Global tuberculosis control WHO Report 2010

For further information about tuberculosis contact: Information Resource Centre HTM/STB World Health Organization 20 Avenue Appia, 1211–Geneva–27, Switzerland Email: [email protected] Web site: www.who.int/tb ISBN 978 92 4 156406 9

Global Tuberculosis Control WHO REPORT 2010

The World Health Organization monitors the global tuberculosis epidemic in support of national TB control programmes.

Global Tuberculosis Control 2010

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his report on global tuberculosis control was produced by a core team of 12 people: Léopold Blanc, Dennis Falzon, Christopher Fitzpatrick, Katherine Floyd, Inés Garcia, Christopher Gilpin, Philippe Glaziou, Tom Hiatt, Delphine Sculier, Charalambos Sismanidis, Hazim Timimi and Mukund Uplekar. The team was led by Katherine Floyd and Léopold Blanc. Overall guidance was provided by the Director of the Stop TB Department, Mario Raviglione. The data collection forms (long and short versions) were developed by Philippe Glaziou, with input from staff throughout the Stop TB Department. Hazim Timimi led and organized all aspects of data management, with support from Tom Hiatt. Christopher Fitzpatrick and Inés Garcia conducted all review and follow-up of financial data. Annemieke Brands, Dennis Falzon, Christopher Gilpin, Malgosia Grzemska, Christian Gunneberg, Tom Hiatt, Eva Nathanson, Salah Ottmani, Delphine Sculier, Hazim Timimi, Wayne Van Gemert, Fraser Wares, Matteo Zignol and four colleagues from the Global Fund – Nino Mdivani, Sai Pothapregada, John Puvimanasinghe and Lal Sadasivan Sreemathy – conducted the review and follow-up of data related to epidemiology and the implementation of the Stop TB Strategy. Data for the European Region were collected and validated jointly by the WHO Regional Office for Europe and the European Centre for Disease Prevention and Control (ECDC), an agency of the European Union based in Stockholm, Sweden. Philippe Glaziou and Charalambos Sismanidis analysed surveillance and epidemiological data and prepared the figures and tables on these topics, with assistance from Tom Hiatt. Delphine Sculier and Tom Hiatt analysed TB/ HIV data and prepared the associated figures and tables. Dennis Falzon analysed data and prepared the figures and tables related to MDR-TB. Mukund Uplekar contributed a summary of recent progress in engaging all care providers through public-private and public-public mix (PPM) approaches, Christopher Gilpin and Karin Weyer provided an update on the Global Laboratory Initiative and Karin Bergstrom analysed data related to human resource development. Christopher Fitzpatrick and Inés Garcia analysed financial data, and prepared the associated figures and tables. Tom Hiatt checked and finalized all figures and tables in an appropriate format, ensuring that they were ready for layout and design according to schedule, and was the focal point for communications with the graphic designer. The main part of the report was written by Katherine Floyd. Annex 1, which explains methods used to produce estimates of disease burden, was written by Philippe Glaziou, Katherine Floyd, Charalambos Sismanidis and Hazim Timimi. Karen Ciceri edited the report. Annex 2, which contains a wealth of global, regional and country-specific data from the global TB database, was prepared by Tom Hiatt and Hazim Timimi. We thank Sue Hobbs for her excellent work on the design and layout of this report; her contribution, as in previous years, is greatly appreciated. The principal source of financial support for WHO’s work on monitoring and evaluation of TB control is the United States Agency for International Development (USAID), without which it would be impossible to produce this report. Data collection, validation and analysis were also supported by funding from the government of Japan and the Global Fund. We acknowledge with gratitude their support. In addition to the core report team and those mentioned above, the report benefited from the input of many staff at the World Health Organization (WHO) and the Joint United Nations Programme on HIV/AIDS (UNAIDS), particularly for data collection, validation and review. Among those listed below, we thank in particular Amal Bassili, Andrei Dadu, Khurshid Alam Hyder, Daniel Kibuga, Rafael López Olarte, Angélica Salomão, Nobuyuki Nishikiori and Daniel Sagebiel for their major contribution to data collection, validation and review.

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he World Health Organization (WHO) has published an annual report on global control of tuberculosis (TB) every year since 1997. The main purpose of the report is to provide a comprehensive and up-to-date assessment of the TB epidemic and progress made in TB care and control at global, regional and country levels. Progress towards global targets set for 2015 is given particular attention. The target included in the Millennium Development Goals (MDGs) is that TB incidence should be falling by 2015. The Stop TB Partnership has set two additional targets, which are to halve rates of prevalence and mortality by 2015 compared with their levels in 1990. Collectively, the WHO’s Stop TB Strategy and the Stop TB Partnership’s Global Plan to Stop TB have set out how the 2015 targets can be achieved. This fifteenth annual report1 contains more up-todate information than any previous report in the series, following earlier data collection and the completion of the production cycle within a calendar year. The estimates of the global burden of disease caused by TB in 2009 are as follows: 9.4 million incident cases (range, 8.9 million–9.9 million), 14 million prevalent cases (range, 12 million–16 million), 1.3 million deaths among HIV-negative people (range, 1.2 million–1.5 million) and 0.38 million deaths among HIV-positive people (range, 0.32 million–0.45 million). Most cases were in the South-East Asia, African and Western Pacific regions (35%, 30% and 20%, respectively). An estimated 11–13% of incident cases were HIV-positive; the African Region accounted for approximately 80% of these cases. There were 5.8 million notified cases of TB in 2009, equivalent to a case detection rate (CDR, defined as the proportion of incident cases that were notified) of 63% (range, 60–67%), up from 61% in 2008. Of the 2.6 million patients with sputum smear-positive pulmonary TB in the 2008 cohort, 86% were successfully treated. New and compelling data from 15 countries show that efforts by national TB programmes (NTPs) to engage all care providers in TB control (termed public-private mix, or PPM) can be a particularly effective way to increase the CDR. In areas where PPM was implemented, nonNTP providers accounted for around one-fifth to onethird of total notifications in 2009. In 2009, 26% of TB patients knew their HIV status (up from 22% in 2008), including 53% of patients in the African Region. A total of 300 000 HIV-positive TB patients were enrolled on co-trimoxazole preventive therapy, and almost 140 000 were enrolled on antiretroviral therapy (75% and 37% respectively of those who

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tested HIV-positive). To prevent TB, almost 80 000 people living with HIV were provided with isoniazid preventive therapy. This is an increase from previous years, but still represents less than 1% of the estimated number of people living with HIV worldwide. Among TB patients notified in 2009, an estimated 250 000 (range, 230 000–270 000) had multidrugresistant TB (MDR-TB). Of these, slightly more than 30 000 (12%) were diagnosed with MDR-TB and notified. Diagnosis and treatment of MDR-TB need to be rapidly expanded. Funding for TB control continues to increase and will reach almost US$ 5 billion in 2011. There is considerable variation in what countries spend on a per patient basis (US$ 1000), and the extent to which countries rely on domestic or external sources of funds. Compared with the funding requirements estimated in the Global Plan, the funding gap is approximately US$ 1 billion in 2011. Given the scale-up of interventions set out in the plan, this could increase to US$ 3 billion by 2015 without intensified efforts to mobilize more resources. Incidence rates are falling globally and in five of WHO’s six regions (the exception is the South-East Asia Region, where the incidence rate is stable). If these trends are sustained, the MDG target will be achieved. Mortality rates at global level fell by around 35% between 1990 and 2009, and the target of a 50% reduction by 2015 could be achieved if the current rate of decline is sustained. At the regional level, the mortality target could be achieved in five of WHO’s six regions; the exception is the African Region (although rates of mortality are falling). Prevalence is falling globally and in all six WHO regions. The target of halving the 1990 prevalence rate by 2015 appears out of reach at global level, but could be achieved in three of six regions: the Region of the Americas, the Eastern Mediterranean Region and the Western Pacific Region. Reductions in the burden of disease achieved to date follow 15 years of intensive efforts to improve TB care and control. Between 1995 and 2009, a total of 41 million TB patients were successfully treated in DOTS programmes, and up to 6 million lives were saved including 2 million among women and children. Looking forwards, the Stop TB Partnership launched an updated version of the Global Plan to Stop TB in October 2010, for the years 2011–2015. In the five years that remain until the target year of 2015, intensified efforts are needed to plan, finance and implement the Stop TB Strategy, according to the updated targets included in this plan. This could save at least one million lives per year.



 

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he World Health Organization (WHO) has published an annual report on global control of tuberculosis (TB) every year since 1997. The main purpose of the report is to provide a comprehensive and up-to-date assessment of the TB epidemic and progress made in TB care and control at global, regional and country levels. This fifteenth annual report1 contains more up-to-date information than any previous report in the series, following earlier data collection and the completion of the production cycle within a calendar year. The main part of the report is structured in eight major sections, as follows: N Methods. This section explains how the data used to produce the report are collected, reviewed and analysed. N The global burden of disease caused by TB in 2009. This section presents estimates of incidence, prevalence and mortality (absolute numbers and rates) at global, regional and country levels in 2009. N Global targets, the WHO Stop TB Strategy and the Global Plan to Stop TB. This section defines the global targets for TB control that have been set for 2015, as part of the Millennium Development Goals (MDGs) and by the Stop TB Partnership. It then describes the main components of the Stop TB Strategy and the Stop TB Partnership’s Global Plan to Stop TB, which in combination have set out how the global targets can be achieved. N Progress in implementing the Stop TB Strategy and the Global Plan to Stop TB. This section includes analysis of case notifications, treatment outcomes, case detection rates (for all forms of TB), the contribution of public–private mix (PPM) initiatives to case notifications, implementation of collaborative TB/HIV activities and the management of drugresistant TB. It also features the topic of human resource development and provides an update about the work of the Global Laboratory Initiative, whose goal is to strengthen laboratories worldwide. N Financing for TB control. Recent trends in funding for TB control, including comparisons with the funding requirements estimated in the Global Plan, are presented and discussed. Recent successes in strengthening planning and budgeting for TB control using the WHO TB planning and budgeting tool are showcased. N Progress towards the 2015 targets. This section analyses trends in rates of TB incidence, prevalence and mortality from 1990 to 2009, and assesses whether the 2015 targets can be achieved at global, regional and country levels.

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N Improving measurement of the burden of disease caused by TB. This section summarizes progress at country level in strengthening surveillance (of cases and deaths) and implementing surveys of the prevalence of TB disease, in the context of the policies and recommendations of the WHO Global Task Force on TB Impact Measurement. N Conclusions. This final section draws together the main findings and recommendations in the report. %22)< explains the methods that were used to produce estimates of disease burden. %22)< contains summary tables that provide global, regional and country-specific data for the main indicators of interest. '39286= 463*-0)7 for all countries are available online at www. who.int/tb/data; their content is advertised in %22)<. 1

Two reports were published in 2009. The first report (March) included key indicators up to and including 2007 (for example, estimates of disease burden and case notifications). The second report (published on the web in December) included key indicators up to and including 2008. Two reports were produced in one year in anticipation of a different production cycle in which reports would always contain data up to and including the previous calendar year.





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or the 2010 round of data collection, WHO updated the forms that were used in 2009. The main change was that questions on surveillance of MDR-TB, which had previously been asked through a separate data collection effort, were integrated into the global TB data collection form. As in 2009, two versions of the form were developed (a long form and a short form). The short form was adapted for use in high-income countries (that is, countries with a gross national income per capita of ≥US$ 12 196 in 2009, as defined by the World Bank) and/ or low-incidence countries (defined as countries with an incidence rate of <20 cases per 100 000 population or <10 cases in total). In consultation with WHO regional offices, a few countries that met the criteria for receiving the short form were instead requested to complete the long form. This included countries that had in previous years provided the more detailed financial data requested on the long form. Both forms requested data on the following topics: case notifications and treatment outcomes, including breakdowns by age, sex and HIV status; an overview of services for the diagnosis and treatment of TB; laboratory diagnostic services; drug management; monitoring and evaluation; surveillance and surveys of drug-resistant TB; management of drug-resistant TB; collaborative TB/ HIV activities; human resource development (HRD); TB control in vulnerable populations and high-risk groups; TB infection control; the Practical Approach to Lung Health (PAL); PPM; advocacy, communication and social mobilization (ACSM); the budgets of national TB control programmes (NTPs) in 2010 and 2011; utilization of general health services (hospitalization and outpatient visits) during treatment; and NTP expenditures in 2009. A web-based online system (www.stoptb.org/tme) was used to report and validate data in all regions except the European Region (&3< ).1 In 2010, data collection was launched in mid-March, about four months earlier than in any previous year, with a deadline of 16 May for all regions except the Region of the Americas (31 May) and the European Region (30 September). Following the deadlines for reporting of data, all reports were carefully reviewed using a system of built-in validation checks (also available to country-based staff reporting data). Followup queries were returned to respondents online. By 16 June (the deadline for responding to queries), 147 countries (excluding the European Region) had reported data (for further details, see &3<).2 In the European Region, 21 out of 53 countries reported data by 16 June. Most of the countries that had not reported data by 16 June were high-income countries in western Europe. Taken together, the 168 countries that reported data by the dead-

line of 16 June account for 99% of the world’s TB cases. All data collected online in 2010 were added to a master dataset that holds the TB-related data that have been compiled by WHO since 1995. Data from the two online systems used in the European Region3 were also uploaded to the master dataset. All data in the global and European online systems as of the morning of 17 June 2010 were then used, together with historical data reported in previous years, to produce the tables and figures that appear in the main part of the report. Country respondents continue to have the option of updating or adding data to the online system. The master dataset was updated for a second time on 31 August 2010, using all data in the global and European online systems at this time. This updated dataset was used to create the detailed tables that are included in %22)< , ensuring that data published for all countries were as up-to-date as possible at the time that the report went to press. Four additional points should be highlighted: N NTPs sometimes provide WHO with updated information for previous years, for incorporation in the global TB database. As a result, the data presented in this report may differ from those published in previous reports. N Assessments of progress made in implementing PPM initiatives and of global efforts to strengthen laboratory services and impact measurement draw on information obtained from key informants as well as data received via the online WHO TB data collection form. N Financial data are presented in real terms, after adjustment for inflation. This allows fair comparison of funding amounts across years, without distortions caused by changes in prices. N The annual data collection form and database system used by WHO are designed for collecting aggregated national data. They are not recommended for collection of data within countries.4 1

2

3

4

The European Region has its own system for online reporting of data, which is managed jointly by the European Centre for Disease Control and Prevention (ECDC) and the WHO Regional Office for Europe. The four countries for which data were not reported by 16 June were Canada, Haiti, Brunei Darussalam and Japan. Data were reported for all except Haiti by 31 August 2010 and as a result data for these countries are included in %22)<. One system for countries of the European Union, managed by the ECDC; the other for all European countries, managed by the WHO Regional Office for the European Region. Two data collection tools are used. Data from the ECDC system are uploaded to the WHO system. WHO recommendations for recording and reporting within countries are described at: http://www.who.int/tb/dots/r_and_r_forms/ en/index.html



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%22)<  provides details about the methods used to produce estimates of the disease burden caused by TB (measured as incidence, prevalence and mortality). In line with the methods explained in this annex, the results provided in the main text of the report and in %22)< are presented as best, low and high estimates.

When the term “range” is used after a best estimate in the main text of the report, the lower and higher numbers correspond to the 2.5th and 97.5th centiles of the outcome distributions produced by simulations. These are distinct from 95% confidence intervals, which are estimated directly from observed, empirical data.





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tinues to increase slightly from year to year, as slow reductions in incidence rates per capita (see 7)'8-32) continue to be outweighed by increases in population. Estimates of the number of cases broken down by age and sex have been prepared by an expert group2 as part of

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n 2009, there were an estimated 9.4 million incident cases (range, 8.9 million–9.9 million)1 of TB globally (equivalent to 137 cases per 100 000 population) (8%&0), *-+96)). The absolute number of cases con-

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The range is the uncertainty interval that corresponds to the 2.5th and 97.5th centiles of the outcome distributions produced by simulations. See also 7)'8-32 and %22)<. This expert group is convened by the WHO Global Task Force on TB Impact Measurement. See also 7)'8-32 of this report.



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an update to the Global Burden of Disease study.1 These indicate that women2 account for an estimated 3.3 million cases (range, 3.1 million–3.5 million), equivalent to 35% of all cases. Estimates of the numbers of TB cases among women and children need to be improved through more reporting and more analysis of notification data disaggregated by age and sex. Most of the estimated number of cases in 2009 occurred in Asia (55%) and Africa (30%);3 smaller proportions of cases occurred in the Eastern Mediterranean Region (7%), the European Region (4%) and the Region of the Americas (3%). The 22 HBCs that have received particular attention at the global level since 2000 account for 81% of all estimated cases worldwide (8%&0)). The five countries with the largest number of incident cases in 2009 were India (1.6–2.4 million), China (1.1–1.5 million), South Africa (0.40–0.59 million), Nigeria (0.37– 0.55 million) and Indonesia (0.35–0.52 million). India alone accounts for an estimated one fifth (21%) of all TB cases worldwide, and China and India combined account for 35%. Of the 9.4 million incident cases in 2009, an estimated 1.0–1.2 million (11–13%) were HIV-positive, with a best estimate of 1.1 million (12%) (8%&0), *-+96)). These numbers are slightly lower than those reported in previous years, reflecting better estimates (based on more direct measurements as documented in %22)<) as well as reductions in HIV prevalence in the general population. Of these HIV-positive TB cases, approximately 80% were in the African Region.


1SFWBMFODF There were an estimated 14 million prevalent cases (range, 12 million–16 million) of TB in 2009 (8%&0)), equivalent to 200 cases per 100 000 population. As explained in %22)< , prevalence is a robust indicator of the burden of disease caused by TB when it is directly

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measured in a nationwide survey. When survey data are not available, it is difficult to estimate its absolute level and trend. In those countries where surveys are done and repeated at periodic intervals (see 7)'8-32), estimates of the prevalence of TB and trends in rates of TB prevalence will improve.


.PSUBMJUZ In 2009, an estimated 1.3 million deaths (range, 1.2 million–1.5 million) occurred among HIV-negative cases of TB (8%&0) ), including 0.38 million deaths (range, 0.3 million–0.5 million) among women. This is equivalent to 20 deaths per 100 000 population. In addition, there were an estimated 0.4 million deaths (range, 0.32 million–0.45 million) among incident TB cases that were HIV-positive (data not shown); these deaths are classified as HIV deaths in the 10th revision of the International Classification of Diseases (ICD-10). Thus in total, approximately 1.7 million people died of TB in 2009. The number of TB deaths per 100 000 population among HIV-negative people plus the estimated number of TB deaths among HIV-positive people equates to a best estimate of 26 deaths per 100 000 population.


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1

2 3

4

5

This study is an update to Lopez AD et al. Global burden of disease and risk factors. New York, Oxford University Press and The World Bank, 2006. Defined as females aged ≥15 years old. Asia here means the WHO regions of South-East Asia and the Western Pacific. Africa means the WHO African Region. The latest estimates are for 2008, as published in March 2010 in: Multidrug and extensively drug-resistant TB (M/XDR-TB): 2010 global report on surveillance and response. Geneva, World Health Organization, 2010 (WHO/HTM/TB/2010.3). Figures have not been updated for this report. XDR-TB is defined as resistance to isoniazid and rifampicin (i.e. MDR-TB) plus resistance to a fluoroquinolone and, at least, one second-line injectable agent (amikacin, kanamycin and/or capreomycin).



 

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lobal targets for reducing the burden of disease caused by TB have been set for 2015 and 2050 (&3<). Currently, most attention is given to the targets set for 2015. The target set within the context of the MDGs is to halt and reverse the incidence of TB by 2015. The additional targets set by the Stop TB Partnership are to halve TB prevalence and death rates by 2015, compared with their levels in 1990.


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his section examines the latest data on implementation of the Stop TB Strategy, and compares progress with the targets included in the Global Plan to Stop TB, 2011–2015 where applicable. The first three topics covered are case notifications, treatment success rates for sputum smear-positive TB patients and case detection rates for all forms of TB. These all illustrate progress in implementing DOTS – the foundation of the Stop TB Strategy. The fourth topic is the engagement of the full range of care providers in TB control (component 4 of the strategy) through PPM. Such engagement is essential to ensure high levels of case detection and treatment success. The next two sections cover collaborative TB/ HIV activities and the diagnosis and treatment of drugresistant TB, both of which fall under component 2 of the Stop TB Strategy. Boxes are used to feature four topics – laboratory strengthening, HRD, strengthened surveillance and rational use of anti-TB medicines. All four topics are closely related to health-system strengthening (component 3 of the Stop TB Strategy) as well as DOTS and the engagement of all care providers. ACSM, community TB

care and research (components 5 and 6 of the strategy) are not discussed because there are limitations in the available data. In future, additional efforts to compile better data on these topics will be needed. The data that are currently available as well as data for all other topics covered in the 2010 data collection form can be viewed and downloaded on the WHO web site (www.who.int/tb/ data).


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No distinction is made between DOTS and non-DOTS programmes. This is because by 2007, virtually all (more than 99%) notified cases were reported to WHO as treated in DOTS programmes. Since 2009, the WHO data collection form has made no distinction between notifications in DOTS and non-DOTS programmes.



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Myanmar (45%), Kenya (46%) and Ethiopia (46%). A comparatively high proportion of notified cases were sputum smear-positive in Bangladesh (81%), the Democratic Republic of the Congo (85%) and Viet Nam (73%).

of the Americas and 66% in the European Region (where death and failure rates are comparatively high). Efforts to increase treatment success rates are warranted in these regions, especially the European Region.


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Globally, the rate of treatment success for new sputum smear-positive cases of pulmonary TB who were treated in the 2008 cohort was 86% (8%&0) ). This is the second successive year that the target of 85% (first set in 1991) has been exceeded globally. Of the 22 HBCs, 13 reached the 85% target. This included Kenya and the United Republic of Tanzania, demonstrating that countries in which there is a high prevalence of HIV among TB patients are able to achieve this target. Among WHO regions, three met or exceeded the 85% target: the Eastern Mediterranean Region, the South-East Asia Region and the Western Pacific Region. The treatment success rate was 80% in the African Region, 77% in the Region

The case detection rate (CDR)1 has been a much-used indicator of national progress in TB control since the mid-1990s. For a given country, it is calculated as the number of notified cases of TB in one year divided by the number of estimated incident cases of TB in the same year, and expressed as a percentage. The considerable attention given to the CDR was in line with the two principal global targets (case detection and treatment success rates) set for TB control during the period 1991 to 2005. The targets of reaching a CDR of ≥70% and a treat1

The CDR is actually a ratio rather than a rate, but the term “rate” has become standard terminology in this context of this indicator.



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indicating that case detection is improving (see *-+96)  in 7)'8-32). In the Western Pacific Region, notifications increased sharply between 2002 and 2006, but have since stabilized; here, patterns are strongly influenced by China, which accounts for almost 70% of incident cases in this region (8%&0)). Despite difficulties with estimating the case detection rate (&3<, %22)<), efforts to increase the percentage of TB cases that are diagnosed and treated according to international guidelines are clearly of major importance. This will be necessary to move towards the 7 million notifications targeted in the Global Plan for 2015 (and eventually, to achieve early detection of all cases). There are three main reasons why incident cases of TB may not be notified (see also %22)<, 8%&0)%). These are: N Cases are diagnosed but not reported. For people in this category, strengthening surveillance systems,

establishing links with the full range of health-care providers and stronger enforcement of legislation regarding notification of cases (where this is mandated by law) will help. N Cases seek care but are not diagnosed. For people in this category, better diagnostic capacity is needed. This could mean better laboratory capacity as well as more knowledgeable and better trained staff, especially in peripheral-level health-care facilities. N Cases do not seek care. For people in this category, reasons could include not recognizing any symptoms of TB and/or no access (financial and/or geographical) to health-care services. To reach cases in this category, health systems need to be strengthened so that basic health-care services are available to more people, and financial barriers to diagnosis (and subsequently treatment) need to be mitigated or removed.



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A case study from China, which illustrates how strengthening surveillance can lead to increased notifications of TB cases and an increase in the CDR, is provided in &3<. Engagement of all care providers is discussed in the next section. Strengthening of laboratory capacity and human resource development are discussed in &3< and &3<, respectively.


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JOJUJBUJWFT In many countries, one of the best ways to increase case detection is for NTPs to establish collaboration with the full range of health-care providers. This is component 4 of the Stop TB Strategy (&3<), and its two subcomponents are: N involvement of all public, voluntary, corporate and private providers through Public-Private Mix (PPM) approaches; and N promotion of the International Standards for Tuberculosis Care through PPM initiatives. Efforts to engage all care providers through PPM initiatives, beyond those which fall under the direct responsibility of the NTP (termed “non-NTP providers” in this report), are being introduced and scaled up in many countries. Unfortunately, demonstrating this progress is not always possible. First, it requires that systematic

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recording and reporting of the source of referral and place of TB treatment is being done. Second, it requires that data reported at the local level are aggregated, analysed and reported at the national level.1 Often, one or both conditions are not yet met. Despite this recording and reporting challenge, substantial progress in engaging non-NTP care providers through PPM can be documented for an increasing number of countries. New and compelling data compiled from 15 countries (including nine HBCs) in 2010, which demonstrate the major contribution that PPM can make to case notifications, are summarized in 8%&0) . In these 15 countries, the contribution of PPM initiatives typically ranges from between about one fifth to one third of total notifications, in the geographical areas in which PPM has been implemented. This has been accompanied by maintenance of high rates of treatment success (data not shown). As also illustrated in 8%&0), NTPs have used a variety of approaches to engage non-NTP care providers, according to the local context. These include incentivebased schemes for individual and institutional providers in India and Myanmar; a web-based system for mandatory reporting of TB cases by all providers in China 1

WHO recommends that the source of referral and the place of treatment should be routinely recorded and reported.



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(&3<); and reimbursement for TB care delivered by private providers through health insurance, when care conforms with agreed-upon standards, in the Philippines. It is also noticeable that countries have prioritized different types of care providers. This includes pharmacies in Cambodia, private hospitals in Nigeria, public hospitals in China and Indonesia, social security organizations in Mexico and prison services in Kazakhstan. In general, only a small proportion of targeted care providers collaborate actively with NTPs and contribute to TB case notifications in most countries. For this reason, it is not surprising that NTPs often give first priority to engaging institutional providers with whom establishing collaborative links may be less demanding and, for a given amount of effort, will yield a higher number of notifications. At the same time, involving front-line health workers such as community-based informal providers, private practitioners and pharmacies – who are often the first point of contact for people with symptoms of TB – can help to reduce diagnostic delays and the out-of-pocket expenditures of TB patients. For these reasons, scaling up PPM, in phases if not at once, should aim to systematically map and engage all relevant care providers in TB care and control.


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BDUJWJUJFT Collaborative TB/HIV activities are essential to ensure that HIV-positive TB patients are identified and treated appropriately, and to prevent TB in HIV-positive people.1 These activities include establishing mechanisms for col-

laboration between TB and HIV programmes; infection control in health-care and congregate settings; HIV testing of TB patients and – for those TB patients infected with HIV – CPT and ART; and intensified TB case-finding among people living with HIV followed by IPT for those without active TB. Testing TB patients for HIV and providing CPT for HIV-positive TB patients are typically the responsibility of NTPs; national HIV programmes are usually responsible for initiating intensified case-finding among HIV-positive people and provision of IPT to those without active TB. Provision of ART to HIV-positive TB patients is often the responsibility of national HIV programmes, but may also be done by NTPs. When NTPs do not provide ART directly, they are responsible for referring HIV-positive TB patients to ART services. Further progress in implementing collaborative TB/ HIV activities was made in 2009, which consolidated the achievements documented in previous reports. Just over 1.6 million TB patients knew their HIV status in 2009 (26% of notified cases), up from 1.4 million in 2008 (*-+ 96) ). The highest rates of HIV testing were reported in the European Region, the African Region and the Region of the Americas, where 86%, 53% and 41% of TB patients knew their HIV status, respectively (8%&0)). In 55 countries, at least 75% of TB patients knew their HIV status, including 16 African countries (*-+96) ), up from 50 countries in total and 11 in the African 1

Interim policy on collaborative TB/HIV activities. Geneva, World Health Organization, 2004 (WHO/HTM/TB/2004.330; WHO/ HTM/HIV/2004.1).



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Globally, just over 30 000 cases of MDR-TB were notified to WHO in 2009, mostly by European countries and South Africa (*-+96), 8%&0)). This represents 12% of the estimated number of cases of MDR-TB among all notified cases of pulmonary TB in 2009 (8%&0)). Country plans suggest that, overall, the numbers of patients diagnosed with MDR-TB and started on treatment will almost double in 2010 and 2011, compared with 2009 (*-+96) ). Substantial increases in the numbers of patients diagnosed with MDR-TB and started on treatment are expected in the three countries where the estimated number of cases is highest: China, India and the Russian Federation (8%&0)). There has been an impressive increase in the share of notified cases enrolled on treatment in projects or programmes approved by the Green Light Committee (GLC), in which patients are known to be receiving treatment according to international guidelines. The number reached around 11 000 in 2009, and is expected to rise to over 30 000 in 2011 (approximately 60% of all notifications of MDR-TB that are projected by countries in that year). This remains a small fraction of the estimated number of TB patients who have MDR-TB (eighth column from right, 8%&0)). Much more rapid expansion of diagnosis and treatment – within and outside projects and programmes approved by the GLC – is needed to approach the targets for MDR-TB that are included in the Global Plan (*-+96)). National data on treatment outcomes among cohorts



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he funding available for TB control in the 22 HBCs has increased year-on-year since 2002, with the exception of a small dip in 2009, and is expected to reach US$ 3.0 billion in 2011 (*-+96), *-+96), *-+96) ). Most of this funding has been used to support DOTS implementation, although the share for MDR-TB (mostly accounted for by funding in the Russian Federation and South Africa) has increased since 2007 (*-+96)). The relatively small amount of funding reported for collaborative TB/HIV activities reflects the fact that funding for most of these interventions is channelled through national HIV programmes and nongovernmental organizations rather than via NTPs. National governments are the largest source of funding (*-+96) ), accounting for 85% of total expected funding in 2011. Financing from the Global Fund has become increasingly important since 2004, and is expected to reach US$ 327 million in 2011 (a 10% increase compared with 2010). Other donor funding is expected to amount to approximately US$ 100 million in 2011. In absolute terms, 61% of the funding expected in 2011 is accounted for by just two countries: the Russian Federation and South Africa (*-+ 96)). Despite increases in funding and nine completed rounds of proposals1 to the Global Fund, NTPs continue to report funding gaps (*-+96) ). Since 2007, these gaps have been in the range of US$ 0.3–0.5 billion per year. In 2011, funding gaps are anticipated for all components of the Stop TB Strategy, including for DOTS (the basic package that underpins the Stop TB Strategy). In some countries, there are still funding gaps for supplies of first-line anti-TB drugs. Trends in funding for the 22 HBCs as a whole conceal important variations among countries (8%&0), *-+96) , *-+96)). Both NTP budgets and funding of NTPs have been increasing in most countries; the exceptions include Kenya, Indonesia and Mozambique, where funding has fallen since 2008 (*-+96)). Funding has been closest to keeping pace with increases in NTP budgets in Brazil, China, India, the Philippines and the Russian Federation. In contrast, funding gaps have persisted in most African countries as well as Cambodia, Myanmar and Pakistan. In 2011, the Russian Federation, Thailand, Brazil, South Africa, China, the Philippines and Viet Nam will rely primarily on domestic funding (including loans from development banks). In other HBCs, there is much greater reliance on donor funding, ranging from around

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40% of available funding in India to more than 90% of available funding in the Democratic Republic of the Congo (*-+96)). There is also considerable variation in the estimated cost per patient treated according to the DOTS strategy (*-+96) ). This ranges from under US$ 100 (in Bangladesh, India, Myanmar, Pakistan and Zimbabwe) to around US$ 750 in Thailand, US$ 1000–1500 in Brazil and South Africa and more than US$ 7 500 in the Russian Federation. In most HBCs, the cost per patient treated under DOTS is around US$ 150–400. As shown in *-+96), variation in the cost per patient treated is clearly related to income levels (for example, Brazil and South Africa are upper-middle income countries, where prices for inputs such as NTP staff and hospital care are higher than in low-income countries). The major reason why the Russian Federation is an outlier is the model of care used: high costs are associated with a policy of lengthy hospitalization of TB patients within an extensive network of TB hospitals and sanatoria. A further explanation for variation in costs appears to be the scale at which treatment is provided. The countries with relatively low costs for their income level (for example, Bangladesh, China, India, Indonesia and the Philippines) are also the countries where the total numbers of patients treated are highest (as shown by the size of the circles in *-+96)). A similar pattern exists for the cost per patient successfully treated, which combines information about both costs and effectiveness (*-+96) ).


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1

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vincing plans and well-justified budgets. The WHO TB planning and budgeting tool was developed in 2006, to assist with the development of comprehensive plans and budgets for all relevant components of TB control. When completed, one advantage of the tool is that it automatically summarizes NTP budgets and sources of funding in the format requested on the annual WHO TB data collection form. Successes in using the tool to help with the development and budgeting of strategic plans in Bangladesh, Cambodia and Mongolia between mid-2009 and mid-2010 are highlighted in &3<.



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rogress made towards achieving the impact targets set for 2015 – to halt and reverse the incidence of TB by 2015 (MDG Target 6.c), and to halve prevalence and mortality rates compared with a baseline of 1990 (the targets set by the Stop TB Partnership) – is illustrated at the global level in *-+96) and at the regional level in *-+96) , *-+96)  and *-+96) .1 Progress in achieving reductions in incidence and mortality is shown for each of the 22 HBCs in *-+96) and *-+96). Globally, rates of incidence, prevalence and mortality are all declining (*-+96)). Incidence rates are falling slowly, at around 1% per year, following a peak at just over 140 cases per 100 000 population in 2004. If current trends are sustained, then MDG Target 6.c will be achieved. Mortality rates have fallen by one third since 1990, and prevalence rates are also in decline. Projections suggest that the target of halving mortality by 2015 compared with 1990 could be achieved at global level. The target of halving the prevalence rate appears out of reach. It should be noted, however, that there is more uncertainty about trends in prevalence, compared with trends in mortality (see also %22)<). Regionally, incidence rates are declining in five of WHO’s six regions (*-+96)). The exception is the South-East Asia Region (where the incidence rate is stable), largely explained by apparent stability in the TB incidence rate in India. Further evaluation of trends in the disease burden in India is needed, and has been

planned for early 2011. Among the five regions where incidence rates are falling, the rate of decline varies from less than 1% per year in the Eastern Mediterranean and European regions to around 2% per year in the African Region (since 2004) and 4% per year in the Region of the Americas. As also illustrated in *-+96), notifications are closest to estimated incidence in the Region of the Americas and the European Region, indicating that the highest rates of case detection are achieved in these regions (see also 7)'8-32 ). As incidence falls slowly, notifications are increasing in the African Region and (particularly since 2000) in the Eastern Mediterranean and South-East Asia regions, indicating improving rates of case detection. In the Western Pacific Region, notifications increased sharply between 2002 and 2006, but have since stabilized; here, patterns are strongly influenced by China, which accounts for almost 70% of incident cases in this region (8%&0)). The latest assessment for the 22 HBCs suggests that incidence rates are falling or stable in all countries except South Africa (*-+96)). Trends in incidence rates are assumed to be stable in Afghanistan, Bangladesh, India, Indonesia, Myanmar and Pakistan, in the absence of convincing evidence to the contrary (%22)< ). The stability in TB incidence rates in India (which accounts for 61% of cases in this region) as well as Bangladesh, Indonesia and Myanmar explains the flat trend in estimated incidence in the South-East Asia Region.

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In most of the HBCs, notifications have been getting closer to estimated incidence in recent years, notably in Afghanistan, Bangladesh, Cambodia, China, Indonesia, Pakistan, South Africa and the United Republic of Tanzania (*-+96)). Prevalence rates are falling in all six WHO regions (*-+ 96)). The most impressive progress is in the Region of the Americas, where the Stop TB Partnership’s target of halving the 1990 prevalence rate has been achieved. Projections suggest that the Western Pacific and Eastern Mediterranean regions are on track to achieve the target by 2015, and the European Region could get close. On current projections, the African and South-East Asian regions will not achieve the target. Mortality rates (excluding TB deaths among HIVpositive people) are falling in all six WHO regions. The best progress towards the 2015 target of halving the 1990 mortality rate is in the Region of the Americas and the Western Pacific Region, both of which appear to have achieved the target already. The Eastern Mediterranean, European and South-East Asia regions are close to reaching the target, and could do so before 2015. In the African Region, achieving the target appears out-of-reach,

following a major increase in TB incidence and mortality rates associated with the HIV epidemic throughout the 1990s and up to around 2004. Among the 22 HBCs, mortality rates appear to be falling with the possible exception of Afghanistan and Uganda (*-+96) ). Even allowing for uncertainty in these estimates, four countries reached the target of halving the 1990 mortality rate by 2009 (Brazil, Cambodia, China and the United Republic of Tanzania), and six additional countries (India, Indonesia, Kenya, Myanmar, Pakistan and the Russian Federation) have a good chance of doing so by 2015. In the other HBCs, current forecasts suggest that the target may not be achieved. The reductions in mortality associated with progress to date in implementing the DOTS strategy (1995–2006) and its successor, the Stop TB Strategy (launched in 2006) have saved millions of lives since 1995, and continued implementation could save millions more in the years up to 2015 (*-+96) ).1 From 1995 to 2009, 49 1

These results are based on the following manuscript: Glaziou P et al. Lives saved by tuberculosis control and prospects for achieving the 2015 global target for reductions in tuberculosis mortality (submitted for publication in May 2010).



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million patients were treated, of whom 41 million were successfully treated in DOTS programmes, saving up to 6 million lives. This includes approximately 2 million lives saved among women and children. From 2010 to 2015, a further 5 million lives could be saved if current efforts and levels of achievement in TB control are sustained, including around 2 million women and children. With expansion of treatment for MDR-TB and interventions such as ART for HIV-positive TB patients in the period 2011–2015, as set out in the Global Plan, even more lives could be saved.

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stimates of TB incidence, prevalence and mortality and their trend (presented in 8%&0)  and in *-+ 96)7 ¦) are based on the best available data and analytical methods. Methods were updated in 2009 following 18 months of work by an expert group convened under the umbrella of the WHO Global Task Force on TB Impact Measurement.1 Improvements to methods (full details are provided in %22)<) include systematic documentation of expert opinion and how this has been used in estimates of the burden of disease caused by TB, simplification of models,2 updates to parameter values based on the results of systematic reviews, much greater use of mortality data from vital registration systems (89 countries for the analyses presented in this report, up from three in the years up to 2008) and systematic documentation of uncertainty. Despite this progress, estimates of the disease burden need to be further improved in the period up to 2015 (and beyond) using better surveillance systems, more extensive and in-depth analysis of available surveillance and programmatic data, and additional survey data. For example, with the exception of Eritrea in 2005, the last nationwide and population-based surveys of the prevalence of TB disease in the African Region were undertaken between 1957 and 1961; only around 10% of TB-attributable deaths (in HIV-negative people) are recorded in vital registration systems and reported to WHO; and most notification systems are recording only around 50–70% of estimated cases. Besides its work on reviewing and updating the methods that are used to produce estimates of the burden of disease caused by TB, the WHO Global Task Force on TB Impact Measurement is thus making concerted efforts to support countries to pursue two other major strategic tracks of work (full details are available in a recent WHO Policy Paper3). These are:

N Surveys of the prevalence of TB disease, with particular attention to 21 “global focus” countries (*-+96) ). These surveys should be carried out according to WHO guidelines and related Task Force recommendations; N Strengthening surveillance of cases and deaths through notification and vital registration systems. The ultimate goal is for TB incidence and mortality to be measured directly from these systems. The Task Force has defined a conceptual framework for this work (*-+96)) and related tools to help countries to implement it in practice. As of mid-2010, all of the countries in the South-East Asia and Western Pacific regions where prevalence sur-

veys are recommended (Bangladesh, Cambodia, China, Indonesia, Myanmar, the Philippines, Thailand and Viet Nam) were on track with survey implementation. Bangladesh (2008), the Philippines (2007) and Viet Nam (2007) recently completed surveys, and subsequent surveys are planned close to 2015. The most notable successes in 2009/2010 among Asian countries were the completion of nationwide surveys in Myanmar (in April 2010; see &3< ) and China (in July 2010). The results of these surveys will be of major importance for gaining a better understanding of the burden of disease (both countries) and the impact of TB control in the past two decades (in China, following previous surveys in 1990 and 2000). Looking forwards, a survey will be implemented in Cambodia in 2011, following a previous survey in 2002. This will allow assessment of the impact of TB control since 2002 i.e. the years since DOTS was implemented. A survey is in the advanced stages of preparation in Thailand, and in Indonesia a follow-up to the 2004 survey is planned for 2013 or 2014. In the Eastern Mediterranean Region, Pakistan secured full funding for a survey in 2008, but security concerns and other factors that affect field operations may preclude implementation. The greatest challenge in terms of implementation of prevalence surveys is in the African Region. Nonetheless, considerable progress was made during 2009 and 2010. As of July 2010, five countries were in a strong position to start surveys in late 2010 or early 2011 (Ethiopia, Ghana, Nigeria, Rwanda and the United Republic of Tanzania). Preparations were relatively advanced in Kenya, Malawi, Uganda, Zambia and South Africa, although funding gaps remained a major bottleneck in Kenya (dependent on the approval of funding from a Round 9 grant from the Global Fund), Uganda (where reprogramming of Global Fund grants is needed) and Zambia (where full funding had been secured but the subsequent suspension of a Global Fund grant now impedes progress). Intensive efforts are needed to ensure that countries planning surveys in 2010 and 2011 are able to do so successfully. In 2009 and 2010, there was substantial progress in 1

2

3

For further details, see the Task Force web site at: http://www. who.int/tb/advisory_bodies/impact_measurement_taskforce/en/ index.html. The review is also the basis for the TB component of the forthcoming update to the Global Burden of Disease, due for publication in 2010. For example, some parameter values are now estimated only at global level or for regions, rather than for each country individually. TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper no. 2; WHO/HTM/TB/2009.416).



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analysing surveillance and programmatic data, with analyses used to develop recommendations for how surveillance systems need to be strengthened and to produce updated estimates of disease burden. Regional workshops to apply the Task Force framework (*-+96) ) for systematic assessment of surveillance data were held in the Eastern Mediterranean, European, SouthEast Asia and Western Pacific regions and the Region of the Americas. Country missions in which the framework was applied were undertaken in the Philippines, the United Republic of Tanzania and Viet Nam. By July 2010, these workshops and country missions had covered a total of 70 countries (*-+96) ). A workshop for 17 countries in the African Region is scheduled for December 2010. An important conclusion from workshops and country missions was that there is an urgent need to strengthen vital registration systems, to allow better measurement of mortality (&3< ). There is also an urgent need to introduce electronic recording and reporting systems, without which it is difficult or impossible to adequately assess many aspects of data quality. Examples of aspects of data quality that are difficult or impossible to assess

without case-based and electronic reporting systems include the extent to which misclassifications and duplications exist. In addition, the availability of electronic data, stored in well-managed relational databases (not Excel spreadsheets), greatly facilitates data analysis. More widespread adoption of updated recommendations on recording and reporting is also required (for example, to ensure availability of data disaggregated by HIV status and source of referral). An example of experience with implementing a casebased and electronic recording and reporting system (from China) in provided in&3<. Besides improving estimates of the disease burden caused by TB, better data from surveys and surveillance combined with better analysis of these data should be of great value in identifying where and why cases are not being detected. In turn, findings should help to identify which components of the Stop TB Strategy need to be introduced or scaled-up to improve TB control. Examples from Cambodia, Myanmar and Viet Nam are highlighted in the second edition of WHO’s guidelines on surveys of the prevalence of TB disease.1

1

The second edition of these guidelines (following publication of the first edition in 2007) has been produced as a major collaborative effort among technical and financial partners and lead survey investigators from Asian and African countries. The guidelines were in the late stages of preparation at the time this report went to press, with publication expected before the end of 2010.



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8

his section summarizes the main conclusions that can be drawn from the findings included in this report. It also draws together the main recommendations that appear in the report, in the form of a Box (&3<). The global burden of TB is falling slowly. Incidence rates have been declining since 2004 at the global level, and if this trend is sustained, MDG Target 6.c will be achieved worldwide. Five of WHO’s six regions are also on track to achieve this target (the exception is the South-East Asia Region, where the incidence rate is stable). Mortality rates at global level fell by around 35% between 1990 and 2009, and the target of a 50% reduction by 2015 could be achieved if the current rate of decline is sustained. At the regional level, the mortality target could be achieved in five of WHO’s six regions; the exception is the African Region (although rates of mortality are falling in this region). Prevalence is fall-

ing globally and in all six WHO regions. However, the target of halving 1990 prevalence rates by 2015 may not be reached at global level. Three regions are on track to achieve this target: the Region of the Americas, the Eastern Mediterranean Region and the Western Pacific Region. Reductions in the disease burden achieved to date follow 15 years of intensive efforts at country level to implement the DOTS strategy (1995–2005) and its successor, the Stop TB Strategy (launched in 2006). Between 1995 and 2009, a cumulative total of 41 million TB patients were successfully treated in DOTS programmes, and up to 6 million lives were saved. The treatment success rate achieved in DOTS cohorts worldwide has now exceeded the global target of 85% for two successive years. Although increasing numbers of TB cases have access to high-quality treatment for TB as well as access to

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related interventions such as ART, much more remains to be done. More than one-third of incident TB cases are not reported as treated in DOTS programmes, around 90% of patients with MDR-TB are not being diagnosed and treated according to international guidelines, many HIV-positive TB cases do not know their HIV status and most of the HIV-positive TB patients who do know their HIV status are not yet being provided with ART. Funding gaps remain large at more than US$ 1 billion per year, despite increases in funding over the past decade and substantial financing from the Global Fund in many countries.

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Looking forwards, the Stop TB Partnership launched an updated version of the Global Plan to Stop TB in October 2010, for the years 2011–2015. In the five years that remain until the target year of 2015, intensified efforts to plan, finance and implement the Stop TB Strategy, according to the updated targets included in the Global Plan, are needed. This could save a cumulative total of 5 million lives, including 2 million women and children.

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his annex explains the methods that were used to produce estimates of the global burden of disease caused by TB (measured in terms of incidence, prevalence and mortality). It has eight major sections: N General approach. This section provides some background information about the methods used to produce estimates of disease burden. N Definitions. This section defines TB incidence, prevalence and mortality and the case fatality rate. It also explains the regions for which estimates of disease burden are produced and sources of information on population estimates. N Estimates of TB incidence, 1990–2009. This section explains the five main methods used to estimate TB incidence, and the countries for which they have been applied. It also discusses estimates of the incidence of sputum smear-positive cases of pulmonary TB, and explains why such estimates (and related estimates of the case detection rate for sputum smear-positive cases of pulmonary TB) are not included in this report. N Estimates of HIV prevalence among incident TB cases, 1990–2009. This section explains the methods used to estimate the prevalence of HIV among incident cases of TB. N Estimates of TB prevalence, 1990–2009. This section explains the two main methods used to estimate TB prevalence. These are national surveys of the prevalence of TB disease and indirect estimates based on combining estimates of incidence with estimates of the duration of TB disease. N Estimates of TB mortality, 1990–2009. This section explains the two methods used to estimate TB mortality. These are direct measurements from vital registration (VR) data and indirect estimates based on combining estimates of TB incidence with estimates of the case fatality rate. The countries for which these methods have been used are explained. Methods for estimating mortality by age and sex are also described. N Projections of TB incidence, prevalence and mortality. This section explains how projections up to 2015 were produced. N Uncertainty framework. This section explains the general approach to including uncertainty in all estimates.


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BQQSPBDI Estimates of the burden of disease caused by TB (measured in terms of incidence, prevalence and mortality) are produced annually by WHO using information gathered through surveillance systems (case notifications and death registrations), special studies (including surveys of the prevalence of disease and in-depth analyses of surveillance data), expert opinion and consultations with countries. Two recent publications provide up-todate guidance about how TB incidence, prevalence and

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mortality should be measured,1,2 based on the work of the WHO Global Task Force on TB Impact Measurement.3 The methods used to estimate the burden of disease were updated in 2009 following 18 months of work by an expert group convened under the umbrella of the Task Force. Improvements to methods include systematic documentation of expert opinion and how this has been used to produce estimates of disease burden, simplification of models,4 updates to parameter values based on the results of systematic reviews, much greater use of mortality data from VR systems (89 countries instead of the three from which estimates were derived up to 2008) and systematic documentation of uncertainty (hence the uncertainty intervals shown on all of the estimates of disease burden in this report).


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 -RGMHIRGITVIZEPIRGIQSVXEPMX]ERH  XLIGEWIJEXEPMX]VEXI Incidence is defined as the number of new and relapse cases of TB (all forms) occurring in a given year. Relapse cases are defined as people who have been previously treated for TB and for whom there was bacteriological confirmation of cure and/or documentation that treatment was completed. Relapse cases may be true relapses or a subsequent episode of TB caused by reinfection. Prevalence is defined as the number of cases of TB disease (all forms) at a given point in time (the middle of the year). Mortality is defined as the number of deaths caused by TB, excluding deaths occurring in HIV-positive TB cases, according to the definitions used in the 10th revision of the International Classification of Diseases (ICD-10). Estimates of deaths caused by TB in HIV-positive cases are presented separately. The case fatality rate is defined as the risk of death from TB among people with active TB disease.  6IKMSRW Regional analyses are generally undertaken for the six WHO regions (that is, the African Region, the Region of the Americas, the Eastern Mediterranean Region, the European Region, the South-East Asia Region and 1

2

3

4

Dye C et al. Measuring tuberculosis burden, trends and the impact of control programmes. Lancet Infectious Diseases (published online 16 January 2008; http://infection.thelancet.com). TB impact ,measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper no. 2; WHO/HTM/TB/2009.416). The policy paper is available on the Task Force’s website http://www.who.int/tb/advisory_ bodies/impact_measurement_taskforce/en/index.html. For further details, see the Task Force web site at: http://www.who. int/tb/advisory_bodies/impact_measurement_taskforce/en/index. html. The review is also the basis for the TB component of the update to the Global Burden of Disease, due for publication in 2010. For example, some parameter values are now estimated only at global level or for regions, rather than for each country individually.



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the Western Pacific Region). For some analyses, Eastern Europe (countries of the former Soviet states plus Bulgaria and Romania) as well as the group of high-income countries1 are distinguished.

For countries participating in these regional workshops, incidence was estimated according to the following equation: incidence =

 4STYPEXMSRIWXMQEXIW Where population sizes are needed to calculate TB indicators, the 2008 revision of estimates provided by the United Nations Population Division (UNPD) was used.2 The UNPD estimates sometimes differ from those made by countries.


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° No country has ever undertaken a nationwide survey of TB incidence because of the large sample sizes required and associated major logistic and financial challenges. As a result, there are no direct measurements of the incidence of TB. Theoretically, data from TB surveillance systems that are linked to health systems of high coverage and performance may capture all (or almost all) incident cases of TB. However, as yet no standard and widely-endorsed criteria and benchmarks for classifying TB surveillance systems are available. The WHO Global Task Force on TB Impact Measurement is working on the development of such standards, and initial ideas are available in a background paper. In the absence of direct measurements, estimates of TB incidence rely on one or more of the five methods described in 7)'8-327¦. It should be noted that, with very few exceptions, incidence estimates are no longer derived from surveys of the prevalence of tuberculous infection as measured in tuberculin surveys. The WHO Global Task Force on TB Impact Measurement has agreed that methods for deriving incidence from the prevalence of infection are unreliable. The Task Force has also stated that it is doubtful whether repeat tuberculin surveys provide a reliable estimate of the trend in TB incidence.4  )WXMQEXMRK8&MRGMHIRGIJVSQIWXMQEXIWSJXLI  TVSTSVXMSRSJGEWIWHIXIGXIH Notification data for new and relapse cases have been analysed in combination with evidence about the coverage of the TB surveillance system5 and expert opinion in five regional workshops and three country missions held 2008–2010, according to a framework developed by the WHO Global Task Force on TB Impact Measurement (see 7)'8-32 of the main part of this report). By mid-2010, these workshops and country missions had covered 71 countries in the Region of the Americas, the Eastern Mediterranean Region, the European Region, the SouthEast Asia Region and the Western Pacific Region. The African region was the only region where such workshops had not been held by mid-2010; at the time this report went to press, the first workshop in this region, for 17 of the 46 countries in the region, was scheduled for December 2010.

case notifications proportion of cases detected

The proportion of all TB cases6 detected (the case detection rate, or CDR) was estimated, with plausible ranges, for three years (1997, 2003 and 2008 or 2009), following in-depth analysis of national and sub-national data. Expert opinion was elicited after in-depth analysis of notification data (including data from sub-national administrative levels) and programmatic data reflecting efforts in TB control (for example, data on infrastructure, staffing, the performance of services and funding). In addition, data on access to health care from Demographic and Health Surveys and the overall performance of health systems (using indicators such as the infant mortality rate) were used to substantiate opinion on the proportion of cases with no or very limited access to health care (8%&0)%). 5"#-&
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As defined by the World Bank. High-income countries are those with a per capita gross national income (GNI) of US$ 12 196 or more in 2009. http://esa.un.org/unpp/; accessed on 7 June 2010. See the second background paper prepared for the fourth meeting of the Global Task Force on TB Impact Measurement, held 17–18 March 2010. The paper is available on the Task Force’s web site http://www.who.int/tb/advisory_bodies/impact_measurement_ taskforce/en/index.html. TB Impact Measurement: Policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper; no. 2 (WHO/HTM/TB/2009.416). The recommendation on tuberculin surveys is provided on page 12. The policy paper is available on the Task Force’s website http://www.who.int/tb/advisory_ bodies/impact_measurement_taskforce/en/index.html. For example, measurements from “inventory” studies or estimation from capture-recapture modelling in which at least three sources of information were used – thus allowing adjustment for between-source dependencies. A useful reference on capture-recapture methods is: Chao A et al. The applications of capture-recapture models to epidemiological data. Statistics in Medicine, 2001, 20(20):3123–3157. Defined as cases of all forms of TB, including sputum smear-positive pulmonary cases, sputum smear-negative pulmonary cases, and extrapulmonary cases.



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Data were assessed using a three-step process. This started with a systematic assessment of data quality, including an assessment of the over-dispersion of count data over time and across regions/districts (or similar geographical areas). This was followed by exploration of potential factors driving time-changes in case notifications (such as improvements in diagnostic capacity and the HIV epidemic), and then by assessment of the likely number of TB cases that are not notified. To facilitate the documentation of expert opinion, an “onion” framework1 was used. In this framework, different “layers” of the onion represent distinct populations of TB cases that are not captured by national TB information systems (for example, cases with no access to health care and cases with access to private health-care services but not reported to NTPs – see 8%&0)%). These methods are documented in a workbook available on the web site of the WHO Global Task Force on TB Impact Measurement.2 Distributions of CDRs for the three years for which they were estimated were assumed to follow a Beta distribution (8%&0) %). Reasons for using Beta distributions include the following:

N They are continuous and defined on the interval (0, 1). Since the variance of CDR distributions tend to be large as a result of high uncertainty, random draws of numbers from a normal distribution would yield numbers outside the interval (0, 1). The use of truncated normal distributions may result in excess density towards one of the bounds. N They are not necessarily symmetrical. N They are defined with two parameters that can be estimated from available data using the method of moments. The two shape parameters necessary to define the Beta distribution were computed using the method of moments, as follows: 1

2

TB impact measurement: policy and recommendations for how to assess the epidemiological burden of TB and the impact of TB control. Geneva, World Health Organization, 2009 (Stop TB policy paper no 2; WHO/ HTM/TB/2009.416. The onion framework is described on pages 19–24). The policy paper is available on the Task Force’s website http://www.who.int/tb/advisory_bodies/impact_measurement_ taskforce/en/index.html. http://www.who.int/tb/advisory_bodies/impact_measurement_ taskforce/en/index.html.



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First, the variance for the distribution was taken as: V = ((u – l)/4)2 where l and u are the lower and upper bounds of the plausible range for the CDR. Shape 1 (noted α) and shape 2 (noted β) follow from: s = E(l – E) – l V α = sE β = s(l – E) where E is the expected value of the distribution. Time series for the period 1990–2009 were built according to the characteristics of the three CDRs that were estimated. A cubic spline extrapolation of V and E, with knots set at the three reference years, was used. Incidence trajectories were derived from the series of notified TB cases using Monte Carlo simulations from which expected values, 2.5th and 97.5th centiles were extracted. All computations were conducted in the R statistical environment.1 If there were insufficient data to determine the factors leading to time-changes in case notifications, incidence was assumed to follow a horizontal trend going through the most recent estimate of incidence.  )WXMQEXMRK8&MRGMHIRGIJVSQHEXESR  GEWIRSXM´GEXMSRWERHI\TIVXSTMRMSRJSV  LMKLMRGSQIGSYRXVMIW For high-income countries, the level of TB incidence was assumed to be distributed between the notification rate for new and relapse cases combined (lower uncertainty bound, noted l) and 1.3 times the notification rate (upper uncertainty bound, noted u), as informed by expert opinion. The distribution of incidence was assumed to follow a Beta distribution with shape parameters computed using the method of moments, as described above. In the absence of country-specific data on the quality and coverage of TB surveillance systems, it was assumed that TB surveillance systems from countries in the highincome group performed similarly well, although the model does allow for stochastic fluctuations.  )WXMQEXMRK8&MRGMHIRGIJVSQIQTMVMGEP  QIEWYVIQIRXWSJHMWIEWITVIZEPIRGI Incidence can be estimated using measurements from national surveys of the prevalence of TB disease combined with estimates of the duration of disease. Incidence is estimated as the prevalence of TB divided by the average duration of disease. The duration of disease cannot be directly measured. For example, measurements of the duration of symptoms in prevalent TB cases that are detected during a preva1

R Development Core Team. R: a language and environment for statistical computing. Vienna, R Foundation for Statistical Computing, , 2009 (ISBN 3-900051-07-0; http://www.R-project.org).

lence survey are systematically biased towards lower values, since active case-finding truncates the natural history of undiagnosed disease. Measurements of the duration of disease in notified cases ignore the duration of disease among non-notified and untreated cases. Literature reviews commissioned by the WHO Global Task Force on TB Impact Measurement have provided estimates of the duration of disease in untreated TB cases from the pre-chemotherapy era (before the 1950s). The best estimate of the mean duration of disease (for smear-positive cases and smear-negative cases combined) in HIV-negative individuals is about three years. There are few data on the duration of disease in HIVpositive individuals. When measurements from two prevalence surveys were available, trends in TB incidence were derived by fitting a log-linear model to indirect estimates of TB incidence. When three or more prevalence measurements were available, the prevalence trajectory was built using cubic spline interpolation. If only one prevalence survey measurement was available, time-trends were assessed using in-depth analysis of surveillance data, as described above. In this report, the prevalence to incidence method was used for only one country (Viet Nam), following a meeting in early 2009 in which consensus was reached among national experts and experts from WHO and the KNCV Tuberculosis Foundation.  )WXMQEXMRK8&MRGMHIRGIJVSQQIEWYVIQIRXWSJ  QSVXEPMX]ERHIWXMQEXIWSJXLIGEWIJEXEPMX]VEXI In three countries (Brazil, Mexico and South Africa), incidence was estimated from 1990 up to 2008 from TB mortality data, using the following equation: incidence =

deaths proportion of incident cases that die

Previously published time-series of incidence for those three countries were then extended to 2009, using methods described in 7)'8-32.  )WXMQEXMRK8&MRGMHIRGIJVSQTVIZMSYWP]  TYFPMWLIHXMQIWIVMIWSJMRGMHIRGI In all remaining countries, previously published timeseries of TB incidence were extended by fitting a log-linear model to the estimates for 2006–2008, to predict a value for 2009.  )WXMQEXMRKXLIMRGMHIRGISJWTYXYQ  WQIEVTSWMXMZI8&ERHXLIGEWIHIXIGXMSR  VEXIJSVWTYXYQWQIEVTSWMXMZI8& All the annual reports on global TB control published by WHO from 1997 to 2009 included estimates of the incidence of sputum smear-positive TB and the related CDR for such cases. The CDR for sputum smear-positive pulmonary TB is the number of new and relapse cases of sputum smear-positive pulmonary TB notified to NTPs divided by



the estimated number of incident cases that occurred in the same year. Estimates of the incidence of sputum smear-positive pulmonary TB and the related CDR for these cases are not published in this report. There are several reasons for this, which are summarized in the main part of the report (&3< ). Among the reasons noted in this box are the findings and associated recommendations from the 18-month expert review of methods used to estimate disease burden described in 7)'8-32 above, and associated updates to methods used to estimate disease burden that have been applied in a series of regional workshops and country missions (7)'8-32). A fuller explanation is provided here. In regional workshops and country missions, the starting point for estimates of the incidence of TB was an estimate of the CDR for all forms of TB. This was because, for many countries, estimates of the incidence of all forms of TB are used to produce indirect estimates of TB mortality and TB prevalence (these do not require estimates of the CDR for smear-positive TB). The incidence of sputum smear-positive pulmonary TB can theoretically be estimated by multiplying the incidence of all forms of TB by the estimated proportion of all incident cases of TB that have sputum smear-positive pulmonary TB. The CDR for sputum smear-positive pulmonary TB would then be estimated by dividing reported notifications of sputum smear-positive cases of pulmonary TB by the estimated incidence of sputum smear-positive pulmonary TB. This approach was used in global reports published up to December 2009. Subsequently, the findings of one of the systematic reviews conducted by the expert group have cast doubts on this approach. A systematic review of the evidence about the proportion of TB cases that have sputum smear-positive pulmonary TB found considerable uncertainty around the best estimate of this proportion.1 It may appear that an alternative method is to assume that, for any given country, the proportion of all incident cases with sputum smear-positive pulmonary TB is equal to the proportion of all notified cases that had smear-positive pulmonary TB in the region of reference (this could be an epidemiologically-defined region or a WHO region, for example). However, use of this method will mean that, for many countries, changes in the estimated CDR for sputum smear-positive pulmonary TB will occur from one year to the next simply because of a change in the share of regional notifications that are smear-positive, without any real change in the level of case detection in the country itself (since a change in the regional proportion will cause the estimated incidence of smear-positive TB in a given country, the denominator of the CDR, to go up and down even when the country’s notifications are stable). This is wrong and likely to cause confusion. Another alternative is to assume that, in any given

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country, the proportion of sputum smear-positive cases of pulmonary TB among all notified cases reflects the true proportion of sputum smear-positive TB among incident cases of TB in the country. In this case, the estimated CDR for all forms of TB and the estimated CDR for sputum smear-positive cases are the same. If needed for reporting purposes, it is suggested that the CDR for smear-positive TB is assumed to be similar to the CDR for all forms of TB.


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the prevalence of HIV was estimated indirectly according to the following equation: t=

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In this equation, t is HIV prevalence among incident TB cases, h is HIV prevalence among the general population (from the latest time-series provided by UNAIDS) and ρ is the incidence rate ratio (IRR) (defined as the incidence rate of TB in HIV-positive people divided by the incidence rate of TB in HIV-negative people).2 To estimate ρ from empirical data (that is, from countries that have an empirical estimate of both t and h), the equation was rearranged as follows: ρ=

t(l – h) h(l – t)

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Research Institute of Tuberculosis, Tokyo 2010 (data not shown). Data on HIV prevalence in the general population are unpublished data provided to WHO by UNAIDS.

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has been estimated by UNAIDS as an independent variable, a linear model of logit-transformed t was fitted using logit-transformed h according to the following equation, written in matrix notation: Tˆ = Xβ where Tˆ is a vector of predicted logit(t), X is an n \ 2 matrix in which the first column holds 1s, and the second column holds logit(h). The vector β holds estimated model parameters. Models were run using Monte Carlo simulations in which h was drawn randomly from a Beta distribution with shape parameters computed as described in 7)' 8-32, (low and high uncertainty bounds are provided by UNAIDS – also see 8%&0)%). The model was run 50 000 times using country-specific distributions for H and T (noted in capital letters to denote vectors or matrices) based on their uncertainty intervals (*-+96) %). The uncertainty bounds for β were chosen as the 2.5th and 97.5th centiles. The source of data used for each country is listed in the %44)2(-<.


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° The best way to measure the prevalence of TB is through national population-based surveys of TB disease.1,2 Data from such surveys are available for an increasing number of countries. It should be noted, however, that measurements of prevalence are typically confined to the adult population. Furthermore, prevalence surveys exclude extrapulmonary cases and do not allow the diagnosis of cases of culture-negative pulmonary TB. When there is no direct measurement from a national survey of the prevalence of TB disease, prevalence is the most uncertain of the three TB indicators used to measure disease burden. This is because prevalence is the product of two uncertain quantities: (i) incidence and (ii) disease duration. The duration of disease is very difficult to quantify because measurements from surveys of the prevalence of TB disease are not reliable (surveys truncate the natural history of disease). Duration can be assessed in self-presenting patients, but there is no practical way to measure the duration of disease in patients who are not notified to NTPs. Indirect estimates of prevalence were calculated according to the following equation:

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where the index variable i denotes HIV+ and HIV–, the index variable j denotes notified and non-notified cases, d denotes the duration of disease and I is total incidence. In the absence of measurements, we did not allow duration in notified cases to vary among countries. Given their underlying uncertainty, prevalence estimates should be used with great caution in the absence of direct measurements from a prevalence survey. Assumptions of the duration of disease are shown in the last four rows of 8%&0)%.


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The best sources of data about deaths from TB (excluding those among HIV-positive people) are VR systems in which causes of death are coded according to ICD-10 (although the older ICD-9 and ICD-8 classification are still in use in several countries). Deaths from TB in HIVpositive people are coded under HIV-associated codes. Estimates of TB mortality were produced directly from VR data, or indirectly from estimates of TB incidence and case-fatality rates (CFRs). The source of data used in each country is listed in the %44)2(-<.  )WXMQEXMRK8&QSVXEPMX]JVSQHMVIGX  QIEWYVIQIRXWSJZMXEPVIKMWXVEXMSRHEXE Data from VR systems are reported to WHO by Member States and territories every year. In countries with 1

2

Glaziou P et al. Tuberculosis prevalence surveys: rationale and cost. International Journal of Tuberculosis and Lung Disease, 2008, 12(9):1003–1008. Assessing tuberculosis prevalence through population-based surveys. Manila, World Health Organization, 2007.



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functioning VR systems in which causes of death are coded according to the two latest revisions of the International Classification of Diseases (underlying cause of death: ICD-10 A15-A19, equivalent to ICD-9: 010018), VR data are the best source of information about deaths from TB among people not infected with HIV. When people with AIDS die from TB, HIV is registered as the underlying cause of death and TB is recorded as a contributory cause. Since one third of countries with VR systems report to WHO only the underlying causes of death and not contributory causes, VR data usually cannot be used to estimate the number of TB deaths in HIV-positive people. In 2009, 90 countries had well-functioning VR systems according to the following definition: (i) coverage of at least 70% of the population, and (ii) ill-defined causes of death (ICD-9 code B46, ICD-10 codes R00-R99) of <20% of all registered deaths.1 These countries included four of the 22 HBCs (Brazil, the Philippines, the Russian Federation and South Africa). However, we could not use the VR data on TB deaths from South Africa because large numbers of HIV deaths were miscoded as TB deaths. Among the remaining 89 countries, there was an average of 6.2 years (interquartile range, 4–8) of VR data on TB mortality between 1991 and 2009 that met the above criteria, equivalent to 602 country-years. We assumed that the proportion of TB deaths among deaths not recorded by the VR system was the same as the proportion of TB deaths in VR-recorded deaths. For VR-recorded deaths with ill-defined causes, we assumed that the proportion of deaths attributable to TB was half of the observed proportion in recorded deaths, since ill-defined causes are typically observed in higher proportions in rural areas with a low population density where the risk of TB is lower. We assumed errors in measurement (due to misclassifications) and assumptions (redistributions) to be log-normally distributed with a standard deviation on a log scale given by σ = 0.05μ / (ν – s/2), where μ is the VR recorded TB mortality rate, v the coverage of the VR system and s the rate of ill-defined causes. Incomplete coverage and ill-defined causes introduce uncertainty in measurements μ. The standard deviation of μ was based on the assumption that uncertainty intervals of μ spanned at least ±10% of the measurement μ, increasing with decreasing VR coverage and with increasing rates of ill-defined causes of death.  )WXMQEXMRK8&QSVXEPMX]JVSQMRHMVIGXIWXMQEXIW  SJGEWIJEXEPMX]VEXIWERH8&MRGMHIRGI For the years in which VR data of sufficient quality and coverage were not available for the 89 countries defined above plus the 124 countries without any VR data, mortality was estimated as the product of TB incidence and 1

Mathers CD et al. Counting the dead and what they died from: an assessment of the global status of cause of death data. Bulletin of the World Health Organization, 2005, 83:171–177.

the CFR. CFRs were estimated separately for TB cases notified to NTPs and non-notified cases and, within these two groups, separate estimates were made for HIV-positive TB cases and HIV-negative TB cases (8%&0)%). For consistency with VR-based mortality estimates, CFRs were estimated such that they gave the best fit to the VR-recorded TB death rates (within their uncertainty ranges) across the 602 country-years of data from the 89 countries with functioning VR systems, in conjunction with WHO estimates of distributions of TB incidence in those countries. This statistical fitting used Bayesian linear models and was done separately for three groups of countries (high-income, eastern Europe, and all other countries), to account for differences in the ratio of reported TB mortality to TB notification rates among these three groups (data not shown). The models used normal errors and Gibbs sampling: y = (I – N)β1 + Nβ2 + ε, ε ~ N(0,σ2) where y is TB mortality from VR, I denotes TB incidence excluding people living with HIV, N denotes TB notifications excluding people living with HIV, and parameters β1 and β2 denote the CFR in non-notified and notified cases respectively. Semi-conjugate priors were set with an uninformative inverse Gamma prior on the conditional error variance: b ~ N(b i ,B i -2),σ2 ~ IG(5.10 -4 ,5.10 -4) Priors b and their precision B were defined based on literature reviews and the country-year CFR parameters used by WHO for the years 1999–2008 (8%&0) %). Convergence of Markov Chains was assessed graphically and using two convergence diagnostic tests. Within each case category 1990–2009, mortality estimates were computed by taking the product of posterior distributions of the CFR, assumed to be time-independent (8%&0) %), and country-year specific distributions of estimated incidence. Among the 89 countries, the combination of using VR data for some years and indirect estimates (based on incidence and CFRs) for others sometimes led to implausible differences between adjacent time-points. Where this occurred, we assumed that VR measurements were more reliable than the indirect estimates. We re-scaled the indirectly estimated TB mortality values to ensure, on average, smooth mortality trend lines. Rescaling factors were defined for each country as the ratio of the mean of available VR-recorded TB mortality rates over the mean of indirectly estimated mortality, among cases excluding those infected with HIV, for the years covered by VR measurements.  )WXMQEXMRK8&QSVXEPMX]JVSQHMWEKKVIKEXIH  IWXMQEXIWSJ8&HIEXLWF]EKIERHWI\ For countries with VR data, it was possible to disaggregate estimated TB deaths by age (with age groups defined as 0–4 years, 5–14 years, 15–24 years, 25–34 years,



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35–44 years, 45–54 years, 55–64 years, ≥65 years) and sex, in line with the way in which deaths are reported. In countries with no functional VR system, the total number of estimated TB deaths was redistributed into the different age and sex strata according to the disaggregation of the combined population of countries with VR data (with standardization against the individual country’s age and sex distribution). TB deaths in HIVpositive people were not disaggregated by age and sex due to limited data from countries with functional VR systems.


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VODFSUBJOUZ There are many potential sources of uncertainty associated with estimates of TB incidence, prevalence and mortality, as well as estimates of the burden of HIVassociated TB and MDR-TB. These include uncertainties in input data, in parameter values, in extrapolations used to impute missing data, and in the model used. We used fixed population values from the UNPD. We did not account for any uncertainty in these values. Notification data are of uneven quality. Cases may be underreported (missing quarterly reports from remote administrative areas are not uncommon), misclassified (in particular, misclassification of relapse cases in the category of new cases is common), or over-reported as a result of duplicated entries in TB information systems. The latter two issues can only be addressed efficiently in countries with case-based nationwide TB databases that include patient identifiers. Sudden changes in notifications over time are often the result of errors or

inconsistencies in reporting, but may sometimes reflect abrupt changes in TB epidemiology (for example, resulting from a rapid influx of migrants from countries with a high-burden of TB, or from rapid improvement in casefinding efforts). Missing national aggregates of new and relapse cases were imputed by cubic spline interpolation. However, notification trajectories were not automatically smoothed over time to avoid introducing systematic errors in countries where time-changes are reflecting true changes in the epidemiology of TB. Attempts to obtain corrections for historical data are made every year, but only rarely do countries provide appropriate data corrections. It is therefore generally unclear when bumps in notifications are most likely reflecting reporting errors. Future regional workshops will include a systematic effort to correct for such data deficiencies using expert opinion, for those cases where corrections appear necessary. Mortality estimates incorporated the following sources of uncertainty: sampling uncertainty in the underlying measurements of TB mortality rates from data sources, uncertainty in estimates of incidence rates and rates of HIV prevalence among both incident and notified TB cases, and parameter uncertainty in the Bayesian model. Time-series of TB mortality were generated for each country through Monte Carlo simulations. Unless otherwise specified, uncertainty bounds and ranges were defined as the 2.5th and 97.5th centiles of outcome distributions. Throughout this report, ranges with upper and lower bounds defined by these centiles are provided for all estimates established with the use of simulations. When uncertainty was established with the use of observed or other empirical data, 95% confidence intervals are reported. The model used the following sequence: (1) incidence estimation, (2) estimation of HIV-positive TB incidence, (3) estimation of mortality, (4) estimation of prevalence. By design, some steps were independent from each other (for example, step 4 may be done before or after step 3). The general approach to uncertainty analyses was to draw values from specified distributions for every



parameter (except for notifications and population values) in Monte Carlo simulations, with the number of simulation runs set so that they were sufficient to ensure stability in the outcome distributions. The same random generator seed was used for every country, and errors were assumed to be time-dependent within countries (thus generating autocorrelation in time-series). Regional parameters were used in some instances (for example, for CFRs). Summaries of quantities of interest were obtained by extracting the 2.5th, 50th and 97.5th centiles of posterior distributions. The country-specific

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estimates produced using the just-described simulations were then used as the building blocks for further simulations, from which aggregated summaries at global and regional levels for incidence, prevalence and mortality were drawn. Two sets of simulations were run, the first to produce aggregates at regional level and the second to produce aggregates at global level. These summary estimates are the result of simulations based on nonsymmetric distributions. As a result, best estimates for regions do not necessarily sum to the best estimate for the world.



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JODJEFODF Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See %22)< for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. Estimates published in previous global TB control reports should no longer be used.

(SBQIT Graphs where displayed show data from all years within the range stated.

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TPVSDF Data shown in this annex are taken from the WHO global TB database on 31 August 2010. Data shown in the main part of the report were taken from the database on 17 June 2010. As a result, data in this annex may differ slightly from those in the main part of the report. Data can be downloaded from www.who.int/tb/data.



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'EVMFFIER-WPERHW Data from the territories of Anguilla, Bermuda, British Virgin Islands, Cayman Islands, Montserrat, Netherlands Antilles, Turks & Caicos Islands and US Virgin Islands are no longer included in the tables. Data collected in previous years from these territories can still be downloaded from www.who.int/tb/data.

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97% In addition to the 51 reporting areas, the USA includes territories that report separately to WHO. The data for these territories are not included in the data reported by the USA. Definitions of case types and outcomes do not exactly match those used by WHO.



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JODJEFODF Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See %22)< for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. Estimates published in previous global TB control reports should no longer be used.

(SBQIT Graphs where displayed show data from all years within the range stated.

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TPVSDF Data shown in this annex are taken from the WHO global TB database on 31 August 2010. Data shown in the main part of the report were taken from the database on 17 June 2010. As a result, data in this annex may differ slightly from those in the main part of the report. Data can be downloaded from www.who.int/tb/data.



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JODJEFODF Estimated values are shown as best estimates followed by lower and upper bounds. The lower and upper bounds are defined as the 2.5th and 97.5th centiles of outcome distributions produced in simulations. See %22)< for further details. Estimated numbers are shown rounded to two significant figures. Estimated rates are shown rounded to three significant figures unless the value is under 100, in which case rates are shown rounded to two significant figures. Estimates for all years are recalculated as new information becomes available and techniques are refined, so they may differ from those published in previous reports in this series. Estimates published in previous global TB control reports should no longer be used.

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OPUFT )9GSYRXVMIW Notification data for countries that are members of the European Union were not available on 31 August 2010. These data will be provided on-line when available. (IRQEVO Data for Denmark exclude Greenland.



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