Strategies to detect and manage latent tuberculosis infection among household contacts of pulmonary TB patients in high TB burden countries ‐ a systematic review and meta‐analysis

OBJECTIVE: To summarise latent tuberculosis infection (LTBI) management strategies among household contacts of bacteriologically confirmed pulmonary tuberculosis (TB) patients in high‐TB burden countries. METHODS: PubMed/MEDLINE (NCBI) and Scopus were searched (January 2006 to December 2021) for studies reporting primary data on LTBI management. Study selection, data management and data synthesis were protocol‐driven (PROSPERO‐CRD42021208715). Primary outcomes were the proportions of LTBI, initiating and completing tuberculosis preventive treatment (TPT). Reported factors influencing the LTBI care cascade were qualitatively synthesised. RESULTS: From 3694 unique records retrieved, 58 studies from 23 countries were included. Most identified contacts were screened (median 99%, interquartile range [IQR] 82%–100%; 46 studies). Random‐effects meta‐analysis yielded pooled proportions for: LTBI 41% (95% confidence interval [CI] 33%–49%; 21,566 tested contacts); TPT initiation 91% (95% CI 79%–97%; 129,573 eligible contacts, 34 studies); TPT completion 65% (95% CI 54%–74%; 108,679 TPT‐initiated contacts, 28 studies). Heterogeneity was significant (I (2) ≥ 95%–100%) and could not be explained in subgroup analyses. Median proportions (IQR) were: LTBI 44% (28%–59%); TPT initiation 86% (60%–100%); TPT completion 68% (44%–82%). Nine broad themes related to diagnostic testing, health system structure and functions, risk perception, documentation and adherence were considered likely to influence the LTBI care cascade. CONCLUSION: The proportions of household contacts screened, detected with LTBI and initiated on TPT, though variable was high, but the proportions completing TPT were lower indicating current strategies used for LTBI management in high TB burden countries are not sufficient

Operational Challenges in Diagnosing Multi-Drug Resistant TB and Initiating Treatment in Andhra Pradesh, India

Revised National TB Control Programme (RNTCP), Andhra Pradesh, India. There is limited information on whether MDR-TB suspects are identified, undergo diagnostic assessment and are initiated on treatment according to the programme guidelines.To assess i) using the programme definition, the number and proportion of MDR-TB suspects in a large cohort of TB patients on first-line treatment under RNTCP ii) the proportion of these MDR-TB suspects who underwent diagnosis for MDR-TB and iii) the number and proportion of those diagnosed as MDR-TB who were successfully initiated on treatment.A retrospective cohort analysis, by reviewing RNTCP records and reports, was conducted in four districts of Andhra Pradesh, India, among patients registered for first line treatment during October 2008 to December 2009.Among 23,999 TB patients registered for treatment there were 559 (2%) MDR-TB suspects (according to programme definition) of which 307 (55%) underwent diagnosis and amongst these 169 (55%) were found to be MDR-TB. Of the MDR-TB patients, 112 (66%) were successfully initiated on treatment. Amongst those eligible for MDR-TB services, significant proportions are lost during the diagnostic and treatment initiation pathway due to a variety of operational challenges. The programme needs to urgently address these challenges for effective delivery and utilisation of the MDR-TB services

Source of Previous Treatment for Re-Treatment TB Cases Registered under the National TB Control Programme, India, 2010

BACKGROUND: In 2009, nearly half (289,756) of global re-treatment TB notifications are from India; no nationally-representative data on the source of previous treatment was available to inform strategies for improvement of initial TB treatment outcome. OBJECTIVES: To assess the source of previous treatment for re-treatment TB patients registered under India's Revised National TB control Programme (RNTCP). METHODOLOGY: A nationally-representative cross sectional study was conducted in a sample of 36 randomly-selected districts. All consecutively registered retreatment TB patients during a defined 15-day period in these 36 districts were contacted and the information on the source of previous treatment sought. RESULTS: Data was collected from all 1712 retreatment TB patients registered in the identified districts during the study period. The data includes information on 595 'relapse' cases, 105 'failure' cases, 437 'treatment after default (TAD)' cases and 575 're-treatment others' cases. The source of most recent previous anti-tuberculosis therapy for 754 [44% (95% CI, 38.2%-49.9%)] of the re-treatment TB patients was from providers outside the TB control programme. A higher proportion of patients registered as TAD (64%) and 'retreatment others' (59%) were likely to be treated outside the National Programme, when compared to the proportion among 'relapse' (22%) or 'failure' (6%). Extrapolated to national registration, of the 292,972 re-treatment registrations in 2010, 128,907 patients would have been most recently treated outside the national programme. CONCLUSIONS: Nearly half of the re-treatment cases registered with the national programme were most recently treated outside the programme setting. Enhanced efforts towards extending treatment support and supervision to patients treated by private sector treatment providers are urgently required to improve the quality of treatment and reduce the numbers of patients with recurrent disease. In addition, reasons for the large number of recurrent TB cases from those already treated by the national programme require urgent detailed investigation

How Do Patients Who Fail First-Line TB Treatment but Who Are Not Placed on an MDR-TB Regimen Fare in South India?

SETTING: Seven districts in Andhra Pradesh, South India. OBJECTIVES: To a) determine treatment outcomes of patients who fail first line anti-TB treatment and are not placed on an multi-drug resistant TB (MDR-TB) regimen, and b) relate the treatment outcomes to culture and drug susceptibility patterns (C&DST). DESIGN: Retrospective cohort study using routine programme data and Mycobacterium TB Culture C&DST between July 2008 and December 2009. RESULTS: There were 202 individuals given a re-treatment regimen and included in the study. Overall treatment outcomes were: 68 (34%) with treatment success, 84 (42%) failed, 36 (18%) died, 13 (6.5%) defaulted and 1 transferred out. Treatment success for category I and II failures was low at 37%. In those with positive cultures, 81 had pan-sensitive strains with 31 (38%) showing treatment success, while 61 had drug-resistance strains with 9 (15%) showing treatment success. In 58 patients with negative cultures, 28 (48%) showed treatment success. CONCLUSION: Treatment outcomes of patients who fail a first-line anti-TB treatment and who are not placed on an MDR-TB regimen are unacceptably poor. The worst outcomes are seen among category II failures and those with negative cultures or drug-resistance. There are important programmatic implications which need to be addressed

Whole-Genome Sequencing to Identify Missed Rifampicin and Isoniazid Resistance Among Tuberculosis Isolates—Chennai, India, 2013–2016

India has a high burden of drug-resistant tuberculosis (DR TB) and many cases go undetected by current drug susceptibility tests (DSTs). This study was conducted to identify rifampicin (RIF) and isoniazid (INH) resistance associated genetic mutations undetected by current clinical diagnostics amongst persons with DR TB in Chennai, India. Retrospectively stored 166 DR TB isolates during 2013–2016 were retrieved and cultured in Löwenstein-Jensen medium. Whole genome sequencing (WGS) and MGIT DST for RIF and INH were performed. Discordant genotypic and phenotypic sensitivity results were repeated for confirmation and the discrepant results considered final. Further, drug resistance-conferring mutations identified through WGS were analyzed for their presence as targets in current WHO-recommended molecular diagnostics. WGS detected additional mutations for rifampicin and isoniazid resistance than WHO-endorsed line probe assays. For RIF, WGS was able to identify an additional 10% (15/146) of rpoB mutant isolates associated with borderline rifampicin resistance compared to MGIT DST. WGS could detect additional DR TB cases than commercially available and WHO-endorsed molecular DST tests. WGS results reiterate the importance of the recent WHO revised critical concentrations of current MGIT DST to detect low-level resistance to rifampicin. WGS may help inform effective treatment selection for persons at risk of, or diagnosed with, DR TB

Piloting Upfront Xpert MTB/RIF Testing on Various Specimens under Programmatic Conditions for Diagnosis of TB & DR-TB in Paediatric Population

India accounts for one-fifth of the global TB incidence. While the exact burden of childhood TB is not known, TB remains one of the leading causes of childhood mortality in India. Bacteriological confirmation of TB in children is challenging due to difficulty in obtaining quality specimens, in the absence of which diagnosis is largely based on clinical judgement. While testing multiple specimens can potentially contribute to higher proportion of laboratory confirmed paediatric TB cases, lack of high sensitivity tests adds to the diagnostic challenge. We describe here our experiences in piloting upfront Xpert MTB/RIF testing, for diagnosis of TB in paediatric population in respiratory and extra pulmonary specimens, as recently recommended by WHO.Xpert MTB/RIF testing was offered to all paediatric (0-14 years) presumptive TB cases (both pulmonary and extra-pulmonary) seeking care at public and private health facilities in the project areas covering 4 cities of India.Under this pilot project, 8,370 paediatric presumptive TB & presumptive DR-TB cases were tested between April and-November 2014. Overall, 9,149 specimens were tested, of which 4,445 (48.6%) were non-sputum specimens. Xpert MTB/RIF gave 9,083 (99.2%, CI 99.0-99.4) valid results. Of the 8,143 presumptive TB cases enrolled, 517 (6.3%, CI 5.8-6.9) were bacteriologically confirmed. TB detection rates were two fold higher with Xpert MTB/RIF as compared to smear microscopy. Further, a total of 60 rifampicin resistant TB cases were detected, of which 38 were detected among 512 presumptive TB cases while 22 were detected amongst 227 presumptive DR-TB cases tested under the project.Xpert MTB/RIF with advantages of quick turnaround testing-time, high proportion of interpretable results and feasibility of rapid rollout, substantially improved the diagnosis of bacteriologically confirmed TB in children, while simultaneously detecting rifampicin resistance

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

How did the TB patients reach DOTS services in Delhi? A study of patient treatment seeking behavior.

SETTING: Revised National Tuberculosis Control Programme (RNTCP), Delhi, India. OBJECTIVE: To ascertain the number and sequence of providers visited by TB patients before availing treatment services from DOTS; to describe the duration between onset of symptoms to treatment. STUDY DESIGN: A cross sectional, qualitative study. Information was gathered through in-depth interviews of TB patients registered during the month of Oct, 2012 for availing TB treatment under the Revised National TB Control Programme from four tuberculosis diagnosis and treatment centers in Delhi. RESULTS: Out of the 114 patients who registered, 108 participated in the study. The study showed that informal providers and retail chemists were the first point of contact and source of clinical advice for two-third of the patients, while the rest sought medical care from qualified providers directly. Most patients sought medical care from more than two providers, before being diagnosed as TB. Female TB patients and patients with extra-pulmonary TB had long mean duration between onset of symptoms to initiation of treatment (6.3 months and 8.4 months respectively). CONCLUSION: The pathways followed by TB patients, illustrated in this study, provide valuable lessons on the importance of different types of providers (both formal and informal) in the health system in a society like India and the delays in the diagnosis and treatment of tuberculosis