been saved in the past 15 years and half of the highest-burden countries were on track to achieve the Millennium Development Goals targets, but there remained a number of major challenges.

“The two major challenges we identified are that of detecting in the system what we call the missed cases,” he told the BBC.

” There are about three million people that we estimate had TB and that are not officially in the system, that are not reported.

“Some of them may actually be never detected, some of them are in fact hidden in the private sector, in the non-state sector, that does not notify the cases.

“So that is I think one of the biggest challenges we have to face and there are opportunities there because we know where these cases may be.”

Drug-resistant TB challenge

The WHO says TB testing services need to be urgently improved in many countries, with help from non-governmental organisations NGOs and volunteers.

And in others, particularly Asian countries, more needs to be done to ensure figures on TB are compiled and reported centrally.

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Unless we take urgent action, we will continue to see an increase in harder-to-treat drug resistant strains of TB”

Dr Philipp du Cros Medecins Sans Frontieres

The other major challenge highlighted is drug-resistant TB.

The WHO estimates that 450,000 people became ill with multidrug-resistant TB (MDR-TB) in 2012. China, India and Russia have the highest rates.

But the report adds that by 2012, deaths from TB had been reduced by 45% since 1990, meaning the target of a 50% reduction by 2015 is within reach.


Charity Medecins Sans Frontieres’ (MSF) infectious disease specialist Dr Philipp du Cros said: “Three in four people with multidrug-resistant tuberculosis are still not diagnosed, and 17,000 of those diagnosed in 2012 did not even start treatment.”

He said: “These shocking figures are an indictment of the global failure to tackle drug-resistant tuberculosis head on. People are paying for this failure with their lives.”

Dr Du Cros added: “Unless we take urgent action, we will continue to see an increase in harder-to-treat drug resistant strains of TB.”

He said more research was needed to make treatments for TB shorter, more effective and less damaging for patients.

“An extra $2bn was needed to plug a funding gap in the treatment of TB, he added.

Methodological and Policy Limitations of Quantifying the Saving of Lives: A Case Study of the Global Fund’s Approach.

Summary Points

·         A recent trend in global health has been a growing emphasis on assessing the effectiveness and impact of specific health interventions.

·         For example, it has been estimated that 8.7 million lives were saved between 2002 and mid-2012 by “Global Fund–supported programmes” (as distinct from The Global Fund alone) through antiretroviral therapy (ART); directly observed tuberculosis treatment, short course (DOTS); and distribution of insecticide-treated mosquito nets (ITNs).

·         This paper assesses the methods used by The Global Fund to quantify “lives saved,” highlights the uncertainty associated with the figures calculated, and suggests that the methods are likely to overestimate the number of “lives saved.”

·         The paper also discusses how the attribution of “lives saved” to specific programmes or actors might negatively affect the overall governance and management of health systems, and how a narrow focus on just ART, DOTS, and ITNs could neglect other interventions and reinforce vertical programmes.

·         Furthermore, the attribution of “lives saved” to Global Fund–supported programmes is potentially misleading, because such programmes include an unstated degree of financial support from recipient governments and other donors.


This paper argues that the number of “lives saved” that are attributed to Global Fund–supported programmes is not as certain as has been suggested by The Global Fund, and is likely to be an overestimate. Furthermore, estimating the “lives saved” by Global Fund–supported programmes is confusing and potentially misleading, because such programmes include a considerable but unstated amount of financial support from other sources. Finally, a number of potentially negative policy effects are associated with the selective impact estimation of downstream clinical interventions.

While this paper focuses on The Global Fund, the issues raised here apply to other global health partnerships and international donor agencies that are increasingly under pressure to quantify the health impact of their investments. The methods for estimating and attributing “lives saved,” and the consequences of doing so, should be questioned and subjected to critical debate.

In the case of The Global Fund, for a start, greater clarity and explanation about the assumptions and generalisations of the methods are required; this should include publication of uncertainty ranges and of disaggregated estimates of “lives saved” for each of the three interventions and for each year. The Global Fund should also conduct and publish sensitivity analyses, particularly in relation to treatment effectiveness, and publish estimates of “lives saved” through DOTS based on alternative counterfactual scenarios.

If the health impact of ART, DOTS, and ITNs is to be estimated in the form of “lives saved,” we argue that this should not be done as an exercise focused on individual external agencies, but rather on the collective contributions of governments and development partners within countries. This would confer a number of benefits. First, the monitoring of service delivery outputs and the estimation of their health impact would be linked to an assessment of the performance of national health systems (a more appropriate unit for assessment) and the degree to which development partners are working in harmonisation with each other and in alignment with ministries of health and their national plans and priorities. This would help shift more attention towards the strengthening of integrated national plans and information systems.

Second, holistic assessments of service delivery results and health improvement at the country level would allow for a context-based analysis of performance, including assessments of efficiency and equity. This would be aided by cross-country comparisons that would reveal variations in effectiveness (and efficiency) of ART, DOTS, and ITNs that arise from differences in, amongst other things, access to health care, quality of care and treatment adherence, and population coverage of nonclinical determinants of health such as access to clean water and nutrition. By describing this variation, policy attention can be directed not just at the delivery of selected clinical interventions, but also at the social, economic, and environmental conditions that influence the degree to which those interventions are effective. This stands in marked contrast to a modelling approach that assumes standardised levels of effectiveness across countries or regions.

Third, estimates of “lives saved” at the country level might be more valid and less uncertain because they would be derived from more appropriate and country-specific modelling assumptions, and because it would motivate countries to improve the quality of their data. In addition, it could stimulate other actors within countries, such as parliamentary health committees, universities, and local nongovernmental organizations, to develop the capacity to scrutinise the performance of the health system. While many countries produce annual health reports, health needs assessments, and national health plans, which provide some description of progress in the health sector, they are often incomplete or weak. Subnational analyses are frequently absent or superficial; and the fragmented and piecemeal nature of reporting systems, encouraged by vertical and donor-driven DAH, still undermines the development of coherent planning, budgeting, management, and information systems.

While an estimate of “lives saved” by ART, DOTS, and ITNs at country level would still be limited by its narrow focus on three interventions, it would provide a platform for monitoring and evaluating other aspects of HIV, TB, and malaria programmes and be more easily incorporated into a national system of data collection and evaluation that takes into account a wider package of health systems inputs, processes, and outputs, enabling policy makers and planners to consider the importance of investments that do not have a measurable or immediate mortality impact.

If individual external agencies need to estimate their specific contribution to “lives saved,” this could be done more simply by apportioning a share of a country’s estimated number of lives saved on the basis of their proportional financial contribution to THE or total HIV/AIDS, TB, and malaria programme financing. This would provide a more meaningful assessment of the contribution of individual agencies, avoid double-counting in reported estimates of “lives saved” by external agencies, and incentivise external agencies to promote coherent national health planning and reporting.

Many of these recommendations  are applicable to external agencies in general. However, since 2012, The Global Fund has been providing more active support for detailed national evaluations of programme performance and impact, and more accurate measures of disease incidence, prevalence, mortality, and morbidity in 20 to 25 “high-impact” countries. This provides it with an opportunity to shift emphasis away from estimating “lives saved” by individual interventions and donor-supported programmes, towards an assessment of health systems performance and impact that incorporates all major actors, programmes, and interventions, and a fuller assessment of the contribution of social, economic, and other upstream determinants of health.


Saving Lives in Health: Global Estimates and Country Measurement.

One of the most compelling reasons for development aid to health is that it saves lives, often for a few hundred dollars per year of life saved. Relatively uniquely in development, health has a set of high-impact interventions that can save lives directly. Insecticide-treated bednets (ITNs) protect families from malaria, antiretrovirals (ARVs) reduce mortality from HIV, and tuberculosis detection and treatment reduce TB mortality. Prevention activities, particularly for HIV, can save millions more lives. Yet, health programs have not always communicated with simple methods the lives they save.

In this week’s PLOS Medicine David McCoy and colleagues discuss the “lives saved” model of The Global Fund to Fight AIDS, Tuberculosis and Malaria (The Global Fund). The Global Fund, together with WHO, UNAIDS, and scientists from the article by McCoy and colleagues [1],[2], have published simple peer-reviewed methods to calculate the lives saved from a restricted set of HIV, TB, and malaria interventions that have known mortality outcomes [3][7]. Our method includes only those health interventions with known, documented mortality effects: ARV treatment; directly observed treatment, short-course (DOTS); and ITNs. Our methodology uses documented data reported to the Global Fund on the individuals receiving these services. These results are first verified by national disease programs (we invest 5%–10% of our funds to build the capacity of country monitoring and evaluation systems), then by the Global Fund (which uses independent local fund agents to check the national data systems measuring these services every six months), and finally by on-site checks in a sample of health facilities to verify that people receive these services (as part of performance-based funding) [8].

In addition, the Global Fund’s method applies the agreed, partner mortality estimates and models from WHO and UNAIDS [4] to these service results—for example, the latest scientific data on how HIV treatment or TB treatment will reduce the chance that a person will die of HIV or TB.

Extensive criteria are used to exclude countries where The Global Fund is not a significant contributor; that is, where The Global Fund does not contribute at least US$50 million; is a significant percentage of HIV, TB, and malaria spending; and does not support a key national-level activity, such as drug procurement. Where this does not occur, as has been the case in Uganda, Kenya, or South Africa in recent years, the results are not included.

The method to assess lives saved provides a conservative estimate. The estimate [3],[4] does not include the impact of HIV prevention (which in certain countries—e.g., Thailand, Uganda, Kenya, and Zimbabwe—has saved several million lives per country); the impact of malaria outside Africa and among adults; and the significant, secondary impact of DOTS treatment on reducing TB (as shown by the declines in TB prevalence in China, and in TB prevalence by 45% in Cambodia). Furthermore, reporting of services by programs in country are subject to substantial delays before they are reported globally. The most recent scale up in ITNs and ARV treatment are not fully included; for example, the lives saved are only half the number of people reported on ARVs. We do acknowledge the method [3],[4] has major limitations. Most importantly, it does not directly measure mortality, because in many countries in which we work vital registration systems are too weak, so the method is based on the latest partner estimates of mortality from WHO and UNAIDS.

The article in this week’s PLOS Medicine by David McCoy and colleagues has great value in discussing the assumptions in the methods the Global Fund uses to assess lives saved and the partner estimates—of ARV adherence, use of ITNs, and the limitations of focusing only on a limited set of services. We agree that assumptions require additional sensitivity analysis, and we will update our estimates in 2014 as modeling is refined with new and improved data from country impact evaluations and updated WHO and UNAIDS estimates. We have published more detailed analysis of the ARV, ITN, and DOTS estimates as used by the McCoy and colleagues[4]. Yet, the uncertainty ranges, with the lives saved from ITNs as low as 27,000, were based on very limited data and provided little additional value. We fully agree with the need for increased country data on estimates and mortality assumptions of lives saved. Most importantly, global modeling needs strengthening with wider and deeper country measurement of epidemic trends and lives saved.

To significantly strengthen our assessment of lives saved, The Global Fund approved a new evaluation plan in 2012, which includes country health, HIV, TB, and malaria reviews to more directly measure mortality and impact on HIV, TB, and malaria trends in 25 countries, where 65% of the global burden of these diseases occurs [9]. To strengthen these direct country data and to put global commitments made with WHO and other partners into practice, we are also investing in five components of data systems: surveys, health information systems, vital registration, financial tracking, and country analytical capacity [10]. These investments in country data and analysis will form a basis to implement some of the recommendations to global modeling provided by McCoy and colleagues [1]. Our initial country reviews provide direct evidence of impact. For example, in Cambodia, malaria deaths have been reduced by over 80%, child mortality has declined in Tanzania, TB has declined in China, HIV prevalence has declined in Zimbabwe (though not in other countries, such as Uganda in recent years) [7],[11]. Some of these declines are not captured by global estimates of lives saved, and suggest these estimates may be conservative and require updating as country-level analysis of mortality is available.

The need for improved country data does highlight some of the weaknesses we see in the paper by David McCoy and colleagues [1]. Their analysis provides very little additional country data on uncertainties, or on the significant changes in child mortality and mortality among adults of working ages, associated with the impact of HIV, TB, and malaria on Millennium Development Goals (MDGs) 4 and 6. It draws upon one meta-analysis of ARVs suggesting 62% retention at 24 months, but our recent country reviews suggest most have moved between districts rather than have died, and mortality rates were often less than 10% [11][13]. Removing a “counterfactual” of TB deaths is unclear and difficult to explain why TB deaths in 1995 might be reduced from deaths reported now, unless we are evaluating a global TB strategy. The aim of The Global Fund’s lives saved figure is not to evaluate a particular strategy, as McCoy and colleagues suggest, nor to “attribute” lives saved to the agency, but to highlight the lives saved each year from services delivered by the programs we support. The adjustment of ITNs based on data on use is important—WHO reports this as over 90% from surveys [14], and we will further adjust our estimates of lives saved as partner estimates from WHO and UNAIDS on the key parameters are updated. However, we believe McCoy and colleagues overstate the figures on ARV retention, ITN use, and issues of removing TB deaths from the 1990s.

The Global Fund is investing in improved country financial data, including funding national health accounts to improve data on spending on health, HIV, TB, and malaria by different partners in 46 countries. At present, it would not be accurate to use the reported share of total health or disease expenditure to attribute lives saved to an agency. Our communications on lives saved [3],[4] are clear that the estimates aim to show the lives saved of the programs we support together with other partners, civil society, and country HIV, TB, and malaria programs themselves. As described above and in our publications [1],[3], we use extensive criteria to exclude countries where The Global Fund does not provide significant financial and programmatic support. We stress that we play an important financing role, but the results are first and foremost those of country HIV, TB, and malaria programs. We will communicate this more clearly going forward and as we refine our methods with improved country data.

Finally, we understand the argument on vertical programs by McCoy and colleagues that reporting on individual HIV, TB, and malaria services can distort health priorities. The Global Fund is clear that it encourages countries to align funding with their health and disease strategies, and uses indicators of individual HIV, TB, and malaria services to measure progress and performance. However, we do think clear targets on HIV, TB, and malaria are important, as shown by the MDGs.

Lives saved is an important measure for health programs. We have based our estimates on real, individual verified data on a limited set of services, which have clear, documented mortality outcomes. We welcome the paper by McCoy and colleagues in this week’s PLOS Medicine, as it discusses more fully the assumptions, explores the potential pitfalls in communication, and stresses the importance of investments in country financial and impact data. Our new evaluation plan fully supports this country investment in country data and analysis. We will update our global estimates with country data from our impact studies in 25 countries where 65% of the global burden of HIV, TB, and malaria occurs. Through these investments in global estimates and country measurement, we are confident the programs The Global Fund supports will save more than the 8.7 million lives estimated so far.