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Assebe LF, Erena AK, Fikadu L, Alemu B, Baruda YS, Jiao B. Cost-effectiveness of TB diagnostic technologies in Ethiopia: a modelling study. COST EFFECTIVENESS AND RESOURCE ALLOCATION 2024; 22:43. [PMID: 38773636 PMCID: PMC11106958 DOI: 10.1186/s12962-024-00544-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 04/16/2024] [Indexed: 05/24/2024] Open
Abstract
BACKGROUND Tuberculosis (TB) is a major threat to public health, particularly in countries where the disease is highly prevalent, such as Ethiopia. Early diagnosis and treatment are the main components of TB prevention and control. Although the national TB guideline recommends the primary use of rapid TB diagnostics whenever feasible, there is limited evidence available that assess the efficiency of deploying various diagnostic tools in the country. Hence, this study aims to evaluate the cost-effectiveness of rapid TB/MDR-TB diagnostic tools in Ethiopia. METHODS A hybrid Markov model for a hypothetical adult cohort of presumptive TB cases was constructed. The following TB diagnostic tools were evaluated: X-pert MTB/RIF, Truenat, chest X-ray screening followed by an X-pert MTB/RIF, TB-LAMP, and smear microscopy. Cost-effectiveness was determined based on incremental costs ($) per Disability-adjusted Life Years (DALY) averted, using a threshold of one times Gross Domestic Product (GDP) per capita ($856). Data on starting and transition probabilities, costs, and health state utilities were derived from secondary sources. The analysis is conducted from the health system perspective, and a probabilistic sensitivity analysis is performed. RESULT The incremental cost-effectiveness ratio for X-pert MTB/RIF, compared to the next best alternative, is $276 per DALY averted, making it a highly cost-effective diagnostic tool. Additionally, chest X-ray screening followed an X-pert MTB/RIF test is less cost-effective, with an ICER of $1666 per DALY averted. Introducing X-pert MTB/RIF testing would enhance TB detection and prevent 9600 DALYs in a cohort of 10,000 TB patients, with a total cost of $3,816,000. CONCLUSION The X-pert MTB/RIF test is the most cost-effective diagnostic tool compared to other alternatives. The use of this diagnostic tool improves the early detection and treatment of TB cases. Increased funding for this diagnostic tool will enhance access, reduce the TB detection gaps, and improve treatment outcomes.
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Affiliation(s)
- Lelisa Fekadu Assebe
- Department of Global Public Health and Primary Care, Faculty of Medicine, University of Bergen, Bergen, Norway.
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | | | - Lemmessa Fikadu
- Health system strengthening through Performance Based Financing Project, Cordaid, Bahir dar, Ethiopia
| | - Bizuneh Alemu
- Department of Health Promotion and disease prevention, Oromia Regional Health Bureau, Addis Ababa, Ethiopia
| | - Yirgalem Shibiru Baruda
- Department of Global Health, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands
| | - Boshen Jiao
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Kasaie P, Pennington J, Gupta A, Dowdy DW, Kendall EA. The Impact of Preventive Treatment for Multidrug- and Rifampin-Resistant Tuberculosis Exceeds Trial-Based Estimates. Clin Infect Dis 2024; 78:133-143. [PMID: 37724763 PMCID: PMC10810707 DOI: 10.1093/cid/ciad557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/18/2023] [Accepted: 09/18/2023] [Indexed: 09/21/2023] Open
Abstract
BACKGROUND Several clinical trials of tuberculosis preventive treatment (TPT) for household contacts of patients with multidrug- or rifampin-resistant tuberculosis (MDR/RR-TB) are nearing completion. The potential benefits of delivering TPT to MDR/RR-TB contacts extend beyond the outcomes that clinical trials can measure. METHODS We developed an agent-based, household-structured TB and MDR/RR-TB transmission model, calibrated to an illustrative setting in India. We simulated contact investigation in households of patients with MDR/RR-TB, comparing an MDR/RR-TPT regimen (assuming 6-month duration, 70% efficacy) and associated active case finding against alternatives of contact investigation without TPT or no household intervention. We simulated the TB and MDR/RR-TB incidence averted relative to placebo over 2 years, as measurable by a typical trial, as well as the incidence averted over a longer time horizon, in the broader population, and relative to no contact investigation. RESULTS Observing TPT and placebo recipients for 2 years as in a typical trial, MDR/RR-TPT was measured to prevent 72% (interquartile range, 45%-100%) of incident MDR/RR-TB among recipients; the median number needed to treat (NNT) to prevent 1 MDR/RR-TB case was 73, compared to placebo. This NNT decreased to 54 with 13-18 years of observation, to 27 when downstream transmission effects were also considered, and to 12 when the effects of active TB screening were included by comparing to a no-household-contact-intervention scenario. CONCLUSIONS If forthcoming trial results demonstrate efficacy, the long-term population impact of TPT for MDR/RR-TB-including the large effect of increased active TB detection among MDR/RR-TB contacts-could be much greater than suggested by trial outcomes alone.
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Affiliation(s)
- Parastu Kasaie
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Jeff Pennington
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Amita Gupta
- Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - David W Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Emily A Kendall
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Richards AS, Sossen B, Emery JC, Horton KC, Heinsohn T, Frascella B, Balzarini F, Oradini-Alacreu A, Häcker B, Odone A, McCreesh N, Grant AD, Kranzer K, Cobelens F, Esmail H, Houben RMGJ. Quantifying progression and regression across the spectrum of pulmonary tuberculosis: a data synthesis study. Lancet Glob Health 2023; 11:e684-e692. [PMID: 36966785 PMCID: PMC10126316 DOI: 10.1016/s2214-109x(23)00082-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 01/30/2023] [Accepted: 02/06/2023] [Indexed: 03/29/2023]
Abstract
BACKGROUND Prevalence surveys show a substantial burden of subclinical (asymptomatic but infectious) tuberculosis, from which individuals can progress, regress, or even persist in a chronic disease state. We aimed to quantify these pathways across the spectrum of tuberculosis disease. METHODS We created a deterministic framework of untreated tuberculosis disease with progression and regression between three states of pulmonary tuberculosis disease: minimal (non-infectious), subclinical (asymptomatic but infectious), and clinical (symptomatic and infectious). We obtained data from a previous systematic review of prospective and retrospective studies that followed and recorded the disease state of individuals with tuberculosis in a cohort without treatment. These data were considered in a Bayesian framework, enabling quantitative estimation of tuberculosis disease pathways with rates of transition between states and 95% uncertainty intervals (UIs). FINDINGS We included 22 studies with data from 5942 individuals in our analysis. Our model showed that after 5 years, 40% (95% UI 31·3-48·0) of individuals with prevalent subclinical disease at baseline recover and 18% (13·3-24·0) die from tuberculosis, with 14% (9·9-19·2) still having infectious disease, and the remainder with minimal disease at risk of re-progression. Over 5 years, 50% (40·0-59·1) of individuals with subclinical disease at baseline never develop symptoms. For those with clinical disease at baseline, 46% (38·3-52·2) die and 20% (15·2-25·8) recover from tuberculosis, with the remainder being in or transitioning between the three disease states after 5 years. We estimated the 10-year mortality of people with untreated prevalent infectious tuberculosis to be 37% (30·5-45·4). INTERPRETATION For people with subclinical tuberculosis, classic clinical disease is neither an inevitable nor an irreversible outcome. As such, reliance on symptom-based screening means a large proportion of people with infectious disease might never be detected. FUNDING TB Modelling and Analysis Consortium and European Research Council.
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Affiliation(s)
- Alexandra S Richards
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK.
| | - Bianca Sossen
- Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Jon C Emery
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK
| | - Katherine C Horton
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK
| | - Torben Heinsohn
- Institute for Global Health, University College London, London, UK; Helmholtz Centre for Infection Research, Braunschweig, Germany; German Centre for Infection Research, Braunschweig, Germany
| | - Beatrice Frascella
- School of Public Health, Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Balzarini
- School of Public Health, Vita-Salute San Raffaele University, Milan, Italy; Local Health Authority of Bergamo, Bergamo, Italy
| | | | - Brit Häcker
- Department of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy
| | - Anna Odone
- German Central Committee Against Tuberculosis, Berlin, Germany
| | - Nicky McCreesh
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK
| | - Alison D Grant
- TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Africa Health Research Institute, School of Laboratory Medicine and Medical Sciences, College of Health Sciences, University of KwaZulu-Natal, Durban, South Africa; School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Katharina Kranzer
- Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical Medicine, London, UK; Biomedical Research and Training Institute, Harare, Zimbabwe; Division of Infectious Diseases and Tropical Medicine, University Hospital, Ludwig Maximilian University of Munich, Munich, Germany
| | - Frank Cobelens
- Department of Global Health and Amsterdam Institute for Global Health and Development, Amsterdam University Medical Centers, Amsterdam, Netherlands
| | - Hanif Esmail
- Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town, South Africa; Institute for Global Health, University College London, London, UK; MRC Clinical Trials Unit, University College London, London, UK
| | - Rein M G J Houben
- TB Modelling Group, TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Infectious Disease Epidemiology Department, London School of Hygiene & Tropical Medicine, London, UK
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Kasaie P, Pennington J, Gupta A, Dowdy DW, Kendall EA. Trials underestimate the impact of preventive treatment for household contacts exposed to multidrug-resistant tuberculosis: a simulation study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.06.23285528. [PMID: 36798407 PMCID: PMC9934809 DOI: 10.1101/2023.02.06.23285528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
Background Several clinical trials of tuberculosis preventive treatment (TPT) for household contacts of patients with multidrug-resistant tuberculosis (MDR-TB) are nearing completion. The potential benefits of TPT for MDR-TB contacts extend beyond the outcomes that clinical trials can measure. Methods We developed an agent-based, household-structured TB and MDR-TB transmission model, calibrated to an illustrative setting in India, the country accounting for 26% of global MDR-TB burden. We simulated household contact investigation for contacts of patients with MDR-TB, comparing an MDR-TPT regimen against alternatives of isoniazid preventive treatment, household contact investigation without TPT, or no household contact intervention. We simulated outcomes of a clinical trial and estimated the patient-level and population-level effects over a longer time horizon. Findings During two years of follow-up per recipient, a simulated 6-month MDR-TPT regimen with 70% efficacy against both DS- and MDR-TB infection could prevent 72% [Interquartile range (IQR): 45 - 100%] of incident MDR-TB among TPT recipients (number needed to treat (NNT) 73 [44 - 176] to prevent one MDR-TB case), compared to household contact investigation without TPT. This NNT decreased to 54 [30 - 183] when median follow-up was increased from two to 16 years, to 27 [11 - Inf] when downstream transmission effects were also considered, and to 12 [8 - 22] when these effects were compared to a scenario of no household contact intervention. Interpretation If forthcoming trial results demonstrate efficacy, the long-term population impact of MDR-TPT implementation could be much greater than suggested by trial outcomes alone. Funding NIH K01AI138853 and K08AI127908; Johns Hopkins Catalyst Award.
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Infectious and clinical tuberculosis trajectories: Bayesian modeling with case finding implications. Proc Natl Acad Sci U S A 2022; 119:e2211045119. [PMID: 36534797 PMCID: PMC9907102 DOI: 10.1073/pnas.2211045119] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
The importance of finding people with undiagnosed tuberculosis (TB) hinges on their future disease trajectories. Assays for systematic screening should be optimized to find those whose TB will contribute most to future transmission or morbidity. In this study, we constructed a mathematical model that tracks the future trajectories of individuals with TB at a cross-sectional timepoint ("baseline"), classifying them by bacterial burden (smear positive/negative) and symptom status (symptomatic/subclinical). We used Bayesian methods to calibrate this model to targets derived from historical survival data and notification, mortality, and prevalence data from five countries. We combined resulting disease trajectories with evidence on infectiousness to estimate each baseline TB state's contribution to future transmission. For a person with smear-negative subclinical TB at baseline, the expected future duration of disease was short (mean 4.8 [95% uncertainty interval 3.3 to 8.4] mo); nearly all disease courses ended in spontaneous resolution, not treatment. In contrast, people with baseline smear-positive subclinical TB had longer undiagnosed disease durations (15.9 [11.1 to 23.5] mo); nearly all eventually developed symptoms and ended in treatment or death. Despite accounting for only 11 to 19% of prevalent disease, smear-positive subclinical TB accounted for 35 to 51% of future transmission-a greater contribution than symptomatic or smear-negative TB. Subclinical TB with a high bacterial burden accounts for a disproportionate share of future transmission. Priority should be given to developing inexpensive, easy-to-use assays for screening both symptomatic and asymptomatic individuals at scale-akin to rapid antigen tests for other diseases-even if these assays lack the sensitivity to detect paucibacillary disease.
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Projecting the impact of variable MDR-TB transmission efficiency on long-term epidemic trends in South Africa and Vietnam. Sci Rep 2019; 9:18099. [PMID: 31792289 PMCID: PMC6889300 DOI: 10.1038/s41598-019-54561-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2019] [Accepted: 11/10/2019] [Indexed: 12/12/2022] Open
Abstract
Whether multidrug-resistant tuberculosis (MDR-TB) is less transmissible than drug-susceptible (DS-)TB on a population level is uncertain. Even in the absence of a genetic fitness cost, the transmission potential of individuals with MDR-TB may vary by infectiousness, frequency of contact, or duration of disease. We used a compartmental model to project the progression of MDR-TB epidemics in South Africa and Vietnam under alternative assumptions about the relative transmission efficiency of MDR-TB. Specifically, we considered three scenarios: consistently lower transmission efficiency for MDR-TB than for DS-TB; equal transmission efficiency; and an initial deficit in the transmission efficiency of MDR-TB that closes over time. We calibrated these scenarios with data from drug resistance surveys and projected epidemic trends to 2040. The incidence of MDR-TB was projected to expand in most scenarios, but the degree of expansion depended greatly on the future transmission efficiency of MDR-TB. For example, by 2040, we projected absolute MDR-TB incidence to account for 5% (IQR: 4–9%) of incident TB in South Africa and 14% (IQR: 9–26%) in Vietnam assuming consistently lower MDR-TB transmission efficiency, versus 15% (IQR: 8–27%)and 41% (IQR: 23–62%), respectively, assuming shrinking transmission efficiency deficits. Given future uncertainty, specific responses to halt MDR-TB transmission should be prioritized.
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Urogenital tuberculosis - epidemiology, pathogenesis and clinical features. Nat Rev Urol 2019; 16:573-598. [PMID: 31548730 DOI: 10.1038/s41585-019-0228-9] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2019] [Indexed: 02/07/2023]
Abstract
Tuberculosis (TB) is the most common cause of death from infectious disease worldwide. A substantial proportion of patients presenting with extrapulmonary TB have urogenital TB (UG-TB), which can easily be overlooked owing to non-specific symptoms, chronic and cryptic protean clinical manifestations, and lack of clinician awareness of the possibility of TB. Delay in diagnosis results in disease progression, irreversible tissue and organ damage and chronic renal failure. UG-TB can manifest with acute or chronic inflammation of the urinary or genital tract, abdominal pain, abdominal mass, obstructive uropathy, infertility, menstrual irregularities and abnormal renal function tests. Advanced UG-TB can cause renal scarring, distortion of renal calyces and pelvic, ureteric strictures, stenosis, urinary outflow tract obstruction, hydroureter, hydronephrosis, renal failure and reduced bladder capacity. The specific diagnosis of UG-TB is achieved by culturing Mycobacterium tuberculosis from an appropriate clinical sample or by DNA identification. Imaging can aid in localizing site, extent and effect of the disease, obtaining tissue samples for diagnosis, planning medical or surgical management, and monitoring response to treatment. Drug-sensitive TB requires 6-9 months of WHO-recommended standard treatment regimens. Drug-resistant TB requires 12-24 months of therapy with toxic drugs with close monitoring. Surgical intervention as an adjunct to medical drug treatment is required in certain circumstances. Current challenges in UG-TB management include making an early diagnosis, raising clinical awareness, developing rapid and sensitive TB diagnostics tests, and improving treatment outcomes.
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Proaño A, Bui DP, López JW, Vu NM, Bravard MA, Lee GO, Tracey BH, Xu Z, Comina G, Ticona E, Mollura DJ, Friedland JS, Moore DAJ, Evans CA, Caligiuri P, Gilman RH. Cough Frequency During Treatment Associated With Baseline Cavitary Volume and Proximity to the Airway in Pulmonary TB. Chest 2018; 153:1358-1367. [PMID: 29559307 PMCID: PMC6026292 DOI: 10.1016/j.chest.2018.03.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2017] [Revised: 02/14/2018] [Accepted: 03/01/2018] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Cough frequency, and its duration, is a biomarker that can be used in low-resource settings without the need of laboratory culture and has been associated with transmission and treatment response. Radiologic characteristics associated with increased cough frequency may be important in understanding transmission. The relationship between cough frequency and cavitary lung disease has not been studied. METHODS We analyzed data in 41 adults who were HIV negative and had culture-confirmed, drug-susceptible pulmonary TB throughout treatment. Cough recordings were based on the Cayetano Cough Monitor, and sputum samples were evaluated using microscopic observation drug susceptibility broth culture; among culture-positive samples, bacillary burden was assessed by means of time to positivity. CT scans were analyzed by a US-board-certified radiologist and a computer-automated algorithm. The algorithm evaluated cavity volume and cavitary proximity to the airway. CT scans were obtained within 1 month of treatment initiation. We compared small cavities (≤ 7 mL) and large cavities (> 7 mL) and cavities located closer to (≤ 10 mm) and farther from (> 10 mm) the airway to cough frequency and cough cessation until treatment day 60. RESULTS Cough frequency during treatment was twofold higher in participants with large cavity volumes (rate ratio [RR], 1.98; P = .01) and cavities located closer to the airway (RR, 2.44; P = .001). Comparably, cough ceased three times faster in participants with smaller cavities (adjusted hazard ratio [HR], 2.89; P = .06) and those farther from the airway (adjusted HR, 3.61;, P = .02). Similar results were found for bacillary burden and culture conversion during treatment. CONCLUSIONS Cough frequency during treatment is greater and lasts longer in patients with larger cavities, especially those closer to the airway.
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Affiliation(s)
- Alvaro Proaño
- Laboratorio de Investigación en Enfermedades Infecciosas, Laboratorio de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru.
| | - David P Bui
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ
| | - José W López
- Laboratorio de Bioinformática y Biología Molecular, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru; Instituto Nacional de Salud del Niño San Borja, Lima, Peru
| | - Nancy M Vu
- Department of Internal Medicine, Cleveland Clinic, Cleveland, OH
| | - Marjory A Bravard
- Innovation for Health and Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Asociación Benéfica PRISMA, Lima, Peru; Department of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Gwenyth O Lee
- Department of Global Community Health and Behavioral Sciences, Tulane University, New Orleans, LA
| | - Brian H Tracey
- Department of Electrical and Computer Engineering, Tufts University, Medford, MA
| | - Ziyue Xu
- Center for Infectious Disease Imaging, Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD
| | - Germán Comina
- Escuela Profesional de Ingeniería Física, Facultad de Ciencias, Universidad Nacional de Ingeniería, Lima, Peru; Department of Global Community Health and Behavioral Sciences, Tulane University, New Orleans, LA
| | - Eduardo Ticona
- Facultad de Medicina, Universidad Nacional Mayor de San Marcos, Lima, Peru; Servicio de Enfermedades Infecciosas y Tropicales, Hospital Nacional Dos de Mayo, Lima, Peru
| | - Daniel J Mollura
- Center for Infectious Disease Imaging, Radiology and Imaging Sciences, National Institutes of Health, Bethesda, MD
| | - Jon S Friedland
- Section of Infectious Diseases & Immunity and Wellcome Trust Imperial College Centre for Global Health Research, Imperial College London, London, England
| | - David A J Moore
- Laboratorio de Investigación en Enfermedades Infecciosas, Laboratorio de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru; Asociación Benéfica PRISMA, Lima, Peru; TB Centre, London School of Hygiene and Tropical Medicine, London, England
| | - Carlton A Evans
- Innovation for Health and Development, Laboratory of Research and Development, Universidad Peruana Cayetano Heredia, Lima, Peru; Asociación Benéfica PRISMA, Lima, Peru; Section of Infectious Diseases & Immunity and Wellcome Trust Imperial College Centre for Global Health Research, Imperial College London, London, England
| | - Philip Caligiuri
- Department of Radiology & Imaging Sciences, University of Utah School of Medicine, Salt Lake City, UT
| | - Robert H Gilman
- Laboratorio de Investigación en Enfermedades Infecciosas, Laboratorio de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Lima, Peru; Asociación Benéfica PRISMA, Lima, Peru; Program in Global Disease Epidemiology and Control, Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD
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