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BACKGROUND: The Ethiopian Government has identified efficiency of TB services as a key priority in planning and budgeting. Understanding the magnitude and sources of inefficiencies is key to ensuring value for money and improved service provision, and a requirement from donors to justify resource needs. This study identifies the cost of providing a wide range of TB services in public and private facilities in Ethiopia.METHODS: Financial and economic unit costs were estimated from a health provider´s perspective, and collected retrospectively in 26 health facilities using both top-down (TD) and bottom-up (BU) costing approaches for each TB service output. Capacity inefficiency was assessed by investigating the variation between TD and BU unit costs where the factor was 2.0 or more.RESULTS: Overall, TD unit costs were two times higher than BU unit costs. There was some variation across facility ownership and level of care. Unit costs in urban facilities were on average 3.8 times higher than in rural facilities.CONCLUSION: We identified some substantial inefficiencies in staff, consumable and capital inputs. Addressing these inefficiencies and rearranging the TB service delivery modality would be important in ensuring the achievement of the country´s End TB strategy.

BACKGROUND: There is a dearth of economic analysis required to support increased investment in TB in India. This study estimates the costs of TB services from a health systems’ perspective to facilitate the efficient allocation of resources by India’s National Tuberculosis Elimination Programme. METHODS: Data were collected from a multi-stage, stratified random sample of 20 facilities delivering TB services in two purposively selected states in India as per Global Health Cost Consortium standards and using Value TB Data Collection Tool. Unit costs were estimated using the top-down (TD) and bottom-up (BU) methodology and are reported in 2018 US dollars. RESULTS: Cost of delivering 50 types of TB services and four interventions varied according to costing method. Key services included sputum smear microscopy, Xpert® MTB/RIF and X-ray with an average BU costs of respectively US$2.45, US$17.36 and US$2.85. Average BU cost for bacille Calmette-Guérin vaccination, passive case-finding, TB prevention in children under 5 years using isoniazid and first-line drug treatment in new pulmonary and extrapulmonary TB cases was respectively US$0.76, US$1.62, US$2.41, US$103 and US$98. CONCLUSION: The unit cost of TB services and outputs are now available to support investment decisions, as diagnosis algorithms are reviewed and prevention or treatment for TB are expanded or updated in India.

BACKGROUND: The reduction of Kenya´s TB burden requires improving resource allocation both to and within the National TB, Leprosy and Lung Disease Program (NTLD-P). We aimed to estimate the unit costs of TB services for budgeting by NTLD-P, and allocative efficiency analyses for future National Strategic Plan (NSP) costing.METHODS: We estimated costs of all TB interventions in a sample of 20 public and private health facilities from eight counties. We calculated national-level unit costs from a health provider´s perspective using bottom-up (BU) and top-down (TD) approaches for the financial year 2017–2018 using Microsoft Excel and STATA v16.RESULTS: The mean unit cost for passive case-finding (PCF) was respectively US$38 and US$60 using the BU and TD approaches. The unit BU and TD costs of a 6-month first-line treatment (FLT) course, including monitoring tests, was respectively US$135 and US$160, while those for adult drug-resistant TB (DR-TB) treatment was respectively US$3,230.28 and US$3,926.52 for the 9-month short regimen. Intervention costs highlighted variations between BU and TD approaches. Overall, TD costs were higher than BU, as these are able to capture more costs due to inefficiency (breaks/downtime/leave).CONCLUSION: The activity-based TB unit costs form a comprehensive cost database, and the costing process has built-in capacity within the NTLD-P and international TB research networks, which will inform future TB budgeting processes.

BACKGROUND: Patient-centred care along with optimal financing of inpatient and outpatient services are the main priorities of the Georgia National TB Programme (NTP). This paper presents TB diagnostics and treatment unit cost, their comparison with NTP tariffs and how the study findings informed TB financing policy.METHODS: Top-down (TD) and bottom-up (BU) mean unit costs for TB interventions by episode of care were calculated. TD costs were compared with NTP tariffs, and variations in these and the unit costs cost composition between public and private facilities was assessed.RESULTS: Outpatient interventions costs exceeded NTP tariffs. Unit costs in private facilities were higher compared with public providers. There was very little difference between per-day costs for drug-susceptible treatment and NTP tariffs in case of inpatient services. Treatment day financing exceeded actual costs in the capital (public facility) for drug-resistant TB, and this was lower in the regions.CONCLUSION: Use of reliable unit costs for TB services at policy discussions led to a shift from per-day payment to a diagnosis-related group model in TB inpatient financing in 2020. A next step will be informing policy decisions on outpatient TB care financing to reduce the existing gap between funding and costs.

BACKGROUND: There is a dearth of economic analysis required to support increased investment in TB in India. This study estimates the costs of TB services from a health systems´ perspective to facilitate the efficient allocation of resources by India´s National Tuberculosis Elimination Programme.METHODS: Data were collected from a multi-stage, stratified random sample of 20 facilities delivering TB services in two purposively selected states in India as per Global Health Cost Consortium standards and using Value TB Data Collection Tool. Unit costs were estimated using the top-down (TD) and bottom-up (BU) methodology and are reported in 2018 US dollars.RESULTS: Cost of delivering 50 types of TB services and four interventions varied according to costing method. Key services included sputum smear microscopy, Xpert® MTB/RIF and X-ray with an average BU costs of respectively US$2.45, US$17.36 and US$2.85. Average BU cost for bacille Calmette-Guérin vaccination, passive case-finding, TB prevention in children under 5 years using isoniazid and first-line drug treatment in new pulmonary and extrapulmonary TB cases was respectively US$0.76, US$1.62, US$2.41, US$103 and US$98.CONCLUSION: The unit cost of TB services and outputs are now available to support investment decisions, as diagnosis algorithms are reviewed and prevention or treatment for TB are expanded or updated in India.

Drug-resistant tuberculosis (DR-TB) is challenging to diagnose, treat, and prevent, but this situation is slowly changing. If the world is to drastically reduce the incidence of DR-TB, we must stop creating new DR-TB as an essential first step. The DR-TB epidemic that is ongoing should also be directly addressed. First-line drug resistance must be rapidly detected using universal molecular testing for resistance to at least rifampin and, preferably, other key drugs at initial TB diagnosis. DR-TB treatment outcomes must also improve dramatically. Effective use of currently available, new, and repurposed drugs, combined with patient-centered treatment that aids adherence and reduces catastrophic costs, are essential. Innovations within sight, such as short, highly effective, broadly indicated regimens, paired with point-of-care drug susceptibility testing, could accelerate progress in treatment outcomes. Preventing or containing resistance to second-line and novel drugs is also critical and will require high-quality systems for diagnosis, regimen selection, and treatment monitoring. Finally, earlier detection and/or prevention of DR-TB is necessary, with particular attention to airborne infection control, case finding, and preventive therapy for contacts of patients with DR-TB. Implementing these strategies can overcome the barrier that DR-TB represents for global TB elimination efforts, and could ultimately make global elimination of DR-TB (fewer than one annual case per million population worldwide) attainable. There is a strong cost-effectiveness case to support pursuing DR-TB elimination; however, achieving this goal will require substantial global investment plus political and societal commitment at national and local levels.

Early in the COVID-19 pandemic, models predicted hundreds of thousands of additional TB deaths as a result of health service disruption. To date, empirical evidence on the effects of COVID-19 on TB outcomes has been limited. Here we summarise the evidence available at a country level, identifying broad mechanisms by which COVID-19 may modify TB burden and mitigation efforts. From the data, it is clear that there have been substantial disruptions to TB health services and an increase in vulnerability to TB. Evidence for changes in Mycobacterium tuberculosis transmission is limited, and it remains unclear how the resources required and available for the TB response have changed. To advocate for additional funding to mitigate the impact of COVID-19 on the global TB burden, and to efficiently allocate resources for the TB response, requires a significant improvement in the TB data available.

BACKGROUND: Despite a scarcity of tuberculosis (TB) cost data, a substantial body of evidence has been accumulating for drug-susceptible TB (DS-TB) treatment. In this study, we review unit costs for DS-TB treatment from a provider´s perspective. We also examine factors driving cost variations and extrapolate unit costs across low- and middle-income countries (LMICs).METHODS: We searched published and grey literature for any empirically collected TB cost estimates. We selected a subgroup of estimates looking at DS-TB treatment. We extracted information on activities and inputs included. We standardised costs into an average per person-month, fitted a multi-level regression model and cross-validated country-level predictions. We then extrapolated estimates for facility-based, directly observed DS-TB treatment across countries.RESULTS: We included 95 cost estimates from 28 studies across 17 countries. Costs predictions were sensitive to characteristics such as delivery mode, whether hospitalisation was included, and inputs accounted for, as well as gross domestic product per capita. Extrapolation results are presented with uncertainty intervals (UIs) for LMICs. Predicted median costs per 6 months of treatment were US$315.30 (95% CI US$222.60–US$417.20) for low-income, US$527.10 (95% CI US$395.70–US$743.70) for lower middle-income and US$896.40 (95% CI US$654.00–US$1214.40) for upper middle-income countries.CONCLUSIONS: Our study provides country-level DS-TB treatment cost estimates suitable for priority setting. These estimates, while not standing as a substitute for local high-quality primary data, can inform global, regional and national exercises.

Setting Initial cost-effectiveness evaluations of Xpert(®) MTB/RIF for tuberculosis (TB) diagnosis have not fully accounted for the realities of implementation in peripheral settings. Objective To evaluate costs and diagnostic outcomes of Xpert testing implemented at various health care levels in Uganda. Design We collected empirical cost data from five health centers utilizing Xpert for TB diagnosis, using an ingredients approach. We reviewed laboratory and patient records to assess outcomes at these sites and10 sites without Xpert. We also estimated incremental cost-effectiveness of Xpert testing; our primary outcome was the incremental cost of Xpert testing per newly detected TB case. Results The mean unit cost of an Xpert test was US$21 based on a mean monthly volume of 54 tests per site, although unit cost varied widely (US$16-58) and was primarily determined by testing volume. Total diagnostic costs were 2.4-fold higher in Xpert clinics than in non-Xpert clinics; however, Xpert only increased diagnoses by 12%. The diagnostic costs of Xpert averaged US$119 per newly detected TB case, but were as high as US$885 at the center with the lowest volume of tests. Conclusion Xpert testing can detect TB cases at reasonable cost, but may double diagnostic budgets for relatively small gains, with cost-effectiveness deteriorating with lower testing volumes.

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.

The cost of multidrug-resistant tuberculosis (MDR-TB) treatment is a major barrier to treatment scale-up in South Africa. To estimate and compare the cost of treatment for rifampicin-resistant tuberculosis (RR-TB) in South Africa in different models of care in different settings. We estimated the costs of different models of care with varying levels of hospitalisation. These costs were used to calculate the total cost of treating all diagnosed cases of RR-TB in South Africa, and to estimate the budget impact of adopting a fully or partially decentralised model vs. a fully hospitalised model. The fully hospitalised model was 42% more costly than the fully decentralised model (US$13 432 vs. US$7753 per patient). A much shorter hospital stay in the decentralised models of care (44-57 days), compared to 128 days of hospitalisation in the fully hospitalised model, was the key contributor to the reduced cost of treatment. The annual total cost of treating all diagnosed cases ranged from US$110 million in the fully decentralised model to US$190 million in the fully hospitalised model. Following a more decentralised approach for treating RR-TB patients could potentially improve the affordability of RR-TB treatment in South Africa.

SETTING: Of 18 sites that participated in an implementation study of the Xpert® MTB/RIF assay in India, we selected five microscopy centres and two reference laboratories. OBJECTIVE: To obtain unit costs of diagnostic tests for tuberculosis (TB) and drug-resistant TB. DESIGN: Laboratories were purposely selected to capture regional variations and different laboratory types. Both bottom-up and the top-down methods were used to estimate unit costs. RESULTS: At the microscopy centres, mean bottom-up unit costs were respectively US$0.83 (range US$0.60-US$1.10) and US$12.29 (US$11.61-US$12.89) for sputum smear microscopy and Xpert. At the reference laboratories, mean unit costs were US$1.69 for the decontamination procedure, US$9.83 for a solid culture, US$11.06 for a liquid culture, US$29.88 for a drug susceptibility test, and US$18.18 for a line-probe assay. Top-down mean unit cost estimates were higher for all tests, and for sputum smear microscopy and Xpert these increased to respectively US$1.51 and US$13.58. The difference between bottom-up and top-down estimates was greatest for tests performed at the reference laboratories. CONCLUSION: These unit costs for TB diagnostics can be used to estimate resource requirements and cost-effectiveness in India, taking into account geographical location, laboratory type and capacity utilisation.

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.

SETTING: Initial cost-effectiveness evaluations of Xpert(®) MTB/RIF for tuberculosis (TB) diagnosis have not fully accounted for the realities of implementation in peripheral settings. OBJECTIVE: To evaluate costs and diagnostic outcomes of Xpert testing implemented at various health care levels in Uganda. DESIGN: We collected empirical cost data from five health centers utilizing Xpert for TB diagnosis, using an ingredients approach. We reviewed laboratory and patient records to assess outcomes at these sites and10 sites without Xpert. We also estimated incremental cost-effectiveness of Xpert testing; our primary outcome was the incremental cost of Xpert testing per newly detected TB case. RESULTS: The mean unit cost of an Xpert test was US$21 based on a mean monthly volume of 54 tests per site, although unit cost varied widely (US$16-58) and was primarily determined by testing volume. Total diagnostic costs were 2.4-fold higher in Xpert clinics than in non-Xpert clinics; however, Xpert only increased diagnoses by 12%. The diagnostic costs of Xpert averaged US$119 per newly detected TB case, but were as high as US$885 at the center with the lowest volume of tests. CONCLUSION: Xpert testing can detect TB cases at reasonable cost, but may double diagnostic budgets for relatively small gains, with cost-effectiveness deteriorating with lower testing volumes.

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.

INTRODUCTION: The World Health Organization recommends point-of-care (POC) lateral flow urine lipoarabinomannan (LF-LAM) for tuberculosis (TB) diagnosis in selected human immunodeficiency virus (HIV) positive people. South Africa had 438 000 new TB episodes in 2016, 58.9% of which were contributed by HIV-positive people. LF-LAM is being considered for scale-up in South Africa. METHODS: We estimated the costs of using LF-LAM in HIV-positive adults with CD4 counts 150 cells/μl enrolled in the TB Fast Track Trial in South Africa. We also estimated costs of POC haemoglobin (Hb), as this was used in the study algorithm. Data on clinic-level (10 intervention clinics) and above-clinic-level costs were collected. RESULTS: A total of 1307 LF-LAM tests were performed at 10 clinics over 24 months. The mean clinic-level costs were US$12.80 per patient for LF-LAM and POC Hb; LF-LAM costs were US$11.49 per patient. The mean above-clinic-level unit costs for LF-LAM were US$12.06 for clinic preparation, training, coordination and mentoring. The mean total cost of LF-LAM was US$23.55 per patient. CONCLUSION: At clinic level, the cost of LF-LAM was comparable to other TB diagnostics in South Africa. It is important to consider above-clinic-level costs for POC tests, as these may be required to support roll-out and ensure successful implementation.