The prevalence and risk factors for tuberculosis among healthcare workers in Yogyakarta, Indonesia.

Healthcare workers (HCWs) are at risk of contracting TB, particularly when in high tuberculosis (TB) burden settings. Routine surveillance data and evidence are limited on the burden of TB amongst HCWs in Indonesia. We aimed to measure the prevalence of TB infection (TBI) and disease among HCWs in four healthcare facilities in Yogyakarta province in Indonesia, and explore risk factors for TBI. A cross-sectional TB screening study targeted all HCWs from four pre-selected facilities (1 hospital, 3 primary care) in Yogyakarta, Indonesia. Voluntary screening included symptom assessment, Chest X-ray (CXR), Xpert MTB/RIF (if indicated) and tuberculin skin test (TST). Analyses were descriptive and included multivariable logistic regression. Of 792 HCWs, 681 consented (86%) to the screening; 59% (n = 401) were female, 62% were medical staff (n = 421), 77% worked in the one participating hospital (n = 524), and the median time working in the health sector was 13 years (IQR: 6-25 years). Nearly half had provided services for people with TB (46%, n = 316) and 9% reported ever having TB (n = 60). Among participants with presumptive TB (15%, n = 99/662), none were diagnosed microbiologically or clinically with active TB disease. TBI was detected in 25% (95% CI: 22-30; n = 112/441) of eligible HCWs with a TST result. A significant association was found between TB infection and being male (adjusted Odds Ratio (aOR) 2.02 (95%CI: 1.29-3.17)), currently working in the participating hospital compared to primary care (aOR 3.15 (95%CI: 1.75-5.66)), and older age (1.05 OR increase per year of life between 19-73 years (95%CI: 1.02-1.06)). This study supports prioritisation of HCWs as a high-risk group for TB infection and disease, and the need for comprehensive prevention and control programs in Indonesia. Further, it identifies characteristics of HCWs in Yogyakarta at higher risk of TBI, who could be prioritised in screening programs if universal coverage of prevention and control measures cannot be achieved.

Prevalence of Latent Tuberculosis Infection among Patients Undergoing Regular Hemodialysis in Disenfranchised Communities: A Multicenter Study during COVID-19 Pandemic.

Background and Objectives: Due to their weakened immune response, hemodialysis (HD) patients with latent tuberculosis infection (LTBI) are at higher risk for active tuberculosis (TB) disease and are more subject to patient-to-patient transmission within dialysis units. Consequently, current guidelines advocate screening these patients for LTBI. To our knowledge, the epidemiology of LTBI in HD patients has never been examined before in Lebanon. In this context, this study aimed to determine LTBI prevalence among patients undergoing regular HD in Northern Lebanon and to identify potential factors associated with this infection. Notably, the study was conducted during the COVID-19 pandemic, which is likely to have catastrophic effects on TB and increase the risk of mortality and hospitalization in HD patients. Materials and Methods: A multicenter cross-sectional study was carried out in three hospital dialysis units in Tripoli, North Lebanon. Blood samples and sociodemographic and clinical data were collected from 93 HD patients. To screen for LTBI, all patient samples underwent the fourth-generation QuantiFERON-TB Gold Plus assay (QFT-Plus). Multivariable logistic regression analysis was used to identify the predictors of LTBI status in HD patients. Results: Overall, 51 men and 42 women were enrolled. The mean age of the study population was 58.3 ± 12.4 years. Nine HD patients had indeterminate QFT-Plus results and were therefore excluded from subsequent statistical analysis. Among the remaining 84 participants with valid results, QFT-Plus was positive in 16 patients, showing a positivity prevalence of 19% (95% interval for p: 11.3%, 29.1%). Multivariable logistic regression analysis showed that LTBI was significantly associated with age [OR = 1.06; 95% CI = 1.01 to 1.13; p = 0.03] and a low-income level [OR = 9.29; 95% CI = 1.62 to 178; p = 0.04]. Conclusion: LTBI was found to be prevalent in one in five HD patients examined in our study. Therefore, effective TB control measures need to be implemented in this vulnerable population, with special attention to elderly patients with low socioeconomic status.

Bayesian spatial modelling of tuberculosis-HIV co-infection in Ethiopia.

An in-depth analysis of the epidemiological patterns of TB/HIV co-infection is essential since it helps to target high-risk areas with effective control measures. The main objective of this study was to assess the spatial clustering of TB/HIV co-infection prevalence in Ethiopia for the year 2018 using district-level aggregated TB and HIV data obtained from the Ethiopian Federal Ministry of Health. The global Moran's index, Getis-Ord [Formula: see text] local statistic, and Bayesian spatial modeling techniques were applied to analyse the data. The result of the study shows that TB among people living with HIV (PLHIV) and HIV among TB patients prevalence were geographically heterogeneous. The highest prevalence of TB among PLHIV in 2018 was reported in the Gambella region (1.44%). The overall prevalence of TB among PLHIV in Ethiopia in the same year was 0.38% while the prevalence of HIV among TB patients was 6.88%. Both district-level prevalences of HIV among TB patients and TB among PLHIV were positively spatially autocorrelated, but the latter was not statistically significant. The local indicators of spatial analysis using the Getis-Ord statistic also identified hot-spots districts for both types of TB/HIV co-infection data. The results of Bayesian spatial logistic regression with spatially structured and unstructured random effects using the Besag, York, and Mollié prior showed that not all the heterogeneities in the prevalence of HIV among TB patients and TB among PLHIV were explained by the spatially structured random effects. This study expanded knowledge about the spatial clustering of TB among PLHIV and HIV among TB patients in Ethiopia at the district level in 2018. The findings provide information to health policymakers in the country to plan geographically targeted and integrated interventions to jointly control TB and HIV.

Time to diagnosis and treatment of pulmonary tuberculosis in indigenous peoples: a systematic review.

BACKGROUND: Time to diagnosis and treatment is a major factor in determining the likelihood of tuberculosis (TB) transmission and is an important area of intervention to reduce the reservoir of TB infection and prevent disease and mortality. Although Indigenous peoples experience an elevated incidence of TB, prior systematic reviews have not focused on this group. We summarize and report findings related to time to diagnosis and treatment of pulmonary TB (PTB) among Indigenous peoples, globally. METHODS: A Systematic review was performed using Ovid and PubMed databases. Articles or abstracts estimating time to diagnosis, or treatment of PTB among Indigenous peoples were included with no restriction on sample size with publication dates restricted up to 2019. Studies that focused on outbreaks, solely extrapulmonary TB alone in non-Indigenous populations were excluded. Literature was assessed using the Hawker checklist. Registration Protocol (PROSPERO): CRD42018102463. RESULTS: Twenty-four studies were selected after initial assessment of 2021 records. These included Indigenous groups from five of six geographical regions outlined by the World Health Organization (all except the European Region). The range of time to treatment (24-240 days), and patient delay (20 days-2.5 years) were highly variable across studies and, in at least 60% of the studies, longer in Indigenous compared to non-Indigenous peoples. Risk factors associated with longer patient delays included poor awareness of TB, type of health provider first seen, and self-treatment. CONCLUSION: Time to diagnosis and treatment estimates for Indigenous peoples are generally within previously reported ranges from other systematic reviews focusing on the general population. However among literature examined in this systematic review that stratified by Indigenous and non-Indigenous peoples, patient delay and time to treatment were longer compared to non-Indigenous populations in over half of the studies. Studies included were sparse and highlight an overall gap in literature important to interrupting transmission and preventing new TB cases among Indigenous peoples. Although, risk factors unique to Indigenous populations were not identified, further investigation is needed as social determinants of health among studies conducted in medium and high incidence countries may be shared across both population groups. Trial registration N/a.

Beyond the Clinic: The Activation of Diverse Cellular and Humoral Factors Shapes the Immunological Status of Patients with Active Tuberculosis.

Mycobacterium tuberculosis (Mtb), the etiologic agent of tuberculosis (TB), has killed nearly one billion people in the last two centuries. Nowadays, TB remains a major global health problem, ranking among the thirteen leading causes of death worldwide. Human TB infection spans different levels of stages: incipient, subclinical, latent and active TB, all of them with varying symptoms, microbiological characteristics, immune responses and pathologies profiles. After infection, Mtb interacts with diverse cells of both innate and adaptive immune compartments, playing a crucial role in the modulation and development of the pathology. Underlying TB clinical manifestations, individual immunological profiles can be identified in patients with active TB according to the strength of their immune responses to Mtb infection, defining diverse endotypes. Those different endotypes are regulated by a complex interaction of the patient's cellular metabolism, genetic background, epigenetics, and gene transcriptional regulation. Here, we review immunological categorizations of TB patients based on the activation of different cellular populations (both myeloid and lymphocytic subsets) and humoral mediators (such as cytokines and lipid mediators). The analysis of the participating factors that operate during active Mtb infection shaping the immunological status or immune endotypes of TB patients could contribute to the development of Host Directed Therapy.

Tuberculosis Outbreak in a State Prison System - Washington, 2021-2022.

During 2014-2020, no tuberculosis (TB) cases were reported within the Washington state prison system. However, during July 2021-June 2022, 25 TB cases were reported among persons incarcerated or formerly incarcerated in two Washington state prisons. Phylogenetic analyses of whole genome sequencing data indicated that Mycobacterium tuberculosis isolates from all 11 patients with culture-confirmed TB were closely related, suggesting that these cases represented a single outbreak. The median infectious period for 12 patients who were considered likely contagious was 170 days. As of November 15, 2022, the Washington State Department of Corrections (WADOC) and Washington State Department of Health (WADOH), with technical assistance from CDC, had identified 3,075 contacts among incarcerated residents and staff members at five state prisons, and 244 contacts without a known TB history received a diagnosis of latent TB infection (LTBI). Persons who were evaluated for TB disease were isolated; those receiving a diagnosis of TB then initiated antituberculosis therapy. Persons with LTBI were offered treatment to prevent progression to TB disease. This ongoing TB outbreak is the largest in Washington in 20 years. Suspension of annual TB screening while limited resources were redirected toward the COVID-19 response resulted in delayed case detection that facilitated TB transmission. In addition, fear of isolation might discourage residents and staff members from reporting symptoms, which likely also leads to delayed TB diagnoses. Continued close collaboration between WADOC and WADOH is needed to end this outbreak and prevent future outbreaks.

First evaluation of the performance of portable IGRA, QIAreach® QuantiFERON®-TB in intermediate TB incidence setting.

Diagnosis and treatment of tuberculosis infection (TBI) are the core elements of tuberculosis elimination. Interferon gamma release assays have advantages over the tuberculin skin test, although their implementation in low-resource settings is challenging. The performance of a novel digital lateral flow assay QIAreach® QuantiFERON®-TB (QIAreach QFT) against the QuantiFERON®-TB Gold Plus (QFT-Plus) assay was evaluated in an intermediate incidence setting (Malaysia) according to the manufacturer's instructions. Individuals aged 4-82 years, who were candidates for TB infection screening for contact investigation were prospectively recruited. On 196 samples, the QIAreach-QFT showed a positive percent agreement (sensitivity) was 96.5% (CI 87.9-99.6%), a negative percent agreement (specificity) 94.2% (CI 88.4% to 97.6%) and an overall percentage of agreement was 94.9% (95% CI 90.6-97.6%) with a Cohen's κ of 0,88. Out of 196, 5.6% (11/196) samples gave an error result on QIAreach-QFT and 4.1% (8/196) samples gave indeterminate result on QFT-plus. The TTR for QIAreach QFT positive samples varied from 210-1200 seconds (20 min) and significantly correlated with IFN-γ level of QFT-Plus. QIAreach QFT could be considered an accurate and reliable point-of-need test to diagnose TB infection helping to achieve the WHO End TB programme goals even in decentralised settings where laboratory expertise and infrastructure may be limited.

Impact of COVID-19 Pandemic on Tuberculosis Preventive Services and Their Post-Pandemic Recovery Strategies: A Rapid Review of Literature.

BACKGROUND: Coronavirus disease 2019 (COVID-19) pandemic has disrupted tuberculosis (TB) care and prevention around the world. The aim of this study is to review literature on the impact of COVID-19 on TB preventive services and discuss their policy options during and after the pandemic. METHODS: We conducted a rapid review of scientific literature on the impact of COVID-19 on TB preventive services and their recovery strategies. After conducting a line-by-line open coding, their codes were applied in the descriptive theme building process, which was guided by the End TB strategy. TB preventive measures were selected and classified into five analytical categories: 1) vaccination against TB, 2) detection and treatment of latent TB infection (LTBI), 3) screening and diagnostics, 4) active case finding and contact tracing, and 5) surveillance. RESULTS: We identified 93 articles, of which 65 were research articles. During the pandemic, we observed decrease in Bacillus Calmette-Guérin (BCG) coverage, TB diagnostic services, case finding activities, and LTBI management. TB case detection was declined, which was not resumed to the pre-pandemic level after loosening the lock-down. Several recommendations were highlighted: 1) secure BCG stocks and its supply chains, 2) consider catch-up activities of routine immunization and LTBI screening, 3) maintain minimal TB health services, infection prevention and control, and surveillance, 4) leverage laboratory capacity and contact tracing mechanisms, 5) consider simultaneous testing for TB and COVID-19, and 6) Incorporate digital health technologies. CONCLUSIONS: Our findings and lessons learnt from the pandemic can aid in the development of future national TB control program.

Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature.

Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups-healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.

Tuberculosis in individuals who recovered from COVID-19: A systematic review of case reports.

BACKGROUND: The emergence of COVID-19 overwhelmed tuberculosis (TB) prevention and control, resulting in a decrease in TB detection rate and an increase in TB deaths. Furthermore, the temporary immunosuppressive effects, lung inflammation, and the corticosteroids used to treat COVID-19, may play a direct role in immunosuppression, leading to reactivation of either previous infection or latent TB or the development of new TB. Thus, the aim of this study was to review TB incidence in individuals who recovered from COVID-19. METHODS: We conducted a systematic search of available databases for previously published studies that reported TB in COVID-19 survivors. The PRISMA checklist was used to guide the review, and the JBI checklist was used to evaluate the study's quality. The descriptive data were summarized. RESULTS: Data were extracted from 21 studies conducted in 13 countries having 33 cases. The median age was 44 years (range; 13.5-80), and more than half (18, 54.5%) were males. Twelve patients immigrated from TB endemic settings. All 17 patients assessed for HIV were seronegative, and all 11 patients assessed for BCG vaccination status were vaccinated. The majority (20, 69%) of patients had some type of comorbidity with diabetes (12/29) and hypertension (9/29) being the most common. Four patients (30.77%) had a history of TB. Corticosteroids were used to treat COVID-19 in 62.5% (10) of individuals. Dexamethasone, remdesivir, azithromycin, hydroxychloroquine, and enoxaparin were the most commonly used drugs to treat COVID-19. The most common TB symptoms were fever, cough, weight loss, dyspnea, and fatigue. Twenty, eleven, and two patients developed pulmonary, extrapulmonary, and disseminated/miliary TB respectively. It may take up to seven months after COVID-19 recovery to develop tuberculosis. Data on the final treatment outcome was found for 24 patients, and five patients died during the anti-TB treatment period. CONCLUSION: Tuberculosis after recovering from COVID-19 is becoming more common, potentially leading to a TB outbreak in the post-COVID-19 era. The immunosuppressive nature of the disease and its treatment modalities may contribute to post COVID-19 TB. Thus, we recommend a further study with a large sample size. Furthermore, we recommend feasibility studies to assess and treat latent TB in COVID-19 patients residing in TB endemic counties since treatment of latent TB is done only in TB non-endemic countries.

Immune responses in COVID-19 and tuberculosis coinfection: A scoping review.

Background and aim: Patients with COVID-19 and tuberculosis coinfection are at an increased risk of severe disease and death. We therefore sought to evaluate the current evidence which assessed the immune response in COVID-19 and tuberculosis coinfection. Methods: We searched Pubmed/MEDLINE, EMBASE, Scopus, and Web of Science to identify articles published between 2020 and 2021. We included observational studies evaluating the immune response in patients with tuberculosis and COVID-19 compared to patients with COVID-19 alone. Results: Four cross-sectional studies (372 participants) were identified. In patients with asymptomatic COVID-19 and latent tuberculosis (LTBI), increased cytokines, chemokines, growth factors and humoral responses were found. In addition, patients with symptomatic COVID-19 and LTBI had higher leukocytes counts and less inflammation. Regarding patients with COVID-19 and active tuberculosis (aTB), they exhibited decreased total lymphocyte counts, CD4 T cells specific against SARS-CoV-2 and responsiveness to SARS-CoV-2 antigens compared to patients with only COVID-19. Conclusion: Although the evidence is limited, an apparent positive immunomodulation is observed in patients with COVID-19 and LTBI. On the other hand, patients with COVID-19 and aTB present a dysregulated immune response. Longitudinal studies are needed to confirm these findings and expand knowledge.

Evaluating the effect of short-course rifapentine-based regimens with or without enhanced behaviour-targeted treatment support on adherence and completion of treatment for latent tuberculosis infection among adults in the UK (RID-TB: Treat): protocol for an open-label, multicentre, randomised controlled trial.

INTRODUCTION: The successful scale-up of a latent tuberculosis (TB) infection testing and treatment programme is essential to achieve TB elimination. However, poor adherence compromises its therapeutic effectiveness. Novel rifapentine-based regimens and treatment support based on behavioural science theory may improve treatment adherence and completion. METHODS AND ANALYSIS: A pragmatic multicentre, open-label, randomised controlled trial assessing the effect of novel short-course rifapentine-based regimens for TB prevention and additional theory-based treatment support on treatment adherence against standard-of-care. Participants aged between 16 and 65 who are eligible to start TB preventive therapy will be recruited in England. 920 participants will be randomised to one of six arms with allocation ratio of 5:5:6:6:6:6: daily isoniazid +rifampicin for 3 months (3HR), routine treatment support (control); 3HR, additional treatment support; weekly isoniazid +rifapentine for 3 months (3HP), routine treatment support; weekly 3HP, additional treatment support ; daily isoniazid +rifapentine for 1 month (1HP), routine treatment support; daily 1HP, additional treatment support. Additional treatment support comprises reminders using an electronic pillbox, a short animation, and leaflets based on the perceptions and practicalities approach. The primary outcome is adequate treatment adherence, defined as taking ≥90% of allocated doses within the pre-specified treatment period, measured by electronic pillboxes. Secondary outcomes include safety and TB incidence within 12 months. We will conduct process evaluation of the trial interventions and assess intervention acceptability and fidelity and mechanisms for effect and estimate the cost-effectiveness of novel regimens. The protocol was developed with patient and public involvement, which will continue throughout the trial. ETHICS AND DISSEMINATION: Ethics approval has been obtained from The National Health Service Health Research Authority (20/LO/1097). All participants will be required to provide written informed consent. We will share the results in peer-reviewed journals. TRIAL REGISTRATION NUMBER: EudraCT 2020-004444-29.

Childhood tuberculosis.

PURPOSE OF REVIEW: We discuss the most recent literature to support the identification of children at risk for tuberculosis and optimal testing and treatment strategies. RECENT FINDINGS: The identification and management of children with tuberculosis has increased in complexity due to the recent severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) pandemic, greater use of immunosuppressive agents, and the administration of shorter, rifamycin-containing treatment regimens. Advancements in the diagnosis and treatment of tuberculosis in children include: use of interferon gamma release assays (IGRAs); molecular-based tests; and shorter courses of treatment. While the essential steps to identify and treat children at risk for tuberculosis remain unchanged, providers must be aware of impact of these challenges. SUMMARY: The SARS-CoV-2 pandemic will likely have a negative impact on global tuberculosis control. It is important that countries maintain a comprehensive approach to the identification and management of children at risk for tuberculosis. Increasing evidence supports enhanced utilization of IGRAs and molecular-based testing to improve the diagnosis of tuberculosis in children. Shorter course, rifamycin-based treatment regimens are available to treat children with tuberculosis infection; however, their use is limited in some immunosuppressed children due to drug-drug interactions.

Changes in interferon-γ release assay readout after COVID-19 vaccination: A prospective cohort study.

OBJECTIVES: Interferon-γ release assays (IGRAs) are widely used in public health practice to diagnose latent tuberculosis. During the COVID-19 pandemic and rollout of COVID-19 vaccination, it has remained unclear whether COVID-19 vaccines interfere with IGRA readouts. METHODS: We prospectively recruited healthcare workers during their annual occupational health examinations in 2021. Baseline IGRA readouts were compared with follow-up data after the participants had received two doses of COVID-19 vaccination. RESULTS: A total of 134 baseline IGRA-negative cases (92 with ChAdOx1 vaccine, 27 with mRNA-1273 vaccine, and 15 with heterologous vaccination) and seven baseline IGRA-positive cases were analyzed. Among the baseline IGRA-negative cases, there were decreased interferon-γ concentrations over the Nil (P = 0.005) and increased Mitogen-Nil (P < 0.001) values after vaccination. For TB2-Nil value, a similar trend (P = 0.057) of increase was observed. Compared with the 0.35 IU/ml threshold, the baseline and follow-up readout differences were less than |± 0.10| IU/ml over the TB1-Nil and TB2-Nil values in >90% baseline IGRA-negative cases. No significant readout difference was observed among baseline IGRA-positive cases. CONCLUSION: COVID-19 vaccination did not change IGRA interpretation in most cases. Cases showing conversion/borderline IGRA readouts should be given special consideration.

Contact investigation of tuberculosis in Brunei Darussalam: Evaluation and risk factor analysis.

INTRODUCTION: We evaluated the yield of tuberculosis (TB) contact investigation in Brunei Darussalam, and identified the associated factors for latent TB infection (LTBI) diagnosis, as well as for initiating and completing LTBI treatment. METHODS: Data were extracted and digitalised for all close contacts of pulmonary TB (PTB) cases at the National TB Coordinating Centre from January 2009 to December 2018. Generalising estimating equations logistic regression models were used to determine the associated factors. Manual matching against electronic health records system was done to identify contacts who had progressed to active TB disease. RESULTS: Among 10 537 contacts, 9.9% (n=1047) were diagnosed as LTBI, out of which 43.0% (n=450) initiated LTBI treatment. Among those who initiated, 74.0% (n=333) completed LTBI treatment. Contact factors associated with LTBI diagnosis include being male (adjusted OR (aOR)=1.18 (95% CI 1.03 to 1.34)), local (aOR=0.70 (95% CI 0.56 to 0.88)) and a household contact (aOR=1.59 (95% CI 1.26 to 1.99)). Contacts of index cases who were <60 years old and diagnosed as smear positive PTB (aOR=1.62 (95% CI 1.19 to 2.20)) had higher odds of being diagnosed with LTBI. Local LTBI cases had higher odds of initiating LTBI treatment (aOR=1.86 (95% CI 1.26 to 2.73)). Also, LTBI cases detected from local (aOR=2.32 (95% CI 1.08 to 4.97)) and smear positive PTB index cases (aOR=2.23 (95% CI 1.09 to 4.55)) had higher odds of completing LTBI treatment. Among 1047 LTBI cases, 5 (0.5%) had progressed to active PTB within 1-8 years post-LTBI diagnosis. DISCUSSION: LTBI burden is disproportionately high towards foreign nationals, with higher odds of LTBI diagnosis but lower odds of treatment initiation. Determining the reasons of not initiating LTBI treatment will be useful to help improve LTBI treatment uptake. Establishing digital databases and building TB laboratory capacity for molecular typing would be useful to determine the contribution of LTBI or reactivation towards TB incidence in Brunei.

GIVE statistic for goodness of fit in instrumental variables models with application to COVID data.

Since COVID-19 outbreak, scientists have been interested to know whether there is any impact of the Bacillus Calmette-Guerin (BCG) vaccine against COVID-19 mortality or not. It becomes more relevant as a large population in the world may have latent tuberculosis infection (LTBI), for which a person may not have active tuberculosis but persistent immune responses stimulated by Mycobacterium tuberculosis antigens, and that means, both LTBI and BCG generate immunity against COVID-19. In order to understand the relationship between LTBI and COVID-19 mortality, this article proposes a measure of goodness of fit, viz., Goodness of Instrumental Variable Estimates (GIVE) statistic, of a model obtained by Instrumental Variables estimation. The GIVE statistic helps in finding the appropriate choice of instruments, which provides a better fitted model. In the course of study, the large sample properties of the GIVE statistic are investigated. As indicated before, the COVID-19 data is analysed using the GIVE statistic, and moreover, simulation studies are also conducted to show the usefulness of the GIVE statistic along with analysis of well-known Card data.