Global tuberculosis targets and milestones set for 2016-2035: definition and rationale.

BACKGROUND: Global tuberculosis (TB) targets were set as part of the World Health Organization's End TB Strategy (2016-2035) and the Sustainable Development Goals (2016-2030). OBJECTIVE: To define and explain the rationale for these targets. DESIGN: Scenarios for plausible reductions in TB deaths and cases were developed using empirical evidence from best-performing countries and modelling of the scale-up of under-used interventions and hypothetical TB vaccines. Results were discussed at consultations in 2012 and 2013. A final proposal was presented to the World Health Assembly in 2014 and unanimously endorsed by all Member States. RESULTS: The 2030 targets are a 90% reduction in TB deaths and 80% reduction in TB incidence compared with 2015 levels. The 2035 targets are for reductions of 95% and 90%, respectively. A third target-that no TB-affected households experience catastrophic costs due to the disease by 2020-was also agreed. CONCLUSION: The global TB targets and milestones set for the period 2016-2035 are ambitious. Achieving them requires concerted action on several fronts, but two things are fundamental: 1) progress towards universal health coverage to ensure that everyone with TB can access high-quality treatment; and 2) substantial investment in research and development for new tools to prevent TB disease among the approximately 1.7 billion people infected

Subclinical tuberculosis disease - a review and analysis of prevalence surveys to inform definitions, burden, associations and screening methodology

While it is known that a substantial proportion of individuals with tuberculosis disease (TB) present subclinically, usually defined as bacteriologically-confirmed but negative on symptom screening, considerable knowledge gaps remain. Our aim was to review data from TB prevalence population surveys and generate a consistent definition and framework for subclinical TB, thus enabling an estimate of the proportion of TB that is subclinical, explore associations with overall burden and programme indicators, and performance of screening strategies. We extracted data from all publicly available prevalence surveys conducted since 1990. Between 36.1-79.7% (median 50.4%) of prevalent bacteriologically-confirmed TB was subclinical. No association was found between prevalence of subclinical and all bacteriologically confirmed TB, patient diagnostic rate or country-level HIV prevalence (p-values, 0.32, 0.4, 0.34, respectively). Chest X-ray detected 89% (range 73-98%) of bacteriologically-confirmed TB disease, highlighting the potential of optimizing current TB case-finding policies

Estimation of subnational tuberculosis burden: generation and application of a new tool in Indonesia.

SETTING: In many high tuberculosis (TB) burden countries, there is substantial geographical heterogeneity in TB burden. In addition, decisions on TB funding and policy are highly decentralised. Subnational estimates of burden, however, are usually unavailable for planning and target setting.OBJECTIVE and DESIGN: We developed a statistical model termed SUBsET to estimate the distribution of the national TB incidence through a weighted score using selected variables, and applied the model to the 514 districts in Indonesia, which have substantial policy and budgetary autonomy in TB. Estimated incidence was compared to reported facility and domicile-based notifications to estimate the case detection rate (CDR). Local stakeholders led model development and dissemination.RESULTS: The final SUBsET model included district population size, level of urbanisation, socio-economic indicators (living floor space and high school completion), human immunodeficiency virus prevalence and air pollution. We estimated district-level TB incidence to be between 201 and 2,485/100 000/year. The facility-based CDR varied between 0 and 190%, with high variation between neighbouring districts, suggesting strong cross-district health utilisation, which was confirmed by domicile-based CDR estimation. SUBsET results informed district-level TB action plans across Indonesia.CONCLUSION: The SUBsET model could be used to estimate the subnational burden in high-burden countries and inform TB policymaking at the relevant decentralised administrative level

TIME Impact - a new user-friendly tuberculosis (TB) model to inform TB policy decisions.

Tuberculosis (TB) is the leading cause of death from infectious disease worldwide, predominantly affecting low- and middle-income countries (LMICs), where resources are limited. As such, countries need to be able to choose the most efficient interventions for their respective setting. Mathematical models can be valuable tools to inform rational policy decisions and improve resource allocation, but are often unavailable or inaccessible for LMICs, particularly in TB. We developed TIME Impact, a user-friendly TB model that enables local capacity building and strengthens country-specific policy discussions to inform support funding applications at the (sub-)national level (e.g. Ministry of Finance) or to international donors (e.g. the Global Fund to Fight AIDS, Tuberculosis and Malaria).TIME Impact is an epidemiological transmission model nested in TIME, a set of TB modelling tools available for free download within the widely-used Spectrum software. The TIME Impact model reflects key aspects of the natural history of TB, with additional structure for HIV/ART, drug resistance, treatment history and age. TIME Impact enables national TB programmes (NTPs) and other TB policymakers to better understand their own TB epidemic, plan their response, apply for funding and evaluate the implementation of the response.The explicit aim of TIME Impact's user-friendly interface is to enable training of local and international TB experts towards independent use. During application of TIME Impact, close involvement of the NTPs and other local partners also builds critical understanding of the modelling methods, assumptions and limitations inherent to modelling. This is essential to generate broad country-level ownership of the modelling data inputs and results. In turn, it stimulates discussions and a review of the current evidence and assumptions, strengthening the decision-making process in general.TIME Impact has been effectively applied in a variety of settings. In South Africa, it informed the first South African HIV and TB Investment Cases and successfully leveraged additional resources from the National Treasury at a time of austerity. In Ghana, a long-term TIME model-centred interaction with the NTP provided new insights into the local epidemiology and guided resource allocation decisions to improve impact

Improving the quality of modelling evidence used for tuberculosis policy evaluation.

Mathematical modelling is commonly used to evaluate policy options for tuberculosis (TB) control in high-burden countries. Although major policy and funding decisions are made based on these analyses, there is concern about the variability of results produced using modelled policy analyses. We discuss new guidance for country-level TB policy modelling. The guidance was developed by the TB Modelling and Analysis Consortium in collaboration with the World Health Organization Global TB Programme, with input from a range of TB stakeholders (funders, modelling groups, country TB programme staff and subject matter experts). The guidance describes principles for country-level TB modelling, as well as good practices for operationalising the principles. The principles cover technical concerns such as model design, parameterisation and validation, as well as approaches for incorporating modelling into country-led policy making and budgeting. For modellers, this guidance suggests approaches to improve the quality and relevance of modelling undertaken to support country-level planning. For non-modellers, this guidance describes considerations for engaging modelling technical assistance, contributing to a modelling exercise and reviewing the results of modelled analyses. If routinely adopted, this guidance should improve the reliability, transparency and usefulness of modelling for country-level TB policy making. However, this guidance will not address all challenges facing modelling, and ongoing work is needed to improve the empirical evidence base for TB policy evaluation and develop stronger mechanisms for validating models. Increasing country ownership of the modelling process remains a challenge, requiring sustained engagement and capacity building

How can mathematical models advance tuberculosis control in high HIV prevalence settings?

Existing approaches to tuberculosis (TB) control have been no more than partially successful in areas with high human immunodeficiency virus (HIV) prevalence. In the context of increasingly constrained resources, mathematical modelling can augment understanding and support policy for implementing those strategies that are most likely to bring public health and economic benefits. In this paper, we present an overview of past and recent contributions of TB modelling in this key area, and suggest a way forward through a modelling research agenda that supports a more effective response to the TB-HIV epidemic, based on expert discussions at a meeting convened by the TB Modelling and Analysis Consortium. The research agenda identified high-priority areas for future modelling efforts, including 1) the difficult diagnosis and high mortality of TB-HIV; 2) the high risk of disease progression; 3) TB health systems in high HIV prevalence settings; 4) uncertainty in the natural progression of TB-HIV; and 5) combined interventions for TB-HIV. Efficient and rapid progress towards completion of this modelling agenda will require co-ordination between the modelling community and key stakeholders, including advocates, health policy makers, donors and national or regional finance officials. A continuing dialogue will ensure that new results are effectively communicated and new policy-relevant questions are addressed swiftly

Evidence-informed policy making at country level: lessons learned from the South African Tuberculosis Think Tank.

BACKGROUND: National Tuberculosis Programmes (NTPs) require specialist input to support the development of policy and practice informed by evidence, typically against tight deadlines. OBJECTIVE: To describe lessons learned from establishing a dedicated tuberculosis (TB) think tank to advise the South African NTP on TB policy. INTERVENTION AND EVALUATION METHODS: A national TB think tank was established to advise the NTP in support of evidence-informed policy. Support was provided for activities, including meetings, modelling and regular telephone calls, with a wider network of unpaid expert advisers under an executive committee and working groups. Intervention evaluation used desktop analysis of documentary evidence, interviews and direct observation. RESULTS: The TB Think Tank evolved over time to acquire three key roles: an 'institution', a 'policy dialogue forum' and an 'interface'. Although enthusiasm was high, motivating participation among the NTP and external experts proved challenging. Motivation of working groups was most successful when aligned to a specific need for NTP decision making. Despite challenges, the TB Think Tank contributed to South Africa's first ever TB and human immunodeficiency virus (HIV) investment case, and the decision to create South Africa's first ever ring-fenced grant for TB. The TB Think Tank also assisted the NTP in formulating strategy to accelerate progress towards reaching World Health Organization targets. DISCUSSION: With partners, the TB Think Tank achieved major successes in supporting evidence-informed decision making, and garnered increased funding for TB in South Africa. Identifying ways to increase the involvement of NTP staff and other experts, and keeping the scope of the Think Tank well defined, could facilitate greater impact. Think tank initiatives could be replicated in other settings to support evidence-informed policy making

Systems medicine and infection

By using a systems based approach, mathematical and computational techniques can be used to develop models that describe the important mechanisms involved in infectious diseases. An iterative approach to model development allows new discoveries to continually improve the model, and ultimately increase the accuracy of predictions. SIR models are used to describe epi demics, predicting the extent and spread of disease. Genome-wide genotyping and sequencing technologies can be used to identify the biological mechanisms behind diseases. These tools help to build strategies for disease prevention and treatment, an example being the recent outbreak of Ebola in West Africa where these techniques were deployed. HIV is a complex disease where much is still to be learnt about the virus and the best effective treatment. With basic mathematical modelling techniques, significant discoveries have been made over the last 20 years. With recent technological advances, the computation al resources now available and interdisciplinary cooperation, further breakthroughs are inevitable. In TB, modelling has traditionally been empirical in nature, with clinical data providing the fuel for this top-down approach. Recently, projects have begun to use data derived from laboratory experiments and clinical trials to create mathematical models that describe the mechanisms responsible for the disease. A systems medicine approach to infection modelling helps identify important biological questions that then direct future experiments , the results of which improve the model in an iterative cycle . This means that data from several model systems can be integrated and synthesised to explore complex biological systems .Postprin