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.

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.

Quantifying gaps in the tuberculosis care cascade in Brazil: A mathematical model study using national program data.

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.

Impact and cost-effectiveness of the 6-month BPaLM regimen for rifampicin-resistant tuberculosis in Moldova: A mathematical modeling analysis.

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, 0.03] 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.

Estimated rates of progression to tuberculosis disease for persons infected with Mycobacterium tuberculosis in the United States.

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.

Associations Between Alcohol Use, Antiretroviral Therapy Use, and Viral Load Suppression Among People Living with HIV in Rural Central Uganda.

Alcohol use among people living with HIV (PWH) is common and may negatively affect engagement in HIV care. We evaluated the relationships between alcohol use, ART use, and viral suppression among PWH in Uganda. PATH/Ekkubo was a trial evaluating a linkage to HIV care intervention in four Ugandan districts, Nov 2015-Sept 2021. Our analytical sample included: (1) baseline data from individuals not enrolled in the intervention trial (previously diagnosed HIV+); and 12-month follow-up data from the control group (newly diagnosed or previously diagnosed, but not in care). Level of alcohol use was categorized using the Alcohol Use Disorders Identification Test-Consumption (AUDIT-C): none (AUDIT-C = 0), low (women = 1-2, men = 1-3), medium (women = 3-5, men = 4-5), high/very high (6-12). Multivariable logistic regression models evaluated associations between alcohol use, ART use and viral suppression (a viral load of < 20); we also stratified by gender. Among 931 PWH, medium (OR: 0.43 [95% CI 0.25-0.72]) and high/very high (OR: 0.22 [95% CI 0.11-0.42]) levels of alcohol use were associated with lower odds of being on ART. In a sub-sample of 664, medium use (OR: 0.63 [95% CI 0.41-0.97]) was associated with lower odds of viral suppression. However, this association was not statistically significant when restricting to those on ART, suggesting the relationship between alcohol use and viral suppression is explained by ART use. Among men, high/very high, and among women, medium alcohol use levels were associated with lower odds of being on ART and being virally suppressed. Interventions for PWH who use higher levels of alcohol may be needed to optimize the benefits of Uganda's Universal Test and Treat strategy.

Predictors of unsuccessful tuberculosis treatment outcomes in Brazil: an analysis of 259,484 patient records.

INTRODUCTION: Tuberculosis (TB) causes over 1 million deaths annually. Providing effective treatment is a key strategy for reducing TB deaths. In this study, we identified factors associated with unsuccessful treatment outcomes among individuals treated for TB in Brazil. METHODS: We obtained data on individuals treated for TB between 2015 and 2018 from Brazil's National Disease Notification System (SINAN). We excluded patients with a history of prior TB disease or with diagnosed TB drug resistance. We extracted information on patient-level factors potentially associated with unsuccessful treatment, including demographic and social factors, comorbid health conditions, health-related behaviors, health system level at which care was provided, use of directly observed therapy (DOT), and clinical examination results. We categorized treatment outcomes as successful (cure, completed) or unsuccessful (death, regimen failure, loss to follow-up). We fit multivariate logistic regression models to identify factors associated with unsuccessful treatment. RESULTS: Among 259,484 individuals treated for drug susceptible TB, 19.7% experienced an unsuccessful treatment outcome (death during treatment 7.8%, regimen failure 0.1%, loss to follow-up 11.9%). The odds of unsuccessful treatment were higher with older age (adjusted odds ratio (aOR) 2.90 [95% confidence interval: 2.62-3.21] for 85-100-year-olds vs. 25-34-year-olds), male sex (aOR 1.28 [1.25-1.32], vs. female sex), Black race (aOR 1.23 [1.19-1.28], vs. White race), no education (aOR 2.03 [1.91-2.17], vs. complete high school education), HIV infection (aOR 2.72 [2.63-2.81], vs. no HIV infection), illicit drug use (aOR 1.95 [1.88-2.01], vs. no illicit drug use), alcohol consumption (aOR 1.46 [1.41-1.50], vs. no alcohol consumption), smoking (aOR 1.20 [1.16-1.23], vs. non-smoking), homelessness (aOR 3.12 [2.95-3.31], vs. no homelessness), and immigrant status (aOR 1.27 [1.11-1.45], vs. non-immigrants). Treatment was more likely to be unsuccessful for individuals treated in tertiary care (aOR 2.20 [2.14-2.27], vs. primary care), and for patients not receiving DOT (aOR 2.35 [2.29-2.41], vs. receiving DOT). CONCLUSION: The risk of unsuccessful TB treatment varied systematically according to individual and service-related factors. Concentrating clinical attention on individuals with a high risk of poor treatment outcomes could improve the overall effectiveness of TB treatment in Brazil.

Predictive power of wastewater for nowcasting infectious disease transmission: A retrospective case study of five sewershed areas in Louisville, Kentucky.

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.

Prioritizing Quality Measures in Acute Stroke Care : A Cost-Effectiveness Analysis.

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.

Population Immunity to Pre-Omicron and Omicron Severe Acute Respiratory Syndrome Coronavirus 2 Variants in US States and Counties Through 1 December 2021.

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.

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.

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.

The potential impact of novel tuberculosis vaccine introduction on economic growth in low- and middle-income countries: A modeling study.

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.

The cost and cost-effectiveness of novel tuberculosis vaccines in low- and middle-income countries: A modeling study.

BACKGROUND: Tuberculosis (TB) is preventable and curable but eliminating it has proven challenging. Safe and effective TB vaccines that can rapidly reduce disease burden are essential for achieving TB elimination. We assessed future costs, cost-savings, and cost-effectiveness of introducing novel TB vaccines in low- and middle-income countries (LMICs) for a range of product characteristics and delivery strategies. METHODS AND FINDINGS: We developed a system of epidemiological and economic models, calibrated to demographic, epidemiological, and health service data in 105 LMICs. For each country, we assessed the likely future course of TB-related outcomes under several vaccine introduction scenarios, compared to a "no-new-vaccine" counterfactual. Vaccine scenarios considered 2 vaccine product profiles (1 targeted at infants, 1 at adolescents/adults), both assumed to prevent progression to active TB. Key economic inputs were derived from the Global Health Cost Consortium, World Health Organization (WHO) patient cost surveys, and the published literature. We estimated the incremental impact of vaccine introduction for a range of health and economic outcomes. In the base-case, we assumed a vaccine price of $4.60 and used a 1× per-capita gross domestic product (GDP) cost-effectiveness threshold (both varied in sensitivity analyses). Vaccine introduction was estimated to require substantial near-term resources, offset by future cost-savings from averted TB burden. From a health system perspective, adolescent/adult vaccination was cost-effective in 64 of 105 LMICs. From a societal perspective (including productivity gains and averted patient costs), adolescent/adult vaccination was projected to be cost-effective in 73 of 105 LMICs and cost-saving in 58 of 105 LMICs, including 96% of countries with higher TB burden. When considering the monetized value of health gains, we estimated that introduction of an adolescent/adult vaccine could produce $283 to 474 billion in economic benefits by 2050. Limited data availability required assumptions and extrapolations that may omit important country-level heterogeneity in epidemiology and costs. CONCLUSIONS: TB vaccination would be highly impactful and cost-effective in most LMICs. Further efforts are needed for future development, adoption, and implementation of novel TB vaccines.

New tuberculosis vaccines in India: modelling the potential health and economic impacts of adolescent/adult vaccination with M72/AS01E and BCG-revaccination.

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.

Tabby2: a user-friendly web tool for forecasting state-level TB outcomes in the United States.

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.

Costs, Health Benefits, and Cost-Effectiveness of Chlamydia Screening and Partner Notification in the United States, 2000-2019: A Mathematical Modeling Analysis.

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.

Reconstructing the course of the COVID-19 epidemic over 2020 for US states and counties: Results of a Bayesian evidence synthesis model.

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.

Generating simple classification rules to predict local surges in COVID-19 hospitalizations.

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes and relaxation of mitigation measures leave many US communities at risk for surges of COVID-19 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations 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 a framework to generate simple classification 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. This framework uses a simulation model of SARS-CoV-2 transmission and COVID-19 hospitalizations in the US to train classification decision trees that are robust to changes in the data-generating process and future uncertainties. These generated classification 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 show that these classification 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. Our proposed classification rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.

Trends, Mechanisms, and Racial/Ethnic Differences of Tuberculosis Incidence in the US-Born Population Aged 50 Years or Older in the United States.

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.

Phylogeography and transmission of M. tuberculosis in Moldova: A prospective genomic analysis.

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.

The Health and Economic Benefits of Tests That Predict Future Progression to Tuberculosis Disease.

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.