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James LP, Klaassen F, Sweeney S, Furin J, Franke MF, Yaesoubi R, Chesov D, Ciobanu N, Codreanu A, Crudu V, Cohen T, Menzies NA. Impact and cost-effectiveness of the 6-month BPaLM regimen for rifampicin-resistant tuberculosis in Moldova: A mathematical modeling analysis. PLoS Med 2024; 21:e1004401. [PMID: 38701084 DOI: 10.1371/journal.pmed.1004401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 04/10/2024] [Indexed: 05/05/2024] Open
Abstract
BACKGROUND Emerging evidence suggests that shortened, simplified treatment regimens for rifampicin-resistant tuberculosis (RR-TB) can achieve comparable end-of-treatment (EOT) outcomes to longer regimens. We compared a 6-month regimen containing bedaquiline, pretomanid, linezolid, and moxifloxacin (BPaLM) to a standard of care strategy using a 9- or 18-month regimen depending on whether fluoroquinolone resistance (FQ-R) was detected on drug susceptibility testing (DST). METHODS AND FINDINGS The primary objective was to determine whether 6 months of BPaLM is a cost-effective treatment strategy for RR-TB. We used genomic and demographic data to parameterize a mathematical model estimating long-term health outcomes measured in quality-adjusted life years (QALYs) and lifetime costs in 2022 USD ($) for each treatment strategy for patients 15 years and older diagnosed with pulmonary RR-TB in Moldova, a country with a high burden of TB drug resistance. For each individual, we simulated the natural history of TB and associated treatment outcomes, as well as the process of acquiring resistance to each of 12 anti-TB drugs. Compared to the standard of care, 6 months of BPaLM was cost-effective. This strategy was estimated to reduce lifetime costs by $3,366 (95% UI: [1,465, 5,742] p < 0.001) per individual, with a nonsignificant change in QALYs (-0.06; 95% UI: [-0.49, 0.032] p = 0.790). For those stopping moxifloxacin under the BPaLM regimen, continuing with BPaL plus clofazimine (BPaLC) provided more QALYs at lower cost than continuing with BPaL alone. Strategies based on 6 months of BPaLM had at least a 93% chance of being cost-effective, so long as BPaLC was continued in the event of stopping moxifloxacin. BPaLM for 6 months also reduced the average time spent with TB resistant to amikacin, bedaquiline, clofazimine, cycloserine, moxifloxacin, and pyrazinamide, while it increased the average time spent with TB resistant to delamanid and pretomanid. Sensitivity analyses showed 6 months of BPaLM to be cost-effective across a broad range of values for the relative effectiveness of BPaLM, and the proportion of the cohort with FQ-R. Compared to the standard of care, 6 months of BPaLM would be expected to save Moldova's national TB program budget $7.1 million (95% UI: [1.3 million, 15.4 million] p = 0.002) over the 5-year period from implementation. Our analysis did not account for all possible interactions between specific drugs with regard to treatment outcomes, resistance acquisition, or the consequences of specific types of severe adverse events, nor did we model how the intervention may affect TB transmission dynamics. CONCLUSIONS Compared to standard of care, longer regimens, the implementation of the 6-month BPaLM regimen could improve the cost-effectiveness of care for individuals diagnosed with RR-TB, particularly in settings with a high burden of drug-resistant TB. Further research may be warranted to explore the impact and cost-effectiveness of shorter RR-TB regimens across settings with varied drug-resistant TB burdens and national income levels.
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Affiliation(s)
- Lyndon P James
- PhD Program in Health Policy, Harvard University, Cambridge, Massachusetts, United States of America
- Center for Health Decision Science, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Fayette Klaassen
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Sedona Sweeney
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jennifer Furin
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Molly F Franke
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Reza Yaesoubi
- Department of Health Policy and Management, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Dumitru Chesov
- Discipline of Pneumology and Allergology, Nicolae Testemitanu State University of Medicine and Pharmacy, Chişinǎu, Moldova
- Clinical Infectious Diseases, Research Center Borstel, Borstel, Germany
| | - Nelly Ciobanu
- Chiril Draganiuc Institute of Phthisiopneumology, Chișinǎu, Moldova
| | | | - Valeriu Crudu
- Chiril Draganiuc Institute of Phthisiopneumology, Chișinǎu, Moldova
| | - Ted Cohen
- Department of Epidemiology and Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Wang D, Shifraw T, Costa JC, Abdelmenan S, Tsegaye S, Berhane Y, Gulema H, Berhane H, Fasil N, Workneh F, Tarekegn W, Wang M, Menzies NA, Worku A, Berhane Y, Fawzi WW. Targeting strategies of antenatal balanced energy and protein supplementation in Addis Ababa, Ethiopia: study protocol for a randomized effectiveness study. Trials 2024; 25:291. [PMID: 38689304 PMCID: PMC11059725 DOI: 10.1186/s13063-024-08002-2] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 02/21/2024] [Indexed: 05/02/2024] Open
Abstract
BACKGROUND Antenatal balanced energy and protein (BEP) supplements have well-documented benefits for pregnancy outcomes. However, considerable practical gaps remain in the effective and cost-effective delivery of antenatal BEP supplements at scale in low- and middle-income countries. METHODS A randomized effectiveness study will be conducted in two sub-cities of Addis Ababa, Ethiopia, to evaluate the effectiveness, cost-effectiveness, and implementation of different targeting strategies of antenatal BEP supplements. Pregnant women aged 18 to 49, with a gestational age of 24 weeks or less, and attending antenatal visits in one of the nine study health facilities are eligible for enrollment. In six of the health facilities, participants will be randomized to one of three study arms: control (Arm 1), targeted BEP provision based on baseline nutritional status (Arm 2), and targeted BEP supplementation based on baseline nutritional status and monthly gestational weight gain (GWG) monitoring (Arm 3). In the remaining three facilities, participants will be assigned to universal BEP provision (Arm 4). Participants in Arms 2 and 3 will receive BEP supplements if they have undernutrition at enrollment, as defined by a baseline body mass index less than 18.5 kg/m2 or mid-upper arm circumference less than 23 cm. In Arm 3, in addition to targeting based on baseline undernutrition, regular weight measurements will be used to identify insufficient GWG and inform the initiation of additional BEP supplements. Participants in Arm 4 will receive BEP supplements until the end of pregnancy, regardless of baseline nutritional status or GWG. All participants will receive standard antenatal care, including iron and folic acid supplementation. A total of 5400 pregnant women will be enrolled, with 1350 participants in each arm. Participants will be followed up monthly during their visits to the antenatal facilities until delivery. Maternal and infant health status will be evaluated within 72 h after delivery and at 6 weeks postpartum. The effectiveness and cost-effectiveness of the different BEP targeting strategies in preventing adverse pregnancy outcomes will be compared across arms. Qualitative data will be analyzed to assess the feasibility, acceptability, and implementation of different supplementation strategies. DISCUSSION This study will inform global recommendations and operational guidelines for the effective and cost-effective delivery of antenatal BEP supplements. The targeted approaches have the potential for broader scale-up in Ethiopia and other low-resource settings with a high burden of undernutrition among pregnant women. TRIAL REGISTRATION ClinicalTrials.gov registration number: NCT06125860. Registered November 9, 2023.
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Affiliation(s)
- Dongqing Wang
- Department of Global and Community Health, College of Public Health, George Mason University, Fairfax, VA, USA
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, 665 Huntington Avenue, Building 1, Room 1108, Boston, MA, 02115, USA
| | - Tigest Shifraw
- Department of Reproductive Health and Population, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Janaina Calu Costa
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, 665 Huntington Avenue, Building 1, Room 1108, Boston, MA, 02115, USA
| | - Semira Abdelmenan
- Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Sitota Tsegaye
- Department of Nutrition and Behavioral Sciences, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Yoseph Berhane
- Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Hanna Gulema
- Department of Global Health and Health Policy, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Hanna Berhane
- Department of Nutrition and Behavioral Sciences, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Nebiyou Fasil
- Department of Global Health and Health Policy, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Firehiwot Workneh
- Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Workagegnhu Tarekegn
- Department of Nutrition and Behavioral Sciences, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Molin Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, 665 Huntington Avenue, Building 1, Room 1108, Boston, MA, 02115, USA
| | - Alemayehu Worku
- Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Yemane Berhane
- Department of Reproductive Health and Population, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
- Department of Epidemiology and Biostatistics, Addis Continental Institute of Public Health, Addis Ababa, Ethiopia
| | - Wafaie W Fawzi
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, 665 Huntington Avenue, Building 1, Room 1108, Boston, MA, 02115, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
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White RG, Menzies NA, Portnoy A, Clark RA, Toscano CM, Weller C, Tufet Bayona M, Silal SP, Karron RA, Lee JS, Excler JL, Lauer JA, Giersing B, Lambach P, Hutubessy R, Jit M. The Full Value of Vaccine Assessments Concept-Current Opportunities and Recommendations. Vaccines (Basel) 2024; 12:435. [PMID: 38675817 PMCID: PMC11053419 DOI: 10.3390/vaccines12040435] [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: 02/26/2024] [Revised: 04/03/2024] [Accepted: 04/06/2024] [Indexed: 04/28/2024] Open
Abstract
For vaccine development and adoption decisions, the 'Full Value of Vaccine Assessment' (FVVA) framework has been proposed by the WHO to expand the range of evidence available to support the prioritization of candidate vaccines for investment and eventual uptake by low- and middle-income countries. Recent applications of the FVVA framework have already shown benefits. Building on the success of these applications, we see important new opportunities to maximize the future utility of FVVAs to country and global stakeholders and provide a proof-of-concept for analyses in other areas of disease control and prevention. These opportunities include the following: (1) FVVA producers should aim to create evidence that explicitly meets the needs of multiple key FVVA consumers, (2) the WHO and other key stakeholders should develop standardized methodologies for FVVAs, as well as guidance for how different stakeholders can explicitly reflect their values within the FVVA framework, and (3) the WHO should convene experts to further develop and prioritize the research agenda for outcomes and benefits relevant to the FVVA and elucidate methodological approaches and opportunities for standardization not only for less well-established benefits, but also for any relevant research gaps. We encourage FVVA stakeholders to engage with these opportunities.
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Affiliation(s)
- Richard G. White
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK; (R.A.C.); (M.J.)
| | - Nicolas A. Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Allison Portnoy
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
- Department of Global Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Rebecca A. Clark
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK; (R.A.C.); (M.J.)
| | - Cristiana M. Toscano
- Department of Collective Health, Institute for Tropical Medicine and Public Health, Federal University of Goiás (UFG), Goiânia 74690-900, Brazil;
| | | | | | - Sheetal Prakash Silal
- Modelling and Simulation Hub, Africa, Department of Statistical Sciences, University of Cape Town, Cape Town 7701, South Africa;
- Centre for Global Health, Nuffield Department of Medicine, Oxford University, Oxford OX3 7BN, UK
| | - Ruth A. Karron
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA;
| | - Jung-Seok Lee
- Policy and Economic Research Department, International Vaccine Institute, Seoul 08826, Republic of Korea;
| | | | - Jeremy A. Lauer
- Department of Management Science, Strathclyde Business School, Strathclyde University, Glasgow G1 1XQ, UK;
| | - Birgitte Giersing
- Immunization, Vaccines and Biologicals Department, WHO, 1211 Geneva, Switzerland; (B.G.); (P.L.); (R.H.)
| | - Philipp Lambach
- Immunization, Vaccines and Biologicals Department, WHO, 1211 Geneva, Switzerland; (B.G.); (P.L.); (R.H.)
| | - Raymond Hutubessy
- Immunization, Vaccines and Biologicals Department, WHO, 1211 Geneva, Switzerland; (B.G.); (P.L.); (R.H.)
| | - Mark Jit
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK; (R.A.C.); (M.J.)
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4
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Kim S, Can MH, Agizew TB, Auld AF, Balcells ME, Bjerrum S, Dheda K, Dorman SE, Esmail A, Fielding K, Garcia-Basteiro AL, Hanrahan CF, Kebede W, Kohli M, Luetkemeyer AF, Mita C, Reeve BWP, Silva DR, Sweeney S, Theron G, Trajman A, Vassall A, Warren JL, Yotebieng M, Cohen T, Menzies NA. Factors associated with tuberculosis treatment initiation among bacteriologically negative individuals evaluated for tuberculosis: an individual patient data meta-analysis. medRxiv 2024:2024.04.07.24305445. [PMID: 38645191 PMCID: PMC11030305 DOI: 10.1101/2024.04.07.24305445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background Globally, over one-third of pulmonary tuberculosis (TB) disease diagnoses are made based on clinical criteria after a negative diagnostic test result. Understanding factors associated with clinicians' decisions to initiate treatment for individuals with negative test results is critical for predicting the potential impact of new diagnostics. Methods We performed a systematic review and individual patient data meta-analysis using studies conducted between January/2010 and December/2022 (PROSPERO: CRD42022287613). We included trials or cohort studies that enrolled individuals evaluated for TB in routine settings. In these studies participants were evaluated based on clinical examination and routinely-used diagnostics, and were followed for ≥1 week after the initial test result. We used hierarchical Bayesian logistic regression to identify factors associated with treatment initiation following a negative result on an initial bacteriological test (e.g., sputum smear microscopy, Xpert MTB/RIF). Findings Multiple factors were positively associated with treatment initiation: male sex [adjusted Odds Ratio (aOR) 1.61 (1.31-1.95)], history of prior TB [aOR 1.36 (1.06-1.73)], reported cough [aOR 4.62 (3.42-6.27)], reported night sweats [aOR 1.50 (1.21-1.90)], and having HIV infection but not on ART [aOR 1.68 (1.23-2.32)]. Treatment initiation was substantially less likely for individuals testing negative with Xpert [aOR 0.77 (0.62-0.96)] compared to smear microscopy and declined in more recent years. Interpretation Multiple factors influenced decisions to initiate TB treatment despite negative test results. Clinicians were substantially less likely to treat in the absence of a positive test result when using more sensitive, PCR-based diagnostics.
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Affiliation(s)
- Sun Kim
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Melike Hazal Can
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Andrew F. Auld
- U.S. Centers for Disease Control and Prevention, Lusaka, Zambia
| | - Maria Elvira Balcells
- Infectious Disease Department, School of Medicine, Pontificia Universidad Católica de Chile
| | - Stephanie Bjerrum
- Department of Clinical Research, University of Southern Denmark, Odense Denmark
- Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Keertan Dheda
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute, Cape Town, South Africa
- South African MRC Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
- Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, UK
| | | | - Aliasgar Esmail
- Centre for Lung Infection and Immunity, Division of Pulmonology, Department of Medicine and UCT Lung Institute, Cape Town, South Africa
- South African MRC Centre for the Study of Antimicrobial Resistance, University of Cape Town, Cape Town, South Africa
| | - Katherine Fielding
- TB Centre, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Alberto L. Garcia-Basteiro
- ISGlobal, Hospital Clínic – Universitat de Barcelona, Barcelona, Spain
- Centro de Investigação em Saúde de Manhiça (CISM), Maputo, Mozambique
- Centro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Barcelona, Spain
| | - Colleen F. Hanrahan
- Epidemiology Department, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Wakjira Kebede
- School of Medical Laboratory Sciences, Jimma University, Jimma Ethiopia
- Mycobacteriology Research Center of Jimma University, Ethiopia
| | | | | | - Carol Mita
- Countway Library of Medicine, Harvard University, Boston, MA, USA
| | - Byron W. P. Reeve
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Denise Rossato Silva
- Faculdade de Medicina, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Sedona Sweeney
- Faculty of Public Health and Policy, London School of Hygiene & Tropical Medicine, London, UK
| | - Grant Theron
- DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research and SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Anete Trajman
- Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
- McGill University, Montreal, QC, Canada
| | - Anna Vassall
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK
| | - Joshua L. Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA
| | - Marcel Yotebieng
- Division of General Internal Medicine, Department of Medicine, Albert Einstein College of Medicine, New York City, NY, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - 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
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5
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Clarke-Deelder E, Suharlim C, Chatterjee S, Portnoy A, Brenzel L, Ray A, Cohen J, Menzies NA, Resch SC. Health impact and cost-effectiveness of expanding routine immunization coverage in India through Intensified Mission Indradhanush. Health Policy Plan 2024:czae024. [PMID: 38590052 DOI: 10.1093/heapol/czae024] [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: 06/30/2023] [Revised: 03/24/2024] [Accepted: 04/02/2024] [Indexed: 04/10/2024] Open
Abstract
Many children do not receive a full schedule of childhood vaccines, yet there is limited evidence on the cost-effectiveness of strategies for improving vaccination coverage. Evidence is even scarcer on the cost-effectiveness of strategies for reaching "zero-dose children," who have not received any routine vaccines. We evaluated the cost-effectiveness of periodic intensification of routine immunization (PIRI), a widely applied strategy for increasing vaccination coverage. We focused on Intensified Mission Indradhanush (IMI), a large-scale PIRI intervention implemented in India in 2017-2018. In 40 sampled districts, we measured the incremental economic cost of IMI using primary data, and used controlled interrupted time-series regression to estimate incremental vaccination doses delivered. We estimated deaths and disability-adjusted life years (DALYs) averted using the Lives Saved Tool and reported cost-effectiveness from immunization program and societal perspectives. We found that, in sampled districts, IMI had an estimated incremental cost of 2021US$13.7 (95% uncertainty interval: 10.6 to 17.4) million from an immunization program perspective and increased vaccine delivery by an estimated 2.2 (-0.5 to 4.8) million doses over a 12-month period, averting an estimated 1,413 (-350 to 3,129) deaths. The incremental cost from a program perspective was $6.21 per dose ($2.80 to dominated), $82.99 per zero-dose child reached ($39.85 to dominated), $327.63 ($147.65 to dominated) per DALY averted, $360.72 ($162.56 to dominated) per life-year saved, and $9,701.35 ($4,372.01 to dominated) per under-five death averted. At a cost-effectiveness threshold of 1x per-capita GDP per DALY averted, IMI was estimated to be cost-effective with 90% probability. This evidence suggests IMI was both impactful and cost-effective for improving vaccination coverage, though there is a high degree of uncertainty in the results. As vaccination programs expand coverage, unit costs may increase due to the higher costs of reaching currently unvaccinated children.
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Affiliation(s)
- Emma Clarke-Deelder
- Harvard T. H. Chan School of Public Health, Department of Global Health and Population
- Swiss Tropical & Public Health Institute, Department of Epidemiology and Public Health
- University of Basel, Basel, Switzerland
| | - Christian Suharlim
- Harvard T. H. Chan School of Public Health, Center for Health Decision Science
- Management Sciences for Health
| | | | - Allison Portnoy
- Harvard T. H. Chan School of Public Health, Center for Health Decision Science
| | | | | | - Jessica Cohen
- Harvard T. H. Chan School of Public Health, Department of Global Health and Population
| | - Nicolas A Menzies
- Harvard T. H. Chan School of Public Health, Department of Global Health and Population
- Harvard T. H. Chan School of Public Health, Center for Health Decision Science
| | - Stephen C Resch
- Harvard T. H. Chan School of Public Health, Center for Health Decision Science
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6
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Li Y, Regan M, Swartwood NA, Barham T, Beeler Asay GR, Cohen T, Hill AN, Horsburgh CR, Khan A, Marks SM, Myles RL, Salomon JA, Self JL, Menzies NA. Disparities in Tuberculosis Incidence by Race and Ethnicity Among the U.S.-Born Population in the United States, 2011 to 2021 : An Analysis of National Disease Registry Data. Ann Intern Med 2024; 177:418-427. [PMID: 38560914 DOI: 10.7326/m23-2975] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Elevated tuberculosis (TB) incidence rates have recently been reported for racial/ethnic minority populations in the United States. Tracking such disparities is important for assessing progress toward national health equity goals and implementing change. OBJECTIVE To quantify trends in racial/ethnic disparities in TB incidence among U.S.-born persons. DESIGN Time-series analysis of national TB registry data for 2011 to 2021. SETTING United States. PARTICIPANTS U.S.-born persons stratified by race/ethnicity. MEASUREMENTS TB incidence rates, incidence rate differences, and incidence rate ratios compared with non-Hispanic White persons; excess TB cases (calculated from incidence rate differences); and the index of disparity. Analyses were stratified by sex and by attribution of TB disease to recent transmission and were adjusted for age, year, and state of residence. RESULTS In analyses of TB incidence rates for each racial/ethnic population compared with non-Hispanic White persons, incidence rate ratios were as high as 14.2 (95% CI, 13.0 to 15.5) among American Indian or Alaska Native (AI/AN) females. Relative disparities were greater for females, younger persons, and TB attributed to recent transmission. Absolute disparities were greater for males. Excess TB cases in 2011 to 2021 represented 69% (CI, 66% to 71%) and 62% (CI, 60% to 64%) of total cases for females and males, respectively. No evidence was found to indicate that incidence rate ratios decreased over time, and most relative disparity measures showed small, statistically nonsignificant increases. LIMITATION Analyses assumed complete TB case diagnosis and self-report of race/ethnicity and were not adjusted for medical comorbidities or social determinants of health. CONCLUSION There are persistent disparities in TB incidence by race/ethnicity. Relative disparities were greater for AI/AN persons, females, and younger persons, and absolute disparities were greater for males. Eliminating these disparities could reduce overall TB incidence by more than 60% among the U.S.-born population. PRIMARY FUNDING SOURCE Centers for Disease Control and Prevention.
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Affiliation(s)
- Yunfei Li
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (Y.L., M.R., N.A.S.)
| | - Mathilda Regan
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (Y.L., M.R., N.A.S.)
| | - Nicole A Swartwood
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (Y.L., M.R., N.A.S.)
| | - Terrika Barham
- Office of Health Equity, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia (T.B., R.L.M.)
| | - Garrett R Beeler Asay
- Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia (G.R.B.A., A.N.H., A.K., S.M.M., J.L.S.)
| | - Ted Cohen
- Yale School of Public Health, New Haven, Connecticut (T.C.)
| | - Andrew N Hill
- Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia (G.R.B.A., A.N.H., A.K., S.M.M., J.L.S.)
| | - C Robert Horsburgh
- Departments of Epidemiology, Biostatistics, Global Health and Medicine, Boston University Schools of Public Health and Medicine, Boston, Massachusetts (C.R.H.)
| | - Awal Khan
- Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia (G.R.B.A., A.N.H., A.K., S.M.M., J.L.S.)
| | - Suzanne M Marks
- Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia (G.R.B.A., A.N.H., A.K., S.M.M., J.L.S.)
| | - Ranell L Myles
- Office of Health Equity, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia (T.B., R.L.M.)
| | - Joshua A Salomon
- Department of Health Policy, Stanford School of Medicine, Stanford University, Stanford, California (J.A.S.)
| | - Julie L Self
- Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, Georgia (G.R.B.A., A.N.H., A.K., S.M.M., J.L.S.)
| | - Nicolas A Menzies
- Department of Global Health and Population and Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, Massachusetts (N.A.M.)
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Ekramnia M, Li Y, Haddad MB, Marks SM, Kammerer JS, Swartwood NA, Cohen T, Miller JW, Horsburgh CR, Salomon JA, Menzies NA. Estimated rates of progression to tuberculosis disease for persons infected with Mycobacterium tuberculosis in the United States. Epidemiology 2024; 35:164-173. [PMID: 38290139 PMCID: PMC10832387 DOI: 10.1097/ede.0000000000001707] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
BACKGROUND In the United States, over 80% of tuberculosis (TB) disease cases are estimated to result from reactivation of latent TB infection (LTBI) acquired more than 2 years previously ("reactivation TB"). We estimated reactivation TB rates for the US population with LTBI, overall, by age, sex, race-ethnicity, and US-born status, and for selected comorbidities (diabetes, end-stage renal disease, and HIV). METHODS We collated nationally representative data for 2011-2012. Reactivation TB incidence was based on TB cases reported to the National TB Surveillance System that were attributed to LTBI reactivation. Person-years at risk of reactivation TB were calculated using interferon-gamma release assay (IGRA) positivity from the National Health and Nutrition Examination Survey, published values for interferon-gamma release assay sensitivity and specificity, and population estimates from the American Community Survey. RESULTS For persons aged ≥6 years with LTBI, the overall reactivation rate was estimated as 0.072 (95% uncertainty interval: 0.047, 0.12) per 100 person-years. Estimated reactivation rates declined with age. Compared to the overall population, estimated reactivation rates were higher for persons with diabetes (adjusted rate ratio [aRR] = 1.6 [1.5, 1.7]), end-stage renal disease (aRR = 9.8 [5.4, 19]), and HIV (aRR = 12 [10, 13]). CONCLUSIONS In our study, individuals with LTBI faced small, non-negligible risks of reactivation TB. Risks were elevated for individuals with medical comorbidities that weaken immune function.
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Affiliation(s)
- Mina Ekramnia
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston MA, USA
| | - Yunfei Li
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston MA, USA
| | - Maryam B Haddad
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, U.S. Centers for Disease Control and Prevention, Atlanta GA, USA
| | - Suzanne M Marks
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, U.S. Centers for Disease Control and Prevention, Atlanta GA, USA
| | - J Steve Kammerer
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, U.S. Centers for Disease Control and Prevention, Atlanta GA, USA
| | - Nicole A Swartwood
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston MA, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven CT, USA
| | - Jeffrey W Miller
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston MA, USA
| | - C Robert Horsburgh
- Departments of Epidemiology, Biostatistics, and Global Health, Boston University School of Public Health and Department of Medicine, Boston University School of Medicine, Boston MA USA
| | - Joshua A Salomon
- Center for Health Policy / Center for Primary Care and Outcomes Research, Stanford University, Stanford CA, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston MA, USA
- Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston MA, USA
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Emani S, Alves K, Alves LC, da Silva DA, Oliveira PB, Castro MC, Cohen T, Couto RDM, Sanchez M, Menzies NA. Quantifying gaps in the tuberculosis care cascade in Brazil: A mathematical model study using national program data. PLoS Med 2024; 21:e1004361. [PMID: 38512968 PMCID: PMC10994550 DOI: 10.1371/journal.pmed.1004361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 04/04/2024] [Accepted: 02/16/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND In Brazil, many individuals with tuberculosis (TB) do not receive appropriate care due to delayed or missed diagnosis, ineffective treatment regimens, or loss-to-follow-up. This study aimed to estimate the health losses and TB program costs attributable to each gap in the care cascade for TB disease in Brazil. METHODS AND FINDINGS We constructed a Markov model simulating the TB care cascade and lifetime health outcomes (e.g., death, cure, postinfectious sequelae) for individuals developing TB disease in Brazil. We stratified the model by age, human immunodeficiency virus (HIV) status, drug resistance, state of residence, and disease severity, and developed a parallel model for individuals without TB that receive a false-positive TB diagnosis. Models were fit to data (adult and pediatric) from Brazil's Notifiable Diseases Information System (SINAN) and Mortality Information System (SIM) for 2018. Using these models, we assessed current program performance and simulated hypothetical scenarios that eliminated specific gaps in the care cascade, in order to quantify incremental health losses and TB diagnosis and treatment costs along the care cascade. TB-attributable disability-adjusted life years (DALYs) were calculated by comparing changes in survival and nonfatal disability to a no-TB counterfactual scenario. We estimated that 90.0% (95% uncertainty interval [UI]: 85.2 to 93.4) of individuals with TB disease initiated treatment and 10.0% (95% UI: 7.6 to 12.5) died with TB. The average number of TB-attributable DALYs per incident TB case varied across Brazil, ranging from 2.9 (95% UI: 2.3 to 3.6) DALYs in Acre to 4.0 (95% UI: 3.3 to 4.7) DALYs in Rio Grande do Sul (national average 3.5 [95% UI: 2.8 to 4.1]). Delayed diagnosis contributed the largest health losses along the care cascade, followed by post-TB sequelae and loss to follow up from TB treatment, with TB DALYs reduced by 71% (95% UI: 65 to 76), 41% (95% UI: 36 to 49), and 10% (95% UI: 7 to 16), respectively, when these factors were eliminated. Total health system costs were largely unaffected by improvements in the care cascade, with elimination of treatment failure reducing attributable costs by 3.1% (95% UI: 1.5 to 5.4). TB diagnosis and treatment of false-positive individuals accounted for 10.2% (95% UI: 3.9 to 21.7) of total programmatic costs but contributed minimally to health losses. Several assumptions were required to interpret programmatic data for the analysis, and we were unable to estimate the contribution of social factors to care cascade outcomes. CONCLUSIONS In this study, we observed that delays to diagnosis, post-disease sequelae and treatment loss to follow-up were primary contributors to the TB burden of disease in Brazil. Reducing delays to diagnosis, improving healthcare after TB cure, and reducing treatment loss to follow-up should be prioritized to improve the burden of TB disease in Brazil.
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Affiliation(s)
- Sivaram Emani
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Kleydson Alves
- National Tuberculosis Programme, Ministry of Health, Brasilia, Brazil
| | | | | | | | - Marcia C. Castro
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston Massachusetts, United States of America
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | | | - Mauro Sanchez
- Health and Environment Surveillance Secretariat, Ministry of Health, Brasilia, Brazil
- Department of Public Health, University of Brasilia, Brasilia, Brazil
| | - Nicolas A. Menzies
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston Massachusetts, United States of America
- Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
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Sumner T, Clark RA, Mukandavire C, Portnoy A, Weerasuriya CK, Bakker R, Scarponi D, Hatherill M, Menzies NA, White RG. Modelling the health and economic impacts ofM72/AS01 E vaccination and BCG-revaccination: Estimates for South Africa. Vaccine 2024; 42:1311-1318. [PMID: 38307747 DOI: 10.1016/j.vaccine.2024.01.072] [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] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/11/2024] [Accepted: 01/22/2024] [Indexed: 02/04/2024]
Abstract
BACKGROUND Tuberculosis remains a major public health problem in South Africa, with an estimated 300,000 cases and 55,000 deaths in 2021. New tuberculosis vaccines could play an important role in reducing this burden. Phase IIb trials have suggested efficacy of the M72/AS01E vaccine candidate and BCG-revaccination. The potential population impact of these vaccines is unknown. METHODS We used an age-stratified transmission model of tuberculosis, calibrated to epidemiological data from South Africa, to estimate the potential health and economic impact of M72/AS01E vaccination and BCG-revaccination. We simulated M72/AS01E vaccination scenarios over the period 2030-2050 and BCG-revaccination scenarios over the period 2025-2050. We explored a range of product characteristics and delivery strategies. We calculated reductions in tuberculosis cases and deaths and costs and cost-effectiveness from health-system and societal perspectives. FINDINGS M72/AS01E vaccination may have a larger impact than BCG-revaccination, averting approximately 80% more cases and deaths by 2050. Both vaccines were found to be cost-effective or cost saving (compared to no new vaccine) across a range of vaccine characteristics and delivery strategies from both the health system and societal perspective. The impact of M72/AS01E is dependent on the assumed efficacy of the vaccine in uninfected individuals. Extending BCG-revaccination to HIV-infected individuals on ART increased health impact by approximately 15%, but increased health system costs by approximately 70%. INTERPRETATION Our results show that M72/AS01E vaccination or BCG-revaccination could be cost-effective in South Africa. However, there is considerable uncertainty in the estimated impact and costs due to uncertainty in vaccine characteristics and the choice of delivery strategy. FUNDING This work was funded by the Bill & Melinda Gates Foundation (INV-001754). This work used the Cirrus UK National Tier-2 HPC Service at EPCC (https://www.cirrus.ac.uk) funded by the University of Edinburgh and EPSRC (EP/P020267/1).
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Affiliation(s)
- Tom Sumner
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom.
| | - Rebecca A Clark
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom; Vaccine Centre, London School of Hygiene and Tropical Medicine, United Kingdom
| | - Christinah Mukandavire
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom
| | - Allison Portnoy
- Department of Global Health, Boston University School of Public Health, Boston, USA; Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Chathika K Weerasuriya
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom
| | - Roel Bakker
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom; KNCV Tuberculosis Foundation, USA
| | - Danny Scarponi
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom
| | - Mark Hatherill
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, South Africa
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, USA
| | - Richard G White
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, United Kingdom; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, United Kingdom; Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom
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Klaassen F, Holm RH, Smith T, Cohen T, Bhatnagar A, Menzies NA. Predictive power of wastewater for nowcasting infectious disease transmission: A retrospective case study of five sewershed areas in Louisville, Kentucky. Environ Res 2024; 240:117395. [PMID: 37838198 PMCID: PMC10863376 DOI: 10.1016/j.envres.2023.117395] [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] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/29/2023] [Accepted: 10/11/2023] [Indexed: 10/16/2023]
Abstract
BACKGROUND Epidemiological nowcasting traditionally relies on count surveillance data. The availability and quality of such count data may vary over time, limiting representation of true infections. Wastewater data correlates with traditional surveillance data and may provide additional value for nowcasting disease trends. METHODS We obtained SARS-CoV-2 case, death, wastewater, and serosurvey data for Jefferson County, Kentucky (USA), between August 2020 and March 2021, and parameterized an existing nowcasting model using combinations of these data. We assessed the predictive performance and variability at the sewershed level and compared the effects of adding or replacing wastewater data to case and death reports. FINDINGS Adding wastewater data minimally improved the predictive performance of nowcasts compared to a model fitted to case and death data (Weighted Interval Score (WIS) 0.208 versus 0.223), and reduced the predictive performance compared to a model fitted to deaths data (WIS 0.517 versus 0.500). Adding wastewater data to deaths data improved the nowcasts agreement to estimates from models using cases and deaths data. These findings were consistent across individual sewersheds as well as for models fit to the aggregated total data of 5 sewersheds. Retrospective reconstructions of epidemiological dynamics created using different combinations of data were in general agreement (coverage >75%). INTERPRETATION These findings show wastewater data may be valuable for infectious disease nowcasting when clinical surveillance data are absent, such as early in a pandemic or in low-resource settings where systematic collection of epidemiologic data is difficult.
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Affiliation(s)
- Fayette Klaassen
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
| | - Rochelle H Holm
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA.
| | - Ted Smith
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA.
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, School of Medicine, University of Louisville, Louisville, KY, USA.
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA; Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA.
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Sinha P, Dauphinais M, Carwile ME, Horsburgh CR, Menzies NA. In-kind nutritional supplementation for household contacts of persons with tuberculosis would be cost-effective for reducing tuberculosis incidence and mortality in India: a modeling study. medRxiv 2024:2023.12.30.23300673. [PMID: 38260435 PMCID: PMC10802630 DOI: 10.1101/2023.12.30.23300673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Background Undernutrition is the leading cause of tuberculosis (TB) globally, but nutritional interventions are often considered cost prohibitive. The RATIONS study demonstrated that nutritional support provided to household contacts of persons with TB can reduce TB incidence. However, the long-term cost-effectiveness of this intervention is unclear. Methods We assessed the cost-effectiveness of a RATIONS-style intervention (daily 750 kcal dietary supplementation and multi-micronutrient tablet). Using a Markov state transition model we simulated TB incidence, treatment, and TB-attributable mortality among household contacts receiving the RATIONS intervention, as compared to no nutritional support. We calculated health outcomes (TB cases, TB deaths, and disability-adjusted life years [DALYs]) over the lifetime of intervention recipients and assessed costs from government and societal perspectives. We tested the robustness of results to parameter changes via deterministic and probabilistic sensitivity analysis. Findings Over two years, household contacts receiving the RATIONS intervention would experience 39% (95% uncertainty interval (UI): 23-52) fewer TB cases and 59% (95% UI: 44-69) fewer TB deaths. The intervention was estimated to avert 13,775 (95% UI: 9036-20,199) TB DALYs over the lifetime of the study cohort comprising 100,000 household contacts and was cost-effective from both government (incremental cost-effectiveness ratio: $229 per DALY averted [95% UI: 133-387]) and societal perspectives ($184 per DALY averted [95% UI: 83-344]). The results were most sensitive to the cost of the nutritional supplement. Interpretation Prompt nutritional support for household contacts of persons with TB disease would be cost-effective in reducing TB incidence and mortality in India. Summary Undernutrition is the leading cause of tuberculosis in India. Using a Markov state-transition model, we found that food baskets for household contacts of persons with tuberculosis would be cost-effective in reducing tuberculosis incidence and mortality in India. Research in context Evidence before this study: Undernutrition is the leading risk factor for TB worldwide. Recently, the RATIONS study demonstrated a roughly 40% reduction in incident TB among household contacts who received in-kind macronutrient and micronutrient supplementation. Added value of this study: Although the RATIONS study demonstrated a dramatic reduction in incident TB, it is unclear if nutritional interventions to prevent TB are cost-effective. Previously, only one cost-effectiveness analysis of nutritional interventions for household contacts has been published. Due to lack of published data, that study had to make assumptions regarding the impact of nutritional interventions on TB incidence and mortality. In this study, we conducted an economic evaluation of a RATIONS-style intervention to reduce incident TB and mortality in India using observed data. Implications of all the available evidence: In-kind nutritional supplementation for household contacts of individuals with TB disease would be cost-effective in reducing incident TB and TB mortality, particularly if TB programs leverage economies of scale to bring down the cost of the nutritional intervention.
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Regan M, Li Y, Swartwood NA, Barham T, Asay GRB, Cohen T, Hill AN, Horsburgh CR, Khan A, Marks SM, Myles RL, Salomon JA, Self JL, Menzies NA. Racial and ethnic disparities in diagnosis and treatment outcomes among US-born people diagnosed with tuberculosis, 2003-19: an analysis of national surveillance data. Lancet Public Health 2024; 9:e47-e56. [PMID: 38176842 DOI: 10.1016/s2468-2667(23)00276-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 10/21/2023] [Accepted: 11/01/2023] [Indexed: 01/06/2024]
Abstract
BACKGROUND Persistent racial and ethnic disparities in tuberculosis incidence exist in the USA, however, less is known about disparities along the tuberculosis continuum of care. This study aimed to describe how race and ethnicity are associated with tuberculosis diagnosis and treatment outcomes. METHODS In this analysis of national surveillance data, we extracted data from the US National Tuberculosis Surveillance System on US-born patients with tuberculosis during 2003-19. To estimate the association between race and ethnicity and tuberculosis diagnosis (diagnosis after death, cavitation, and sputum smear positivity) and treatment outcomes (treatment for more than 12 months, treatment discontinuation, and death during treatment), we fitted log-binomial regression models adjusting for calendar year, sex, age category, and regional division. Race and ethnicity were defined based on US Census Bureau classification as White, Black, Hispanic, Asian, American Indian or Alaska Native, Native Hawaiian or Pacific Islander, and people of other ethnicities. We quantified racial and ethnic disparities as adjusted relative risks (aRRs) using non-Hispanic White people as the reference group. We also calculated the Index of Disparity as a summary measure that quantifies the dispersion in a given outcome across all racial and ethnic groups, relative to the population mean. We estimated time trends in each outcome to evaluate whether disparities were closing or widening. FINDINGS From 2003 to 2019, there were 72 809 US-born individuals diagnosed with tuberculosis disease of whom 72 369 (35·7% women and 64·3% men) could be included in analyses. We observed an overall higher risk of any adverse outcome (defined as diagnosis after death, treatment discontinuation, or death during treatment) for non-Hispanic Black people (aRR 1·27, 95% CI 1·22-1·32), Hispanic people (1·20, 1·14-1·27), and American Indian or Alaska Native people (1·24, 1·12-1·37), relative to non-Hispanic White people. The Index of Disparity for this summary outcome remained unchanged over the study period. INTERPRETATION This study, based on national surveillance data, indicates racial and ethnic disparaties among US-born tuberculosis patients along the tuberculosis continuum of care. Initiatives are needed to reduce diagnostic delays and improve treatment outcomes for US-born racially marginalised people in the USA. FUNDING US Centers for Disease Control and Prevention.
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Affiliation(s)
- Mathilda Regan
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA.
| | - Yunfei Li
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Nicole A Swartwood
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Terrika Barham
- Office of Health Equity, National Center for HIV, Viral Hepatitis, STD, and TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA
| | - Garrett R Beeler Asay
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA
| | - Ted Cohen
- Yale School of Public Health, New Haven, CT, USA
| | - Andrew N Hill
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA
| | - C Robert Horsburgh
- Departments of Epidemiology, Biostatistics, Global Health, and Medicine, Boston University Schools of Public Health and Medicine, Boston, MA, USA
| | - Awal Khan
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA
| | - Suzanne M Marks
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA
| | - Ranell L Myles
- Office of Health Equity, National Center for HIV, Viral Hepatitis, STD, and TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA
| | - Joshua A Salomon
- Department of Health Policy, Stanford University, Stanford, CA, USA
| | - Julie L Self
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB prevention, US Centers for Disease Control and Prevention, Atlanta, GE, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA
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Chang W, Cohen J, Wang DQ, Abdulla S, Mahende MK, Gavana T, Scott V, Msuya HM, Mwanyika-Sando M, Njau RJA, Lu SN, Temu S, Masanja H, Anthony W, Aregawi W M, Sunder N, Kun T, Bruxvoort K, Kitau J, Kihwele F, Chila G, Michael M, Castro M, Menzies NA, Kim S, Ning X, Zhou XN, Chaki P, Mlacha YP. Impact of 1,7-malaria reactive community-based testing and response (1,7-mRCTR) approach on malaria prevalence in Tanzania. Infect Dis Poverty 2023; 12:116. [PMID: 38105258 PMCID: PMC10726614 DOI: 10.1186/s40249-023-01166-0] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/20/2023] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Progress in malaria control has stalled in recent years and innovative surveillance and response approaches are needed to accelerate malaria control and elimination efforts in endemic areas of Africa. Building on a previous China-UK-Tanzania pilot study on malaria control, this study aimed to assess the impact of the 1,7-malaria Reactive Community-Based Testing and Response (1,7-mRCTR) approach implemented over two years in three districts of Tanzania. METHODS The 1,7-mRCTR approach provides community-based malaria testing via rapid diagnostic tests and treatment in villages with the highest burden of malaria incidence based on surveillance data from health facilities. We used a difference-in-differences quasi-experimental design with linear probability models and two waves of cross-sectional household surveys to assess the impact of 1,7-mRCTR on malaria prevalence. We conducted sensitivity analyses to assess the robustness of our results, examined how intervention effects varied in subgroups, and explored alternative explanations for the observed results. RESULTS Between October 2019 and September 2021, 244,771 community-based malaria rapid tests were completed in intervention areas, and each intervention village received an average of 3.85 rounds of 1-7mRCTR. Malaria prevalence declined from 27.4% at baseline to 11.7% at endline in the intervention areas and from 26.0% to 16.0% in the control areas. 1,7-mRCTR was associated with a 4.5-percentage-point decrease in malaria prevalence (95% confidence interval: - 0.067, - 0.023), equivalent to a 17% reduction from the baseline. In Rufiji, a district characterized by lower prevalence and where larviciding was additionally provided, 1,7-mRCTR was associated with a 63.9% decline in malaria prevalence. CONCLUSIONS The 1,7-mRCTR approach reduced malaria prevalence. Despite implementation interruptions due to the COVID-19 pandemic and supply chain challenges, the study provided novel evidence on the effectiveness of community-based reactive approaches in moderate- to high-endemicity areas and demonstrated the potential of South-South cooperation in tackling global health challenges.
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Affiliation(s)
- Wei Chang
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jessica Cohen
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Duo-Quan Wang
- Chinese Center for Disease Control and Prevention, National Institute of Parasitic Diseases, Shanghai, People's Republic of China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- Chinese Center for Tropical Diseases Research, Shanghai, People's Republic of China
- WHO Collaborating Centre for Tropical Diseases, Shanghai, People's Republic of China
- National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, People's Republic of China
- Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, People's Republic of China
| | - Salim Abdulla
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | - Muhidin Kassim Mahende
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | - Tegemeo Gavana
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | - Valerie Scott
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Hajirani M Msuya
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | | | - Ritha John A Njau
- Muhimbili University of Health and Allied Sciences, Dar es Salaam, Tanzania
| | - Shen-Ning Lu
- Chinese Center for Disease Control and Prevention, National Institute of Parasitic Diseases, Shanghai, People's Republic of China
- Chinese Center for Tropical Diseases Research, Shanghai, People's Republic of China
- WHO Collaborating Centre for Tropical Diseases, Shanghai, People's Republic of China
- National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, People's Republic of China
- Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, People's Republic of China
| | - Silas Temu
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | - Honorati Masanja
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | | | - Maru Aregawi W
- Global Malaria Programme, World Health Organization, Geneva, Switzerland
| | | | - Tang Kun
- Vanke School of Public Health, Tsinghua University, Beijing, People's Republic of China
| | - Katia Bruxvoort
- School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jovin Kitau
- Global Malaria Programme, World Health Organization, Geneva, Switzerland
| | - Fadhila Kihwele
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | - Godlove Chila
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | - Mihayo Michael
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
| | - Marcia Castro
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Sein Kim
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xiao Ning
- Chinese Center for Disease Control and Prevention, National Institute of Parasitic Diseases, Shanghai, People's Republic of China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- Chinese Center for Tropical Diseases Research, Shanghai, People's Republic of China
- WHO Collaborating Centre for Tropical Diseases, Shanghai, People's Republic of China
- National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, People's Republic of China
- Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, People's Republic of China
| | - Xiao-Nong Zhou
- Chinese Center for Disease Control and Prevention, National Institute of Parasitic Diseases, Shanghai, People's Republic of China
- School of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
- Chinese Center for Tropical Diseases Research, Shanghai, People's Republic of China
- WHO Collaborating Centre for Tropical Diseases, Shanghai, People's Republic of China
- National Center for International Research on Tropical Diseases, Ministry of Science and Technology, Shanghai, People's Republic of China
- Key Laboratory of Parasite and Vector Biology, Ministry of Health, Shanghai, 200025, People's Republic of China
| | - Prosper Chaki
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania
- The Pan-African Mosquito Control Association (PAMCA), KEMRI Headquarters, Mbagathi Road, Nairobi, 54840-00200, Kenya
| | - Yeromin P Mlacha
- Ifakara Health Institute, #5 Ifakara Street, Plot 463 Mikocheni, P.O. Box 78 373, Dar es Salaam, United Republic of Tanzania.
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14
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Havumaki J, Warren JL, Zelner J, Menzies NA, Calderon R, Contreras C, Lecca L, Becerra MC, Murray M, Cohen T. Spatially-targeted tuberculosis screening has limited impact beyond household contact tracing in Lima, Peru: A model-based analysis. PLoS One 2023; 18:e0293519. [PMID: 37903091 PMCID: PMC10615320 DOI: 10.1371/journal.pone.0293519] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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: 10/21/2022] [Accepted: 10/15/2023] [Indexed: 11/01/2023] Open
Abstract
Mathematical models have suggested that spatially-targeted screening interventions for tuberculosis may efficiently accelerate disease control, but empirical data supporting these findings are limited. Previous models demonstrating substantial impacts of these interventions have typically simulated large-scale screening efforts and have not attempted to capture the spatial distribution of tuberculosis in households and communities at a high resolution. Here, we calibrate an individual-based model to the locations of case notifications in one district of Lima, Peru. We estimate the incremental efficiency and impact of a spatially-targeted interventions used in combination with household contact tracing (HHCT). Our analysis reveals that HHCT is relatively efficient with a median of 40 (Interquartile Range: 31.7 to 49.9) household contacts required to be screened to detect a single case of active tuberculosis. However, HHCT has limited population impact, producing a median incidence reduction of only 3.7% (Interquartile Range: 5.8% to 1.9%) over 5 years. In comparison, spatially targeted screening (which we modeled as active case finding within high tuberculosis prevalence areas 100 m2 grid cell) is far less efficient, requiring evaluation of ≈12 times the number of individuals as HHCT to find a single individual with active tuberculosis. Furthermore, the addition of the spatially targeted screening effort produced only modest additional reductions in tuberculosis incidence over the 5 year period (≈1.3%) in tuberculosis incidence. In summary, we found that HHCT is an efficient approach for tuberculosis case finding, but has limited population impact. Other screening approaches which target areas of high tuberculosis prevalence are less efficient, and may have limited impact unless very large numbers of individuals can be screened.
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Affiliation(s)
- Joshua Havumaki
- Department of Epidemiology of Microbial Diseases, Yale University, New Haven, CT, United States of America
| | - Joshua L. Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States of America
| | - Jon Zelner
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States of America
- Center for Social Epidemiology and Population Health, University of Michigan School of Public Health, Ann Arbor, MI, United States of America
| | - Nicolas A. Menzies
- Department of Global Health and Population, Harvard T. H. Chan, School of Public Health, Boston, MA, United States of America
| | - Roger Calderon
- Socios en Salud Sucursal Peru, Lima, Peru
- Programa Acadêmico de Tuberculose, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | | | - Leonid Lecca
- Department of Global Health and Population, Harvard T. H. Chan, School of Public Health, Boston, MA, United States of America
- Socios en Salud Sucursal Peru, Lima, Peru
| | - Mercedes C. Becerra
- Department of Global Health and Population, Harvard T. H. Chan, School of Public Health, Boston, MA, United States of America
| | - Megan Murray
- Department of Global Health and Population, Harvard T. H. Chan, School of Public Health, Boston, MA, United States of America
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale University, New Haven, CT, United States of America
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15
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Menzies NA, Allwood BW, Dean AS, Dodd PJ, Houben RMGJ, James LP, Knight GM, Meghji J, Nguyen LN, Rachow A, Schumacher SG, Mirzayev F, Cohen T. Global burden of disease due to rifampicin-resistant tuberculosis: a mathematical modeling analysis. Nat Commun 2023; 14:6182. [PMID: 37794037 PMCID: PMC10550952 DOI: 10.1038/s41467-023-41937-9] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 09/22/2023] [Indexed: 10/06/2023] Open
Abstract
In 2020, almost half a million individuals developed rifampicin-resistant tuberculosis (RR-TB). We estimated the global burden of RR-TB over the lifetime of affected individuals. We synthesized data on incidence, case detection, and treatment outcomes in 192 countries (99.99% of global tuberculosis). Using a mathematical model, we projected disability-adjusted life years (DALYs) over the lifetime for individuals developing tuberculosis in 2020 stratified by country, age, sex, HIV, and rifampicin resistance. Here we show that incident RR-TB in 2020 was responsible for an estimated 6.9 (95% uncertainty interval: 5.5, 8.5) million DALYs, 44% (31, 54) of which accrued among TB survivors. We estimated an average of 17 (14, 21) DALYs per person developing RR-TB, 34% (12, 56) greater than for rifampicin-susceptible tuberculosis. RR-TB burden per 100,000 was highest in former Soviet Union countries and southern African countries. While RR-TB causes substantial short-term morbidity and mortality, nearly half of the overall disease burden of RR-TB accrues among tuberculosis survivors. The substantial long-term health impacts among those surviving RR-TB disease suggest the need for improved post-treatment care and further justify increased health expenditures to prevent RR-TB transmission.
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Affiliation(s)
- Nicolas A Menzies
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, USA.
- Center for Health Decision Science, Harvard T. H. Chan School of Public Health, Boston, USA.
| | - Brian W Allwood
- Division of Pulmonology, Department of Medicine, Stellenbosch University & Tygerberg Hospital, Cape Town, South Africa
| | - Anna S Dean
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Pete J Dodd
- School of Health and Related Research, University of Sheffield, Sheffield, United Kingdom
| | - Rein M G J Houben
- TB Modelling Group, TB Centre, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Lyndon P James
- Center for Health Decision Science, Harvard T. H. Chan School of Public Health, Boston, USA
- Harvard Interfaculty Initiative in Health Policy, Harvard University, Cambridge, USA
| | - Gwenan M Knight
- AMR Centre, Department of Infectious Disease Epidemiology, EPH, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Jamilah Meghji
- National Heart & Lung Institute, Imperial College London, London, United Kingdom
| | - Linh N Nguyen
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Andrea Rachow
- Division of Infectious Diseases and Tropical Medicine, Medical Centre of the University of Munich (LMU), Munich, Germany
- German Centre for Infection Research (DZIF), Partner Site Munich, Munich, Germany
- Unit Global Health, Helmholtz Zentrum München, German Research Center for Environmental Health (HMGU), Neuherberg, Germany
| | - Samuel G Schumacher
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Fuad Mirzayev
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
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Portnoy A, Yamanaka T, Nguhiu P, Nishikiori N, Garcia Baena I, Floyd K, Menzies NA. Costs incurred by people receiving tuberculosis treatment in low-income and middle-income countries: a meta-regression analysis. Lancet Glob Health 2023; 11:e1640-e1647. [PMID: 37734806 PMCID: PMC10522775 DOI: 10.1016/s2214-109x(23)00369-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 07/20/2023] [Accepted: 07/25/2023] [Indexed: 09/23/2023]
Abstract
BACKGROUND People accessing and completing treatment for tuberculosis can face large economic costs, even when treatment is provided free of charge. The WHO End TB Strategy targets the elimination of catastrophic costs among tuberculosis-affected households. While low-income and middle-income countries (LMICs) represent 99% of global tuberculosis cases, only 29 of 135 LMICs had conducted national surveys of costs for patients with tuberculosis by December, 2022. We estimated costs for patients with tuberculosis in countries that have not conducted a national survey, to provide evidence on the economic burden of tuberculosis in these settings and inform estimates of global economic burden. METHODS We extracted data from 22 national surveys of costs faced by patients with tuberculosis that were completed across 2015-22 and met inclusion criteria. Using a Bayesian meta-regression approach, we used these data and covariate data for all 135 LMICs to estimate per-patient costs (2021 US$) by cost category (ie, direct medical, direct non-medical, and indirect), country, drug resistance, and household income quintile. We also estimated the proportion of households experiencing catastrophic total costs (defined as >20% of annual household income) as a result of tuberculosis disease. FINDINGS Across LMICs, mean direct medical costs incurred by patients with tuberculosis were estimated as US$211 (95% uncertainty interval 154-302), direct non-medical costs were $512 (428-620), and indirect costs were $530 (423-663) per episode of tuberculosis. Overall, per-patient costs were $1253 (1127-1417). Estimated proportions of tuberculosis-affected households experiencing catastrophic total costs ranged from 75·2% (70·3-80·0) in the poorest quintile to 42·5% (34·3-51·5) in the richest quintile, compared with 54·9% (47·0-63·2) overall. INTERPRETATION Tuberculosis diagnosis and treatment impose substantial costs on affected households. Eliminating these economic losses is crucial for removing barriers to accessing tuberculosis diagnosis and completing treatment among affected households and achieving the targets set in WHO's End TB Strategy. FUNDING World Health Organization.
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Affiliation(s)
- Allison Portnoy
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA; Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA.
| | - Takuya Yamanaka
- Global TB Programme, World Health Organization, Geneva, Switzerland
| | - Peter Nguhiu
- Global TB Programme, World Health Organization, Geneva, Switzerland
| | | | | | - Katherine Floyd
- Global TB Programme, World Health Organization, Geneva, Switzerland
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA; Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA
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17
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Clark RA, Portnoy A, Weerasuriya CK, Sumner T, Bakker R, Harris RC, Rade K, Mattoo SK, Tumu D, Menzies NA, White RG. The potential health and economic impacts of new tuberculosis vaccines under varying delivery strategies in Delhi and Gujarat, India: a modelling study. medRxiv 2023:2023.09.27.23296211. [PMID: 37808744 PMCID: PMC10557803 DOI: 10.1101/2023.09.27.23296211] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Background India has the largest tuberculosis burden globally, but this burden varies nationwide. All-age tuberculosis prevalence in 2021 ranged from 747/100,000 in Delhi to 137/100,000 in Gujarat. Previous modelling has demonstrated the benefits and costs of introducing novel tuberculosis vaccines in India overall. However, no studies have compared the potential impact of tuberculosis vaccines in regions within India with differing tuberculosis disease and infection prevalence. We used mathematical modelling to investigate how the health and economic impact of two potential tuberculosis vaccines, M72/AS01E and BCG-revaccination, could differ in Delhi and Gujarat under varying delivery strategies. Methods We applied a compartmental tuberculosis model separately for Delhi (higher disease and infection prevalence) and Gujarat (lower disease and infection prevalence), and projected epidemiological trends to 2050 assuming no new vaccine introduction. We simulated M72/AS01E and BCG-revaccination scenarios varying target ages and vaccine characteristics. We estimated cumulative cases, deaths, and disability-adjusted life years averted between 2025-2050 compared to the no-new-vaccine scenario and compared incremental cost-effectiveness ratios to three cost-effectiveness thresholds. Results M72/AS01E averted a higher proportion of tuberculosis cases than BCG-revaccination in both regions (Delhi: 16.0% vs 8.3%, Gujarat: 8.5% vs 5.1%) and had higher vaccination costs (Delhi: USD$118 million vs USD$27 million, Gujarat: US$366 million vs US$97 million). M72/AS01E in Delhi could be cost-effective, or even cost-saving, for all modelled vaccine characteristics. M72/AS01E could be cost-effective in Gujarat, unless efficacy was assumed only for those with current infection at vaccination. BCG-revaccination could be cost-effective, or cost-saving, in both regions for all modelled vaccine scenarios. Discussion M72/AS01E and BCG-revaccination could be impactful and cost-effective in Delhi and Gujarat. Differences in impact, costs, and cost-effectiveness between vaccines and regions, were determined partly by differences in disease and infection prevalence, and demography. Age-specific regional estimates of infection prevalence could help to inform delivery strategies for vaccines that may only be effective in people with a particular infection status. Evidence on the mechanism of effect of M72/AS01E and its effectiveness in uninfected individuals, which were important drivers of impact and cost-effectiveness, particularly in Gujarat, are also key to improve estimates of population-level impact.
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Affiliation(s)
- Rebecca A Clark
- TB Modelling Group and TB Centre, LSHTM
- Centre for the Mathematical Modelling of Infectious Diseases, LSHTM
- Department of Infectious Disease Epidemiology, LSHTM
- Vaccine Centre, LSHTM
| | - Allison Portnoy
- Department of Global Health, Boston University School of Public Health
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health
| | - Chathika K Weerasuriya
- TB Modelling Group and TB Centre, LSHTM
- Centre for the Mathematical Modelling of Infectious Diseases, LSHTM
- Department of Infectious Disease Epidemiology, LSHTM
| | - Tom Sumner
- TB Modelling Group and TB Centre, LSHTM
- Centre for the Mathematical Modelling of Infectious Diseases, LSHTM
- Department of Infectious Disease Epidemiology, LSHTM
| | - Roel Bakker
- TB Modelling Group and TB Centre, LSHTM
- Centre for the Mathematical Modelling of Infectious Diseases, LSHTM
- Department of Infectious Disease Epidemiology, LSHTM
- KNCV Tuberculosis Foundation
| | - Rebecca C Harris
- TB Modelling Group and TB Centre, LSHTM
- Centre for the Mathematical Modelling of Infectious Diseases, LSHTM
- Department of Infectious Disease Epidemiology, LSHTM
- Sanofi Pasteur, Singapore
| | | | - Sanjay Kumar Mattoo
- Central TB Division, National Tuberculosis Elimination Program, MoHFW Govt of India. New Delhi, India
| | - Dheeraj Tumu
- World Health Organization, India
- Central TB Division, National Tuberculosis Elimination Program, MoHFW Govt of India. New Delhi, India
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health
| | - Richard G White
- TB Modelling Group and TB Centre, LSHTM
- Centre for the Mathematical Modelling of Infectious Diseases, LSHTM
- Department of Infectious Disease Epidemiology, LSHTM
- Vaccine Centre, LSHTM
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18
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Rönn MM, Menzies NA, Salomon JA. Vaccination and Voting Patterns in the U.S.: Analysis of COVID-19 and Flu Surveys From 2010 to 2022. Am J Prev Med 2023; 65:458-466. [PMID: 36893952 PMCID: PMC9991323 DOI: 10.1016/j.amepre.2023.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/09/2023]
Abstract
INTRODUCTION The study assessed the relationship between COVID-19 and influenza (flu) vaccination and voting patterns during the pandemic and the time trends between flu vaccination and voting patterns. METHODS Flu and COVID-19 vaccination coverage were analyzed using National Immunization Surveys for flu (Years 2010-2022) and COVID-19 (National Immunization Surveys Adult COVID-19 Module 2021-2022), Centers for Disease Control and Prevention surveillance of COVID-19 vaccination coverage (2021-2022) and U.S. COVID-19 Trends and Impact Survey (2021-2022). The study described the correlations between state-level COVID-19 and flu vaccination coverage, examined individual-level characteristics of vaccination for COVID-19 and for flu using logistic regression (COVID-19 Trends and Impact Survey May-June 2022), and analyzed flu vaccination coverage by age (National Immunization Surveys for flu 2010-2022) and its relationship with voting patterns. RESULTS There was a strong correlation between state-level COVID-19 vaccination coverage and voting share for the Democratic candidate in the 2020 presidential elections. COVID-19 vaccination coverage in June 2022 was higher than flu vaccination coverage, and it had a stronger correlation with voting patterns (R=0.90 vs R=0.60 in COVID-19 Trends and Impact Survey). Vaccinated people were more likely to be living in a county where the majority voted for the Democratic candidate in 2020 elections both for COVID-19 (adjusted OR=1.77, 95% CI=1.71, 1.84) and for flu (adjusted OR=1.27, 95% CI=1.23, 1.31). There is a longstanding correlation between voting patterns and flu vaccination coverage, which varies by age, with the strongest correlation in the youngest ages. CONCLUSIONS There are existing prepandemic patterns between vaccination coverage and voting patterns. The findings align with research that has identified an association between adverse health outcomes and the political environment in the U.S.
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Affiliation(s)
- Minttu M Rönn
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Joshua A Salomon
- Department of Health Policy, School of Medicine, Stanford University, Stanford, California
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19
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Swartwood NA, Testa C, Cohen T, Marks SM, Hill AN, Beeler Asay G, Cochran J, Cranston K, Randall LM, Tibbs A, Horsburgh CR, Salomon JA, Menzies NA. Tabby2: a user-friendly web tool for forecasting state-level TB outcomes in the United States. BMC Med 2023; 21:331. [PMID: 37649031 PMCID: PMC10469407 DOI: 10.1186/s12916-023-02785-y] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 02/13/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND In the United States, the tuberculosis (TB) disease burden and associated factors vary substantially across states. While public health agencies must choose how to deploy resources to combat TB and latent tuberculosis infection (LTBI), state-level modeling analyses to inform policy decisions have not been widely available. METHODS We developed a mathematical model of TB epidemiology linked to a web-based user interface - Tabby2. The model is calibrated to epidemiological and demographic data for the United States, each U.S. state, and the District of Columbia. Users can simulate pre-defined scenarios describing approaches to TB prevention and treatment or create their own intervention scenarios. Location-specific results for epidemiological outcomes, service utilization, costs, and cost-effectiveness are reported as downloadable tables and customizable visualizations. To demonstrate the tool's functionality, we projected trends in TB outcomes without additional intervention for all 50 states and the District of Columbia. We further undertook a case study of expanded treatment of LTBI among non-U.S.-born individuals in Massachusetts, covering 10% of the target population annually over 2025-2029. RESULTS Between 2022 and 2050, TB incidence rates were projected to decline in all states and the District of Columbia. Incidence projections for the year 2050 ranged from 0.03 to 3.8 cases (median 0.95) per 100,000 persons. By 2050, we project that majority (> 50%) of TB will be diagnosed among non-U.S.-born persons in 46 states and the District of Columbia; per state percentages range from 17.4% to 96.7% (median 83.0%). In Massachusetts, expanded testing and treatment for LTBI in this population was projected to reduce cumulative TB cases between 2025 and 2050 by 6.3% and TB-related deaths by 8.4%, relative to base case projections. This intervention had an incremental cost-effectiveness ratio of $180,951 (2020 USD) per quality-adjusted life year gained from the societal perspective. CONCLUSIONS Tabby2 allows users to estimate the costs, impact, and cost-effectiveness of different TB prevention approaches for multiple geographic areas in the United States. Expanded testing and treatment for LTBI could accelerate declines in TB incidence in the United States, as demonstrated in the Massachusetts case study.
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Affiliation(s)
- Nicole A Swartwood
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, 02120, USA.
| | - Christian Testa
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Suzanne M Marks
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Andrew N Hill
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Garrett Beeler Asay
- Division of Tuberculosis Elimination, National Center for HIV, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jennifer Cochran
- Bureau of Infectious Disease and Laboratory Sciences, Massachusetts Department of Public Health, Boston, MA, USA
| | - Kevin Cranston
- Bureau of Infectious Disease and Laboratory Sciences, Massachusetts Department of Public Health, Boston, MA, USA
| | - Liisa M Randall
- Bureau of Infectious Disease and Laboratory Sciences, Massachusetts Department of Public Health, Boston, MA, USA
| | - Andrew Tibbs
- Bureau of Infectious Disease and Laboratory Sciences, Massachusetts Department of Public Health, Boston, MA, USA
| | - C Robert Horsburgh
- Departments of Epidemiology, Biostatistics, Global Health and Medicine, Boston University Schools of Public Health and Medicine, Boston, MA, USA
| | - Joshua A Salomon
- Center for Health Policy / Center for Primary Care and Outcomes Research, Stanford University, Stanford, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, 02120, USA
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Klaassen F, Chitwood MH, Cohen T, Pitzer VE, Russi M, Swartwood NA, Salomon JA, Menzies NA. Changes in Population Immunity Against Infection and Severe Disease From Severe Acute Respiratory Syndrome Coronavirus 2 Omicron Variants in the United States Between December 2021 and November 2022. Clin Infect Dis 2023; 77:355-361. [PMID: 37074868 PMCID: PMC10425195 DOI: 10.1093/cid/ciad210] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/24/2023] [Accepted: 04/04/2023] [Indexed: 04/20/2023] Open
Abstract
BACKGROUND Although a substantial fraction of the US population was infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during December 2021-February 2022, the subsequent evolution of population immunity reflects the competing influences of waning protection over time and acquisition or restoration of immunity through additional infections and vaccinations. METHODS Using a Bayesian evidence synthesis model of reported coronavirus disease 2019 (COVID-19) data (diagnoses, hospitalizations), vaccinations, and waning patterns for vaccine- and infection-acquired immunity, we estimate population immunity against infection and severe disease from SARS-CoV-2 Omicron variants in the United States, by location (national, state, county) and week. RESULTS By 9 November 2022, 97% (95%-99%) of the US population were estimated to have prior immunological exposure to SARS-CoV-2. Between 1 December 2021 and 9 November 2022, protection against a new Omicron infection rose from 22% (21%-23%) to 63% (51%-75%) nationally, and protection against an Omicron infection leading to severe disease increased from 61% (59%-64%) to 89% (83%-92%). Increasing first booster uptake to 55% in all states (current US coverage: 34%) and second booster uptake to 22% (current US coverage: 11%) would increase protection against infection by 4.5 percentage points (2.4-7.2) and protection against severe disease by 1.1 percentage points (1.0-1.5). CONCLUSIONS Effective protection against SARS-CoV-2 infection and severe disease in November 2022 was substantially higher than in December 2021. Despite this high level of protection, a more transmissible or immune evading (sub)variant, changes in behavior, or ongoing waning of immunity could lead to a new SARS-CoV-2 wave.
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Affiliation(s)
- Fayette Klaassen
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Melanie H Chitwood
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Marcus Russi
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Nicole A Swartwood
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Joshua A Salomon
- Department of Health Policy, Stanford University School of Medicine, Stanford, California, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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Clark RA, Weerasuriya CK, Portnoy A, Mukandavire C, Quaife M, Bakker R, Scarponi D, Harris RC, Rade K, Mattoo SK, Tumu D, Menzies NA, White RG. New tuberculosis vaccines in India: modelling the potential health and economic impacts of adolescent/adult vaccination with M72/AS01 E and BCG-revaccination. BMC Med 2023; 21:288. [PMID: 37542319 PMCID: PMC10403932 DOI: 10.1186/s12916-023-02992-7] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 07/20/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND India had an estimated 2.9 million tuberculosis cases and 506 thousand deaths in 2021. Novel vaccines effective in adolescents and adults could reduce this burden. M72/AS01E and BCG-revaccination have recently completed phase IIb trials and estimates of their population-level impact are needed. We estimated the potential health and economic impact of M72/AS01E and BCG-revaccination in India and investigated the impact of variation in vaccine characteristics and delivery strategies. METHODS We developed an age-stratified compartmental tuberculosis transmission model for India calibrated to country-specific epidemiology. We projected baseline epidemiology to 2050 assuming no-new-vaccine introduction, and M72/AS01E and BCG-revaccination scenarios over 2025-2050 exploring uncertainty in product characteristics (vaccine efficacy, mechanism of effect, infection status required for vaccine efficacy, duration of protection) and implementation (achieved vaccine coverage and ages targeted). We estimated reductions in tuberculosis cases and deaths by each scenario compared to the no-new-vaccine baseline, as well as costs and cost-effectiveness from health-system and societal perspectives. RESULTS M72/AS01E scenarios were predicted to avert 40% more tuberculosis cases and deaths by 2050 compared to BCG-revaccination scenarios. Cost-effectiveness ratios for M72/AS01E vaccines were around seven times higher than BCG-revaccination, but nearly all scenarios were cost-effective. The estimated average incremental cost was US$190 million for M72/AS01E and US$23 million for BCG-revaccination per year. Sources of uncertainty included whether M72/AS01E was efficacious in uninfected individuals at vaccination, and if BCG-revaccination could prevent disease. CONCLUSIONS M72/AS01E and BCG-revaccination could be impactful and cost-effective in India. However, there is great uncertainty in impact, especially given the unknowns surrounding the mechanism of effect and infection status required for vaccine efficacy. Greater investment in vaccine development and delivery is needed to resolve these unknowns in vaccine product characteristics.
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Affiliation(s)
- Rebecca A Clark
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK.
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
- Vaccine Centre, London School of Hygiene and Tropical Medicine, London, UK.
| | - Chathika K Weerasuriya
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Allison Portnoy
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA
- Department of Global Health, Boston University School of Public Health, Boston, USA
| | - Christinah Mukandavire
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Matthew Quaife
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Roel Bakker
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
- KNCV Tuberculosis Foundation, The Hague, Netherlands
| | - Danny Scarponi
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
| | - Rebecca C Harris
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
- Sanofi Pasteur, Singapore, Singapore
| | | | | | - Dheeraj Tumu
- World Health Organization, New Delhi, India
- Central TB Division, NTEP, MoHFW Govt of India, New Delhi, India
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Richard G White
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
- Vaccine Centre, London School of Hygiene and Tropical Medicine, London, UK
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Clark RA, Weerasuriya CK, Portnoy A, Mukandavire C, Quaife M, Bakker R, Scarponi D, Harris RC, Rade K, Mattoo SK, Tumu D, Menzies NA, White RG. New tuberculosis vaccines in India: Modelling the potential health and economic impacts of adolescent/adult vaccination with M72/AS01 E and BCG-revaccination. medRxiv 2023:2023.02.24.23286406. [PMID: 36865172 PMCID: PMC9980245 DOI: 10.1101/2023.02.24.23286406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
Abstract
Background India had an estimated 2.9 million tuberculosis cases and 506 thousand deaths in 2021. Novel vaccines effective in adolescents and adults could reduce this burden. M72/AS01E and BCG-revaccination have recently completed Phase IIb trials and estimates of their population-level impact are needed. We estimated the potential health and economic impact of M72/AS01E and BCG-revaccination in India and investigated the impact of variation in vaccine characteristics and delivery strategies. Methods We developed an age-stratified compartmental tuberculosis transmission model for India calibrated to country-specific epidemiology. We projected baseline epidemiology to 2050 assuming no-new-vaccine introduction, and M72/AS01E and BCG-revaccination scenarios over 2025-2050 exploring uncertainty in product characteristics (vaccine efficacy, mechanism of effect, infection status required for vaccine efficacy, duration of protection) and implementation (achieved vaccine coverage and ages targeted). We estimated reductions in tuberculosis cases and deaths by each scenario compared to no-new-vaccine introduction, as well as costs and cost-effectiveness from health-system and societal perspectives. Results M72/AS01E scenarios were predicted to avert 40% more tuberculosis cases and deaths by 2050 compared to BCG-revaccination scenarios. Cost-effectiveness ratios for M72/AS01E vaccines were around seven times higher than BCG-revaccination, but nearly all scenarios were cost-effective. The estimated average incremental cost was US$190 million for M72/AS01E and US$23 million for BCG-revaccination per year. Sources of uncertainty included whether M72/AS01E was efficacious in uninfected individuals at vaccination, and if BCG-revaccination could prevent disease. Conclusions M72/AS01E and BCG-revaccination could be impactful and cost-effective in India. However, there is great uncertainty in impact, especially given unknowns surrounding mechanism of effect and infection status required for vaccine efficacy. Greater investment in vaccine development and delivery is needed to resolve these unknowns in vaccine product characteristics.
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Affiliation(s)
- Rebecca A Clark
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
- Vaccine Centre, London School of Hygiene and Tropical Medicine
| | - Chathika K Weerasuriya
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
| | - Allison Portnoy
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Christinah Mukandavire
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
| | - Matthew Quaife
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
| | - Roel Bakker
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
- KNCV Tuberculosis Foundation
| | - Danny Scarponi
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
| | - Rebecca C Harris
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
- Sanofi Pasteur, Singapore
| | | | | | - Dheeraj Tumu
- World Health Organization, India
- Central TB Division, NTEP, MoHFW Govt of India. New Delhi, India
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, USA
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health
| | - Richard G White
- TB Modelling Group and TB Centre, London School of Hygiene and Tropical Medicine
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine
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Portnoy A, Arcand JL, Clark RA, Weerasuriya CK, Mukandavire C, Bakker R, Patouillard E, Gebreselassie N, Zignol M, Jit M, White RG, Menzies NA. The potential impact of novel tuberculosis vaccine introduction on economic growth in low- and middle-income countries: A modeling study. PLoS Med 2023; 20:e1004252. [PMID: 37432972 PMCID: PMC10335702 DOI: 10.1371/journal.pmed.1004252] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/30/2023] [Indexed: 07/13/2023] Open
Abstract
BACKGROUND Most individuals developing tuberculosis (TB) are working age adults living in low- and middle-income countries (LMICs). The resulting disability and death impact economic productivity and burden health systems. New TB vaccine products may reduce this burden. In this study, we estimated the impact of introducing novel TB vaccines on gross domestic product (GDP) growth in 105 LMICs. METHODS AND FINDINGS We adapted an existing macroeconomic model to simulate country-level GDP trends between 2020 and 2080, comparing scenarios for introduction of hypothetical infant and adolescent/adult vaccines to a no-new-vaccine counterfactual. We parameterized each scenario using estimates of TB-related mortality, morbidity, and healthcare spending from linked epidemiological and costing models. We assumed vaccines would be introduced between 2028 and 2047 and estimated incremental changes in GDP within each country from introduction to 2080, in 2020 US dollars. We tested the robustness of results to alternative analytic specifications. Both vaccine scenarios produced greater cumulative GDP in the modeled countries over the study period, equivalent to $1.6 (95% uncertainty interval: $0.8, 3.0) trillion for the adolescent/adult vaccine and $0.2 ($0.1, 0.4) trillion for the infant vaccine. These GDP gains were substantially lagged relative to the time of vaccine introduction, particularly for the infant vaccine. GDP gains resulting from vaccine introduction were concentrated in countries with higher current TB incidence and earlier vaccine introduction. Results were sensitive to secular trends in GDP growth but relatively robust to other analytic assumptions. Uncertain projections of GDP could alter these projections and affect the conclusions drawn by this analysis. CONCLUSIONS Under a range of assumptions, introducing novel TB vaccines would increase economic growth in LMICs.
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Affiliation(s)
- Allison Portnoy
- Department of Global Health, Boston University School of Public Health, Boston, Massachusetts, United States of America
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Jean-Louis Arcand
- Department of International Economics, The Graduate Institute of International and Development Studies, Geneva, Switzerland
- Fondation pour les études et recherches sur le développement international (FERDI), Clermont-Ferrand, France
- Global Development Network, New Delhi, India
- Université Mohammed VI Polytechnique, Rabat, Morocco
| | - Rebecca A. Clark
- TB Modelling Group, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Chathika K. Weerasuriya
- TB Modelling Group, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | | | - Roel Bakker
- TB Modelling Group, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- KNCV Tuberculosis Foundation, The Hague, the Netherlands
| | - Edith Patouillard
- Department of Health Systems Governance and Financing, World Health Organization, Geneva, Switzerland
| | | | - Matteo Zignol
- Global TB Programme, World Health Organization, Geneva, Switzerland
| | - Mark Jit
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- School of Public Health, University of Hong Kong, Hong Kong SAR, China
| | - Richard G. White
- TB Modelling Group, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Nicolas A. Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Portnoy A, Clark RA, Weerasuriya CK, Mukandavire C, Quaife M, Bakker R, Garcia Baena I, Gebreselassie N, Zignol M, Jit M, White RG, Menzies NA. The potential impact of novel tuberculosis vaccines on health equity and financial protection in low-income and middle-income countries. BMJ Glob Health 2023; 8:e012466. [PMID: 37438049 PMCID: PMC10347450 DOI: 10.1136/bmjgh-2023-012466] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 06/10/2023] [Indexed: 07/14/2023] Open
Abstract
INTRODUCTION One in two patients developing tuberculosis (TB) in low-income and middle-income countries (LMICs) faces catastrophic household costs. We assessed the potential financial risk protection from introducing novel TB vaccines, and how health and economic benefits would be distributed across income quintiles. METHODS We modelled the impact of introducing TB vaccines meeting the World Health Organization preferred product characteristics in 105 LMICs. For each country, we assessed the distribution of health gains, patient costs and household financial vulnerability following introduction of an infant vaccine and separately for an adolescent/adult vaccine, compared with a 'no-new-vaccine' counterfactual. Patient-incurred direct and indirect costs of TB disease exceeding 20% of annual household income were defined as catastrophic. RESULTS Over 2028-2050, the health gains resulting from vaccine introduction were greatest in lower income quintiles, with the poorest 2 quintiles in each country accounting for 56% of total LMIC TB cases averted. Over this period, the infant vaccine was estimated to avert US$5.9 (95% uncertainty interval: US$5.3-6.5) billion in patient-incurred total costs, and the adolescent/adult vaccine was estimated to avert US$38.9 (US$36.6-41.5) billion. Additionally, 3.7 (3.3-4.1) million fewer households were projected to face catastrophic costs with the infant vaccine and 22.9 (21.4-24.5) million with the adolescent/adult vaccine, with 66% of gains accruing in the poorest 2 income quintiles. CONCLUSION Under a range of assumptions, introducing novel TB vaccines would reduce income-based inequalities in the health and household economic outcomes of TB in LMICs.
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Affiliation(s)
- Allison Portnoy
- Department of Global Health, Boston University School of Public Health, Boston, MA, USA
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rebecca A Clark
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- TB Modelling Group, London School of Hygiene & Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropica Medicine, London, UK
| | - Chathika K Weerasuriya
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- TB Modelling Group, London School of Hygiene & Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropica Medicine, London, UK
| | | | - Matthew Quaife
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- TB Modelling Group, London School of Hygiene & Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropica Medicine, London, UK
| | - Roel Bakker
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- TB Modelling Group, London School of Hygiene & Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropica Medicine, London, UK
- KNCV Tuberculosis Foundation, Den Haag, The Netherlands
| | - Inés Garcia Baena
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | | | - Matteo Zignol
- Global Tuberculosis Programme, World Health Organization, Geneva, Switzerland
| | - Mark Jit
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropica Medicine, London, UK
- School of Public Health, The University of Hong Kong, Hong Kong SAR, People's Republic of China
| | - Richard G White
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
- TB Modelling Group, London School of Hygiene & Tropical Medicine, London, UK
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropica Medicine, London, UK
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Rönn MM, Li Y, Gift TL, Chesson HW, Menzies NA, Hsu K, Salomon JA. Costs, Health Benefits, and Cost-Effectiveness of Chlamydia Screening and Partner Notification in the United States, 2000-2019: A Mathematical Modeling Analysis. Sex Transm Dis 2023; 50:351-358. [PMID: 36804917 PMCID: PMC10184801 DOI: 10.1097/olq.0000000000001786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 02/05/2023] [Indexed: 02/22/2023]
Abstract
BACKGROUND Chlamydia remains a significant public health problem that contributes to adverse reproductive health outcomes. In the United States, sexually active women 24 years and younger are recommended to receive annual screening for chlamydia. In this study, we evaluated the impact of estimated current levels of screening and partner notification (PN), and the impact of screening based on guidelines on chlamydia associated sequelae, quality adjusted life years (QALYs) lost and costs. METHODS We conducted a cost-effectiveness analysis of chlamydia screening, using a published calibrated pair formation transmission model that estimated trends in chlamydia screening coverage in the United States from 2000 to 2015 consistent with epidemiological data. We used probability trees to translate chlamydial infection outcomes into estimated numbers of chlamydia-associated sequelae, QALYs lost, and health care services costs (in 2020 US dollars). We evaluated the costs and population health benefits of screening and PN in the United States for 2000 to 2015, as compared with no screening and no PN. We also estimated the additional benefits that could be achieved by increasing screening coverage to the levels indicated by the policy recommendations for 2016 to 2019, compared with screening coverage achieved by 2015. RESULTS Screening and PN from 2000 to 2015 were estimated to have averted 1.3 million (95% uncertainty interval [UI] 490,000-2.3 million) cases of pelvic inflammatory disease, 430,000 (95% UI, 160,000-760,000) cases of chronic pelvic pain, 300,000 (95% UI, 104,000-570,000) cases of tubal factor infertility, and 140,000 (95% UI, 47,000-260,000) cases of ectopic pregnancy in women. We estimated that chlamydia screening and PN cost $9700 per QALY gained compared with no screening and no PN. We estimated the full realization of chlamydia screening guidelines for 2016 to 2019 to cost $30,000 per QALY gained, compared with a scenario in which chlamydia screening coverage was maintained at 2015 levels. DISCUSSION Chlamydia screening and PN as implemented in the United States from 2000 through 2015 has substantially improved population health and provided good value for money when considering associated health care services costs. Further population health gains are attainable by increasing screening further, at reasonable cost per QALY gained.
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Affiliation(s)
- Minttu M. Rönn
- From the Harvard School of Public Health
- Harvard T.H. Chan School of Public Health, Boston, MA
| | - Yunfei Li
- Harvard T.H. Chan School of Public Health, Boston, MA
| | | | | | | | - Katherine Hsu
- Massachusetts Department of Public Health, Boston, MA
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Zhu J, Kamel H, Gupta A, Mushlin AI, Menzies NA, Gaziano TA, Rosenthal MB, Pandya A. Prioritizing Quality Measures in Acute Stroke Care : A Cost-Effectiveness Analysis. Ann Intern Med 2023; 176:649-657. [PMID: 37126821 PMCID: PMC10211083 DOI: 10.7326/m22-3186] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/03/2023] Open
Abstract
BACKGROUND The American Heart Association and American Stroke Association (AHA/ASA) endorsed 15 process measures for acute ischemic stroke (AIS) to improve the quality of care. Identifying the highest-value measures could reduce the administrative burden of quality measure adoption while retaining much of the value of quality improvement. OBJECTIVE To prioritize AHA/ASA-endorsed quality measures for AIS on the basis of health impact and cost-effectiveness. DESIGN Individual-based stroke simulation model. DATA SOURCES Published literature. TARGET POPULATION U.S. patients with incident AIS. TIME HORIZON Lifetime. PERSPECTIVE Health care sector. INTERVENTION Current versus complete (100%) implementation at the population level of quality measures endorsed by the AHA/ASA with sufficient clinical evidence (10 of 15). OUTCOME MEASURES Life-years, quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios, and incremental net health benefits. RESULTS OF BASE-CASE ANALYSIS Discounted life-years gained from complete implementation would range from 472 (tobacco use counseling) to 34 688 (early carotid imaging) for an annual AIS patient cohort. All AIS quality measures were cost-saving or highly cost-effective by AHA standards (<$50 000 per QALY for high-value care). Early carotid imaging and intravenous tissue plasminogen activator contributed the largest fraction of the total potential value of quality improvement (measured as incremental net health benefit), accounting for 72% of the total value. The top 5 quality measures accounted for 92% of the total potential value. RESULTS OF SENSITIVITY ANALYSIS A web-based user interface allows for context-specific sensitivity and scenario analyses. LIMITATION Correlations between quality measures were not incorporated. CONCLUSION Substantial variation exists in the potential net benefit of quality improvement across AIS quality measures. Benefits were highly concentrated among 5 of 10 measures assessed. Our results can help providers and payers set priorities for quality improvement efforts and value-based payments in AIS care. PRIMARY FUNDING SOURCE National Institute of Neurological Disorders and Stroke.
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Affiliation(s)
- Jinyi Zhu
- Department of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Hooman Kamel
- Clinical and Translational Neuroscience Unit, Feil Family Brain and Mind Research Institute and Department of Neurology, Weill Cornell Medicine, New York, NY, USA
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Alvin I Mushlin
- Departments of Population Health Sciences and Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Thomas A Gaziano
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Meredith B Rosenthal
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ankur Pandya
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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27
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Clark RA, Mukandavire C, Portnoy A, Weerasuriya CK, Deol A, Scarponi D, Iskauskas A, Bakker R, Quaife M, Malhotra S, Gebreselassie N, Zignol M, Hutubessy RCW, Giersing B, Jit M, Harris RC, Menzies NA, White RG. The impact of alternative delivery strategies for novel tuberculosis vaccines in low-income and middle-income countries: a modelling study. Lancet Glob Health 2023; 11:e546-e555. [PMID: 36925175 PMCID: PMC10030455 DOI: 10.1016/s2214-109x(23)00045-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2022] [Revised: 11/03/2022] [Accepted: 01/13/2023] [Indexed: 03/15/2023]
Abstract
BACKGROUND Tuberculosis is a leading infectious cause of death worldwide. Novel vaccines will be required to reach global targets and reverse setbacks resulting from the COVID-19 pandemic. We estimated the impact of novel tuberculosis vaccines in low-income and middle-income countries (LMICs) in several delivery scenarios. METHODS We calibrated a tuberculosis model to 105 LMICs (accounting for 93% of global incidence). Vaccine scenarios were implemented as the base-case (routine vaccination of those aged 9 years and one-off vaccination for those aged 10 years and older, with country-specific introduction between 2028 and 2047, and 5-year scale-up to target coverage); accelerated scale-up similar to the base-case, but with all countries introducing vaccines in 2025, with instant scale-up; and routine-only (similar to the base-case, but including routine vaccination only). Vaccines were assumed to protect against disease for 10 years, with 50% efficacy. FINDINGS The base-case scenario would prevent 44·0 million (95% uncertainty range 37·2-51·6) tuberculosis cases and 5·0 million (4·6-5·4) tuberculosis deaths before 2050, compared with equivalent estimates of cases and deaths that would be predicted to occur before 2050 with no new vaccine introduction (the baseline scenario). The accelerated scale-up scenario would prevent 65·5 million (55·6-76·0) cases and 7·9 million (7·3-8·5) deaths before 2050, relative to baseline. The routine-only scenario would prevent 8·8 million (95% uncertainty range 7·6-10·1) cases and 1·1 million (0·9-1·2) deaths before 2050, relative to baseline. INTERPRETATION Our results suggest novel tuberculosis vaccines could have substantial impact, which will vary depending on delivery strategy. Including a one-off vaccination campaign will be crucial for rapid impact. Accelerated introduction-at a pace similar to that seen for COVID-19 vaccines-would increase the number of lives saved before 2050 by around 60%. Investment is required to support vaccine development, manufacturing, prompt introduction, and scale-up. FUNDING WHO (2020/985800-0). TRANSLATIONS For the French, Spanish, Italian and Dutch translations of the abstract see Supplementary Materials section.
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Affiliation(s)
- Rebecca A Clark
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Vaccine Centre, London School of Hygiene & Tropical Medicine, London, UK.
| | - Christinah Mukandavire
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Allison Portnoy
- Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Chathika K Weerasuriya
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Arminder Deol
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Danny Scarponi
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Andrew Iskauskas
- Department of Mathematical Sciences, Durham University, Durham, UK
| | - Roel Bakker
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; KNCV Tuberculosis Foundation, The Hague, Netherlands
| | - Matthew Quaife
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | | | | | - Matteo Zignol
- Global TB Programme, World Health Organization, Geneva, Switzerland
| | - Raymond C W Hutubessy
- Department of Immunization, Vaccines, and Biologicals, World Health Organization, Geneva, Switzerland
| | - Birgitte Giersing
- The Initiative for Vaccine Research, World Health Organization, Geneva, Switzerland
| | - Mark Jit
- Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Rebecca C Harris
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; Global Medical Evidence Generation for Influenza Vaccines, Sanofi Pasteur, Singapore
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA; Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Richard G White
- TB Modelling Group and TB Centre, London School of Hygiene & Tropical Medicine, London, UK; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
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Klaassen F, Chitwood MH, Cohen T, Pitzer VE, Russi M, Swartwood NA, Salomon JA, Menzies NA. Population Immunity to Pre-Omicron and Omicron Severe Acute Respiratory Syndrome Coronavirus 2 Variants in US States and Counties Through 1 December 2021. Clin Infect Dis 2023; 76:e350-e359. [PMID: 35717642 PMCID: PMC9214178 DOI: 10.1093/cid/ciac438] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/20/2022] [Accepted: 05/28/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Both severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) vaccination contribute to population-level immunity against SARS-CoV-2. This study estimated the immunological exposure and effective protection against future SARS-CoV-2 infection in each US state and county over 2020-2021 and how this changed with the introduction of the Omicron variant. METHODS We used a Bayesian model to synthesize estimates of daily SARS-CoV-2 infections, vaccination data and estimates of the relative rates of vaccination conditional on infection status to estimate the fraction of the population with (1) immunological exposure to SARS-CoV-2 (ever infected with SARS-CoV-2 and/or received ≥1 doses of a COVID-19 vaccine), (2) effective protection against infection, and (3) effective protection against severe disease, for each US state and county from 1 January 2020 to 1 December 2021. RESULTS The estimated percentage of the US population with a history of SARS-CoV-2 infection or vaccination as of 1 December 2021 was 88.2% (95% credible interval [CrI], 83.6%-93.5%). Accounting for waning and immune escape, effective protection against the Omicron variant on 1 December 2021 was 21.8% (95% CrI, 20.7%-23.4%) nationally and ranged between 14.4% (13.2%-15.8%; West Virginia) and 26.4% (25.3%-27.8%; Colorado). Effective protection against severe disease from Omicron was 61.2% (95% CrI, 59.1%-64.0%) nationally and ranged between 53.0% (47.3%-60.0%; Vermont) and 65.8% (64.9%-66.7%; Colorado). CONCLUSIONS While more than four-fifths of the US population had prior immunological exposure to SARS-CoV-2 via vaccination or infection on 1 December 2021, only a fifth of the population was estimated to have effective protection against infection with the immune-evading Omicron variant.
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Affiliation(s)
- Fayette Klaassen
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Melanie H Chitwood
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Marcus Russi
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, Connecticut, USA
| | - Nicole A Swartwood
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Joshua A Salomon
- Department of Health Policy, Stanford University School of Medicine, Stanford, California, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
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Clarke-Deelder E, Opondo K, Achieng E, Garg L, Han D, Henry J, Guha M, Lightbourne A, Makin J, Miller N, Otieno B, Borovac-Pinheiro A, Suarez-Rebling D, Menzies NA, Burke T, Oguttu M, McConnell M, Cohen J. Quality of care for postpartum hemorrhage: A direct observation study in referral hospitals in Kenya. PLOS Glob Public Health 2023; 3:e0001670. [PMID: 36963063 PMCID: PMC10022124 DOI: 10.1371/journal.pgph.0001670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 02/08/2023] [Indexed: 03/06/2023]
Abstract
Postpartum hemorrhage (PPH) is the leading cause of maternal mortality in Kenya. The aim of this study was to measure quality and timeliness of care for PPH in a sample of deliveries in referral hospitals in Kenya. We conducted direct observations of 907 vaginal deliveries in three Kenyan hospitals from October 2018 through February 2019, observing the care women received from admission for labor and delivery through hospital discharge. We identified cases of "suspected PPH", defined as cases in which providers indicated suspicion of and/or took an action to manage abnormal bleeding. We measured adherence to World Health Organization and Kenyan guidelines for PPH risk assessment, prevention, identification, and management and the timeliness of care in each domain. The rate of suspected PPH among the observed vaginal deliveries was 9% (95% Confidence Interval: 7% - 11%). Health care providers followed all guidelines for PPH risk assessment in 7% (5% - 10%) of observed deliveries and all guidelines for PPH prevention in 4% (3% - 6%) of observed deliveries. Lowest adherence was observed for taking vital signs and for timely administration of a prophylactic uterotonic. Providers did not follow guidelines for postpartum monitoring in any of the observed deliveries. When suspected PPH occurred, providers performed all recommended actions in 23% (6% - 40%) of cases. Many of the critical actions for suspected PPH were performed in a timely manner, but, in some cases, substantial delays were observed. In conclusion, we found significant gaps in the quality of risk assessment, prevention, identification, and management of PPH after vaginal deliveries in referral hospitals in Kenya. Efforts to reduce maternal morbidity and mortality from PPH should emphasize improvements in the quality of care, with a particular focus on postpartum monitoring and timely emergency response.
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Affiliation(s)
- Emma Clarke-Deelder
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States of America
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
| | - Kennedy Opondo
- Kisumu Medical and Education Trust, Kisumu, Kenya
- Vayu Global Health Foundation, Boston, MA, United States of America
| | | | - Lorraine Garg
- Department of Emergency Medicine, Global Health Innovation Laboratory, Massachusetts General Hospital, Boston, MA, United States of America
| | - Dan Han
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States of America
- Lee Kuan Yew School of Public Policy, National University of Singapore, Singapore, Singapore
| | - Junita Henry
- Economics Department, Massachusetts Institute of Technology, Cambridge, MA, United States of America
| | - Moytrayee Guha
- Department of Emergency Medicine, Global Health Innovation Laboratory, Massachusetts General Hospital, Boston, MA, United States of America
- Brown University, Providence, RI, United States of America
| | - Alicia Lightbourne
- Department of Emergency Medicine, Global Health Innovation Laboratory, Massachusetts General Hospital, Boston, MA, United States of America
- Duke University, Durham, North Carolina, United States of America
| | - Jennifer Makin
- Department of Emergency Medicine, Global Health Innovation Laboratory, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Obstetrics and Gynecology, University of Pittsburgh Medical Center, Pittsburgh, PA, United States of America
| | - Nora Miller
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States of America
| | | | - Anderson Borovac-Pinheiro
- Department of Emergency Medicine, Global Health Innovation Laboratory, Massachusetts General Hospital, Boston, MA, United States of America
- Department of Obstetrics and Gynecology, School of Medical Sciences, University of Campinas, Campinas (SP), Brazil
| | - Daniela Suarez-Rebling
- Department of Emergency Medicine, Global Health Innovation Laboratory, Massachusetts General Hospital, Boston, MA, United States of America
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States of America
| | - Thomas Burke
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States of America
- Department of Emergency Medicine, Global Health Innovation Laboratory, Massachusetts General Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | | | - Margaret McConnell
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States of America
| | - Jessica Cohen
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, United States of America
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Quaife M, Medley GF, Jit M, Drake T, Asaria M, van Baal P, Baltussen R, Bollinger L, Bozzani F, Brady O, Broekhuizen H, Chalkidou K, Chi YL, Dowdy DW, Griffin S, Haghparast-Bidgoli H, Hallett T, Hauck K, Hollingsworth TD, McQuaid CF, Menzies NA, Merritt MW, Mirelman A, Morton A, Ruiz FJ, Siapka M, Skordis J, Tediosi F, Walker P, White RG, Winskill P, Vassall A, Gomez GB. Considering equity in priority setting using transmission models: Recommendations and data needs. Epidemics 2022; 41:100648. [PMID: 36343495 PMCID: PMC9623400 DOI: 10.1016/j.epidem.2022.100648] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 09/20/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022] Open
Abstract
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.
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Affiliation(s)
- M. Quaife
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK,Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - GF Medley
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK
| | - M. Jit
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - T. Drake
- Center for Global Development in Europe (CGD Europe), UK
| | - M. Asaria
- LSE Health, London School of Economics, UK
| | - P. van Baal
- Erasmus School of Health Policy & Management, Erasmus University Rotterdam, the Netherlands
| | - R. Baltussen
- Nijmegen International Center for Health Systems Research and Education, Radboudmc, the Netherlands
| | | | - F. Bozzani
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK
| | - O. Brady
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - H. Broekhuizen
- Centre for Space, Place, and Society, Wageningen University and Research, Netherlands
| | - K. Chalkidou
- International Decision Support Initiative, Imperial College London, UK
| | - Y.-L. Chi
- International Decision Support Initiative, Imperial College London, UK
| | - DW Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, USA
| | - S. Griffin
- Centre for Health Economics, University of York, UK
| | - H. Haghparast-Bidgoli
- Institute for Global Health, Centre for Global Health Economics, University College London, UK
| | - T. Hallett
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - K. Hauck
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - TD Hollingsworth
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, UK
| | - CF McQuaid
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - NA Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, USA
| | - MW Merritt
- Johns Hopkins Berman Institute of Bioethics and Department of International Health, Johns Hopkins Bloomberg School of Public Health, United States
| | - A. Mirelman
- Centre for Health Economics, University of York, UK
| | - A. Morton
- Department of Management Science, University of Strathclyde, UK
| | - FJ Ruiz
- International Decision Support Initiative, Imperial College London, UK
| | - M. Siapka
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK,Impact Elipsis, Greece
| | - J. Skordis
- Institute for Global Health, Centre for Global Health Economics, University College London, UK
| | - F. Tediosi
- Swiss Tropical and Public Health Institute and Universität Basel, Switzerland
| | - P. Walker
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - RG White
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, UK
| | - P. Winskill
- Department of Infectious Disease Epidemiology, Imperial College London, UK
| | - A. Vassall
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK,Correspondence to: London School of Hygiene and Tropical Medicine, 15 – 17 Tavistock Place, London WC1H 9SH, UK
| | - GB Gomez
- Department of Global Health and Development, London School of Hygiene and Tropical Medicine, UK
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Klaassen F, Chitwood MH, Cohen T, Pitzer VE, Russi M, Swartwood NA, Salomon JA, Menzies NA. Changes in population immunity against infection and severe disease from SARS-CoV-2 Omicron variants in the United States between December 2021 and November 2022. medRxiv 2022:2022.11.19.22282525. [PMID: 36451882 PMCID: PMC9709792 DOI: 10.1101/2022.11.19.22282525] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Importance While a substantial fraction of the US population was infected with SARS-CoV-2 during December 2021 - February 2022, the subsequent evolution of population immunity against SARS-CoV-2 Omicron variants reflects the competing influences of waning protection over time and acquisition or restoration of immunity through additional infections and vaccinations. Objective To estimate changes in population immunity against infection and severe disease due to circulating SARS-CoV-2 Omicron variants in the United States from December 2021 to November 2022, and to quantify the protection against a potential 2022-2023 winter SARS-CoV-2 wave. Design setting participants Bayesian evidence synthesis of reported COVID-19 data (diagnoses, hospitalizations), vaccinations, and waning patterns for vaccine- and infection-acquired immunity, using a mathematical model of COVID-19 natural history. Main Outcomes and Measures Population immunity against infection and severe disease from SARS-CoV-2 Omicron variants in the United States, by location (national, state, county) and week. Results By November 9, 2022, 94% (95% CrI, 79%-99%) of the US population were estimated to have been infected by SARS-CoV-2 at least once. Combined with vaccination, 97% (95%-99%) were estimated to have some prior immunological exposure to SARS-CoV-2. Between December 1, 2021 and November 9, 2022, protection against a new Omicron infection rose from 22% (21%-23%) to 63% (51%-75%) nationally, and protection against an Omicron infection leading to severe disease increased from 61% (59%-64%) to 89% (83%-92%). Increasing first booster uptake to 55% in all states (current US coverage: 34%) and second booster uptake to 22% (current US coverage: 11%) would increase protection against infection by 4.5 percentage points (2.4-7.2) and protection against severe disease by 1.1 percentage points (1.0-1.5). Conclusions and Relevance Effective protection against SARS-CoV-2 infection and severe disease in November 2022 was substantially higher than in December 2021. Despite this high level of protection, a more transmissible or immune evading (sub)variant, changes in behavior, or ongoing waning of immunity could lead to a new SARS-CoV-2 wave. Key points Question: How did population immunity against SARS-CoV-2 infection and subsequent severe disease change between December 2021, and November 2022?Findings: On November 9, 2022, the protection against a SARS-CoV-2 infection with the Omicron variant was estimated to be 63% (51%-75%) in the US, and the protection against severe disease was 89% (83%-92%).Meaning: As most of the newly acquired immunity has been accumulated in the December 2021-February 2022 Omicron wave, risk of reinfection and subsequent severe disease remains present at the beginning of the 2022-2023 winter, despite high levels of protection.
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Affiliation(s)
- Fayette Klaassen
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston MA
| | - Melanie H Chitwood
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven CT
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven CT
| | - Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven CT
| | - Marcus Russi
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven CT
| | - Nicole A Swartwood
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston MA
| | - Joshua A Salomon
- Department of Health Policy, Stanford University School of Medicine, Stanford CA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston MA
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Zhu J, Lyatuu G, Sudfeld CR, Kiravu A, Sando D, Machumi L, Minde J, Chisonjela F, Cohen T, Menzies NA. Re-evaluating the health impact and cost-effectiveness of tuberculosis preventive treatment for modern HIV cohorts on antiretroviral therapy: a modelling analysis using data from Tanzania. Lancet Glob Health 2022; 10:e1646-e1654. [PMID: 36240830 PMCID: PMC9553191 DOI: 10.1016/s2214-109x(22)00372-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 08/13/2022] [Accepted: 08/15/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND Isoniazid preventive therapy (IPT) can prevent tuberculosis among people receiving antiretroviral therapy (ART). HIV programmes are now initiating patients on ART with higher average CD4 cell counts and lower tuberculosis risks under test-and-treat guidelines. We aimed to investigate how this change has affected the health impact and cost-effectiveness of IPT. METHODS We constructed a tuberculosis-HIV microsimulation model parameterised using data from a large HIV treatment programme in Dar es Salaam, Tanzania. We simulated long-term health and cost outcomes for the 211 748 individuals initiating ART between Jan 1, 2014, and Dec 31, 2020, under three scenarios: no IPT access; observed levels of IPT access (75%) and completion (71%); and full (100%) IPT access and completion. We stratified results by ART initiation year and starting CD4 cell count. FINDINGS Observed levels of IPT access were estimated to have averted 12 800 (95% uncertainty interval 7300 to 21 600) disability-adjusted life-years (DALYs) and saved US$23 000 (-2 268 000 to 1 388 000). Full IPT access would have averted 24 500 (15 100 to 38 300) DALYs and cost $825 000 (-1 594 000 to 4 751 000), equivalent to $23·4 per DALY averted. Lifetime health benefits of IPT were estimated to be greater for more recent ART cohorts, while lifetime costs were stable. In subgroup analyses, a higher CD4 cell count at ART initiation was associated with greater health gains from IPT (15 900 [10 300 to 22 500] DALYs averted by full IPT per 100 000 patients for CD4 count >500 cells per μL at ART initiation, versus 7400 [4500 to 11 600] for CD4 count <100 cells per μL) and lower incremental lifetime costs. INTERPRETATION IPT remains highly cost-effective or cost-saving for recent ART cohorts. The health impact and cost-effectiveness of IPT are estimated to improve as patients initiate ART earlier in the course of infection. FUNDING US National Institutes of Health.
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Affiliation(s)
- Jinyi Zhu
- Department of Health Policy, Vanderbilt University School of Medicine, Nashville, TN, USA; Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Goodluck Lyatuu
- Management and Development for Health, Dar es Salaam, Tanzania
| | - Christopher R Sudfeld
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Anna Kiravu
- Management and Development for Health, Dar es Salaam, Tanzania
| | - David Sando
- Management and Development for Health, Dar es Salaam, Tanzania
| | - Lameck Machumi
- Management and Development for Health, Dar es Salaam, Tanzania
| | - John Minde
- Management and Development for Health, Dar es Salaam, Tanzania
| | | | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Li Y, de Macedo Couto R, Pelissari DM, Costa Alves L, Bartholomay P, Maciel EL, Sanchez M, Castro MC, Cohen T, Menzies NA. Excess tuberculosis cases and deaths following an economic recession in Brazil: an analysis of nationally representative disease registry data. Lancet Glob Health 2022; 10:e1463-e1472. [PMID: 36049488 PMCID: PMC9472578 DOI: 10.1016/s2214-109x(22)00320-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 06/22/2022] [Accepted: 07/05/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND In 2019, tuberculosis incidence and mortality in Brazil were 46 and 3·3 per 100 000 population, respectively, and the country has reported rising tuberculosis case rates since 2016, following an economic crisis beginning in mid-2014. We aimed to estimate the number of excess tuberculosis cases and deaths during the recession period, and assessed potential causes. METHODS In this multi-level regression modelling study, we extracted tuberculosis case notifications from Brazil's National Notifiable Disease Information System (known as SINAN), and tuberculosis deaths from the Mortality Information System (known as SIM), for all ages. We fitted mixed-effects regression models estimating trends in these outcomes-stratified by sex, age group, and state-during the pre-recession period (Jan 1, 2010-Dec 31, 2014). We calculated excess cases and deaths between Jan 1, 2015, and Dec 31, 2019 (the recession period) as the difference between reported values and a counterfactual of continued pre-recession trends. We examined the relationship between excess cases and possible explanatory factors using ordinary least squares regression. We tested the robustness of our findings to alternative model specifications related to the pre-recession period and criteria for defining tuberculosis deaths. FINDINGS We estimated 22 900 excess tuberculosis cases (95% uncertainty interval 18 100-27 500) during 2015-19. By 2019, reported cases were 12% (10-13) higher than predicted by historical trends. 54% (44-66) of excess cases occurred among 20-29-year-old men. In this group, reported cases in 2019 were 30% (25-36) higher than predicted. Excess cases were positively associated with an increasing fraction of cases among incarcerated individuals (p=0·001) and higher unemployment (p=0·04) at the state level. Estimated excess deaths for 2015-19 were not statistically significant from 0 (-600 [-2100 to 1000]). These results were robust to alternative definitions of the pre-recession period and criteria for defining tuberculosis deaths. INTERPRETATION Tuberculosis cases in Brazil rose substantially in 2015-19 during the recession, largely affecting young men. This increase seems to be linked to increasing tuberculosis transmission among incarcerated populations. Rising tuberculosis case rates threaten tuberculosis control in Brazil, and highlight the threat posed by prison-based tuberculosis transmission. FUNDING US National Institutes of Health. TRANSLATION For the Portuguese translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Yunfei Li
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA.
| | | | | | | | | | - Ethel L Maciel
- Laboratorio de Epidemiologia, Universidade Federal do Espirito Santo, Vitória, Brazil
| | - Mauro Sanchez
- Department of Tropical Medicine, University of Brasilia, Brasilia, Brazil
| | - Marcia C Castro
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA
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Cates L, Codreanu A, Ciobanu N, Fosburgh H, Allender CJ, Centner H, Engelthaler DM, Crudu V, Cohen T, Menzies NA. Budget impact of next-generation sequencing for diagnosis of TB drug resistance in Moldova. Int J Tuberc Lung Dis 2022; 26:963-969. [PMID: 36163669 DOI: 10.5588/ijtld.22.0104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Diagnosing drug resistance is critical for choosing effective TB treatment regimens. Next-generation sequencing (NGS) represents an alternative approach to conventional phenotypic drug susceptibility testing (pDST) for diagnosing TB drug resistance.METHODS We undertook a budget impact analysis estimating the costs of introduction and routine use of NGS in the Moldovan National TB Programme. We conducted an empirical costing study and collated price and operating characteristics for NGS platforms. We examined multiple NGS scenarios in comparison to the current approach (pDST) for pre-treatment drug resistance testing over 2021-2025.RESULTS Annual testing volume ranged from 912 to 1,926 patients. For the pDST scenario, we estimated total costs of US$362,000 (2021 USD) over the 5-year study period. Total costs for NGS scenarios ranged from US$475,000 to US$1,486,000. Lowest cost NGS options involved targeted sequencing as a replacement for pDST, and excluded individuals diagnosed as RIF-susceptible on Xpert® MTB/RIF. For all NGS scenarios, the majority (55-80%) of costs were devoted to reagent kits. Start-up costs of NGS were small relative to routine costs borne each year.CONCLUSION NGS adoption will require expanded resources compared to conventional pDST. Further work is required to better understand the feasibility of NGS in settings such as Moldova.
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Affiliation(s)
- L Cates
- Department of Global Health and Population Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - A Codreanu
- Institute of Phthisiopneumology, Chisinau, Moldova
| | - N Ciobanu
- Institute of Phthisiopneumology, Chisinau, Moldova
| | - H Fosburgh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - C J Allender
- Translational Genomics Research Institute, Flagstaff, AZ, USA
| | - H Centner
- Translational Genomics Research Institute, Flagstaff, AZ, USA
| | - D M Engelthaler
- Translational Genomics Research Institute, Flagstaff, AZ, USA
| | - V Crudu
- Institute of Phthisiopneumology, Chisinau, Moldova
| | - T Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - N A Menzies
- Department of Global Health and Population Harvard T. H. Chan School of Public Health, Boston, MA, USA
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Chitwood MH, Russi M, Gunasekera K, Havumaki J, Klaassen F, Pitzer VE, Salomon JA, Swartwood NA, Warren JL, Weinberger DM, Cohen T, Menzies NA. Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model. PLoS Comput Biol 2022; 18:e1010465. [PMID: 36040963 PMCID: PMC9467347 DOI: 10.1371/journal.pcbi.1010465] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 09/12/2022] [Accepted: 08/03/2022] [Indexed: 12/11/2022] Open
Abstract
Reported COVID-19 cases and deaths provide a delayed and incomplete picture of SARS-CoV-2 infections in the United States (US). Accurate estimates of both the timing and magnitude of infections are needed to characterize viral transmission dynamics and better understand COVID-19 disease burden. We estimated time trends in SARS-CoV-2 transmission and other COVID-19 outcomes for every county in the US, from the first reported COVID-19 case in January 13, 2020 through January 1, 2021. To do so we employed a Bayesian modeling approach that explicitly accounts for reporting delays and variation in case ascertainment, and generates daily estimates of incident SARS-CoV-2 infections on the basis of reported COVID-19 cases and deaths. The model is freely available as the covidestim R package. Nationally, we estimated there had been 49 million symptomatic COVID-19 cases and 404,214 COVID-19 deaths by the end of 2020, and that 28% of the US population had been infected. There was county-level variability in the timing and magnitude of incidence, with local epidemiological trends differing substantially from state or regional averages, leading to large differences in the estimated proportion of the population infected by the end of 2020. Our estimates of true COVID-19 related deaths are consistent with independent estimates of excess mortality, and our estimated trends in cumulative incidence of SARS-CoV-2 infection are consistent with trends in seroprevalence estimates from available antibody testing studies. Reconstructing the underlying incidence of SARS-CoV-2 infections across US counties allows for a more granular understanding of disease trends and the potential impact of epidemiological drivers.
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Affiliation(s)
- Melanie H. Chitwood
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Marcus Russi
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Kenneth Gunasekera
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Joshua Havumaki
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Fayette Klaassen
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts United States of America
| | - Virginia E. Pitzer
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Joshua A. Salomon
- Department of Health Policy, Stanford University, Stanford, California United States of America
| | - Nicole A. Swartwood
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts United States of America
| | - Joshua L. Warren
- Department of Biostatistics and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Daniel M. Weinberger
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut United States of America
| | - Nicolas A. Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts United States of America
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Saronga HP, Manji K, Liu E, Duggan CP, Menzies NA. Cost-effectiveness of Zinc Supplementation for Prevention of Childhood Diarrhoea in Tanzania. Public Health Nutr 2022; 25:1-26. [PMID: 35272738 PMCID: PMC9991691 DOI: 10.1017/s1368980022000568] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 02/21/2022] [Accepted: 03/01/2022] [Indexed: 11/07/2022]
Abstract
OBJECTIVE To assess the cost-effectiveness of prophylactic zinc supplementation for preventing diarrhoea in young children in Tanzania. DESIGN Cost-effectiveness analysis using decision-analytic modelling. Cost-effectiveness ratios were calculated as the incremental cost (2019 USD) per disability-adjusted life year (DALY) averted, from a societal perspective, and with a 3% discount rate applied to future outcomes. Sensitivity analyses were performed to test the robustness of results to alternative assumptions. SETTING Tanzania. PARTICIPANTS A hypothetical cohort of 10,000 children ages 6 weeks to 18 months. RESULTS The intervention costs of zinc supplementation were estimated as $109,800 (95% uncertainty interval: 61,716-171,507). Zinc supplementation was estimated to avert 2,200 (776-3,737) diarrhoeal episodes, 14,080 (4,692-25,839) sick days, 1,584 (522-2,927) outpatient visits, 561 (160-1,189) inpatient bed-days, 0.51 (0.15-1.03) deaths, and 19.3 (6.1-37.5) DALYs (discounted at 3% per year). Zinc supplementation reduced diarrhoea care costs by $12, 887 (4,089-25,058). The incremental cost per DALY averted was $4,950 (1,678-17,933). Incremental cost-effectiveness ratios (ICERs) estimated from a health system perspective were similar to the results from the societal perspective. ICERs were substantially lower (more favourable) when future outcomes were not discounted, but all ICERs were above contemporary thresholds for cost-effectiveness in this setting. CONCLUSION Prophylactic zinc reduced diarrhoea incidence and associated healthcare utilization; however it did not appear to be cost-effective for prevention of childhood diarrhoea in the scenario examined in this study. Reducing intervention costs, or identifying high risk groups for intervention targeting, may be needed to improve cost-effectiveness in this setting.
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Affiliation(s)
- Happiness Pius Saronga
- Behavioural Sciences Department, School of Public Health and Social Sciences, Muhimbili University of Health and Allied Sciences, 65001Dar-es-salaam, Tanzania
| | - Karim Manji
- Department of Paediatrics and Child Health, School of Medicine, Muhimbili University of Health and Allied Sciences, Dar-es-salaam, Tanzania
| | - Enju Liu
- Division of Gastroenterology, Hepatology, and Nutrition, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Institutional Centers for Clinical and Translational Research, Boston Children’s Hospital, Boston, MA, USA
| | - Christopher P Duggan
- Division of Gastroenterology, Hepatology, and Nutrition, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Nutrition, Harvard T.H Chan School of Public Health, Boston, MA, USA
- Department of Global Health and Population, Harvard T.H Chan School of Public Health, Boston, MA, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H Chan School of Public Health, Boston, MA, USA
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Klaassen F, Chitwood MH, Cohen T, Pitzer VE, Russi M, Swartwood NA, Salomon JA, Menzies NA. Population immunity to pre-Omicron and Omicron SARS-CoV-2 variants in US states and counties through December 1, 2021. medRxiv 2022:2021.12.23.21268272. [PMID: 34981078 PMCID: PMC8722621 DOI: 10.1101/2021.12.23.21268272] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Prior infection and vaccination both contribute to population-level SARS-CoV-2 immunity. We used a Bayesian model to synthesize evidence and estimate population immunity to prevalent SARS-CoV-2 variants in the United States over the course of the epidemic until December 1, 2021, and how this changed with the introduction of the Omicron variant. We used daily SARS-CoV-2 infection estimates and vaccination coverage data for each US state and county. We estimated relative rates of vaccination conditional on previous infection status using the Census Bureau’s Household Pulse Survey. We used published evidence on natural and vaccine-induced immunity, including waning and immune escape. The estimated percentage of the US population with a history of SARS-CoV-2 infection or vaccination as of December 1, 2021, was 88.2% (95%CrI: 83.6%-93.5%), compared to 24.9% (95%CrI: 18.5%-34.1%) on January 1, 2021. State-level estimates for December 1, 2021, ranged between 76.9% (95%CrI: 67.6%-87.6%, West Virginia) and 94.4% (95%CrI: 91.2%-97.3%, New Mexico). Accounting for waning and immune escape, the effective protection against the Omicron variant on December 1, 2021, was 21.8% (95%CrI: 20.7%-23.4%) nationally and ranged between 14.4% (95%CrI: 13.2%-15.8%, West Virginia), to 26.4% (95%CrI: 25.3%-27.8%, Colorado). Effective protection against severe disease from Omicron was 61.2% (95%CrI: 59.1%-64.0%) nationally and ranged between 53.0% (95%CrI: 47.3%-60.0%, Vermont) and 65.8% (95%CrI: 64.9%-66.7%, Colorado). While over three-quarters of the US population had prior immunological exposure to SARS-CoV-2 via vaccination or infection on December 1, 2021, only a fifth of the population was estimated to have effective protection to infection with the immune-evading Omicron variant. Significance Both SARS-CoV-2 infection and COVID-19 vaccination contribute to population-level immunity against SARS-CoV-2. This study estimates the immunity and effective protection against future SARS-CoV-2 infection in each US state and county over 2020-2021. The estimated percentage of the US population with a history of SARS-CoV-2 infection or vaccination as of December 1, 2021, was 88.2% (95%CrI: 83.6%-93.5%). Accounting for waning and immune escape, protection against the Omicron variant was 21.8% (95%CrI: 20.7%-23.4%). Protection against infection with the Omicron variant ranged between 14.4% (95%CrI: 13.2%-15.8%%, West Virginia) and 26.4% (95%CrI: 25.3%-27.8%, Colorado) across US states. The introduction of the immune-evading Omicron variant resulted in an effective absolute increase of approximately 30 percentage points in the fraction of the population susceptible to infection.
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Affiliation(s)
- Fayette Klaassen
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Melanie H. Chitwood
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT
| | - Virginia E. Pitzer
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT
| | - Marcus Russi
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT
| | - Nicole A. Swartwood
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Joshua A. Salomon
- Department of Health Policy, Stanford University School of Medicine, Stanford, CA
| | - Nicolas A. Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA
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Yerramsetti S, Cohen T, Atun R, Menzies NA. Global estimates of paediatric tuberculosis incidence in 2013-19: a mathematical modelling analysis. Lancet Glob Health 2022; 10:e207-e215. [PMID: 34895517 PMCID: PMC8800006 DOI: 10.1016/s2214-109x(21)00462-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 08/18/2021] [Accepted: 09/29/2021] [Indexed: 12/11/2022]
Abstract
BACKGROUND Many children who develop tuberculosis are thought to be missed by diagnostic and reporting systems. We aimed to estimate paediatric tuberculosis incidence and underreporting between 2013 and 2019 in countries representing more than 99% of the global tuberculosis burden. METHODS We developed a mathematical model of paediatric tuberculosis natural history, accounting for key mechanisms and risk factors for infectious exposure (HIV, malnutrition, and BCG non-vaccination), the probability of infection given exposure, and progression to disease among infected individuals. We extracted paediatric population estimates from UN Population Division data, and we used WHO estimates for adult tuberculosis incidence rates. We parameterised this model for 185 countries and calibrated it using data from countries with stronger case detection and reporting systems. Using this model, we estimated trends in paediatric incidence, and the proportion of these cases that are diagnosed and reported (case detection ratio [CDR]) for each country, age group, and year. FINDINGS For 2019, we estimated 997 500 (95% credible interval [CrI] 868 700-1 163 100) incident tuberculosis cases among children, with 481 000 cases (398 400-587 400) among those aged 0-4 years and 516 500 cases (442 900-608 000) among those aged 5-14 years. The paediatric CDR was estimated to be lower in children aged 0-4 years (41%, 95% CrI 34-50) than in those aged 5-14 years (63%, 53-75) and varied widely between countries. Estimated CDRs increased substantially over the study period, from 18% (15-20) in 2013 to 53% (45-60) in 2019, with improvements concentrated in the Eastern Mediterranean, South-East Asia, and Western Pacific regions. Over the study period, global incidence was estimated to have declined slowly at an average annual rate of 1·52% (1·42-1·66). INTERPRETATION Paediatric tuberculosis causes substantial morbidity and mortality, and these data indicate that cases (and, thus, probably associated mortality) are currently substantially underreported. These findings reinforce the need to ensure prompt diagnosis and care for children developing tuberculosis, strengthen reporting systems, and invest in research to develop more accurate and easy-to-use diagnostics for paediatric tuberculosis in high-burden settings. FUNDING National Institutes of Health.
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Affiliation(s)
- Sita Yerramsetti
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Rifat Atun
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - 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.
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Yang C, Sobkowiak B, Naidu V, Codreanu A, Ciobanu N, Gunasekera KS, Chitwood MH, Alexandru S, Bivol S, Russi M, Havumaki J, Cudahy P, Fosburgh H, Allender CJ, Centner H, Engelthaler DM, Menzies NA, Warren JL, Crudu V, Colijn C, Cohen T. Phylogeography and transmission of M. tuberculosis in Moldova: A prospective genomic analysis. PLoS Med 2022; 19:e1003933. [PMID: 35192619 PMCID: PMC8903246 DOI: 10.1371/journal.pmed.1003933] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Revised: 03/08/2022] [Accepted: 01/31/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND The incidence of multidrug-resistant tuberculosis (MDR-TB) remains critically high in countries of the former Soviet Union, where >20% of new cases and >50% of previously treated cases have resistance to rifampin and isoniazid. Transmission of resistant strains, as opposed to resistance selected through inadequate treatment of drug-susceptible tuberculosis (TB), is the main driver of incident MDR-TB in these countries. METHODS AND FINDINGS We conducted a prospective, genomic analysis of all culture-positive TB cases diagnosed in 2018 and 2019 in the Republic of Moldova. We used phylogenetic methods to identify putative transmission clusters; spatial and demographic data were analyzed to further describe local transmission of Mycobacterium tuberculosis. Of 2,236 participants, 779 (36%) had MDR-TB, of whom 386 (50%) had never been treated previously for TB. Moreover, 92% of multidrug-resistant M. tuberculosis strains belonged to putative transmission clusters. Phylogenetic reconstruction identified 3 large clades that were comprised nearly uniformly of MDR-TB: 2 of these clades were of Beijing lineage, and 1 of Ural lineage, and each had additional distinct clade-specific second-line drug resistance mutations and geographic distributions. Spatial and temporal proximity between pairs of cases within a cluster was associated with greater genomic similarity. Our study lasted for only 2 years, a relatively short duration compared with the natural history of TB, and, thus, the ability to infer the full extent of transmission is limited. CONCLUSIONS The MDR-TB epidemic in Moldova is associated with the local transmission of multiple M. tuberculosis strains, including distinct clades of highly drug-resistant M. tuberculosis with varying geographic distributions and drug resistance profiles. This study demonstrates the role of comprehensive genomic surveillance for understanding the transmission of M. tuberculosis and highlights the urgency of interventions to interrupt transmission of highly drug-resistant M. tuberculosis.
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Affiliation(s)
- Chongguang Yang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | | | - Vijay Naidu
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
| | | | - Nelly Ciobanu
- Phthisiopneumology Institute, Chisinau, Republic of Moldova
| | - Kenneth S. Gunasekera
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Melanie H. Chitwood
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | | | - Stela Bivol
- Center for Health Policies and Studies, Chisinau, Republic of Moldova
| | - Marcus Russi
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Joshua Havumaki
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Patrick Cudahy
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Heather Fosburgh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
| | | | - Heather Centner
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
| | - David M. Engelthaler
- Translational Genomics Research Institute, Flagstaff, Arizona, United States of America
| | - Nicolas A. Menzies
- Department of Global Health and Population, and Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Joshua L. Warren
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America
| | - Valeriu Crudu
- Phthisiopneumology Institute, Chisinau, Republic of Moldova
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, Canada
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, United States of America
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Menzies NA, Berthé F, Hitchings M, Aruna P, Hamza MA, Nanama S, Steve-Edemba C, Shehu I, Grais RF, Isanaka S. Cost-effectiveness of monthly follow-up for the treatment of uncomplicated severe acute malnutrition: An economic evaluation of a randomized controlled trial. PLOS Glob Public Health 2022; 2:e0001189. [PMID: 36962786 PMCID: PMC10022243 DOI: 10.1371/journal.pgph.0001189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/07/2022] [Indexed: 12/14/2022]
Abstract
Severe acute malnutrition (SAM) is a major source of mortality for children in low resource settings. Alternative treatment models that improve acceptability and reduce caregiver burden are needed to improve treatment access. We assessed costs and cost-effectiveness of monthly vs. weekly follow-up (standard-of-care) for treating uncomplicated SAM in children 6-59 months of age. To do so, we conducted a cost-effectiveness analysis of a cluster-randomized trial of treatment for newly-diagnosed uncomplicated SAM in northwestern Nigeria (clinicaltrials.gov ID NCT03140904). We collected empirical costing data from enrollment up to 3 months post-discharge. We quantified health outcomes as the fraction of children recovered at discharge (primary cost-effectiveness outcome), the fraction recovered 3 months post-discharge, and total DALYs due to acute malnutrition. We estimated cost-effectiveness from both provider and societal perspectives. Costs are reported in 2019 US dollars. Provider costs per child were $67.07 (95% confidence interval: $64.79, $69.29) under standard-of-care, and $78.74 ($77.06, $80.66) under monthly follow-up. Patient costs per child were $21.04 ($18.18, $23.51) under standard-of-care, and $14.16 ($12.79, $15.25) under monthly follow-up. Monthly follow-up performed worse than standard-of-care for each health outcome assessed and was dominated (produced worse health outcomes at higher cost) by the standard-of-care in cost-effectiveness analyses. This result was robust to statistical uncertainty and to alternative costing assumptions. These findings provide evidence against monthly follow-up for treatment of uncomplicated SAM in situations where weekly follow-up of patients is feasible. While monthly follow-up may reduce burdens on caregivers and providers, other approaches are needed to do so while maintaining the effectiveness of care.
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Affiliation(s)
- Nicolas A Menzies
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | | | - Matt Hitchings
- Department of Biology and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Philip Aruna
- Médecins sans Frontières-Operational Center Amsterdam, Amsterdam, Netherlands
| | | | - Siméon Nanama
- UNICEF West and Central Regional Office, Dakar, Senegal
| | | | | | | | - Sheila Isanaka
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
- Epicentre, Paris, France
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America
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Menzies NA, Shrestha S, Parriott A, Marks SM, Hill AN, Dowdy DW, Shete PB, Cohen T, Salomon JA. The Health and Economic Benefits of Tests That Predict Future Progression to Tuberculosis Disease. Epidemiology 2022; 33:75-83. [PMID: 34669631 PMCID: PMC8633045 DOI: 10.1097/ede.0000000000001418] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Effective targeting of latent tuberculosis infection (LTBI) treatment requires identifying those most likely to progress to tuberculosis (TB). We estimated the potential health and economic benefits of diagnostics with improved discrimination for LTBI that will progress to TB. METHODS A base case scenario represented current LTBI testing and treatment services in the United States in 2020, with diagnosis via. interferon-gamma release assay (IGRA). Alternative scenarios represented tests with higher positive predictive value (PPV) for future TB but similar price to IGRA, and scenarios that additionally assumed higher treatment initiation and completion. We predicted outcomes using multiple transmission-dynamic models calibrated to different geographic areas and estimated costs from a societal perspective. RESULTS In 2020, 2.1% (range across model results: 1.1%-3.4%) of individuals with LTBI were predicted to develop TB in their remaining lifetime. For IGRA, we estimated the PPV for future TB as 1.3% (0.6%-1.8%). Relative to IGRA, we estimated a test with 10% PPV would reduce treatment volume by 87% (82%-94%), reduce incremental costs by 30% (15%-52%), and increase quality-adjusted life years by 3% (2%-6%). Cost reductions and health improvements were substantially larger for scenarios in which higher PPV for future TB was associated with greater initiation and completion of treatment. CONCLUSIONS We estimated that tests with better predictive performance would substantially reduce the number of individuals treated to prevent TB but would have a modest impact on incremental costs and health impact of TB prevention services, unless accompanied by greater treatment acceptance and completion.
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Affiliation(s)
| | - Sourya Shrestha
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Andrea Parriott
- Philip R. Lee Institute for Health Policy Studies, University of California San Francisco, San Francisco, CA
| | - Suzanne M Marks
- Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA
| | - Andrew N Hill
- Division of Tuberculosis Elimination, Centers for Disease Control and Prevention, Atlanta, GA
| | - David W Dowdy
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Priya B Shete
- Division of Pulmonary and Critical Care Medicine, University of California San Francisco, San Francisco, CA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT
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Kishore N, Taylor AR, Jacob PE, Vembar N, Cohen T, Buckee CO, Menzies NA. Evaluating the reliability of mobility metrics from aggregated mobile phone data as proxies for SARS-CoV-2 transmission in the USA: a population-based study. Lancet Digit Health 2022; 4:e27-e36. [PMID: 34740555 PMCID: PMC8563007 DOI: 10.1016/s2589-7500(21)00214-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 07/22/2021] [Accepted: 09/01/2021] [Indexed: 01/05/2023]
Abstract
BACKGROUND In early 2020, the response to the SARS-CoV-2 pandemic focused on non-pharmaceutical interventions, some of which aimed to reduce transmission by changing mixing patterns between people. Aggregated location data from mobile phones are an important source of real-time information about human mobility on a population level, but the degree to which these mobility metrics capture the relevant contact patterns of individuals at risk of transmitting SARS-CoV-2 is not clear. In this study we describe changes in the relationship between mobile phone data and SARS-CoV-2 transmission in the USA. METHODS In this population-based study, we collected epidemiological data on COVID-19 cases and deaths, as well as human mobility metrics collated by advertisement technology that was derived from global positioning systems, from 1396 counties across the USA that had at least 100 laboratory-confirmed cases of COVID-19. We grouped these counties into six ordinal categories, defined by the National Center for Health Statistics (NCHS) and graded from urban to rural, and quantified the changes in COVID-19 transmission using estimates of the effective reproduction number (Rt) between Jan 22 and July 9, 2020, to investigate the relationship between aggregated mobility metrics and epidemic trajectory. For each county, we model the time series of Rt values with mobility proxies. FINDINGS We show that the reproduction number is most strongly associated with mobility proxies for change in the travel into counties (0·757 [95% CI 0·689 to 0·857]), but this relationship primarily holds for counties in the three most urban categories as defined by the NCHS. This relationship weakens considerably after the initial 15 weeks of the epidemic (0·442 [-0·492 to -0·392]), consistent with the emergence of more complex local policies and behaviours, including masking. INTERPRETATION Our study shows that the integration of mobility metrics into retrospective modelling efforts can be useful in identifying links between these metrics and Rt. Importantly, we highlight potential issues in the data generation process for transmission indicators derived from mobile phone data, representativeness, and equity of access, which must be addressed to improve the interpretability of these data in public health. FUNDING There was no funding source for this study.
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Affiliation(s)
- Nishant Kishore
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Aimee R Taylor
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T H Chan School of Public Health, Boston, MA, USA; Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Pierre E Jacob
- Department of Information Systems, Decision Sciences and Statistics, ESSEC Business School, Cergy, France
| | | | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Caroline O Buckee
- Department of Epidemiology, Center for Communicable Disease Dynamics, Harvard T H Chan School of Public Health, Boston, MA, USA.
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA
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Chitwood MH, Alves LC, Bartholomay P, Couto RM, Sanchez M, Castro MC, Cohen T, Menzies NA. A spatial-mechanistic model to estimate subnational tuberculosis burden with routinely collected data: An application in Brazilian municipalities. PLOS Glob Public Health 2022; 2:e0000725. [PMID: 36962578 PMCID: PMC10021638 DOI: 10.1371/journal.pgph.0000725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 08/17/2022] [Indexed: 11/19/2022]
Abstract
Reliable subnational estimates of TB incidence would allow national policy makers to focus disease control resources in areas of highest need. We developed an approach for generating small area estimates of TB incidence, and the fraction of individuals missed by routine case detection, based on available notification and mortality data. We demonstrate the feasibility of this approach by creating municipality-level burden estimates for Brazil. We developed a mathematical model describing the relationship between TB incidence and TB case notifications and deaths, allowing for known biases in each of these data sources. We embedded this model in a regression framework with spatial dependencies between local areas, and fitted the model to municipality-level case notifications and death records for Brazil during 2016-2018. We estimated outcomes for 5568 municipalities. Incidence rate ranged from 8.6 to 57.2 per 100,000 persons/year for 90% of municipalities, compared to 44.8 (95% UI: 43.3, 46.8) per 100,000 persons/year nationally. Incidence was concentrated geographically, with 1% of municipalities accounting for 50% of incident TB. The estimated fraction of incident TB cases receiving diagnosis and treatment ranged from 0.73 to 0.95 across municipalities (compared to 0.86 (0.82, 0.89) nationally), and the rate of untreated TB ranged from 0.8 to 72 cases per 100,000 persons/year (compared to 6.3 (4.8, 8.3) per 100,000 persons/year nationally). Granular disease burden estimates can be generated using routine data. These results reveal substantial subnational differences in disease burden and other metrics useful for designing high-impact TB control strategies.
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Affiliation(s)
- Melanie H Chitwood
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Haven, Connecticut, United States of America
| | - Layana C Alves
- Chronic and Airborne Diseases Surveillance Coordination, Ministry of Health, Rio de Janeiro, Brazil
| | - Patrícia Bartholomay
- Chronic and Airborne Diseases Surveillance Coordination, Ministry of Health, Rio de Janeiro, Brazil
| | - Rodrigo M Couto
- Chronic and Airborne Diseases Surveillance Coordination, Ministry of Health, Rio de Janeiro, Brazil
| | - Mauro Sanchez
- Department of Tropical Medicine, University of Brasília, Brasilia, Brazil
| | - Marcia C Castro
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Mumbai, India
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, Haven, Connecticut, United States of America
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Mumbai, India
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44
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Yaesoubi R, You S, Xi Q, Menzies NA, Tuite A, Grad YH, Salomon JA. Simple decision rules to predict local surges in COVID-19 hospitalizations during the winter and spring of 2022. medRxiv 2021:2021.12.13.21267657. [PMID: 34931196 PMCID: PMC8687467 DOI: 10.1101/2021.12.13.21267657] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes leave many U.S. communities at risk for surges of COVID-19 during the winter and spring of 2022 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations during this period are expected to differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop simple decision rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. These decision rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We showed that these decision rules present reasonable accuracy, sensitivity, and specificity (all ≥80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19 during the winter and spring of 2022. Our proposed decision rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations. SIGNIFICANCE STATEMENT In many U.S. communities, the risk of exceeding local healthcare capacity during the winter and spring of 2022 remains substantial since COVID-19 hospitalizations may rise due to seasonal changes, low vaccination coverage, and the emergence of new variants of SARS-CoV-2, such as the omicron variant. Here, we provide simple and easy-to-communicate decision rules to predict whether local hospital occupancy is expected to exceed capacity within a 4- or 8-week period if no additional mitigating measures are implemented. These decision rules can serve as an alert system for local policymakers to respond proactively to mitigate future surges in the COVID-19 hospitalization and minimize risk of overwhelming local healthcare capacity.
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Affiliation(s)
- Reza Yaesoubi
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA
| | - Shiying You
- Department of Health Policy and Management, Yale School of Public Health, New Haven, CT, USA
| | - Qin Xi
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Nicolas A. Menzies
- Department of Global Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ashleigh Tuite
- Epidemiology Division, University of Toronto Dalla Lana School of Public Health, Toronto, Ontario, Canada
| | - Yonatan H. Grad
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA
- Division of Infectious Diseases, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA
| | - Joshua A. Salomon
- Department of Health Policy, Stanford University School of Medicine, Palo Alto, CA, USA
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45
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Marx FM, Hauer B, Menzies NA, Haas W, Perumal N. Targeting screening and treatment for latent tuberculosis infection towards asylum seekers from high-incidence countries - a model-based cost-effectiveness analysis. BMC Public Health 2021; 21:2172. [PMID: 34836526 PMCID: PMC8622109 DOI: 10.1186/s12889-021-12142-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 11/01/2021] [Indexed: 11/26/2022] Open
Abstract
Background Enhancing tuberculosis (TB) prevention and care in a post-COVID-19-pandemic phase will be essential to ensure progress towards global TB elimination. In low-burden countries, asylum seekers constitute an important high-risk group. TB frequently arises post-immigration due to the reactivation of latent TB infection (LTBI). Upon-entry screening for LTBI and TB preventive treatment (TPT) are considered worthwhile if targeted to asylum seekers from high-incidence countries who usually present with higher rates of LTBI. However, there is insufficient knowledge about optimal incidence thresholds above which introduction could be cost-effective. We aimed to estimate, among asylum seekers in Germany, the health impact and costs of upon-entry LTBI screening/TPT introduced at different thresholds of country-of-origin TB incidence. Methods We sampled hypothetical cohorts of 30–45 thousand asylum seekers aged 15 to 34 years expected to arrive in Germany in 2022 from cohorts of first-time applicants observed in 2017–2019. We modelled LTBI prevalence as a function of country-of-origin TB incidence fitted to data from observational studies. We then used a probabilistic decision-analytic model to estimate health-system costs and quality-adjusted life years (QALYs) under interferon gamma release assay (IGRA)-based screening for LTBI and rifampicin-based TPT (daily, 4 months). Incremental cost-effectiveness ratios (ICERs) were calculated for scenarios of introducing LTBI screening/TPT at different incidence thresholds. Results We estimated that among 15- to 34-year-old asylum seekers arriving in Germany in 2022, 17.5% (95% uncertainty interval: 14.2–21.6%) will be latently infected. Introducing LTBI screening/TPT above 250 per 100,000 country-of-origin TB incidence would gain 7.3 (2.7–14.8) QALYs at a cost of €51,000 (€18,000–€114,100) per QALY. Lowering the threshold to ≥200 would cost an incremental €53,300 (€19,100–€122,500) per additional QALY gained relative to the ≥250 threshold scenario; ICERs for the ≥150 and ≥ 100 thresholds were €55,900 (€20,200–€128,200) and €62,000 (€23,200–€142,000), respectively, using the next higher threshold as a reference, and considerably higher at thresholds below 100. Conclusions LTBI screening and TPT among 15- to 34-year-old asylum seekers arriving in Germany could produce health benefits at reasonable additional cost (with respect to international benchmarks) if introduced at incidence thresholds ≥100. Empirical trials are needed to investigate the feasibility and effectiveness of this approach.
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Affiliation(s)
- Florian M Marx
- Department for Infectious Disease Epidemiology, Respiratory Infections Unit, Robert Koch Institute, Berlin, Germany. .,Department of Paediatrics and Child Health, Desmond Tutu TB Centre, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. .,DSI-NRF South African Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, Stellenbosch, South Africa.
| | - Barbara Hauer
- Department for Infectious Disease Epidemiology, Respiratory Infections Unit, Robert Koch Institute, Berlin, Germany
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, USA
| | - Walter Haas
- Department for Infectious Disease Epidemiology, Respiratory Infections Unit, Robert Koch Institute, Berlin, Germany
| | - Nita Perumal
- Department for Infectious Disease Epidemiology, Respiratory Infections Unit, Robert Koch Institute, Berlin, Germany.,Immunization Unit, Department for Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany
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46
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Portnoy A, Menzies NA. Financing sustainable health systems for the next decade. Lancet 2021; 398:1852-1853. [PMID: 34742370 DOI: 10.1016/s0140-6736(21)01828-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 08/06/2021] [Indexed: 11/25/2022]
Affiliation(s)
- Allison Portnoy
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Boston, MA 02115, USA.
| | - Nicolas A Menzies
- Center for Health Decision Science, Harvard T H Chan School of Public Health, Boston, MA 02115, USA; Department of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA 02115, USA
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47
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Earnest R, Rönn MM, Bellerose M, Menon-Johansson AS, Berruti AA, Chesson HW, Gift TL, Hsu KK, Testa C, Zhu L, Malyuta Y, Menzies NA, Salomon JA. Modeling the Cost-Effectiveness of Express Multisite Gonorrhea Screening Among Men Who Have Sex With Men in the United States. Sex Transm Dis 2021; 48:805-812. [PMID: 33993161 PMCID: PMC8505150 DOI: 10.1097/olq.0000000000001467] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 04/29/2021] [Indexed: 12/01/2022]
Abstract
BACKGROUND Men who have sex with men (MSM) experience high rates of gonococcal infection at extragenital (rectal and pharyngeal) anatomic sites, which often are missed without asymptomatic screening and may be important for onward transmission. Implementing an express pathway for asymptomatic MSM seeking routine screening at their clinic may be a cost-effective way to improve extragenital screening by allowing patients to be screened at more anatomic sites through a streamlined, less costly process. METHODS We modified an agent-based model of anatomic site-specific gonococcal infection in US MSM to assess the cost-effectiveness of an express screening pathway in which all asymptomatic MSM presenting at their clinic were screened at the urogenital, rectal, and pharyngeal sites but forewent a provider consultation and physical examination and self-collected their own samples. We calculated the cumulative health effects expressed as gonococcal infections and cases averted over 5 years, labor and material costs, and incremental cost-effectiveness ratios for express versus traditional scenarios. RESULTS The express scenario averted more infections and cases in each intervention year. The increased diagnostic costs of triple-site screening were largely offset by the lowered visit costs of the express pathway and, from the end of year 3 onward, this pathway generated small cost savings. However, in a sensitivity analysis of assumed overhead costs, cost savings under the express scenario disappeared in the majority of simulations once overhead costs exceeded 7% of total annual costs. CONCLUSIONS Express screening may be a cost-effective option for improving multisite anatomic screening among US MSM.
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Affiliation(s)
- Rebecca Earnest
- From the Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT
- Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA
| | - Minttu M. Rönn
- Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA
| | - Meghan Bellerose
- Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA
| | | | - Andrés A. Berruti
- Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA
| | - Harrell W. Chesson
- Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA
| | - Thomas L. Gift
- Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA
| | - Katherine K. Hsu
- Division of STD Prevention and HIV/AIDS Surveillance, Massachusetts Department of Public Health, Boston, MA
| | - Christian Testa
- Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA
| | - Lin Zhu
- Center for Health Policy/Center for Primary Care and Outcomes Research, School of Medicine, Stanford University, Stanford, CA
| | - Yelena Malyuta
- Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA
| | - Nicolas A. Menzies
- Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA
| | - Joshua A. Salomon
- Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA
- Center for Health Policy/Center for Primary Care and Outcomes Research, School of Medicine, Stanford University, Stanford, CA
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Pitzer VE, Chitwood M, Havumaki J, Menzies NA, Perniciaro S, Warren JL, Weinberger DM, Cohen T. The Impact of Changes in Diagnostic Testing Practices on Estimates of COVID-19 Transmission in the United States. Am J Epidemiol 2021; 190:1908-1917. [PMID: 33831148 PMCID: PMC8083380 DOI: 10.1093/aje/kwab089] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 03/22/2021] [Accepted: 03/26/2021] [Indexed: 12/28/2022] Open
Abstract
Estimates of the reproductive number for novel pathogens such as severe acute respiratory syndrome coronavirus 2 are essential for understanding the potential trajectory of the epidemic and the level of intervention that is needed to bring the epidemic under control. However, most methods for estimating the basic reproductive number (R0) and time-varying effective reproductive number (Rt) assume that the fraction of cases detected and reported is constant through time. We explore the impact of secular changes in diagnostic testing and reporting on estimates of R0 and Rt using simulated data. We then compare these patterns to data on reported cases of coronavirus disease and testing practices from different states in the United States from March 4 to August 30, 2020. We find that changes in testing practices and delays in reporting can result in biased estimates of R0 and Rt. Examination of changes in the daily number of tests conducted and the percent of patients testing positive may be helpful for identifying the potential direction of bias. Changes in diagnostic testing and reporting processes should be monitored and taken into consideration when interpreting estimates of the reproductive number of coronavirus disease.
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Affiliation(s)
- Virginia E Pitzer
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States
- Correspondence to: Virginia E. Pitzer, Yale School of Public Health, P.O. Box 208034, New Haven, CT 06520-8034 (e-mail: )
| | - Melanie Chitwood
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States
| | - Joshua Havumaki
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, United States
| | - Stephanie Perniciaro
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States
| | - Joshua L Warren
- Department of Biostatistics and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States
| | - Daniel M Weinberger
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, Yale University, New Haven, Connecticut, United States
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49
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McQuaid CF, Clarkson MC, Bellerose M, Floyd K, White RG, Menzies NA. An approach for improving the quality of country-level TB modelling. Int J Tuberc Lung Dis 2021; 25:614-619. [PMID: 34330345 PMCID: PMC8327628 DOI: 10.5588/ijtld.21.0127] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Mathematical modelling is increasingly used to inform budgeting and strategic decision-making by national TB programmes. Despite the importance of these decisions, there is currently no mechanism to review and confirm the appropriateness of modelling analyses. We have developed a benchmarking, reporting, and review (BRR) approach and accompanying tools to allow constructive review of country-level TB modelling applications. This approach has been piloted in five modelling applications and the results of this study have been used to revise and finalise the approach. The BRR approach consists of 1) quantitative benchmarks against which model assumptions and results can be compared, 2) standardised reporting templates and review criteria, and 3) a multi-stage review process providing feedback to modellers during the application, as well as a summary evaluation after completion. During the pilot, use of the tools prompted important changes in the approaches taken to modelling. The pilot also identified issues beyond the scope of a review mechanism, such as a lack of empirical evidence and capacity constraints. This approach provides independent evaluation of the appropriateness of modelling decisions during the course of an application, allowing meaningful changes to be made before results are used to inform decision-making. The use of these tools can improve the quality and transparency of country-level TB modelling applications.
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Affiliation(s)
- C F McQuaid
- TB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - M C Clarkson
- TB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - M Bellerose
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - K Floyd
- Global TB Programme, World Health Organization, Geneva, Switzerland
| | - R G White
- TB Modelling Group, TB Centre and Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - N A Menzies
- Department of Global Health and Population, Harvard TH Chan School of Public Health, Boston, MA, USA, Center for Health Decision Science, Harvard TH Chan School of Public Health, Boston, MA, USA
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50
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Kim S, Cohen T, Horsburgh CR, Miller JW, Hill AN, Marks SM, Li R, Kammerer JS, Salomon JA, Menzies NA. Trends, mechanisms, and racial/ethnic differences of tuberculosis incidence in the US-born population aged 50 years or older in the United States. Clin Infect Dis 2021; 74:1594-1603. [PMID: 34323959 PMCID: PMC8799750 DOI: 10.1093/cid/ciab668] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Indexed: 11/13/2022] Open
Abstract
Background Older age is a risk factor for tuberculosis (TB) in low incidence settings. Using data from the US National TB Surveillance System and American Community Survey, we estimated trends and racial/ethnic differences in TB incidence among US-born cohorts aged ≥50 years. Methods In total, 42 000 TB cases among US-born persons ≥50 years were reported during 2001–2019. We used generalized additive regression models to decompose the effects of birth cohort and age on TB incidence rates, stratified by sex and race/ethnicity. Using genotype-based estimates of recent transmission (available 2011–2019), we implemented additional models to decompose incidence trends by estimated recent versus remote infection. Results Estimated incidence rates declined with age, for the overall cohort and most sex and race/ethnicity strata. Average annual percentage declines flattened for older individuals, from 8.80% (95% confidence interval [CI] 8.34–9.23) in 51-year-olds to 4.51% (95% CI 3.87–5.14) in 90-year-olds. Controlling for age, incidence rates were lower for more recent birth cohorts, dropping 8.79% (95% CI 6.13–11.26) on average between successive cohort years. Incidence rates were substantially higher for racial/ethnic minorities, and these inequalities persisted across all birth cohorts. Rates from recent infection declined at approximately 10% per year as individuals aged. Rates from remote infection declined more slowly with age, and this annual percentage decline approached zero for the oldest individuals. Conclusions TB rates were highest for racial/ethnic minorities and for the earliest birth cohorts and declined with age. For the oldest individuals, annual percentage declines were low, and most cases were attributed to remote infection.
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Affiliation(s)
- Sun Kim
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - C Robert Horsburgh
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Jeffrey W Miller
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Andrew N Hill
- Division of Tuberculosis Elimination, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Suzanne M Marks
- Division of Tuberculosis Elimination, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Rongxia Li
- Division of Tuberculosis Elimination, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - J Steve Kammerer
- Division of Tuberculosis Elimination, U.S. Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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