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Background Recent technological and radiological advances have renewed interest in using X-rays to screen and triage people with tuberculosis (TB). The miniaturization of digital X-ray (DXR), combined with automatic interpretation using computer-aided detection (CAD) software can extend the reach of DXR screening interventions for TB. This qualitative study assessed early implementers’ experiences and lessons learned when using ultra-portable (UP) DXR systems integrated with CAD software to screen and triage TB. Methods Semi-structured interviews were conducted with project staff and healthcare workers at six pilot sites. Transcripts were coded and analyzed using a framework approach. The themes that emerged were subsequently organized and presented using the Consolidated Framework for Implementation Research (CFIR). Results There were 26 interviewees with varying roles: supervisory, clinicians, radiographers, and radiologists. Participants recognized the portability as the main advantage, but criticize that it involves several compromises on throughput, internet dependence, manoeuvrability, and stability, as well as suitability for patients with larger body sizes. Furthermore, compared to using hardware and software from the same supplier and without digital health information systems, complexity increases with interoperability between hardware and software, and between different electronic health information systems. Currently, there is a limited capacity to implement these technologies, especially due to the need for threshold selection, and lack of guidance on radiation protection suitable for UP DXR machines. Finally, the respondents stressed the importance of having protected means of sharing patient medical data, as well as comprehensive support and warranty plans. Conclusion Study findings suggest that UP DXR with CAD was overall well received to decentralize radiological assessment for TB, however, the improved portability involved programmatic compromises. The main barriers to uptake included insufficient capacity and lack of guidance on radiation protection suitable for UP DXR.

BackgroundRecent technological and radiological advances have renewed interest in using X-rays to screen and triage people with tuberculosis (TB). The miniaturization of digital X-ray (DXR), combined with automatic interpretation using computer-aided detection (CAD) software can extend the reach of DXR screening interventions for TB. This qualitative study assessed early implementers' experiences and lessons learned when using ultra-portable (UP) DXR systems integrated with CAD software to screen and triage TB.MethodsSemi-structured interviews were conducted with project staff and healthcare workers at six pilot sites. Transcripts were coded and analyzed using a framework approach. The themes that emerged were subsequently organized and presented using the Consolidated Framework for Implementation Research (CFIR).ResultsThere were 26 interviewees with varying roles: supervisory, clinicians, radiographers, and radiologists. Participants recognized the portability as the main advantage, but criticize that it involves several compromises on throughput, internet dependence, manoeuvrability, and stability, as well as suitability for patients with larger body sizes. Furthermore, compared to using hardware and software from the same supplier and without digital health information systems, complexity increases with interoperability between hardware and software, and between different electronic health information systems. Currently, there is a limited capacity to implement these technologies, especially due to the need for threshold selection, and lack of guidance on radiation protection suitable for UP DXR machines. Finally, the respondents stressed the importance of having protected means of sharing patient medical data, as well as comprehensive support and warranty plans.ConclusionStudy findings suggest that UP DXR with CAD was overall well received to decentralize radiological assessment for TB, however, the improved portability involved programmatic compromises. The main barriers to uptake included insufficient capacity and lack of guidance on radiation protection suitable for UP DXR.

In Pakistan and globally, a large proportion of people with TB who are not receiving treatment are key populations with poor access to diagnosis and care. Transgender women and male sex workers (MSW) are heavily stigmatized and marginalized groups. While HIV rates are well documented among these key populations, little such data exists for TB. We engaged local organizations working with transgender women and MSW communities in Karachi and five urban cities in Sindh Province. People from the communities served as screening facilitators and treatment supporters. Verbal screening was followed by testing with Xpert MTB/RIF and HIV testing was offered. People with TB were supported through treatment. We screened 18,272 transgender women and 24,253 MSW. 8,921 (21.0%) individuals had presumptive TB and 7,472 (83.8%) provided sputum samples. We detected 438 (5.9%) people with positive results including 140 transgender women and 298 MSW. Including people diagnosed clinically, 625 people with TB were identified and 98.1% initiated treatment. Overall, 1.5% of people screened had TB, 1.7% among MSW and 1.1% among transgender women. Of 1,508 people tested for HIV, 243 had HIV infection (HIV+). The rates of TB among HIV+ transgender women (8.8%) were slightly lower than among MSW (10.3%). Previously, few attempts have been made to address TB in transgender women and MSW. Our work shows that these groups carry a significant burden of both TB and HIV in Pakistan and do not regularly access services. Effective interventions should include the engagement of community leaders and peers.

In Pakistan and globally, a large proportion of people with TB who are not receiving treatment are key populations with poor access to diagnosis and care. Transgender women and male sex workers (MSW) are heavily stigmatized and marginalized groups. While HIV rates are well documented among these key populations, little such data exists for TB. We engaged local organizations working with transgender women and MSW communities in Karachi and five urban cities in Sindh Province. People from the communities served as screening facilitators and treatment supporters. Verbal screening was followed by testing with Xpert MTB/RIF and HIV testing was offered. People with TB were supported through treatment. We screened 18,272 transgender women and 24,253 MSW. 8,921 (21.0%) individuals had presumptive TB and 7,472 (83.8%) provided sputum samples. We detected 438 (5.9%) people with positive results including 140 transgender women and 298 MSW. Including people diagnosed clinically, 625 people with TB were identified and 98.1% initiated treatment. Overall, 1.5% of people screened had TB, 1.7% among MSW and 1.1% among transgender women. Of 1,508 people tested for HIV, 243 had HIV infection (HIV+). The rates of TB among HIV+ transgender women (8.8%) were slightly lower than among MSW (10.3%). Previously, few attempts have been made to address TB in transgender women and MSW. Our work shows that these groups carry a significant burden of both TB and HIV in Pakistan and do not regularly access services. Effective interventions should include the engagement of community leaders and peers.

Computer-aided detection (CAD) was recently recommended by the WHO for TB screening and triage based on several evaluations, but unlike traditional diagnostic tests, software versions are updated frequently and require constant evaluation. Since then, newer versions of two of the evaluated products have already been released. We used a case control sample of 12,890 chest X-rays to compare performance and model the programmatic effect of upgrading to newer versions of CAD4TB and qXR. We compared the area under the receiver operating characteristic curve (AUC), overall, and with data stratified by age, TB history, gender, and patient source. All versions were compared against radiologist readings and WHO's Target Product Profile (TPP) for a TB triage test. Both newer versions significantly outperformed their predecessors in terms of AUC: CAD4TB version 6 (0.823 [0.816-0.830]), version 7 (0.903 [0.897-0.908]) and qXR version 2 (0.872 [0.866-0.878]), version 3 (0.906 [0.901-0.911]). Newer versions met WHO TPP values, older versions did not. All products equalled or surpassed the human radiologist performance with improvements in triage ability in newer versions. Humans and CAD performed worse in older age groups and among those with TB history. New versions of CAD outperform their predecessors. Prior to implementation CAD should be evaluated using local data because underlying neural networks can differ significantly. An independent rapid evaluation centre is necessitated to provide implementers with performance data on new versions of CAD products as they are developed.

Computer-aided detection (CAD) was recently recommended by the WHO for TB screening and triage based on several evaluations, but unlike traditional diagnostic tests, software versions are updated frequently and require constant evaluation. Since then, newer versions of two of the evaluated products have already been released. We used a case control sample of 12,890 chest X-rays to compare performance and model the programmatic effect of upgrading to newer versions of CAD4TB and qXR. We compared the area under the receiver operating characteristic curve (AUC), overall, and with data stratified by age, TB history, gender, and patient source. All versions were compared against radiologist readings and WHO’s Target Product Profile (TPP) for a TB triage test. Both newer versions significantly outperformed their predecessors in terms of AUC: CAD4TB version 6 (0.823 [0.816–0.830]), version 7 (0.903 [0.897–0.908]) and qXR version 2 (0.872 [0.866–0.878]), version 3 (0.906 [0.901–0.911]). Newer versions met WHO TPP values, older versions did not. All products equalled or surpassed the human radiologist performance with improvements in triage ability in newer versions. Humans and CAD performed worse in older age groups and among those with TB history. New versions of CAD outperform their predecessors. Prior to implementation CAD should be evaluated using local data because underlying neural networks can differ significantly. An independent rapid evaluation centre is necessitated to provide implementers with performance data on new versions of CAD products as they are developed. Author summary The World Health Organization recommended the use of artificial intelligence (AI)-powered computer-aided detection (CAD) for TB screening and triage in 2021. One year on, we comprehensively compare the performance of the newest versions of two CAD (CAD4TB and qXR) to their WHO-evaluated predecessors. We found that both newer versions significantly improved upon their predecessor’s ability to detect TB, performing better than the human readers. We also showed that the AI underlying new software versions can differ remarkably from the old and resemble an entirely new product altogether. We further demonstrate that, unlike laboratory diagnostic tools, CAD software updates could significantly impact the selection of appropriate threshold scores, the number of people with TB detected and cost-effectiveness. With newer CAD versions being rolled out almost annually, our results therefore underscore the need for rapid evidence generation to evaluate newer CAD versions in the fast-growing medical AI industry.

PurposeInterventions that can help streamline and reduce gaps in the tuberculosis (TB) care cascade can play crucial roles in TB prevention and care, but are often operationally complex and resource intensive, given the heterogenous settings in which they are implemented. In this study, we present a comparative analysis on cost-effectiveness of TB REACH Wave 5 projects with diverse programmatic objectives to inform future decisions regarding funding, strategic adoption, and scale-up.MethodsWe comprehensively reviewed project reports and financial statements from TB REACH Wave 5, a funding mechanism for interventions that aimed to strengthen the TB care cascade in diverse settings. Two independent reviewers abstracted cost (in 2017 US dollars) and key programmatic data, including project type (case-finding only; case-finding and linkage-to-care; or case-finding, linkage-to-care and patient support), operational setting (urban or rural), and project outputs (numbers of people with TB diagnosed, started on treatment, and successfully completing treatment). Cost-effectiveness ratios for each project were calculated as ratios of apportioned programmatic expenditures to corresponding project outputs.ResultsOf 32 case finding and patient support projects funded through TB REACH Wave 5, 29 were included for analysis (11 case-finding only; 9 case-finding and linkage-to-care; and 9 case-finding, linkage-to-care and patient support). 21 projects (72%) were implemented in either Africa or Southeast Asia, and 19 (66%) focused on serving urban areas. Average cost-effectiveness was $184 per case diagnosed (range: $30-$10,497), $332 per diagnosis and treatment initiation ($123-$10,608), and $40 per patient treatment supported ($8-$160). Cost per case diagnosed was lower for case-finding-only projects ($132) than projects including linkage-to-care ($342) or linkage-to-care and patient support ($254), and generally increased with the corresponding country's per-capita GDP ($543 per $1000 increase, 95% confidence interval: -$53, $1138).ConclusionThe costs and cost-effectiveness of interventions to strengthen the TB care cascade were heterogenous, reflecting differences in context and programmatic objective. Nevertheless, many such interventions are likely to offer good value for money. Systematic collection and analysis of cost-effectiveness data can help improve comparability, monitoring, and evaluation.

The COVID-19 pandemic created the need for large-scale testing of populations. However, most laboratories do not have sufficient testing capacity for mass screening. We evaluated pooled testing of samples, as a strategy to increase testing capacity in Lao PDR. Samples of consecutive patients were tested in pools of four using the Xpert Xpress SARS CoV-2 assay. Positive pools were confirmed by individual testing, and we describe the performance of the test and savings achieved. We also diluted selected positive samples to describe its effect on the assays CT values. 1,568 patients were tested in 392 pools of four. 361 (92.1%) pools were negative and 31 (7.9%) positive. 29/31 (93.5% (95%CI 77-99%) positive pools were confirmed by individual testing of the samples but, in 2/31 (6.5%) the four individual samples were negative, suggesting contamination. Pools with only one positive sample had higher CT values (lower RNA concentrations) than the respective individual samples, indicating a dilution effect, which suggested an increased risk of false negative results with dilutions >1:10. However, this risk may be low if the prevalence of infection is high, when pools are more likely to contain more than one positive sample. Pooling saved 67% of cartridges and substantially increased testing capacity. Pooling samples increased SARS-CoV-2 testing capacity and resulted in considerable cartridge savings. Given the need for high-volume testing, countries may consider implementation of pooling for SARS-CoV-2 screening.

The COVID-19 pandemic created the need for large-scale testing of populations. However, most laboratories do not have sufficient testing capacity for mass screening. We evaluated pooled testing of samples, as a strategy to increase testing capacity in Lao PDR. Samples of consecutive patients were tested in pools of four using the Xpert Xpress SARS CoV-2 assay. Positive pools were confirmed by individual testing, and we describe the performance of the test and savings achieved. We also diluted selected positive samples to describe its effect on the assays CT values. 1,568 patients were tested in 392 pools of four. 361 (92.1%) pools were negative and 31 (7.9%) positive. 29/31 (93.5% (95%CI 77–99%) positive pools were confirmed by individual testing of the samples but, in 2/31 (6.5%) the four individual samples were negative, suggesting contamination. Pools with only one positive sample had higher CT values (lower RNA concentrations) than the respective individual samples, indicating a dilution effect, which suggested an increased risk of false negative results with dilutions >1:10. However, this risk may be low if the prevalence of infection is high, when pools are more likely to contain more than one positive sample. Pooling saved 67% of cartridges and substantially increased testing capacity. Pooling samples increased SARS-CoV-2 testing capacity and resulted in considerable cartridge savings. Given the need for high-volume testing, countries may consider implementation of pooling for SARS-CoV-2 screening.

Purpose Interventions that can help streamline and reduce gaps in the tuberculosis (TB) care cascade can play crucial roles in TB prevention and care, but are often operationally complex and resource intensive, given the heterogenous settings in which they are implemented. In this study, we present a comparative analysis on cost-effectiveness of TB REACH Wave 5 projects with diverse programmatic objectives to inform future decisions regarding funding, strategic adoption, and scale-up. Methods We comprehensively reviewed project reports and financial statements from TB REACH Wave 5, a funding mechanism for interventions that aimed to strengthen the TB care cascade in diverse settings. Two independent reviewers abstracted cost (in 2017 US dollars) and key programmatic data, including project type (case-finding only; case-finding and linkage-to-care; or case-finding, linkage-to-care and patient support), operational setting (urban or rural), and project outputs (numbers of people with TB diagnosed, started on treatment, and successfully completing treatment). Cost-effectiveness ratios for each project were calculated as ratios of apportioned programmatic expenditures to corresponding project outputs. Results Of 32 case finding and patient support projects funded through TB REACH Wave 5, 29 were included for analysis (11 case-finding only; 9 case-finding and linkage-to-care; and 9 case-finding, linkage-to-care and patient support). 21 projects (72%) were implemented in either Africa or Southeast Asia, and 19 (66%) focused on serving urban areas. Average cost-effectiveness was $184 per case diagnosed (range: $30-$10,497), $332 per diagnosis and treatment initiation ($123-$10,608), and $40 per patient treatment supported ($8-$160). Cost per case diagnosed was lower for case-finding-only projects ($132) than projects including linkage-to-care ($342) or linkage-to-care and patient support ($254), and generally increased with the corresponding country’s per-capita GDP ($543 per $1000 increase, 95% confidence interval: -$53, $1138). Conclusion The costs and cost-effectiveness of interventions to strengthen the TB care cascade were heterogenous, reflecting differences in context and programmatic objective. Nevertheless, many such interventions are likely to offer good value for money. Systematic collection and analysis of cost-effectiveness data can help improve comparability, monitoring, and evaluation.

There is a large gap between the number of people who develop tuberculosis (TB) and those who are diagnosed, treated and notified, with only an estimated 71% of people with TB notified globally in 2019. Implementing better TB case finding strategies is necessary to close this gap. In Cameroon, 1,597 healthcare workers at 725 health facilities were trained and engaged to intensively screen and test people for TB, then follow-up to link people to appropriate care. Primary care centers were linked to TB testing through a locally-tailored specimen referral network. This intervention was implemented across 6 regions of the country, with a population of 16 million people, while the remaining 4 regions in the country, with 7.3 million people, served as a control area. Controlled interrupted time series analyses were used to compare routinely-collected programmatic TB case notification rates in the intervention versus control area for 12 quarters prior to (2016-2018) and for 8 quarters after the start of the intervention (2019-2020). In 2019-2020, a total of 167,508 people were tested for TB at intervention sites, including 52,980 people attending primary care facilities that did not previously provide organized TB services. The number of people tested for TB increased by 45% during the intervention as compared to prior to the intervention. The controlled interrupted time series analyses showed that after two years of the intervention, the all-forms TB case notification rate in the intervention population increased by 9% (ratio of case notification rate ratios = 1.09, 95% CI 1.06 to 1.12), as compared with the counterfactual estimated from pre-intervention trends. This increase was observed even during a negative national impact on case finding from the COVID-19 pandemic. These results support the use of this health-facility based intervention to improve access to TB testing and care in this setting.

There is a large gap between the number of people who develop tuberculosis (TB) and those who are diagnosed, treated and notified, with only an estimated 71% of people with TB notified globally in 2019. Implementing better TB case finding strategies is necessary to close this gap. In Cameroon, 1,597 healthcare workers at 725 health facilities were trained and engaged to intensively screen and test people for TB, then follow-up to link people to appropriate care. Primary care centers were linked to TB testing through a locally-tailored specimen referral network. This intervention was implemented across 6 regions of the country, with a population of 16 million people, while the remaining 4 regions in the country, with 7.3 million people, served as a control area. Controlled interrupted time series analyses were used to compare routinely-collected programmatic TB case notification rates in the intervention versus control area for 12 quarters prior to (2016–2018) and for 8 quarters after the start of the intervention (2019–2020). In 2019–2020, a total of 167,508 people were tested for TB at intervention sites, including 52,980 people attending primary care facilities that did not previously provide organized TB services. The number of people tested for TB increased by 45% during the intervention as compared to prior to the intervention. The controlled interrupted time series analyses showed that after two years of the intervention, the all-forms TB case notification rate in the intervention population increased by 9% (ratio of case notification rate ratios = 1.09, 95% CI 1.06 to 1.12), as compared with the counterfactual estimated from pre-intervention trends. This increase was observed even during a negative national impact on case finding from the COVID-19 pandemic. These results support the use of this health-facility based intervention to improve access to TB testing and care in this setting.

The global Covid-19 pandemic has limited access to molecular TB diagnostics and National Programmes are struggling to maintain essential services. The pooling method (testing several samples together) could reduce the number of cartridges and staff time needed for TB diagnosis but has not been tested within the pandemic. We conducted two independent cross-sectional surveys. Pools composed of four sputum samples were tested using either Xpert-MTB/RIF or Xpert-Ultra. Pooled and individual results were compared to determine the level of agreement. Each survey included 840 participants and 210 pools. In the Xpert MTB/RIF survey, 77/81 (sensitivity 95.1%, 95%CI 87.8%-98.6%) pools containing ≥1 positive sample tested MTB-positive and 4/81 (4.9%, 95%CI 1.4%-12.2%) tested MTB-negative. All 129/129 pools containing MTB-negative samples tested MTB-negative (specificity 100%, 95%CI 97.2%-100%), with 98.1% agreement (Kappa: 0.959). In the Xpert-Ultra survey, 70/70 (sensitivity 100%, 95%CI 94.9%-100%) pools containing ≥ 1 MTB-positive sample tested MTB-positive and 140/140 (specificity 100%, 95%CI 97.4%-100%) pools containing only MTB-negative samples tested MTB-negative, with 100% agreement (Kappa: 1). Pooled testing with Xpert-MTB/RIF and Xpert-Ultra saved 38.3% and 41.7% (322/840 and 350/840, respectively) in cartridge costs alone. The pooling method with Xpert-MTB/RIF and Xpert-Ultra has similar performance to individual testing and can reduce the number of cartridges needed. These efficiencies can facilitate maintenance of stocks and sustain essential services as countries face difficulties for laboratory procurement during the pandemic and will provide cost and time savings post-pandemic.

Pharmacies represent a key health system entry point for people with TB in Viet Nam, but high fragmentation hinders their broader engagement. Professional networking apps may be able to facilitate pharmacy engagement for systematic TB screening and referral. Between September and December 2019, we piloted the use of a social networking app, SwipeRx, to recruit pharmacists for a TB referral scheme across four districts of Ho Chi Minh City, Viet Nam. We measured chest X-ray (CXR) referrals and TB detection yields at participating pharmacies and fielded 100 acceptability surveys, divided into pharmacists who did and did not make a CXR referral. We then fitted mixed-effect odds proportional models to explore acceptability factors that were associated with making a CXR referral. 1,816 push notifications were sent to pharmacists via the SwipeRx app and 78 indicated their interest in participating; however, only one was within the pilot's intervention area. Additional in-person outreach resulted in the recruitment of 146 pharmacists, with 54 (37.0%) making at least one CXR referral. A total of 182 pharmacy customers were referred, resulting in a total of 64 (35.2%) CXR screens and seven people being diagnosed with TB. Compared to pharmacists who did not make any CXR referrals, pharmacists making at least one CXR referral understood the pilot's objectives more clearly (aOR = 2.6, 95% CI: 1.2-5.8) and they believed that TB screening increased customer trust (aOR = 2.7, 95% CI: 1.2-5.8), benefited their business (aOR = 2.8, 95% CI: 1.3-6.2) and constituted a competitive advantage (aOR = 4.4, 95% CI: 1.9-9.9). They were also more confident in using mHealth apps (aOR = 3.1, 95 CI%: 1.4-6.8). Pharmacies can play an important role in early and increased TB case finding. It is critical to highlight the value proposition of TB referral schemes to their business during recruitment. Digital networking platforms, such as SwipeRx, can facilitate referrals for TB screening by pharmacists, but their ability to identify and recruit pharmacists requires optimization, particularly when targeting specific segments of a nation-wide digital network.

The global Covid-19 pandemic has limited access to molecular TB diagnostics and National Programmes are struggling to maintain essential services. The pooling method (testing several samples together) could reduce the number of cartridges and staff time needed for TB diagnosis but has not been tested within the pandemic. We conducted two independent cross-sectional surveys. Pools composed of four sputum samples were tested using either Xpert-MTB/RIF or Xpert-Ultra. Pooled and individual results were compared to determine the level of agreement. Each survey included 840 participants and 210 pools. In the Xpert MTB/RIF survey, 77/81 (sensitivity 95.1%, 95%CI 87.8%-98.6%) pools containing ≥1 positive sample tested MTB-positive and 4/81 (4.9%, 95%CI 1.4%-12.2%) tested MTB-negative. All 129/129 pools containing MTB-negative samples tested MTB-negative (specificity 100%, 95%CI 97.2%-100%), with 98.1% agreement (Kappa: 0.959). In the Xpert-Ultra survey, 70/70 (sensitivity 100%, 95%CI 94.9%-100%) pools containing ≥ 1 MTB-positive sample tested MTB-positive and 140/140 (specificity 100%, 95%CI 97.4%-100%) pools containing only MTB-negative samples tested MTB-negative, with 100% agreement (Kappa: 1). Pooled testing with Xpert-MTB/RIF and Xpert-Ultra saved 38.3% and 41.7% (322/840 and 350/840, respectively) in cartridge costs alone. The pooling method with Xpert-MTB/RIF and Xpert-Ultra has similar performance to individual testing and can reduce the number of cartridges needed. These efficiencies can facilitate maintenance of stocks and sustain essential services as countries face difficulties for laboratory procurement during the pandemic and will provide cost and time savings post-pandemic.

Pharmacies represent a key health system entry point for people with TB in Viet Nam, but high fragmentation hinders their broader engagement. Professional networking apps may be able to facilitate pharmacy engagement for systematic TB screening and referral. Between September and December 2019, we piloted the use of a social networking app, SwipeRx, to recruit pharmacists for a TB referral scheme across four districts of Ho Chi Minh City, Viet Nam. We measured chest X-ray (CXR) referrals and TB detection yields at participating pharmacies and fielded 100 acceptability surveys, divided into pharmacists who did and did not make a CXR referral. We then fitted mixed-effect odds proportional models to explore acceptability factors that were associated with making a CXR referral. 1,816 push notifications were sent to pharmacists via the SwipeRx app and 78 indicated their interest in participating; however, only one was within the pilot’s intervention area. Additional in-person outreach resulted in the recruitment of 146 pharmacists, with 54 (37.0%) making at least one CXR referral. A total of 182 pharmacy customers were referred, resulting in a total of 64 (35.2%) CXR screens and seven people being diagnosed with TB. Compared to pharmacists who did not make any CXR referrals, pharmacists making at least one CXR referral understood the pilot’s objectives more clearly (aOR = 2.6, 95% CI: 1.2–5.8) and they believed that TB screening increased customer trust (aOR = 2.7, 95% CI: 1.2–5.8), benefited their business (aOR = 2.8, 95% CI: 1.3–6.2) and constituted a competitive advantage (aOR = 4.4, 95% CI: 1.9–9.9). They were also more confident in using mHealth apps (aOR = 3.1, 95 CI%: 1.4–6.8). Pharmacies can play an important role in early and increased TB case finding. It is critical to highlight the value proposition of TB referral schemes to their business during recruitment. Digital networking platforms, such as SwipeRx, can facilitate referrals for TB screening by pharmacists, but their ability to identify and recruit pharmacists requires optimization, particularly when targeting specific segments of a nation-wide digital network.

BackgroundThe World Health Organization recently recommended Video Observed Therapy (VOT) as one option for monitoring tuberculosis (TB) treatment adherence. There is evidence that private sector TB treatment has substandard treatment follow-up, which could be improved using VOT. However, acceptability of VOT in the private sector has not yet been evaluated.MethodsWe conducted a cross-sectional survey employing a theoretical framework for healthcare intervention acceptability to measure private provider perceptions of VOT across seven constructs in three cities of Viet Nam: Ha Noi, Ho Chi Minh City, and Hai Phong. We investigated the differences in private providers' attitudes and perceptions of VOT using mixed ordinal models to test for significant differences in responses between groups of providers stratified by their willingness to use VOT.ResultsA total of 79 private providers completed the survey. Sixty-two providers (75%) indicated they would use VOT if given the opportunity. Between private providers who would and would not use VOT, there were statistically significant differences (p≤0.001) in the providers' beliefs that VOT would help identify side effects faster and in their confidence to monitor treatment and provide differentiated care with VOT. There were also significant differences in providers' beliefs that VOT would save them time and money, address problems faced by their patients, benefit their practice and patients, and be relevant for all their patients.ConclusionPrivate providers who completed the survey have positive views towards using VOT and specific subpopulations acknowledge the value of integrating VOT into their practice. Future VOT implementation in the private sector should focus on emphasizing the benefits and relevance of VOT during recruitment and provide programmatic support for implementing differentiated care with the technology.

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.

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.

BackgroundA decade of Boko Haram insurgency brought conflict, mass displacement, and the destruction of basic infrastructure to Northeast Nigeria. Over 2 million internally displaced persons (IDPs) suffering from lack of basic hygienic conditions, malnutrition, and disease live in camps or are hosted by communities in the region, where the conflict has contributed to a massive destruction of health facilities. Infectious diseases like tuberculosis (TB) and HIV are especially difficult to address under such conditions, and IDPs are vulnerable to both. Although international investment supports some health interventions among IDPs, locally sourced solutions are lacking.Methods and findingsWe evaluated the impact of an active case finding (ACF) intervention for TB and testing for HIV in IDP communities and provided linkages to treatment in 3 states in Northeast Nigeria: Adamawa, Gombe, and Yobe. The ACF was a component of a multistakeholder collaboration between government, civil society, and IDP community partners, which also included mapping of IDP populations and health services, supporting existing health facilities, developing a sample transport network, and organizing community outreach to support ACF. Between July 1, 2017, and June 30, 2018, ACF was conducted in 26 IDP camps and 963 host communities in 12 local government areas (LGAs) with another 12 LGAs serving as a control population. Outreach efforts resulted in 283,556 screening encounters. We screened 13,316 children and 270,239 adults including 150,303 (55.6%) adult women and 119,936 (44.4%) men. We tested 17,134 people for TB and 58,976 for HIV. We detected 1,423 people with TB and 874 people living with HIV. We linked 1,419 people to anti-TB treatment and 874 people with HIV to antiretroviral treatment sites. We evaluated additional TB cases notified and conducted comparative interrupted time series (ITS) analyses to assess the impact of ACF on TB case notifications. Through our efforts, bacteriologically confirmed TB notifications increased by 847 (45.1%) during the intervention period, with IDPs accounting for 46% of these notifications. The ITS analyses detected significant positive postintervention trend differences in TB notification rates between the intervention and control areas in all forms TB (incidence rate ratio [IRR] = 1.136 [1.072, 1.204]; p ≤ 0.001) and bacteriologically positive TB (IRR = 1.141 [1.058, 1.229]; p = 0.001). The TB prevalence (502 cases per 100,000 screening encounters) was 10 times the national notification rates and 2.3 times the estimated national incidence. Rates of HIV infection (1.8%) were higher than HIV prevalence estimates in the 3 states. Our study was limited by the nonrandom selection of LGAs. Furthermore, we did not use sensitive screening tools like chest X-ray and likely missed people with TB.ConclusionsIn this study, we observed a burden of TB in IDP populations of Northeast Nigeria many times higher than national rates and HIV rates higher than state level estimates. The impact of the intervention showed that ACF can greatly increase TB case notifications. Engaging IDP communities, local governments, and civil society organizations is essential to ensuring the success of interventions targeting TB and HIV, and such approaches can provide sustained solutions to these and other health crises among vulnerable populations.

INTRODUCTION:Over the years, technological and process innovations enabled active case finding (ACF) programs to expand their capacities and scope to have evolved to close gaps in missing TB patients globally. However, with increased ACF program's operational complexity and a need for significant resource commitments, a comprehensive, transparent, and standardized approach in evaluating costs of ACF programs is needed to properly determine costs and value of ACF programs. METHODS:Based on reviews of program activity and financial reports, multiple interviews with program managers of two TB REACH funded ACF programs deployed in Cambodia and Tajikistan, we first identified common program components, which formed the basis of the cost data collection, analysis, reporting framework. Within each program component and sub-activity group, cost data were collected and organized by relevant resource types (human resource, capital, recurrent, and overhead costs). Total shared, indirect and overhead costs were apportioned into each activity category based on direct human resource contribution (e.g. a number of staff and their relative level of effort dedicated to each program component). Capital assets were assessed specific to program components and were annualized based on their expected useful life and a 3% discount rate. All costs were assessed based on the service provider perspective and expressed in 2015 USD. RESULTS:Over the two program years (April 2013 to December 2015), the Cambodia and Tajikistan ACF programs cumulated a total cost of $336,951 and $771,429 to screen 68,846 and 1,980,516 target population, bacteriologically test 4,589 and 19,764 presumptive TB, diagnose 731 and 2,246 TB patients in the respective programs. Recurrent costs were the largest cost components (54% and 34%) of the total costs for the respective programs and Xpert MTB/RIF (Xpert) testing incurred largest program component/activity cost for both programs. Cost per screening was $0.63 and $0.10 and cost per Xpert test was $25 and $18; Cost per TB case detected (Xpert) was $373 and $343 in Cambodia and Tajikistan. CONCLUSIONS:Results from two contextually and programmatically different multi-component ACF programs demonstrate that our tool is fully capable of comprehensively and transparently evaluating and comparing costs of various ACF programs.

Tuberculosis prevalence surveys have demonstrated the benefit of screening with chest x-ray (CXR) and sensitive diagnostic tests compared to symptoms and smear microscopy. However, in programmatic practice there is little evidence on the yield of different algorithms. We implemented contact tracing in Chennai, India for adult sputum-positive TB patients registered from January 2015 to March 2016. Patients with symptoms or abnormal X-ray findings further underwent testing using Xpert MTB/RIF (Xpert) and smear microscopy. A retrospective cohort study was done to summarize the key findings. We verbally screened 5553 contacts for symptoms, CXR through private sector collaboration, Xpert, and smear microscopy. Overall, 1312 (23.6%) contacts screened positive. CXR alone identified 531 (40.5%) of them, 679 (51.8%) were symptom-positive only, while 102 (7.8%) were positive on both the symptom and CXR screen. Overall, 35 bacteriologically positive cases were identified (0.7%). A standard approach of symptoms screening followed by microscopy identified only 9 (25.7%) of the total number of bacteriologically positive cases, whereas the combination of a CRX screening followed by microscopy identified 13 (37.1%) of the cases. The algorithm of symptoms screening followed by Xpert testing, detected 20 cases, whereas the combination of symptoms and CXR followed by Xpert increased this number to 35 (75% increase compared to symptoms and Xpert). Optimal use of more sensitive screening tests, better diagnostic tests, and novel private sector engagement can improve diagnostic yield in a programmatic setting.

BackgroundIn Bangladesh, about 80% of healthcare is provided by the private sector. Although free diagnosis and care is offered in the public sector, only half of the estimated number of people with tuberculosis are diagnosed, treated, and notified to the national program. Private sector engagement strategies often have been small scale and time limited. We evaluated a Social Enterprise Model combining external funding and income generation at three tuberculosis screening centres across the Dhaka Metropolitan Area for diagnosing and treating tuberculosis.Methods and findingsThe model established three tuberculosis screening centres across Dhaka Metropolitan Area that carried the icddr,b brand and offered free Xpert MTB/RIF tests to patients visiting the screening centres for subsidized, digital chest radiographs from April 2014 to December 2017. A network of private and public health care providers, and community recommendation was formed for patient referral. No financial incentives were offered to physicians for referrals. Revenues from radiography were used to support screening centres' operation. Tuberculosis patients could choose to receive treatment from the private or public sector. Between 2014 and 2017, 1,032 private facilities networked with 8,466 private providers were mapped within the Dhaka Metropolitan Area. 64, 031 patients with TB symptoms were referred by the private providers, public sector and community residents to the three screening centres with 80% coming from private providers. 4,270 private providers made at least one referral. Overall, 10,288 pulmonary and extra-pulmonary tuberculosis cases were detected and 7,695 were bacteriologically positive by Xpert, corresponding to 28% of the total notifications in Dhaka Metropolitan Area.ConclusionThe model established a network of private providers who referred individuals with presumptive tuberculosis without financial incentives to icddr,b's screening centres, facilitating a quarter of total tuberculosis notifications in Dhaka Metropolitan Area. Scaling up this approach may enhance national and international tuberculosis response.

BACKGROUND:Tuberculosis (TB) is the deadliest infectious disease globally. Current case finding approaches may miss many people with TB or detect them too late. DATA AND METHODS:This study was a retrospective, spatial analysis of routine TB surveillance and cadastral data in Go Vap district, Ho Chi Minh City. We geocoded TB notifications from 2011 to 2015 and calculated theoretical yields of simulated door-to-door screening in three concentric catchment areas (50m, 100m, 200m) and three notification window scenarios (one, two and four quarters) for each index case. We calculated average yields, compared them to published reference values and fit a GEE (Generalized Estimating Equation) linear regression model onto the data. RESULTS:The sample included 3,046 TB patients. Adjusted theoretical yields in 50m, 100m and 200m catchment areas were 0.32% (95%CI: 0.27,0.37), 0.21% (95%CI: 0.14,0.29) and 0.17% (95%CI: 0.09,0.25), respectively, in the baseline notification window scenario. Theoretical yields in the 50m-catchment area for all notification window scenarios were significantly higher than a reference yield from literature. Yield was positively associated with treatment failure index cases (beta = 0.12, p = 0.001) and short-term inter-province migrants (beta = 0.06, p = 0.022), while greater distance to the DTU (beta = -0.02, p

Currently, only 62% of incident tuberculosis (TB) cases are reported to the national programme in Pakistan. Several innovative interventions are being recommended to detect the remaining 'missed' TB cases. One such intervention involved expanding contact investigation to the community using the Xpert MTB/RIF test.This was a before and after intervention study involving retrospective record review. Passive case finding and household contact investigation was routinely done in the pre-intervention period July 2011-June 2013. Four districts with a high concentration of slums were selected as intervention areas; Lahore, Rawalpindi, Faisalabad and Islamabad. Here, in the intervention period, July 2013-June 2015, contact investigation beyond household was conducted: all people staying within a radius of 50 metres (using Geographical Information System) from the household of smear positive TB patients were screened for tuberculosis. Those with presumptive TB were investigated using smear microscopy and the Xpert MTB/RIF test was performed on smear negative patients. All the diagnosed TB patients were linked to TB treatment and care.A total of 783043 contacts were screened for tuberculosis: 23741(3.0%) presumptive TB patients were identified of whom, 4710 (19.8%) all forms and 4084(17.2%) bacteriologically confirmed TB patients were detected. The contribution of Xpert MTB/RIF to bacteriologically confirmed TB patients was 7.6%. The yield among investigated presumptive child TB patients was 5.1%. The overall yield of all forms TB patients among investigated was 22.3% among household and 19.1% in close community. The intervention contributed an increase of case detection of bacteriologically confirmed tuberculosis by 6.8% and all forms TB patients by 7.9%.Community contact investigation beyond household not only detected additional TB patients but also increased TB case detection. However, further long term assessments and cost-effectiveness studies are required before national scale-up.

Screening of household contacts of tuberculosis (TB) patients is a recommended strategy to improve early case detection. While it has been widely implemented in low prevalence countries, the most optimal protocols for contact investigation in high prevalence, low resource settings is yet to be determined. This study evaluated contact investigation interventions in eleven lower and middle income countries and reviewed the association between context or program-related factors and the yield of cases among contacts.We reviewed data from nineteen first wave TB REACH funded projects piloting innovations to improve case detection. These nineteen had fulfilled the eligibility criteria: contact investigation implementation and complete data reporting. We performed a cross-sectional analysis of the percentage yield and case notifications for each project. Implementation strategies were delineated and the association between independent variables and yield was analyzed by fitting a random effects logistic regression.Overall, the nineteen interventions screened 139,052 household contacts, showing great heterogeneity in the percentage yield of microscopy confirmed cases (SS+), ranging from 0.1% to 6.2%). Compared to the most restrictive testing criteria (at least two weeks of cough) the aOR's for lesser (any TB related symptom) and least (all contacts) restrictive testing criteria were 1.71 (95%CI 0.94-3.13) and 6.90 (95% CI 3.42-13.93) respectively. The aOR for inclusion of SS- and extra-pulmonary TB was 0.31 (95% CI 0.15-0.62) compared to restricting index cases to SS+ TB. Contact investigation contributed between

BackgroundIn Pakistan, like many Asian countries, a large proportion of healthcare is provided through the private sector. We evaluated a systematic screening strategy to identify people with tuberculosis in private facilities in Karachi and assessed the approaches' ability to diagnose patients earlier in their disease progression.Methods and findingsLay workers at 89 private clinics and a large hospital outpatient department screened all attendees for tuberculosis using a mobile phone-based questionnaire during one year. The number needed to screen to detect a case of tuberculosis was calculated. To evaluate early diagnosis, we tested for differences in cough duration and smear grading by screening facility. 529,447 people were screened, 1,010 smear-positive tuberculosis cases were detected and 942 (93.3%) started treatment, representing 58.7% of all smear-positive cases notified in the intervention area. The number needed to screen to detect a smear-positive case was 124 (prevalence 806/100,000) at the hospital and 763 (prevalence 131/100,000) at the clinics; however, ten times the number of individuals were screened in clinics. People with smear-positive TB detected at the hospital were less likely to report cough lasting 2-3 weeks (RR 0.66 95%CI [0.49-0.90]) and more likely to report cough duration >3 weeks (RR 1.10 95%CI [1.03-1.18]). Smear-positive cases at the clinics were less likely to have a +3 grade (RR 0.76 95%CI [0.63-0.92]) and more likely to have +1 smear grade (RR 1.24 95%CI [1.02-1.51]).ConclusionsTuberculosis screening at private facilities is acceptable and can yield large numbers of previously undiagnosed cases. Screening at general practitioner clinics may find cases earlier than at hospitals although more people must be screened to identify a case of tuberculosis. Limitations include lack of culture testing, therefore underestimating true TB prevalence. Using more sensitive and specific screening and diagnostic tests such as chest x-ray and Xpert MTB/RIF may improve results.

BackgroundGlobally, TB notifications have stagnated since 2007, and sputum smear positive notifications have been declining despite policies to improve case detection. We evaluate results of 28 interventions focused on improving TB case detection.MethodsWe measured additional sputum smear positive cases treated, defined as the intervention area's increase in case notification during the project compared to the previous year. Projects were encouraged to select control areas and collect historical notification data. We used time series negative binomial regression for over-dispersed cross-sectional data accounting for fixed and random effects to test the individual projects' effects on TB notification while controlling for trend and control populations.ResultsTwenty-eight projects, 19 with control populations, completed at least four quarters of case finding activities, covering a population of 89.2 million. Among all projects sputum smear positive (SS+) TB notifications increased 24.9% and annualized notification rates increased from 69.1 to 86.2/100,000 (p = 0.0209) during interventions. Among the 19 projects with control populations, SS+TB case notifications increased 36.9% increase while in the control populations a 3.6% decrease was observed. Fourteen (74%) of the 19 projects' SS+TB notification rates in intervention areas increased from the baseline to intervention period when controlling for historical trends and notifications in control areas.ConclusionsInterventions were associated with large increases in TB notifications across many settings, using an array of interventions. Many people with TB are not reached using current approaches. Different methods and interventions tailored to local realities are urgently needed.

BackgroundThe potential population-level impact of private-sector initiatives for tuberculosis (TB) case finding in Southeast Asia remains uncertain. In 2011, the Indus Hospital TB Control Program in Karachi, Pakistan, undertook an aggressive case-finding campaign that doubled notification rates, providing an opportunity to investigate potential population-level effects.MethodsWe constructed an age-structured compartmental model of TB in the intervention area. We fit the model using field and literature data, assuming that TB incidence equaled the estimated nationwide incidence in Pakistan (primary analysis), or 1.5 times greater (high-incidence scenario). We modeled the intervention as an increase in the rate of formal-sector TB diagnosis and evaluated the potential impact of sustaining this rate for five years.ResultsIn the primary analysis, the five-year intervention averted 24% (95% uncertainty range, UR: 18-30%) of five-year cumulative TB cases and 52% (95% UR: 45-57%) of cumulative TB deaths. Corresponding reductions in the high-incidence scenario were 12% (95% UR: 8-17%) and 27% (95% UR: 21-34%), although the absolute number of lives saved was higher. At the end of five years, TB notification rates in the primary analysis were below their 2010 baseline, incidence had dropped by 45%, and annual mortality had fallen by 72%. About half of the cumulative impact on incidence and mortality could be achieved with a one-year intervention.ConclusionsSustained, multifaceted, and innovative approaches to TB case-finding in Asian megacities can have substantial community-wide epidemiological impact.