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Satyanarayana S, Pretorius C, Kanchar A, Garcia Baena I, Den Boon S, Miller C, Zignol M, Kasaeva T, Falzon D. Scaling Up TB Screening and TB Preventive Treatment Globally: Key Actions and Healthcare Service Costs. Trop Med Infect Dis 2023; 8:214. [PMID: 37104339 PMCID: PMC10144108 DOI: 10.3390/tropicalmed8040214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/17/2023] [Accepted: 03/27/2023] [Indexed: 04/05/2023] Open
Abstract
The 2018 United Nations High-Level Meeting on Tuberculosis (UNHLM) set targets for case detection and TB preventive treatment (TPT) by 2022. However, by the start of 2022, about 13.7 million TB patients still needed to be detected and treated, and 21.8 million household contacts needed to be given TPT globally. To inform future target setting, we examined how the 2018 UNHLM targets could have been achieved using WHO-recommended interventions for TB detection and TPT in 33 high-TB burden countries in the final year of the period covered by the UNHLM targets. We used OneHealth-TIME model outputs combined with the unit cost of interventions to derive the total costs of health services. Our model estimated that, in order to achieve UNHLM targets, >45 million people attending health facilities with symptoms would have needed to be evaluated for TB. An additional 23.1 million people with HIV, 19.4 million household TB contacts, and 303 million individuals from high-risk groups would have required systematic screening for TB. The estimated total costs amounted to ~USD 6.7 billion, of which ~15% was required for passive case finding, ~10% for screening people with HIV, ~4% for screening household contacts, ~65% for screening other risk groups, and ~6% for providing TPT to household contacts. Significant mobilization of additional domestic and international investments in TB healthcare services will be needed to reach such targets in the future.
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Affiliation(s)
- Srinath Satyanarayana
- Centre for Operational Research, International Union against Tuberculosis and Lung Disease (The Union), New Delhi 110016, India
| | - Carel Pretorius
- Centre for Modelling and Analysis, Avenir Health, Glastonbury, CT 06033, USA
| | - Avinash Kanchar
- Global TB Programme (GTB), World Health Organization, 1211 Geneva, Switzerland
| | - Ines Garcia Baena
- Global TB Programme (GTB), World Health Organization, 1211 Geneva, Switzerland
| | - Saskia Den Boon
- Global TB Programme (GTB), World Health Organization, 1211 Geneva, Switzerland
| | - Cecily Miller
- Global TB Programme (GTB), World Health Organization, 1211 Geneva, Switzerland
| | - Matteo Zignol
- Global TB Programme (GTB), World Health Organization, 1211 Geneva, Switzerland
| | - Tereza Kasaeva
- Global TB Programme (GTB), World Health Organization, 1211 Geneva, Switzerland
| | - Dennis Falzon
- Global TB Programme (GTB), World Health Organization, 1211 Geneva, Switzerland
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Abou Jaoude GJ, Garcia Baena I, Nguhiu P, Siroka A, Palmer T, Goscé L, Allel K, Sinanovic E, Skordis J, Haghparast-Bidgoli H. National tuberculosis spending efficiency and its associated factors in 121 low-income and middle-income countries, 2010–19: a data envelopment and stochastic frontier analysis. The Lancet Global Health 2022; 10:e649-e660. [PMID: 35427522 PMCID: PMC9023749 DOI: 10.1016/s2214-109x(22)00085-7] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 01/25/2022] [Accepted: 02/21/2022] [Indexed: 12/12/2022] Open
Abstract
Background Maximising the efficiency of national tuberculosis programmes is key to improving service coverage, outcomes, and progress towards End TB targets. We aimed to determine the overall efficiency of tuberculosis spending and investigate associated factors in 121 low-income and middle-income countries between 2010 and 2019. Methods In this data envelopment and stochastic frontier analysis, we used data from the WHO Global TB report series on tuberculosis spending as the input and treatment coverage as the output to estimate tuberculosis spending efficiency. We investigated associations between 25 independent variables and overall efficiency. Findings We estimated global tuberculosis spending efficiency to be between 73·8% (95% CI 71·2–76·3) and 87·7% (84·9–90·6) in 2019, depending on the analytical method used. This estimate suggests that existing global tuberculosis treatment coverage could be increased by between 12·3% (95% CI 9·4–15·1) and 26·2% (23·7–28·8) for the same amount of spending. Efficiency has improved over the study period, mainly since 2015, but a substantial difference of 70·7–72·1 percentage points between the most and least efficient countries still exists. We found a consistent significant association between efficiency and current health expenditure as a share of gross domestic product, out-of-pocket spending on health, and some Sustainable Development Goal (SDG) indicators such as universal health coverage. Interpretation To improve efficiency, treatment coverage will need to be increased, particularly in the least efficient contexts where this might require additional spending. However, progress towards global End TB targets is slow even in the most efficient countries. Variables associated with TB spending efficiency suggest efficiency is complimented by commitments to improving health-care access that is free at the point of use and wider progress towards the SDGs. These findings support calls for additional investment in tuberculosis care. Funding None.
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Affiliation(s)
| | | | - Peter Nguhiu
- Kenya Medical Research Institute (KEMRI) Wellcome Trust, Nairobi, Kenya
| | | | - Tom Palmer
- Institute for Global Health, University College London, London, UK
| | - Lara Goscé
- Institute for Global Health, University College London, London, UK
| | - Kasim Allel
- Institute for Global Health, University College London, London, UK; Department of Disease Control, Faculty of Infectious & Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Edina Sinanovic
- Health Economics Unit, School of Public Health & Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Jolene Skordis
- Institute for Global Health, University College London, London, UK
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Muttamba W, Tumwebaze R, Mugenyi L, Batte C, Sekibira R, Nkolo A, Katamba A, Kasasa S, Majwala RK, Turyahabwe S, Mugabe F, Mugagga K, Lochoro P, Dejene S, Birabwa E, Marra C, Baena IG, Kirenga B. Households experiencing catastrophic costs due to tuberculosis in Uganda: magnitude and cost drivers. BMC Public Health 2020; 20:1409. [PMID: 32938411 PMCID: PMC7493412 DOI: 10.1186/s12889-020-09524-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Accepted: 09/09/2020] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Tuberculosis (TB) patients in Uganda incur large costs related to the illness, and while seeking and receiving health care. Such costs create access and adherence barriers which affect health outcomes and increase transmission of disease. The study ascertained the proportion of Ugandan TB affected households incurring catastrophic costs and the main cost drivers. METHODS A cross-sectional survey with retrospective data collection and projections was conducted in 2017. A total of 1178 drug resistant (DR) TB (44) and drug sensitive (DS) TB patients (1134), 2 weeks into intensive or continuation phase of treatment were consecutively enrolled across 67 randomly selected TB treatment facilities. RESULTS Of the 1178 respondents, 62.7% were male, 44.7% were aged 15-34 years and 55.5% were HIV positive. For each TB episode, patients on average incurred costs of USD 396 for a DS-TB episode and USD 3722 for a Multi drug resistant tuberculosis (MDR TB) episode. Up to 48.5% of households borrowed, used savings or sold assets to defray these costs. More than half (53.1%) of TB affected households experienced TB-related costs above 20% of their annual household expenditure, with the main cost drivers being non-medical expenditure such as travel, nutritional supplements and food. CONCLUSION Despite free health care in public health facilities, over half of Ugandan TB affected households experience catastrophic costs. Roll out of social protection interventions like TB assistance programs, insurance schemes, and enforcement of legislation related to social protection through multi-sectoral action plans with central NTP involvement would palliate these costs.
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Affiliation(s)
- Winters Muttamba
- Makerere University Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda.
| | - Racheal Tumwebaze
- Makerere University Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Levicatus Mugenyi
- Makerere University Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Charles Batte
- Makerere University Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Rogers Sekibira
- Makerere University Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Abel Nkolo
- University Research Co, LLC (URC) & Center for Human Services (CHS), Kampala, Uganda
| | - Achilles Katamba
- School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Simon Kasasa
- School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda
| | - Robert Kaos Majwala
- University Research Co, LLC (URC) & Center for Human Services (CHS), Kampala, Uganda
- National Tuberculosis and Leprosy Program, Ministry of Health, Kampala, Uganda
| | - Stavia Turyahabwe
- National Tuberculosis and Leprosy Program, Ministry of Health, Kampala, Uganda
| | - Frank Mugabe
- National Tuberculosis and Leprosy Program, Ministry of Health, Kampala, Uganda
| | | | | | | | | | - Claudio Marra
- National Tuberculosis and Leprosy Program, Ministry of Health, Kampala, Uganda
| | | | - Bruce Kirenga
- Makerere University Lung Institute, College of Health Sciences, Makerere University, Kampala, Uganda
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Su Y, Garcia Baena I, Harle AC, Crosby SW, Micah AE, Siroka A, Sahu M, Tsakalos G, Murray CJL, Floyd K, Dieleman JL. Tracking total spending on tuberculosis by source and function in 135 low-income and middle-income countries, 2000-17: a financial modelling study. Lancet Infect Dis 2020; 20:929-942. [PMID: 32334658 PMCID: PMC7649746 DOI: 10.1016/s1473-3099(20)30124-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 01/31/2020] [Accepted: 02/14/2020] [Indexed: 12/17/2022]
Abstract
BACKGROUND Estimates of government spending and development assistance for tuberculosis exist, but less is known about out-of-pocket and prepaid private spending. We aimed to provide comprehensive estimates of total spending on tuberculosis in low-income and middle-income countries for 2000-17. METHODS We extracted data on tuberculosis spending, unit costs, and health-care use from the WHO global tuberculosis database, Global Fund proposals and reports, National Health Accounts, the WHO-Choosing Interventions that are Cost-Effective project database, and the Institute for Health Metrics and Evaluation Development Assistance for Health Database. We extracted data from at least one of these sources for all 135 low-income and middle-income countries using the World Bank 2019 definitions. We estimated tuberculosis spending by source and function for notified (officially reported) and non-notified tuberculosis cases separately and combined, using spatiotemporal Gaussian process regression to fill in for missing data and estimate uncertainty. We aggregated estimates of government, out-of-pocket, prepaid private, and development assistance spending on tuberculosis to estimate total spending in 2019 US$. FINDINGS Total spending on tuberculosis in 135 low-income and middle-income countries increased annually by 3·9% (95% CI 3·0 to 4·6), from $5·7 billion (5·2 to 6·5) in 2000 to $10·9 billion (10·3 to 11·8) in 2017. Government spending increased annually by 5·1% (4·4 to 5·7) between 2000 and 2017, and reached $6·9 billion (6·5 to 7·5) or 63·5% (59·2 to 66·8) of all tuberculosis spending in 2017. Of government spending, $5·8 billion (5·6 to 6·1) was spent on notified cases. Out-of-pocket spending decreased annually by 0·8% (-2·9 to 1·3), from $2·4 billion (1·9 to 3·1) in 2000 to $2·1 billion (1·6 to 2·7) in 2017. Development assistance for country-specific spending on tuberculosis increased from $54·6 million in 2000 to $1·1 billion in 2017. Administrative costs and development assistance for global projects related to tuberculosis care increased from $85·3 million in 2000 to $576·2 million in 2017. 30 high tuberculosis burden countries of low and middle income accounted for 73·7% (71·8-75·8) of tuberculosis spending in 2017. INTERPRETATION Despite substantial increases since 2000, funding for tuberculosis is still far short of global financing targets and out-of-pocket spending remains high in resource-constrained countries, posing a barrier to patient's access to care and treatment adherence. Of the 30 countries with a high-burden of tuberculosis, just over half were primarily funded by government, while others, especially lower-middle-income and low-income countries, were still primarily dependent on development assistance for tuberculosis or out-of-pocket health spending. FUNDING Bill & Melinda Gates Foundation.
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Affiliation(s)
- Yanfang Su
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | | | - Anton C Harle
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | - Sawyer W Crosby
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | - Angela E Micah
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | | | - Maitreyi Sahu
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | - Golsum Tsakalos
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
| | | | - Katherine Floyd
- Institute for Health Metrics and Evaluation, Seattle, WA, USA
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Menzies NA, Gomez GB, Bozzani F, Chatterjee S, Foster N, Baena IG, Laurence YV, Qiang S, Siroka A, Sweeney S, Verguet S, Arinaminpathy N, Azman AS, Bendavid E, Chang ST, Cohen T, Denholm JT, Dowdy DW, Eckhoff PA, Goldhaber-Fiebert JD, Handel A, Huynh GH, Lalli M, Lin HH, Mandal S, McBryde ES, Pandey S, Salomon JA, Suen SC, Sumner T, Trauer JM, Wagner BG, Whalen CC, Wu CY, Boccia D, Chadha VK, Charalambous S, Chin DP, Churchyard G, Daniels C, Dewan P, Ditiu L, Eaton JW, Grant AD, Hippner P, Hosseini M, Mametja D, Pretorius C, Pillay Y, Rade K, Sahu S, Wang L, Houben RMGJ, Kimerling ME, White RG, Vassall A. Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models. Lancet Glob Health 2016; 4:e816-e826. [PMID: 27720689 PMCID: PMC5527122 DOI: 10.1016/s2214-109x(16)30265-0] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Revised: 08/05/2016] [Accepted: 08/26/2016] [Indexed: 12/25/2022]
Abstract
BACKGROUND The post-2015 End TB Strategy sets global targets of reducing tuberculosis incidence by 50% and mortality by 75% by 2025. We aimed to assess resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa. METHODS We examined intervention scenarios developed in consultation with country stakeholders, which scaled up existing interventions to high but feasible coverage by 2025. Nine independent modelling groups collaborated to estimate policy outcomes, and we estimated the cost of each scenario by synthesising service use estimates, empirical cost data, and expert opinion on implementation strategies. We estimated health effects (ie, disability-adjusted life-years averted) and resource implications for 2016-35, including patient-incurred costs. To assess resource requirements and cost-effectiveness, we compared scenarios with a base case representing continued current practice. FINDINGS Incremental tuberculosis service costs differed by scenario and country, and in some cases they more than doubled existing funding needs. In general, expansion of tuberculosis services substantially reduced patient-incurred costs and, in India and China, produced net cost savings for most interventions under a societal perspective. In all three countries, expansion of access to care produced substantial health gains. Compared with current practice and conventional cost-effectiveness thresholds, most intervention approaches seemed highly cost-effective. INTERPRETATION Expansion of tuberculosis services seems cost-effective for high-burden countries and could generate substantial health and economic benefits for patients, although substantial new funding would be required. Further work to determine the optimal intervention mix for each country is necessary. FUNDING Bill & Melinda Gates Foundation.
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Affiliation(s)
- Nicolas A Menzies
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA; Center for Health Decision Science, Harvard T H Chan School of Public Health, Boston, MA, USA.
| | - Gabriela B Gomez
- Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands; Department of Global Health, Academic Medical Center, University of Amsterdam, Netherlands; Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK
| | - Fiammetta Bozzani
- Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Nicola Foster
- Health Economics Unit, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa
| | | | - Yoko V Laurence
- Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK
| | - Sun Qiang
- School of Health Care Management and Key Laboratory of Health Economics and Policy Research of Ministry of Health, Shandong University, Jinan, China
| | | | - Sedona Sweeney
- Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK
| | - Stéphane Verguet
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Nimalan Arinaminpathy
- Public Health Foundation of India, Delhi NCR, India; Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Andrew S Azman
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Eran Bendavid
- Department of Medicine, Stanford University, Stanford, CA, USA
| | | | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Justin T Denholm
- Victorian Tuberculosis Program at the Peter Doherty Institute, Melbourne, VIC, Australia; Department of Microbiology and Immunology, University of Melbourne, Melbourne, VIC, Australia
| | - David W Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Jeremy D Goldhaber-Fiebert
- Stanford Health Policy, Centers for Health Policy and Primary Care and Outcomes Research, Stanford University, Stanford, CA, USA
| | - Andreas Handel
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA
| | - Grace H Huynh
- Institute for Disease Modeling, Seattle, WA, USA; Synthetic Neurobiology Group, Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Marek Lalli
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Hsien-Ho Lin
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | | | - Emma S McBryde
- Victorian Tuberculosis Program at the Peter Doherty Institute, Melbourne, VIC, Australia; Department of Microbiology and Immunology, University of Melbourne, Melbourne, VIC, Australia; Burnet Institute, Melbourne, VIC, Australia
| | | | - Joshua A Salomon
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA; Center for Health Decision Science, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Sze-Chuan Suen
- Department of Management Science and Engineering, Stanford University, Stanford, CA, USA
| | - Tom Sumner
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK
| | - James M Trauer
- Victorian Tuberculosis Program at the Peter Doherty Institute, Melbourne, VIC, Australia; Department of Microbiology and Immunology, University of Melbourne, Melbourne, VIC, Australia; Burnet Institute, Melbourne, VIC, Australia
| | | | - Christopher C Whalen
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA
| | - Chieh-Yin Wu
- Institute of Epidemiology and Preventive Medicine, National Taiwan University, Taipei, Taiwan
| | - Delia Boccia
- Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Vineet K Chadha
- Epidemiology and Research Division, National Tuberculosis Institute, Bangalore, India
| | | | | | - Gavin Churchyard
- Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; Aurum Institute, Johannesburg, South Africa; School of Public Health, University of Witwatersrand, Johannesburg, South Africa
| | | | - Puneet Dewan
- Bill & Melinda Gates Foundation, New Delhi, India
| | | | - Jeffrey W Eaton
- Department of Infectious Disease Epidemiology, Imperial College London, London, UK
| | - Alison D Grant
- Department of Clinical Research, London School of Hygiene & Tropical Medicine, London, UK; School of Public Health, University of Witwatersrand, Johannesburg, South Africa; Africa Centre for Population Health, School of Nursing & Public Health, University of KwaZulu-Natal, Durban, South Africa
| | | | - Mehran Hosseini
- Strategic Information Department, The Global Fund, Geneva, Switzerland
| | - David Mametja
- National Department of Health, Pretoria, South Africa
| | | | - Yogan Pillay
- National Department of Health, Pretoria, South Africa
| | - Kiran Rade
- World Health Organization Country Office for India, New Delhi, India
| | | | - Lixia Wang
- National Center for Tuberculosis Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Rein M G J Houben
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK
| | | | - Richard G White
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Faculty of Epidemiology and Public Health, London School of Hygiene & Tropical Medicine, London, UK
| | - Anna Vassall
- Department of Global Health and Development, London School of Hygiene & Tropical Medicine, London, UK
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