Considering equity in priority setting using transmission models: Recommendations and data needs.

OBJECTIVES: Disease transmission models are used in impact assessment and economic evaluations of infectious disease prevention and treatment strategies, prominently so in the COVID-19 response. These models rarely consider dimensions of equity relating to the differential health burden between individuals and groups. We describe concepts and approaches which are useful when considering equity in the priority setting process, and outline the technical choices concerning model structure, outputs, and data requirements needed to use transmission models in analyses of health equity. METHODS: We reviewed the literature on equity concepts and approaches to their application in economic evaluation and undertook a technical consultation on how equity can be incorporated in priority setting for infectious disease control. The technical consultation brought together health economists with an interest in equity-informative economic evaluation, ethicists specialising in public health, mathematical modellers from various disease backgrounds, and representatives of global health funding and technical assistance organisations, to formulate key areas of consensus and recommendations. RESULTS: We provide a series of recommendations for applying the Reference Case for Economic Evaluation in Global Health to infectious disease interventions, comprising guidance on 1) the specification of equity concepts; 2) choice of evaluation framework; 3) model structure; and 4) data needs. We present available conceptual and analytical choices, for example how correlation between different equity- and disease-relevant strata should be considered dependent on available data, and outline how assumptions and data limitations can be reported transparently by noting key factors for consideration. CONCLUSIONS: Current developments in economic evaluations in global health provide a wide range of methodologies to incorporate equity into economic evaluations. Those employing infectious disease models need to use these frameworks more in priority setting to accurately represent health inequities. We provide guidance on the technical approaches to support this goal and ultimately, to achieve more equitable health policies.

Efficiency of TB service provision in the public and private health sectors in Ethiopia.

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.

Cost of TB services: approach and summary findings of a multi-country study (Value TB).

BACKGROUND: There are currently large gaps in unit cost data for TB, and substantial variation in the quality and methods of unit cost estimates. Uncertainties remain about sample size, range and comprehensiveness of cost data collection for different purposes. We present the methods and results of a project implemented in Kenya, Ethiopia, India, The Philippines and Georgia to estimate unit costs of TB services, focusing on findings most relevant to these remaining methodological challenges.METHODS: We estimated financial and economic unit costs, in close collaboration with national TB programmes. Gold standard methods included both top-down and bottom-up approaches to resource use measurement. Costs are presented in 2018 USD and local currency unit.RESULTS: Cost drivers of outputs varied by service and across countries, as did levels of capacity inefficiency. There was substantial variation in unit cost estimates for some interventions and high overhead costs were observed. Estimates were subject to sampling uncertainty, and some data gaps remain.CONCLUSION: This paper describes detailed methods for the largest TB costing effort to date, to inform prioritisation and planning for TB services. This study provides a strong baseline and some cost estimates may be extrapolated from this data; however, regular further studies of similar quality are needed to add estimates for remaining gaps, or to add new or changing services and interventions. Further research is needed on the best approach to extrapolation of cost data. Costing studies are best implemented as partnerships with policy makers to generate a community of mutual learning and capacity development.

Cost of TB prevention and treatment in the Philippines in 2017.

BACKGROUND: The Philippines aims to accelerate TB reduction through the provision of universally accessible and affordable services. The objectives of this paper are to estimate the costs of TB services and interventions using a health systems´ perspective, and to explore cost differences in service delivery via primary care facilities or hospitals.METHODS: Data were collected from a multi-stage stratified random sampling of 28 facilities in accordance with Global Health Cost Consortium costing standards and analysis tools. Unit costs (in US$) estimated using top-down (TD) and bottom-up (BU) approaches, are summarised following Value TB reporting standards and by broad facility type.RESULTS: Cost of delivering 32 TB services and eight interventions varied by costing method and delivery platform. Average BU costs ranged from US$0.38 for treatment support visits, US$2.5 for BCG vaccination, US$19.48 for the Xpert® MTB/RIF test to US$3,677 for MDR-TB treatment using the long regimen. Delivering TB care in hospitals was generally more costly than in primary care facilities, except for TB prevention in children and MDR-TB treatment using the long regimen.CONCLUSION: Comprehensive costing data for TB care in the Philippines are now available to aid in the design, planning, and prioritisation of delivery models to End TB.

Costs of TB services in India (No 1).

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.

Cost of TB services in the public and private sectors in Georgia (No 2).

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.

Cost of TB services in healthcare facilities in Kenya (No 3).

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.

The impact of COVID-19 on TB: a review of the data.

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.

Cost of tuberculosis treatment in low- and middle-income countries: systematic review and meta-regression.

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.

What will it take to eliminate drug-resistant tuberculosis?

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.

How can we evaluate the cost-effectiveness of health system strengthening? A typology and illustrations.

Health interventions often depend on a complex system of human and capital infrastructure that is shared with other interventions, in the form of service delivery platforms, such as healthcare facilities, hospitals, or community services. Most forms of health system strengthening seek to improve the efficiency or effectiveness of such delivery platforms. This paper presents a typology of ways in which health system strengthening can improve the economic efficiency of health services. Three types of health system strengthening are identified and modelled: (1) investment in the efficiency of an existing shared platform that generates positive benefits across a range of existing interventions; (2) relaxing a capacity constraint of an existing shared platform that inhibits the optimization of existing interventions; (3) providing an entirely new shared platform that supports a number of existing or new interventions. Theoretical models are illustrated with examples, and illustrate the importance of considering the portfolio of interventions using a platform, and not just piecemeal individual analysis of those interventions. They show how it is possible to extend principles of conventional cost-effectiveness analysis to identify an optimal balance between investing in health system strengthening and expenditure on specific interventions. The models developed in this paper provide a conceptual framework for evaluating the cost-effectiveness of investments in strengthening healthcare systems and, more broadly, shed light on the role that platforms play in promoting the cost-effectiveness of different interventions.

Cost of point-of-care lateral flow urine lipoarabinomannan antigen testing in HIV-positive adults in South Africa.

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.

An intervention to optimise the delivery of integrated tuberculosis and HIV services at primary care clinics: results of the MERGE cluster randomised trial.

OBJECTIVES: To evaluate the effect of an intervention to optimize TB/HIV integration on patient outcomes. METHODS: Cluster randomised control trial at 18 primary care clinics in South Africa. The intervention was placement of a nurse (TB/HIV integration officer) to facilitate provision of integrated TB/HIV services, and a lay health worker (TB screening officer) to facilitate TB screening for 24 months. Primary outcomes were i) incidence of hospitalisation/death among individuals newly diagnosed with HIV, ii) incidence of hospitalisation/death among individuals newly diagnosed with TB and iii) proportion of HIV-positive individuals newly diagnosed with TB who were retained in HIV care 12 months after enrolment. RESULTS: Of 3328 individuals enrolled, 3024 were in the HIV cohort, 731 in TB cohort and 427 in TB-HIV cohort. For the HIV cohort, the hospitalisation/death rate was 12.5 per 100 person-years (py) (182/1459py) in the intervention arm vs. 10.4/100py (147/1408 py) in the control arms respectively (Relative Risk (RR) 1.17 [95% CI 0.92-1.49]).For the TB cohort, hospitalisation/ death rate was 17.1/100 py (67/ 392py) vs. 11.1 /100py (32/289py) in intervention and control arms respectively (RR 1.37 [95% CI 0.78-2.43]). For the TB-HIV cohort, retention in care at 12 months was 63.0% (213/338) and 55.9% (143/256) in intervention and control arms (RR 1.11 [95% 0.89-1.38]). CONCLUSIONS: The intervention as implemented failed to improve patient outcomes beyond levels at control clinics. Effective strategies are needed to achieve better TB/HIV service integration and improve TB and HIV outcomes in primary care clinics. TRIAL REGISTRATION: South African Register of Clinical Trials (registration number DOH-27-1011-3846).

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.

Bottom-up or top-down: unit cost estimation of tuberculosis diagnostic tests in India.

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.

Cost and cost-effectiveness of tuberculosis treatment shortening: a model-based analysis.

BACKGROUND: Despite improvements in treatment success rates for tuberculosis (TB), current six-month regimen duration remains a challenge for many National TB Programmes, health systems, and patients. There is increasing investment in the development of shortened regimens with a number of candidates in phase 3 trials. METHODS: We developed an individual-based decision analytic model to assess the cost-effectiveness of a hypothetical four-month regimen for first-line treatment of TB, assuming non-inferiority to current regimens of six-month duration. The model was populated using extensive, empirically-collected data to estimate the economic impact on both health systems and patients of regimen shortening for first-line TB treatment in South Africa, Brazil, Bangladesh, and Tanzania. We explicitly considered 'real world' constraints such as sub-optimal guideline adherence. RESULTS: From a societal perspective, a shortened regimen, priced at USD1 per day, could be a cost-saving option in South Africa, Brazil, and Tanzania, but would not be cost-effective in Bangladesh when compared to one gross domestic product (GDP) per capita. Incorporating 'real world' constraints reduces cost-effectiveness. Patient-incurred costs could be reduced in all settings. From a health service perspective, increased drug costs need to be balanced against decreased delivery costs. The new regimen would remain a cost-effective option, when compared to each countries' GDP per capita, even if new drugs cost up to USD7.5 and USD53.8 per day in South Africa and Brazil; this threshold was above USD1 in Tanzania and under USD1 in Bangladesh. CONCLUSION: Reducing the duration of first-line TB treatment has the potential for substantial economic gains from a patient perspective. The potential economic gains for health services may also be important, but will be context-specific and dependent on the appropriate pricing of any new regimen.

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

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

A simplified cost-effectiveness model to guide decision-making for shortened anti-tuberculosis treatment regimens.

User-friendly models (UFMs) allow local decision makers to explore relationships and apply results from more detailed models of such outcomes as cost-effectiveness. When developing UFMs, modelers must decide which simplifications may be appropriate, enabling the UFM to retain accuracy while reducing complexity. We use the example of cost-effectiveness analysis (CEA) for novel shortened anti-tuberculosis treatment regimens across four settings to demonstrate how UFMs can allow decision makers to adapt published results to their local context. We simplified a complex model to produce a UFM that provides similar results, the ability to modify key parameter values, and receive customized results in seconds.