The WHO global tuberculosis 2021 report - not so good news and turning the tide back to end TB

Objective: To review the data presented in the 2021 WHO global TB report and discuss the current constraints in the global response. Introduction and methods: The WHO global TB reports, consolidate TB data from countries and provide up to date assessment of the global TB epidemic. We reviewed the data presented in the 2021 report. Results: We noted that the 2021 WHO global TB report presents a rather grim picture on the trajectory of the global epidemic of TB including a stagnation in the annual decline in TB incidence, a decline in TB notifications and an increase in estimated TB deaths. All the targets set at the 2018 United Nations High Level Meeting on TB were off track. Interpretation and conclusion: The sub-optimal global performance on achieving TB control targets in 2020 is attributed to the on-going COVID-19 pandemic, however, TB programs were already off track well before the onset of the pandemic, suggesting that the pandemic amplified an already fragile global TB response. We emphasize that ending the global TB epidemic will require bold leadership, optimization of existing interventions, widespread coverage, addressing social determinants of TB and importantly mobilization of adequate funding required for TB care and preventio

Accuracy of computer-aided chest X-ray in community-based tuberculosis screening: Lessons from the 2016 Kenya National Tuberculosis Prevalence Survey

Community-based screening for tuberculosis (TB) could improve detection but is resource intensive. We set out to evaluate the accuracy of computer-aided TB screening using digital chest X-ray (CXR) to determine if this approach met target product profiles (TPP) for community-based screening. CXR images from participants in the 2016 Kenya National TB Prevalence Survey were evaluated using CAD4TBv6 (Delft Imaging), giving a probabilistic score for pulmonary TB ranging from 0 (low probability) to 99 (high probability). We constructed a Bayesian latent class model to estimate the accuracy of CAD4TBv6 screening compared to bacteriologically-confirmed TB across CAD4TBv6 threshold cut-offs, incorporating data on Clinical Officer CXR interpretation, participant demographics (age, sex, TB symptoms, previous TB history), and sputum results. We compared model-estimated sensitivity and specificity of CAD4TBv6 to optimum and minimum TPPs. Of 63,050 prevalence survey participants, 61,848 (98%) had analysable CXR images, and 8,966 (14.5%) underwent sputum bacteriological testing; 298 had bacteriologically-confirmed pulmonary TB. Median CAD4TBv6 scores for participants with bacteriologically-confirmed TB were significantly higher (72, IQR: 58–82.75) compared to participants with bacteriologically-negative sputum results (49, IQR: 44–57, p<0.0001). CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, (95% credible interval [CrI]: 83.0%—83.7%, CAD4TBv6 threshold: 55). There was considerable variation in accuracy by participant characteristics, with older individuals and those with previous TB having lowest specificity. CAD4TBv6 met the optimal TPP for TB community screening. To optimise screening accuracy and efficiency of confirmatory sputum testing, we recommend that an adaptive approach to threshold setting is adopted based on participant characteristics

Study protocol: analysis of regional lung health policies and stakeholders in Africa

Background Lung health is a critical area for research in sub-Saharan Africa. The International Multidisciplinary Programme to Address Lung Health and TB in Africa (IMPALA) is a collaborative programme that seeks to fill evidence gaps to address high-burden lung health issues in Africa. In order to generate demand for and facilitate use of IMPALA research by policy-makers and other decision-makers at the regional level, an analysis of regional lung health policies and stakeholders will be undertaken to inform a programmatic strategy for policy engagement. Methods and analysis This analysis will be conducted in three phases. The first phase will be a rapid desk review of regional lung health policies and stakeholders that seeks to understand the regional lung health policy landscape, which issues are prioritised in existing regional policy, key regional actors, and opportunities for engagement with key stakeholders. The second phase will be a rapid desk review of the scientific literature, expanding on the work in the first phase by looking at the external factors that influence regional lung health policy, the ways in which regional bodies influence policy at the national level, investments in lung health, structures for discussion and advocacy, and the role of evidence at the regional level. The third phase will involve a survey of IMPALA partners and researchers as well as interviews with key regional stakeholders to further shed light on regional policies, including policy priorities and gaps, policy implementation status and challenges, stakeholders, and platforms for engagement and promoting uptake of evidence. Discussion Health policy analysis provides insights into power dynamics and the political nature of the prioritisation of health issues, which are often overlooked. In order to ensure the uptake of new knowledge and evidence generated by IMPALA, it is important to consider these complex factors

Introduction of operational modelling in policy uptake: A case study of chest X-ray in tuberculosis screening in Kenya

Tuberculosis (TB) is among the leading infectious killers in the world. Despite increases in case detection, there are still three million people with TB who are undiagnosed, untreated or not reported to national programmes. Scaling up of systematic TB screening and use of more sensitive diagnostic tools is required to identify missing people with TB. Chest X-ray (CXR) and computer aided diagnostic (CAD) software for TB are now recommended by the World Health Organization as useful tools for TB screening and triage. Policymakers in lower-and middle-income countries must, however, contextualize this guidance and consider which tools to adopt, and how they will incorporate these into their algorithms. Operational modelling using the Witness package, a visual and interactive modelling tool, has been demonstrated to aid policymakers in decision making processes. It, however, remains unclear where operational modelling would best fit in the policy process and its influence and usefulness in the policy development process has not been formally studied. The overall aim of this study was to generate new knowledge related to CXR use in TB screening, develop an operational model using this information and other sources, and assess if the modelling approach is a feasible technique to influence TB policy in Kenya. This mixed-methods, multidisciplinary study incorporated clinical research, operational modelling and policy analysis. Secondary retrospective quantitative analysis was conducted on cross-sectional study data using individual-level participant CXR data from adult community members who took part in the 2016 Kenya National TB Prevalence Survey. An operational model was built to assess the impact of scale up of CXR in different screening and diagnostic algorithms. Finally, a qualitative, retrospective, and prospective analysis of lung health policy in Kenya was conducted employing the policy triangle and heuristic frameworks. This process generated novel findings related to CXR use in TB screening with important health policy implications. Firstly, the accuracy of CAD met the optimal WHO target product profile for a community TB screening tool. The specificity was lower in adults with previous TB and those aged 41 years or older hence an adaptive approach to setting CAD thresholds will be required to optimize use. Secondly, the use of CXR for TB population-based studies identified many patients with non-TB related abnormalities that would likely be missed by use of CAD. Implementation of CXR TB screening offers an opportunity to integrate disease screening efforts and improvement on all future CAD versions would require scoring for non-TB abnormalities. The modelling demonstrated that a strategy using CXR-CAD screening for all, then GeneXpert though the most expensive, had the ability to identify more persons with TB. Though a relatively new concept, operational modelling was an acceptable and feasible tool to aid in TB policymaking in Kenya and a framework for its adoption in policymaking was developed

OA-03-521-21 Chronic Lung Diseases Remain Under-Prioritized in Africa Despite Their Growing Burden: Findings from a Lung Health Policy Analysis

Background: Globally, 4 million people die prematurely from CLDs (e.g. asthma and chronic obstructive pulmo- nary disease (COPD)) (Global Impact of Respiratory Disease – Second Edition, 2017). In sub-Saharan Africa (SSA), the burden of CLDs is estimated to be large and growing (Bigna and Noubiap, 2019). This study seeks to provide evidence on CLD policy and programme re- sponses, prioritised CLDs, health system approaches to address CLDs, and CLD financial investments in East Africa, focusing on Kenya and Uganda. Design/Methods: We conducted a desk review of CLD- relevant policies at regional level (East Africa) and na- tional level for Kenya and Uganda. Interviews with lung health stakeholders in Uganda and Kenya were conduct- ed to contextualise findings from the desk review. This paper fills an evidence gap on lung health policy in SSA and will inform future CLD research, policies, and pro- grammes. Results: Preliminary findings reveal no CLD-specific policies in East Africa, Kenya or Uganda and a narrow focus of lung health policies on tuberculosis. East African policies do not name CLDs however national-level policies refer to CLDs, namely COPD and asthma. The main approach to CLD control in the two countries is prevention by addressing their risk factors (e.g. tobacco exposure and poor air quality). Documentation of CLD financial investments was not available. Interviews re- vealed political will, but insufficient resources to man- age CLDs. Conclusions: We found a lack of CLD policy prioriti- zation in Kenya, Uganda, and East Africa. The narrow focus of lung health policy investments on tuberculosis calls for local evidence on CLDs’ disease burden, eco- nomic burden, and interventions to address their risk factors, as well as effective research translation initiatives to drive policy action. Given SSA’s resource-constrained context, investments must be evidence-informed to en- sure resource allocations are commensurate to the scope of the problem and proven to improve management and prevention of CLDs

The WHO Global Tuberculosis 2021 Report – not so good news and turning the tide back to End TB

Objective To review the data presented in the 2021 WHO global TB report and discuss the current constraints in the global response. Introduction and methods The WHO global TB reports, consolidate TB data from countries and provide up to date assessment of the global TB epidemic. We reviewed the data presented in the 2021 report. Results We noted that the 2021 WHO global TB report presents a rather grim picture on the trajectory of the global epidemic of TB including a stagnation in the annual decline in TB incidence, a decline in TB notifications and an increase in estimated TB deaths. All the targets set at the 2018 United Nations High Level Meeting on TB were off track. Interpretation and conclusion The sub-optimal global performance on achieving TB control targets in 2020 is attributed to the on-going COVID-19 pandemic, however, TB programs were already off track well before the onset of the pandemic, suggesting that the pandemic amplified an already fragile global TB response. We emphasize that ending the global TB epidemic will require bold leadership, optimization of existing interventions, widespread coverage, addressing social determinants of TB and importantly mobilization of adequate funding required for TB care and prevention

Using Survival Analysis to Identify Risk Factors for Treatment Interruption among New and Retreatment Tuberculosis Patients in Kenya.

Despite high tuberculosis (TB) treatment success rate, treatment adherence is one of the major obstacles to tuberculosis control in Kenya. Our objective was to identify patient-related factors that were associated with time to TB treatment interruption and the geographic distribution of the risk of treatment interruption by county. Data of new and retreatment patients registered in TIBU, a Kenyan national case-based electronic data recording system, between 2013 and 2014 was obtained. Kaplan-Meier curves and log rank tests were used to assess the adherence patterns. Mixed-effects Cox proportional hazards modeling was used for multivariate analysis. Records from 90,170 patients were included in the study. The cumulative incidence of treatment interruption was 4.5% for new patients, and 8.5% for retreatment patients. The risk of treatment interruption was highest during the intensive phase of treatment. Having previously been lost to follow-up was the greatest independent risk factor for treatment interruption (HR: 4.79 [3.99, 5.75]), followed by being HIV-positive not on ART (HR: 1.96 [1.70, 2.26]) and TB relapse (HR: 1.70 [1.44, 2.00]). Male and underweight patients had high risks of treatment interruption (HR: 1.46 [1.35, 1.58]; 1.11 [1.03, 1.20], respectively). High rates of treatment interruption were observed in counties in the central part of Kenya while counties in the northeast had the lowest risk of treatment interruption. A better understanding of treatment interruption risk factors is necessary to improve adherence to treatment. Interventions should focus on patients during the intensive phase, patients who have previously been lost to follow-up, and promotion of integrated TB and HIV services among public and private facilities

Ep25-335-23 It’s not TB but what could it be? Abnormalities on chest X-rays from the 2016 Kenya National Tuberculosis Prevalence Survey

Background: The prevalence of diseases other than tuberculosis(TB) detected on chest-Xray(CXR) during TB screening in Kenya is unknown. Our study aimed to characterise and quantify non-TB abnormalities on CXR and to compare radiologist interpretation with Computer-Aided Detection for Tuberculosis (CAD4TB). We hypothesized that non-TB abnormalities requiring further clinical input are prevalent and may be missed using CAD4TB. Design/Methods: We undertook a cross-sectional study from May 2019-February 2020, analyzing CXRs from the 2016 Kenya National TB Prevalence Survey, sam- pling films classified either as “abnormal, suggestive of TB” or “abnormal other”. We developed a reporting tool which comprised four anatomical categories and a list of common diagnoses. Readers were blinded, films double reported and discordant results resolved by a third reader. We used CAD4TB 6.0. and R v3.6.2. for analysis. Results: Of 1123 films sampled, 600(53.4%) were ab- normal (Figure-1). Prevalence of abnormalities in major categories: 26.3% (95% CI 23.7%-28.9%) heart and/ or great vessels, 26.1% (95% CI23.5%-28.8%) lung parenchyma, 7.6% (95% CI 6.1%-9.3%) pleura and 3% (95% CI 2.1%-4.2%) mediastinum. Prevalence of active-TB 4% (95% CI 2%-4%), severe post TB lung changes (bronchiectasis/destroyed lung) 2% (95% CI 0-2%). Non-TB related diagnoses: cardiomegaly 23.1% (95% CI 20.6%-25.6%), suspected cardiac failure 1.9% (95% CI1.2-2.8%), non-specific airspace opacification/ interstitial disease 6% (95% CI 4%-8%), suspected emphysema 2% (95% CI 2%-4%) and mediastinal masses 0.8% (95% CI 0.4%-1.5%). Median CAD4TB scores: Severe post TB lung changes 76 (IQR 71-81), active-TB 66 (IQR 55-72), suspected emphysema 57 (IQR 54-59), non-specific airspace opacification/interstitial disease 56(IQR 50-61), mediastinal mass 52 (IQR 47-59) and cardiomegaly 50(IQR 46-56). Conclusions: Abnormalities unrelated to TB were prev- alent, most notably cardiomegaly. These non-TB ab- normalities will go undetected using CAD stratification based on threshold scores alone. Further refinement of CAD algorithms to include non-TB diagnoses could attenuate this risk. Incorporation of blood pressure monitoring and spirometry should be considered in TB screening activities

'If not TB, what could it be?' Chest X-ray findings from the 2016 Kenya Tuberculosis Prevalence Survey

Background: The prevalence of diseases other than tuberculosis (TB) detected during chest X-ray (CXR) screening is unknown in sub-Saharan Africa. This represents a missed opportunity for identification and treatment of potentially significant disease. Our aim was to describe and quantify non-TB abnormalities identified by TB-focused CXR screening during the 2016 Kenya National TB prevalence survey. Methods: We reviewed a random sample of 1140 adult (≥15 years) CXRs classified as “abnormal, suggestive of TB” or “abnormal other” during field interpretation from the TB Prevalence Survey. Each image was read (blinded to field classification and study radiologist read) by two expert radiologists, with images classified into one of four major anatomical categories and primary radiological findings. A third reader resolved discrepancies. Prevalence and 95% confidence intervals of abnormalities diagnosis were estimated. Findings: Cardiomegaly was the most common non-TB abnormality at 259/1123 (23∙1%, 95% CI 20∙6%-25∙6%), while cardiomegaly with features of cardiac failure occurred in 17/1123 (1∙5 %, 95% CI 0.9%-2∙4%). We also identified chronic pulmonary pathology including suspected chronic obstructive pulmonary disease in 3∙2% (95% CI 2∙3%- 4∙4%) and non-specific patterns in 4∙6% (95% CI 3∙5%-6∙0%). Prevalence of active-TB and severe post-TB lung changes was 3∙6% (95% CI 2∙6%- 4∙8%) and 1∙4% (95% CI 0∙8%- 2∙3%) respectively. Interpretation: Based on radiological findings, we identified a wide variety of non-TB abnormalities during population-based TB screening. TB prevalence surveys and active case finding activities using mass CXR offer an opportunity to integrate disease screening efforts