An Evaluation of Programmatic Community-Based Chest X-ray Screening for Tuberculosis in Ho Chi Minh City, Vietnam

Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries

Background

In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics.

Methods

We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all other countries). We modeled four ordinal screening and testing approaches involving AI-aided CXR interpretation to indicate individual and pooled testing. Setting a false negative rate of 5%, for each approach we calculated additional and cumulative savings over the baseline of universal Xpert testing, as well as the theoretical expansion in diagnostic coverage.

Results

In each country, the optimal screening and testing approach was to use AI to rule out testing in deciles with low AI scores and to guide pooled vs individual testing in persons with moderate and high AI scores, respectively. This approach yielded cumulative savings in Xpert tests over baseline ranging from 50.8% in Zambia to 57.5% in Nigeria and 61.5% in Bangladesh and Viet Nam. Using these savings, diagnostic coverage theoretically could be expanded by 34% to 160% across the different approaches and countries.

Conclusions

Using AI software data generated during CXR interpretation to inform a differentiated pooled testing strategy may optimize TB diagnostic test use, and could extend molecular tests to more people who need them. The optimal AI thresholds and pooled testing strategy varied across countries, which suggests that bespoke screening and testing approaches may be needed for differing populations and settings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44263-024-00081-2.

An Effective Health System Approach to End TB: Implementing the Double X Strategy in Vietnam

Countries that are high burden for TB must reverse the COVID-19 pandemic's devastating effects to accelerate progress toward ending TB. Vietnam's Double X (2X) strategy uses chest radiography (CXR) and GeneXpert (Xpert) rapid diagnostic testing to improve early detection of TB disease. Household contacts and vulnerable populations (e.g., individuals aged 60 years and older, smokers, diabetics, those with alcohol use disorders, and those previously treated for TB) with and without TB symptoms were screened in community campaigns using CXRs, followed by Xpert for those with a positive screen. In public non-TB district facilities, diabetics, respiratory outpatients, inpatients with lung disease, and other vulnerable populations underwent 2X evaluation. During COVID-19 restrictions in Vietnam, the 2X strategy improved access to TB services by decentralization to commune health stations, the lowest level of the health system, and enabling self-screening using a quick response mobile application. The number needed to screen (NNS) with CXRs to diagnose 1 person with TB disease was calculated for all 2X models and showed the highest yield among self-screeners (11 NNS with CXR), high yield for vulnerable populations in communities (60 NNS) and facilities (19 NNS), and moderately high yield for household contacts in community campaigns (154 NNS). Computer-aided diagnosis for CXRs was incorporated into community and facility implementation and improved physicians' CXR interpretations and Xpert referral decisions. Integration of TB infection and TB disease evaluation increased eligibility for TB preventive treatment among household contacts, a major challenge during implementation. The 2X strategy increased the rational use of Xpert, employing a health system-wide approach that reached vulnerable populations with and without TB symptoms in communities and facilities for early detection of TB disease. This strategy was effectively adapted to different levels of the health system during COVID-19 restrictions and contributed to post-pandemic TB recovery in Vietnam.

Systems analysis and improvement approach to optimize tuberculosis (SAIA-TB) screening, treatment, and prevention in South Africa: a stepped-wedge cluster randomized trial

BACKGROUND

The use of systems engineering tools, including the development and use of care cascades using routinely collected data, process mapping, and continuous quality improvement, is used for frontline healthcare workers to devise systems level change. South Africa experiences high rates of tuberculosis (TB) infection and disease as well as HIV co-infection. The Department of Health has made significant gains in HIV services over the last two decades, reaching their set "90-90-90" targets for HIV. However, TB services, although robust, have lagged in comparison for both disease and infection. The Systems Analysis and Improvement Approach (SAIA) is a five-step implementation science method, drawn from systems engineering, to identify, define, and implement workflow modifications using cascade analysis, process mapping, and repeated quality improvement cycles within healthcare facilities.

METHODS

This stepped-wedge cluster randomized trial will evaluate the effectiveness of SAIA on TB (SAIA-TB) cascade optimization for patients with TB and high-risk contacts across 16 clinics in four local municipalities in the Sarah Baartman district, Eastern Cape, South Africa. We hypothesize that SAIA-TB implementation will lead to a 20% increase in each of: TB screening, TB preventive treatment initiation, and TB disease treatment initiation during the 18-month intervention period. Focus group discussions and key informant interviews with clinic staff will also be conducted to determine drivers of implementation variability across clinics.

DISCUSSION

This study has the potential to improve TB screening, treatment initiation, and completion for both active disease and preventive measures among individuals with and without HIV in a high burden setting. SAIA-TB provides frontline health care workers with a systems-level view of their care delivery system with the aim of sustainable systems-level improvements.

TRIAL REGISTRATION

Clinicaltrials.gov, NCT06314386. Registered 18 March 2024, https://clinicaltrials.gov/study/NCT06314386 . NCT06314386.

Tuberculosis Case Finding in Kulon Progo District, Yogyakarta, Indonesia: Passive versus Active Case Finding Using Mobile Chest X-ray

Active-case finding (ACF) using chest X-ray is an essential method of finding and diagnosing Tuberculosis (TB) cases that may be missed in Indonesia's routine TB case finding. This study compares active and passive TB case-finding strategies. A retrospective study of TB case notification was conducted. Data between 1 January and 31 December 2021, was used. The population in this study were TB cases notified from Kulon Progo District health facilities, including those found through routine activities or active-case findings. A total of 249 TB cases were diagnosed in Kulon Progo in 2021, and 102 (41%) were bacteriologically confirmed. The TB patients' ages ranged from 0 to 85 years (median 52, IQR 31-61). The majority of cases were male (59%, 147/249) and mostly among people aged 15-59 (61.4%, 153/249). The proportion of clinical TB diagnoses among cases found from active-case findings was 74.7% (68/91) while the proportion among passive-case findings was 50% (79/158). Active-case finding contributed 91 (36.5%) TB cases to the total cases detected in Kulon Progo in 2021. The use of chest X-rays in active-case findings likely contributed to the detection of a higher proportion of clinical TB than in passive-case findings.

Accuracy of digital chest x-ray analysis with artificial intelligence software as a triage and screening tool in hospitalized patients being evaluated for tuberculosis in Lima, Peru

Tuberculosis (TB) transmission in healthcare facilities is common in high-incidence countries. Yet, the optimal approach for identifying inpatients who may have TB is unclear. We evaluated the diagnostic accuracy of qXR (Qure.ai, India) computer-aided detection (CAD) software versions 3.0 and 4.0 (v3 and v4) as a triage and screening tool within the FAST (Find cases Actively, Separate safely, and Treat effectively) transmission control strategy. We prospectively enrolled two cohorts of patients admitted to a tertiary hospital in Lima, Peru: one group had cough or TB risk factors (triage) and the other did not report cough or TB risk factors (screening). We evaluated the sensitivity and specificity of qXR for the diagnosis of pulmonary TB using culture and Xpert as primary and secondary reference standards, including stratified analyses based on risk factors. In the triage cohort (n = 387), qXR v4 sensitivity was 0.91 (59/65, 95% CI 0.81-0.97) and specificity was 0.32 (103/322, 95% CI 0.27-0.37) using culture as reference standard. There was no difference in the area under the receiver-operating-characteristic curve (AUC) between qXR v3 and qXR v4 with either a culture or Xpert reference standard. In the screening cohort (n = 191), only one patient had a positive Xpert result, but specificity in this cohort was high (>90%). A high prevalence of radiographic lung abnormalities, most notably opacities (81%), consolidation (62%), or nodules (58%), was detected by qXR on digital CXR images from the triage cohort. qXR had high sensitivity but low specificity as a triage in hospitalized patients with cough or TB risk factors. Screening patients without cough or risk factors in this setting had a low diagnostic yield. These findings further support the need for population and setting-specific thresholds for CAD programs.

Ensuring Continuity of Tuberculosis Care during Social Distancing through Integrated Active Case Finding at COVID-19 Vaccination Events in Vietnam: A Cohort Study

COVID-19 significantly disrupted tuberculosis (TB) services in Vietnam. In response, the National TB Program (NTP) integrated TB screening using mobile chest X-rays into COVID-19 vaccination events. This prospective cohort study evaluated the integrated model's yield, treatment outcomes, and costs. We further fitted regressions to identify risk factors and conduct interrupted time-series analyses in the study area, Vietnam's eight economic regions, and at the national level. At 115 events, we conducted 48,758 X-ray screens and detected 174 individuals with TB. We linked 89.7% to care, while 92.9% successfully completed treatment. The mean costs per person diagnosed with TB was $547. TB risk factors included male sex (aOR = 6.44, p < 0.001), age of 45-59 years (aOR = 1.81, p = 0.006) and ≥60 years (aOR = 1.99, p = 0.002), a history of TB (aOR = 7.96, p < 0.001), prior exposure to TB (aOR = 3.90, p = 0.001), and symptomatic presentation (aOR = 2.75, p < 0.001). There was a significant decline in TB notifications during the Delta wave and significant increases immediately after lockdowns were lifted (IRR(γ1) = 5.00; 95%CI: (2.86, 8.73); p < 0.001) with a continuous upward trend thereafter (IRR(γ2) = 1.39; 95%CI: (1.22, 1.38); p < 0.001). Similar patterns were observed at the national level and in all regions but the northeast region. The NTP's swift actions and policy decisions ensured continuity of care and led to the rapid recovery of TB notifications, which may serve as blueprint for future pandemics.

Active screening for tuberculosis among high-risk populations in high-burden areas in Zhejiang province, China

OBJECTIVES

Tuberculosis (TB) is a major global public health concern. Although the incidence of TB in China is declining, the country continues to face many challenges regarding TB control. This study aimed to develop an active case finding (ACF) strategy for high-risk populations in areas with high TB burden and evaluate the effectiveness of the ACF strategy for early TB detection in patients to reduce TB transmission.

STUDY DESIGN

This was a descriptive study.

METHODS

From May to October 2019, active TB screening was conducted in Zhejiang Province, China. Overall, 24 high-burden townships were chosen as study sites. Residents aged ≥65 years, suffering from diabetes, diagnosed with HIV/AIDS, or with a history of TB were mobilized for screening. Chest radiography was performed for all participants in the community. Sputum specimens were collected for sputum smear tests and cultures at county-level TB-designed hospitals. A professional medical team performed the final diagnoses.

RESULTS

Overall, 130,643 residents were included, accounting for 8.85% of the total population in the selected areas. After screening, 89 confirmed cases and 419 suspected cases were identified. The detection rates for suspected and confirmed cases were 320.72/100,000 and 68.12/100,000, respectively. Individuals with a history of TB accounted for a large proportion of detected cases, and the detection rate was higher among males than in females. This study identified 10.5% of reported cases in the selected areas in 2019. In Zhejiang province, compared with the previous year, the rates of TB notification in 2019 and 2020 declined by 7.0% and 7.4%, respectively, compared with the previous year. However, the TB notification rate in 2019 was almost the same as that in 2018 (a decline of 2.5%) but sharply declined in 2020 (14.4%) in the screened areas.

CONCLUSIONS

Our findings suggest that the ACF strategy may have helped to maintain the downward trends in TB notification rates by detecting patients with TB and suspected cases in the short term.

Early user perspectives on using computer-aided detection software for interpreting chest X-ray images to enhance access and quality of care for persons with tuberculosis

Despite 30 years as a public health emergency, tuberculosis (TB) remains one of the world's deadliest diseases. Most deaths are among persons with TB who are not reached with diagnosis and treatment. Thus, timely screening and accurate detection of TB, particularly using sensitive tools such as chest radiography, is crucial for reducing the global burden of this disease. However, lack of qualified human resources represents a common limiting factor in many high TB-burden countries. Artificial intelligence (AI) has emerged as a powerful complement in many facets of life, including for the interpretation of chest X-ray images. However, while AI may serve as a viable alternative to human radiographers and radiologists, there is a high likelihood that those suffering from TB will not reap the benefits of this technological advance without appropriate, clinically effective use and cost-conscious deployment. The World Health Organization recommended the use of AI for TB screening in 2021, and early adopters of the technology have been using the technology in many ways. In this manuscript, we present a compilation of early user experiences from nine high TB-burden countries focused on practical considerations and best practices related to deployment, threshold and use case selection, and scale-up. While we offer technical and operational guidance on the use of AI for interpreting chest X-ray images for TB detection, our aim remains to maximize the benefit that programs, implementers, and ultimately TB-affected individuals can derive from this innovative technology.

Accuracy of digital chest x-ray analysis with artificial intelligence software as a triage and screening tool in hospitalized patients being evaluated for tuberculosis in Lima, Peru

Introduction

Tuberculosis (TB) transmission in healthcare facilities is common in high-incidence countries. Yet, the optimal approach for identifying inpatients who may have TB is unclear. We evaluated the diagnostic accuracy of qXR (Qure.ai, India) computer-aided detection (CAD) software versions 3.0 and 4.0 (v3 and v4) as a triage and screening tool within the FAST (Find cases Actively, Separate safely, and Treat effectively) transmission control strategy.

Methods

We prospectively enrolled two cohorts of patients admitted to a tertiary hospital in Lima, Peru: one group had cough or TB risk factors (triage) and the other did not report cough or TB risk factors (screening). We evaluated the sensitivity and specificity of qXR for the diagnosis of pulmonary TB using culture and Xpert as primary and secondary reference standards, including stratified analyses based on risk factors.

Results

In the triage cohort (n=387), qXR v4 sensitivity was 0.91 (59/65, 95% CI 0.81-0.97) and specificity was 0.32 (103/322, 95% CI 0.27-0.37) using culture as reference standard. There was no difference in the area under the receiver-operating-characteristic curve (AUC) between qXR v3 and qXR v4 with either a culture or Xpert reference standard. In the screening cohort (n=191), only one patient had a positive Xpert result, but specificity in this cohort was high (>90%). A high prevalence of radiographic lung abnormalities, most notably opacities (81%), consolidation (62%), or nodules (58%), was detected by qXR on digital CXR images from the triage cohort.

Conclusions

qXR had high sensitivity but low specificity as a triage in hospitalized patients with cough or TB risk factors. Screening patients without cough or risk factors in this setting had a low diagnostic yield. These findings further support the need for population and setting-specific thresholds for CAD programs.

Active Tuberculosis Screening via a Mobile Health App in Myanmar: Incremental Cost-Effectiveness Evaluation

BACKGROUND

A mobile app that calculates a tuberculosis (TB) risk score based on individual social and pathological characteristics has been shown to be a better predictor of the risk of contracting TB than conventionally used TB signs and symptoms (TBSS) in Myanmar, where the TB burden is high. Its cost-effectiveness, however, has not yet been assessed.

OBJECTIVE

This study aimed to determine the incremental costs of this mobile app and of chest x-rays (CXRs) in averting disability-adjusted life years (DALYs) among missed cases of active TB in the population being screened.

METHODS

Elements of incremental costs and effectiveness of 3 initial TB screening strategies were examined, including TBSS followed by CXR, the mobile app followed by CXR, and universal CXR. The incremental cost-effectiveness ratio (ICER; ie, the additional cost for each additional DALY averted) was compared to TBSS screening. Based on the latest 2020 gross domestic product (GDP) per capita of Myanmar (US $1477.50), the ICER was compared to willingness-to-pay (WTP) thresholds of 1, 2, and 3 times the GDP per capita. Probabilistic sensitivity analysis was conducted with a Monte Carlo simulation to compute the levels of probability that the ICER for each strategy was below each WTP threshold.

RESULTS

For each 100,000 population, the incremental cost compared to TBSS of active TB screening was US $345,942 for the mobile app and US $1,810,712 for universal CXR. The incremental effectiveness was 325 DALYs averted for the mobile app and 576 DALYs averted for universal CXR. For the mobile app, the estimated ICER was US $1064 (72% of GDP per capita) per 1 DALY averted. Furthermore, 100% of the simulated values were below an additional cost of 1 times the GDP per capita for 1 additional DALY averted. The universal CXR strategy has an estimated ICER of US $3143 (2.1 times the GDP per capita) per 1 DALY averted and an additional 77.2% DALYs averted compared to the app (ie, 576 - 325 / 325 DALYs); however, 0.5% of the simulated values were higher than an additional expenditure of 3 times the GDP per capita.

CONCLUSIONS

Based on the status of the economy in 2020, the mobile app strategy is affordable for Myanmar. The universal CXR strategy, although it could prevent an additional 77% of DALYs, is probably unaffordable. Compared to the TBSS strategy, the mobile app system based on social and pathological characteristics of TB has potential as a TB screening tool to identify missing TB cases and to reduce TB morbidity and mortality, thereby helping to achieve the global goal of "End TB" in resource-limited settings with a high TB burden.

Computer-Aided Detection for Chest Radiography to Improve the Quality of Tuberculosis Diagnosis in Vietnam's District Health Facilities: An Implementation Study

In Vietnam, chest radiography (CXR) is used to refer people for GeneXpert (Xpert) testing to diagnose tuberculosis (TB), demonstrating high yield for TB but a wide range of CXR abnormality rates. In a multi-center implementation study, computer-aided detection (CAD) was integrated into facility-based TB case finding to standardize CXR interpretation. CAD integration was guided by a programmatic framework developed for routine implementation. From April through December 2022, 24,945 CXRs from TB-vulnerable populations presenting to district health facilities were evaluated. Physicians interpreted all CXRs in parallel with CAD (qXR 3.0) software, for which the selected TB threshold score was ≥0.60. At three months, there was 47.3% concordance between physician and CAD TB-presumptive CXR results, 7.8% of individuals who received CXRs were referred for Xpert testing, and 858 people diagnosed with Xpert-confirmed TB per 100,000 CXRs. This increased at nine months to 76.1% concordant physician and CAD TB-presumptive CXRs, 9.6% referred for Xpert testing, and 2112 people with Xpert-confirmed TB per 100,000 CXRs. Our programmatic CAD-CXR framework effectively supported physicians in district facilities to improve the quality of referral for diagnostic testing and increase TB detection yield. Concordance between physician and CAD CXR results improved with training and was important to optimize Xpert testing.

Comparative performance evaluation of QIAreach QuantiFERON-TB and tuberculin skin test for diagnosis of tuberculosis infection in Viet Nam

Current WHO-recommended diagnostic tools for tuberculosis infection (TBI) have well-known limitations and viable alternatives are urgently needed. We compared the diagnostic performance and accuracy of the novel QIAreach QuantiFERON-TB assay (QIAreach; index) to the QuantiFERON-TB Gold Plus assay (QFT-Plus; reference). The sample included 261 adults (≥ 18 years) recruited at community-based TB case finding events. Of these, 226 underwent Tuberculin Skin Tests and 200 returned for interpretation (TST; comparator). QIAreach processing and TST reading were completed at lower-level healthcare facilities. We conducted matched-pair comparisons for QIAreach and TST with QFT-Plus, calculated sensitivity, specificity and area under a receiver-operating characteristic curve (AUC), and analyzed concordant-/discordant-pair interferon-gamma (IFN-γ) levels. QIAreach sensitivity and specificity were 98.5% and 72.3%, respectively, for an AUC of 0.85. TST sensitivity (53.2%) at a 5 mm induration threshold was significantly below QIAreach, while specificity (82.4%) was statistically equivalent. The corrected mean IFN-γ level of 0.08 IU/ml and corresponding empirical threshold (0.05) of false-positive QIAreach results were significantly lower than the manufacturer-recommended QFT-Plus threshold (≥ 0.35 IU/ml). Despite QIAreach's higher sensitivity at equivalent specificity to TST, the high number of false positive results and low specificity limit its utility and highlight the continued need to expand the diagnostic toolkit for TBI.

Comparing Catastrophic Costs: Active vs. Passive Tuberculosis Case Finding in Urban Vietnam

Active case finding (ACF) is a strategy that aims to identify people with tuberculosis (TB) earlier in their disease. This outreach approach may lead to a reduction in catastrophic cost incurrence (costs exceeding 20% of annual household income), a main target of WHO's End TB Strategy. Our study assessed the socio-economic impact of ACF by comparing patient costs in actively and passively detected people with TB. Longitudinal patient cost surveys were prospectively fielded for people with drug-sensitive pulmonary TB, with 105 detected through ACF and 107 passively detected. Data were collected in four Vietnamese cities between October 2020 and March 2022. ACF reduced pre-treatment (USD 10 vs. 101, p < 0.001) and treatment costs (USD 888 vs. 1213, p < 0.001) in TB-affected individuals. Furthermore, it reduced the occurrence of job loss (15.2% vs. 35.5%, p = 0.001) and use of coping strategies (28.6% vs. 45.7%, p = 0.004). However, catastrophic cost incurrence was high at 52.8% and did not differ between cohorts. ACF did not significantly decrease indirect costs, the largest contributor to catastrophic costs. ACF reduces costs but cannot sufficiently reduce the risk of catastrophic costs. As income loss is the largest driver of costs during TB treatment, social protection schemes need to be expanded.

Economic evaluation of a community health worker model for tuberculosis care in Ho Chi Minh City, Viet Nam: a mixed-methods Social Return on Investment Analysis

BACKGROUND

There is extensive evidence for the cost-effectiveness of programmatic and additional tuberculosis (TB) interventions, but no studies have employed the social return on investment (SROI) methodology. We conducted a SROI analysis to measure the benefits of a community health worker (CHW) model for active TB case finding and patient-centered care.

METHODS

This mixed-method study took place alongside a TB intervention implemented in Ho Chi Minh City, Viet Nam, between October-2017 - September-2019. The valuation encompassed beneficiary, health system and societal perspectives over a 5-year time-horizon. We conducted a rapid literature review, two focus group discussions and 14 in-depth interviews to identify and validate pertinent stakeholders and material value drivers. We compiled quantitative data from the TB program's and the intervention's surveillance systems, ecological databases, scientific publications, project accounts and 11 beneficiary surveys. We mapped, quantified and monetized value drivers to derive a crude financial benefit, which was adjusted for four counterfactuals. We calculated a SROI based on the net present value (NPV) of benefits and investments using a discounted cash flow model with a discount rate of 3.5%. A scenario analysis assessed SROI at varying discount rates of 0-10%.

RESULTS

The mathematical model yielded NPVs of US$235,511 in investments and US$8,497,183 in benefits. This suggested a return of US$36.08 for each dollar invested, ranging from US$31.66-US39.00 for varying discount rate scenarios.

CONCLUSIONS

The evaluated CHW-based TB intervention generated substantial individual and societal benefits. The SROI methodology may be an alternative for the economic evaluation of healthcare interventions.

Optimising diagnosis and treatment of tuberculosis infection in community and primary care settings in two urban provinces of Viet Nam: a cohort study

OBJECTIVES

To end tuberculosis (TB), the vast reservoir of 1.7-2.3 billion TB infections (TBIs) must be addressed, but achieving global TB preventive therapy (TPT) targets seems unlikely. This study assessed the feasibility of using interferon-γ release assays (IGRAs) at lower healthcare levels and the comparative performance of 3-month and 9-month daily TPT regimens (3HR/9H).

DESIGN, SETTING, PARTICIPANTS AND INTERVENTION

This cohort study was implemented in two provinces of Viet Nam from May 2019 to September 2020. Participants included household contacts (HHCs), vulnerable community members and healthcare workers (HCWs) recruited at community-based TB screening events or HHC investigations at primary care centres, who were followed up throughout TPT.

PRIMARY AND SECONDARY OUTCOMES

We constructed TBI care cascades describing indeterminate and positivity rates to assess feasibility, and initiation and completion rates to assess performance. We fitted mixed-effects logistic and stratified Cox models to identify factors associated with IGRA positivity and loss to follow-up (LTFU).

RESULTS

Among 5837 participants, the indeterminate rate was 0.8%, and 30.7% were IGRA positive. TPT initiation and completion rates were 63.3% (3HR=61.2% vs 9H=63.6%; p=0.147) and 80.6% (3HR=85.7% vs 9H=80.0%; p=0.522), respectively. Being male (adjusted OR=1.51; 95% CI: 1.28 to 1.78; p<0.001), aged 45-59 years (1.30; 1.05 to 1.60; p=0.018) and exhibiting TB-related abnormalities on X-ray (2.23; 1.38 to 3.61; p=0.001) were associated with positive IGRA results. Risk of IGRA positivity was lower in periurban districts (0.55; 0.36 to 0.85; p=0.007), aged <15 years (0.18; 0.13 to 0.26; p<0.001), aged 15-29 years (0.56; 0.42 to 0.75; p<0.001) and HCWs (0.34; 0.24 to 0.48; p<0.001). The 3HR regimen (adjusted HR=3.83; 1.49 to 9.84; p=0.005) and HCWs (1.38; 1.25 to 1.53; p<0.001) showed higher hazards of LTFU.

CONCLUSION

Providing IGRAs at lower healthcare levels is feasible and along with shorter regimens may expand access and uptake towards meeting TPT targets, but scale-up may require complementary advocacy and education for beneficiaries and providers.

Discordant results of Xpert MTB/Rif assay and BACTEC MGIT 960 liquid culture to detect Mycobacterium tuberculosis in community screening in Vietnam

BACKGROUND

Xpert MTB/Rif, a molecular test to detect tuberculosis (TB), has been proven to have high sensitivity and specificity when compared with liquid culture in clinical settings. However, little is known about its performance in community TB screening.

METHODS

In Vietnam, a national TB prevalence survey was conducted in 2017. Survey participants who screened positive by chest X-ray, cough symptoms and/or recent history of tuberculosis were requested to provide at least two sputum samples that were tested for Mycobacterium tuberculosis by Xpert MTB/Rif G4 (Xpert) and BACTEC MGIT960 culture (MGIT).

RESULTS

There were 4,649 eligible participants provided both samples for testing. Among them, 236 (5.1%) participants tested positive for TB by Xpert, 244 (5.3%) tested positive by MGIT and 317 tested positive by at least one test; 163 (51.4%) had discordant test results. Of the positive Xpert, 162 (68.6%) showed a low or very low bacterial load. In multivariate logistic regression comparing discordant with Xpert-MGIT concordant positive results, discordant Xpert-positive results occurred more often among participants who had low sputum bacterial load, male sex, a history of TB treatment, or night sweats. The associated factors were male sex, abnormal chest X-ray and having night sweats when the logistic model was against those with both Xpert and MGIT negative.

CONCLUSIONS

We found high rates of discordance in the performance of Xpert and MGIT for community-based TB case finding. In situations where the majority of TB cases are expected to have a low bacterial load, multiple diagnostic tests and/or multiple samples are required to reach sufficient sensitivity.

Independent evaluation of 12 artificial intelligence solutions for the detection of tuberculosis

There have been few independent evaluations of computer-aided detection (CAD) software for tuberculosis (TB) screening, despite the rapidly expanding array of available CAD solutions. We developed a test library of chest X-ray (CXR) images which was blindly re-read by two TB clinicians with different levels of experience and then processed by 12 CAD software solutions. Using Xpert MTB/RIF results as the reference standard, we compared the performance characteristics of each CAD software against both an Expert and Intermediate Reader, using cut-off thresholds which were selected to match the sensitivity of each human reader. Six CAD systems performed on par with the Expert Reader (Qure.ai, DeepTek, Delft Imaging, JF Healthcare, OXIPIT, and Lunit) and one additional software (Infervision) performed on par with the Intermediate Reader only. Qure.ai, Delft Imaging and Lunit were the only software to perform significantly better than the Intermediate Reader. The majority of these CAD software showed significantly lower performance among participants with a past history of TB. The radiography equipment used to capture the CXR image was also shown to affect performance for some CAD software. TB program implementers now have a wide selection of quality CAD software solutions to utilize in their CXR screening initiatives.

Prevalence of Mycobacterium tuberculosis in sputum and reported symptoms among clinic attendees compared to a community survey in rural South Africa

BACKGROUND

Tuberculosis (TB) case finding efforts typically target symptomatic people attending health facilities. We compared the prevalence of Mycobacterium tuberculosis (Mtb) sputum culture-positivity among adult clinic attendees in rural South Africa with a concurrent, community-based estimate from the surrounding demographic surveillance area (DSA).

METHODS

Clinic: Randomly-selected adults (≥18 years) attending two primary healthcare clinics were interviewed and requested to give sputum for mycobacterial culture. HIV and antiretroviral therapy (ART) status were based on self-report and record review. Community: All adult (≥15 years) DSA residents were invited to a mobile clinic for health screening, including serological HIV testing; those with ≥1 TB symptom (cough, weight loss, night sweats, fever) or abnormal chest radiograph were asked for sputum.

RESULTS

Clinic: 2,055 patients were enrolled (76.9% female, median age 36 years); 1,479 (72.0%) were classified HIV-positive (98.9% on ART) and 131 (6.4%) reported ≥1 TB symptom. Of 20/2,055 (1.0% [95% CI 0.6-1.5]) with Mtb culture-positive sputum, 14 (70%) reported no symptoms. Community: 10,320 residents were enrolled (68.3% female, median age 38 years); 3,105 (30.3%) tested HIV-positive (87.4% on ART) and 1,091 (10.6%) reported ≥1 TB symptom. Of 58/10,320 (0.6% [95% CI 0.4-0.7]) with Mtb culture-positive sputum, 45 (77.6%) reported no symptoms.In both surveys, sputum culture positivity was associated with male sex and reporting >1 TB symptom.

CONCLUSIONS

In both clinic and community settings, most participants with Mtb culture-positive sputum were asymptomatic. TB screening based only on symptoms will miss many people with active disease in both settings.

The impact of active case finding on transmission dynamics of tuberculosis: A modelling study

Background

In the last decade, active case finding (ACF) strategies for tuberculosis (TB) have been implemented in many diverse settings, with some showing large increases in case detection and reporting at the sub-national level. There have also been several studies which seek to provide evidence for the benefits of ACF to individuals and communities in the broader context. However, there remains no quantification of the impact of ACF with regards to reducing the burden of transmission. We sought to address this knowledge gap and quantify the potential impact of active case finding on reducing transmission of TB at the national scale and further, to determine the intensification of intervention efforts required to bring the reproduction number (R₀) below 1 for TB.

Methods

We adopt a dynamic transmission model that incorporates heterogeneity in risk to TB to assess the impact of an ACF programme (IMPACT TB) on reducing TB incidence in Vietnam and Nepal. We fit the models to country-level incidence data using a Bayesian Markov Chain Monte Carlo approach. We assess the impact of ACF using a parameter in our model, which we term the treatment success rate. Using programmatic data, we estimate how much this parameter has increased as a result of IMPACT TB in the implementation districts of Vietnam and Nepal and quantify additional efforts needed to eliminate transmission of TB in these countries by 2035.

Results

Extending the IMPACT TB programme to national coverage would lead to moderate decreases in TB incidence and would not be enough to interrupt transmission by 2035. Decreasing transmission sufficiently to bring the reproduction number (R0) below 1, would require a further intensification of current efforts, even at the sub-national level.

Conclusions

Active case finding programmes are effective in reducing TB in the short term. However, interruption of transmission in high-burden countries, like Vietnam and Nepal, will require comprehensive incremental efforts. Complementary measures to reduce progression from infection to disease, and reactivation of latent infection, are needed to meet the WHO End TB incidence targets.

Socio-protective effects of active case finding on catastrophic costs from tuberculosis in Ho Chi Minh City, Viet Nam: a longitudinal patient cost survey

BACKGROUND

Many tuberculosis (TB) patients incur catastrophic costs. Active case finding (ACF) may have socio-protective properties that could contribute to the WHO End TB Strategy target of zero TB-affected families suffering catastrophic costs, but available evidence remains limited. This study measured catastrophic cost incurrence and socioeconomic impact of an episode of TB and compared those socioeconomic burdens in patients detected by ACF versus passive case finding (PCF).

METHODS

This cross-sectional study fielded a longitudinal adaptation of the WHO TB patient cost survey alongside an ACF intervention from March 2018 to March 2019. The study was conducted in six intervention (ACF) districts and six comparison (PCF) districts of Ho Chi Minh City, Viet Nam. Fifty-two TB patients detected through ACF and 46 TB patients in the PCF cohort were surveyed within two weeks of treatment initiation, at the end of the intensive phase of treatment, and after treatment concluded. The survey measured income, direct and indirect costs, and socioeconomic impact based on which we calculated catastrophic cost as the primary outcome. Local currency was converted into US$ using the average exchange rates reported by OANDA for the study period (VNĐ1 = US$0.0000436, 2018-2019). We fitted logistic regressions for comparisons between the ACF and PCF cohorts as the primary exposures and used generalized estimating equations to adjust for autocorrelation.

RESULTS

ACF patients were poorer than PCF patients (multidimensional poverty ratio: 16 % vs. 7 %; p = 0.033), but incurred lower median pre-treatment costs (US$18 vs. US$80; p < 0.001) and lower median total costs (US$279 vs. US$894; p < 0.001). Fewer ACF patients incurred catastrophic costs (15 % vs. 30 %) and had lower odds of catastrophic cost (aOR = 0.17; 95 % CI: [0.05, 0.67]; p = 0.011), especially during the intensive phase (OR = 0.32; 95 % CI: [0.12, 0.90]; p = 0.030). ACF patient experienced less social exclusion (OR = 0.41; 95 % CI: [0.18, 0.91]; p = 0.030), but more often resorted to financial coping mechanisms (OR = 5.12; 95 % CI: [1.73, 15.14]; p = 0.003).

CONCLUSIONS

ACF can be effective in reaching vulnerable populations and mitigating the socioeconomic burden of TB, and can contribute to achieving the WHO End TB Strategy goals. Nevertheless, as TB remains a catastrophic life event, social protection efforts must extend beyond ACF.

Early Evaluation of an Ultra-Portable X-ray System for Tuberculosis Active Case Finding

X-ray screening is an important tool in tuberculosis (TB) prevention and care, but access has historically been restricted by its immobile nature. As recent advancements have improved the portability of modern X-ray systems, this study represents an early evaluation of the safety, image quality and yield of using an ultra-portable X-ray system for active case finding (ACF). We reported operational and radiological performance characteristics and compared image quality between the ultra-portable and two reference systems. Image quality was rated by three human readers and by an artificial intelligence (AI) software. We deployed the ultra-portable X-ray alongside the reference system for community-based ACF and described TB care cascades for each system. The ultra-portable system operated within advertised specifications and radiologic tolerances, except on X-ray capture capacity, which was 58% lower than the reported maximum of 100 exposures per charge. The mean image quality rating from radiologists for the ultra-portable system was significantly lower than the reference (3.71 vs. 3.99, p < 0.001). However, we detected no significant differences in TB abnormality scores using the AI software (p = 0.571), nor in any of the steps along the TB care cascade during our ACF campaign. Despite some shortcomings, ultra-portable X-ray systems have significant potential to improve case detection and equitable access to high-quality TB care.

Identifying barriers and facilitators to implementation of community-based tuberculosis active case finding with mobile X-ray units in Lima, Peru: a RE-AIM evaluation

OBJECTIVES

Identify barriers and facilitators to integrating community tuberculosis screening with mobile X-ray units into a health system.

METHODS

Reach, effectiveness, adoption, implementation and maintenance evaluation.

SETTING

3-district region of Lima, Peru.

PARTICIPANTS

63 899 people attended the mobile units from 7 February 2019 to 6 February 2020.

INTERVENTIONS

Participants were screened by chest radiography, which was scored for abnormality by computer-aided detection. People with abnormal X-rays were evaluated clinically and by GeneXpert MTB/RIF (Xpert) sputum testing. People diagnosed with tuberculosis at the mobile unit were accompanied to health facilities for treatment initiation.

PRIMARY AND SECONDARY OUTCOME MEASURES

Reach was defined as the percentage of the population of the three-district region that attended the mobile units. Effectiveness was defined as the change in tuberculosis case notifications over a historical baseline. Key implementation fidelity indicators were the percentages of people who had chest radiography performed, were evaluated clinically, had sputum samples collected, had valid Xpert results and initiated treatment.

RESULTS

The intervention reached 6% of the target population and was associated with an 11% (95% CI 6 to 16) increase in quarterly case notifications, adjusting for the increasing trend in notifications over the previous 3 years. Implementation indicators for screening, sputum collection and Xpert testing procedures all exceeded 85%. Only 82% of people diagnosed with tuberculosis at the mobile units received treatment; people with negative or trace Xpert results were less likely to receive treatment. Suboptimal treatment initiation was driven by health facility doctors' lack of familiarity with Xpert and lack of confidence in diagnoses made at the mobile unit.

CONCLUSION

Mobile X-ray units were a feasible and effective strategy to extend tuberculosis diagnostic services into communities and improve early case detection. Effective deployment however requires advance coordination among stakeholders and targeted provider training to ensure that people diagnosed with tuberculosis by new modalities receive prompt treatment.

Framework for planning and monitoring active TB case finding interventions to meet the global targets in the COVID-19 era and beyond: South-East Asia perspective

There was an estimated 20-40% decline in tuberculosis (TB) case detection in the South-East Asia Region (SEA Region) during 2020 due to COVID-19 outbreak. This is over and above a million people with TB who were missed each year, prior to the pandemic. Active case finding (ACF) for TB has been gaining considerable interest and investment in the SEA Region and will be even more essential for finding people with TB missed due to the COVID-19 pandemic. Many countries in the Region have incorporated ACF activities into national strategic plans and are conducting large scale activities with varying results. ACF can reach people with TB earlier than routine approaches, can lead to increases in the numbers of people diagnosed, and is often needed for certain key populations who face stigma, social, and economic barriers. However, ACF is not a one size fits all approach, and has higher costs than routine care. So, planning interventions in consultation with relevant stakeholders including the affected communities is critical. Furthermore, continuous monitoring during the intervention and after completion is crucial as national TB programmes review progress and decide on the effective utilization of limited resources. Planning and monitoring become more relevant in the COVID-19 era because of constraints posed by resource diversion towards pandemic control. Here, we summarize different aspects of planning and monitoring of ACF approaches to inform national TB programmes and partners based on experiences in the SEA Region, as programmes look to reach those who are missed and catch-up on progress towards ending TB.