CIDRZ Research
Permanent URI for this communityhttps://pubs.cidrz.org/handle/123456789/1
Welcome to the CIDRZ Research Repository
The CIDRZ Research Repository serves as an open-access archive for peer-reviewed publications, conference papers, and other scholarly outputs from CIDRZ researchers. Our goal is to promote the dissemination of knowledge and support evidence-based public health initiatives.
News
New Research Publications Added
We have recently added new publications on HIV prevention, maternal health, and epidemiology. Browse the latest research in our repository.
Open Access Week 2025
Join us in celebrating Open Access Week! Learn how open-access publishing enhances research visibility and impact.
Browse
46 results
Search Results
Item Engagement of private health care facilities in TB management in Lusaka district of Zambia: lessons learned and achievements.(2024-Mar-14) Hambwalula R; Kagujje M; Mwaba I; Musonda D; Singini D; Mutti L; Sanjase N; Kaumba PC; Ziko LM; Zimba KM; Kasese-Chanda P; Muyoyeta M; Division of Health, United States Agency for International Development, Lusaka, Zambia.; TB department, Centre of Infectious Disease Research in Zambia, Plot # 34620 Off Alick Nkhata Road, Mass Media, P.O. Box 34681, Lusaka, 10101, Zambia. Mary.Kagujje@cidrz.org.; Lusaka District Health Office, Ministry of Health, Great East Road, Lusaka, Zambia.; TB department, Centre of Infectious Disease Research in Zambia, Plot # 34620 Off Alick Nkhata Road, Mass Media, P.O. Box 34681, Lusaka, 10101, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)BACKGROUND: Globally, at least 3 million TB patients are missed every year. In Zambia, the TB treatment coverage increased from 66% in 2020 to 92% in 2022. Involvement of all levels of health care service delivery is critical to finding all the missing TB patients. METHODS: A survey was undertaken in 15 private facilities in Lusaka district of Zambia using a structured tool administered by project team and a district health team member. Data collected during the survey was analysed and results were used to determine the type of TB services that were offered as well as barriers and enablers to TB service provision. This was followed by a set of interventions that included; training and mentorship on active case finding and systematic TB screening, increased diagnostic capacity, provision of national recording and reporting tools and provision of TB medication through linkage with the National TB program (NTP). We report findings from the baseline survey and changes in presumptive TB identification and notification following interventions. RESULTS: Major barriers to TB service delivery were the high cost of TB diagnostic testing and treatment in facilities where services were not supported by the National TB program; the mean cost was 33 (SD 33) and 93 (SD 148) for GeneXpert testing and a full course of treatment respectively. Pre-intervention, presumptive TB identification appeared to increase monthly by 4 (P = 0.000, CI=[3.00-5.00]). The monthly trends of presumptive TB identification during the intervention period increased by 5.32 (P = 0.000, [CI 4.31-6.33. Pre-intervention, the notification of TB appeared to decrease every month by -4.0 (P = 0.114, CI=[-9.00-0.10]) followed by an immediate increase in notifications of 13.94 TB patients (P = 0.001, CI [6.51, 21.36] in the first month on intervention. The monthly trends of notification during the intervention period changed by 0.34 (P = 0.000 [CI 0.19-0.48]). Private facility contribution to TB notification increased from 3 to 7%. CONCLUSION: Engagement and inclusion of private health facilities in TB service provision through a systems strengthening approach can increase contribution to TB notification by private health facilities.Item Knowledge, attitudes, and practices towards childhood tuberculosis among healthcare workers at two primary health facilities in Lusaka, Zambia.(2024) Kaumba PC; Siameka D; Kagujje M; Chungu C; Nyangu S; Sanjase N; Maimbolwa MM; Shuma B; Chilukutu L; Muyoyeta M; Catholic Relief Services, Ibex, Lusaka.; Centre of Infectious Disease Research in Zambia (CIDRZ), Mass Media, Lusaka, Zambia.BACKGROUND: Zambia is among the 30 high-burden countries for tuberculosis (TB), Human Immunodeficiency Virus (HIV)-associated TB, and multi-drug resistant/rifampicin resistant TB with over 5000 children developing TB every year. However, at least 32% of the estimated children remain undiagnosed. We assessed healthcare workers' (HCWs) knowledge, attitudes, and practices (KAP) towards childhood TB and the factors associated with good KAP towards childhood TB. METHODS: Data was collected at two primary healthcare facilities in Lusaka, Zambia from July to August 2020. Structured questionnaires were administered to HCWs that were selected through stratified random sampling. Descriptive analysis was done to determine KAP. A maximum knowledge, attitude, and practice scores for a participant were 44, 10, and 8 points respectively. The categorization as either "poor" or "good" KAP was determined based on the mean/ median. Logistic regression analysis was performed to assess the associations between participant characteristics and KAP at statistically significant level of 0.05%. RESULTS: Among the 237 respondents, majority were under 30 years old (63.7%) and were female (72.6%). Half of the participants (50.6%) were from the outpatient department (OPD) and antiretroviral therapy (ART) clinic, 109 (46.0) had been working at the facility for less than 1 year, 134 (56.5%) reported no previous training in TB. The median/mean KAP scores were 28 (IQR 24.0-31.0), 7 (IQR = 6.0-8.0) and 5 points (SD = 1.9) respectively. Of the participants, 43.5% (103/237) had good knowledge, 48.1% (114/237) had a good attitude, and 54.4% (129/237) had good practice scores on childhood TB. In the multivariate analysis, clinical officers and individuals with 1-5 years' work experience at the facility had higher odds, 2.61 (95% CI = 1.18-5.80, p = 0.018) and 3.09 (95% CI = 1.69-5.65, p = 0.001) of having good attitude respectively, and medical doctors had 0.17 lower odds (95% CI = 0.18-5.80, p = 0.018) of good childhood TB practice. Other participant characteristics didn't show a significant association with the scores. CONCLUSION: The study found suboptimal levels of knowledge, attitude, and practices regarding childhood TB among HCWs. Targeted programmatic support needs to be provided to address the above gaps.Item The Incidence and Risk Factors for Enterotoxigenic(2024-Mar-29) Sukwa N; Bosomprah S; Somwe P; Muyoyeta M; Mwape K; Chibesa K; Luchen CC; Silwamba S; Mulenga B; Munyinda M; Muzazu S; Chirwa M; Chibuye M; Simuyandi M; Chilengi R; Svennerholm AM; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka P.O. Box 34681, Zambia.; Department of Microbiology and Immunology, University of Gothenburg, 40530 Gothenburg, Sweden.; Department of Biostatistics, School of Public Health, University of Ghana, Accra P.O. Box LG13, Ghana.This study aimed to estimate the incidence and risk factors for EnterotoxigenicItem Prospective multicentre accuracy evaluation of the FUJIFILM SILVAMP TB LAM test for the diagnosis of tuberculosis in people living with HIV demonstrates lot-to-lot variability.(2024) Székely R; Sossen B; Mukoka M; Muyoyeta M; Nakabugo E; Hella J; Nguyen HV; Ubolyam S; Chikamatsu K; Macé A; Vermeulen M; Centner CM; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Mitarai S; Nguyen NV; Avihingsanon A; Reither K; Nakiyingi L; Kerkhoff AD; MacPherson P; Meintjes G; Denkinger CM; Ruhwald M; Clinical Research Department, London School of Hygiene & Tropical Medicine, London, United Kingdom.; HIV-NAT, Thai Red Cross AIDS Research Centre and Centre of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; National Lung Hospital, Ha Noi, Viet Nam.; Taksin Hospital, Bangkok, Thailand.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; University of Basel, Basel, Switzerland.; Department of Mycobacterium Reference and Research, Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Tokyo, Japan.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi.; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Ifakara Health Institute, Dar es Salaam, Tanzania.; FIND, The Global Alliance for Diagnostics, Geneva, Switzerland.; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, CA, United States of America.; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital and Faculty of Medicine, Heidelberg University, Heidelberg, Germany.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; Swiss Tropical and Public Health Institute, Allschwil, Switzerland.; German Centre for Infection Research (DZIF), Partner site Heidelberg University Hospital, Heidelberg, Germany.; Division of Medical Microbiology, University of Cape Town and National Health Laboratory Service, Groote Schuur Hospital, Cape Town, South Africa.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)There is an urgent need for rapid, non-sputum point-of-care diagnostics to detect tuberculosis. This prospective trial in seven high tuberculosis burden countries evaluated the diagnostic accuracy of the point-of-care urine-based lipoarabinomannan assay FUJIFILM SILVAMP TB LAM (FujiLAM) among inpatients and outpatients living with HIV. Diagnostic performance of FujiLAM was assessed against a mycobacterial reference standard (sputum culture, blood culture, and Xpert Ultra from urine and sputum at enrollment, and additional sputum culture ≤7 days from enrollment), an extended mycobacterial reference standard (eMRS), and a composite reference standard including clinical evaluation. Of 1637 participants considered for the analysis, 296 (18%) were tuberculosis positive by eMRS. Median age was 40 years, median CD4 cell count was 369 cells/ul, and 52% were female. Overall FujiLAM sensitivity was 54·4% (95% CI: 48·7-60·0), overall specificity was 85·2% (83·2-87·0) against eMRS. Sensitivity and specificity estimates varied between sites, ranging from 26·5% (95% CI: 17·4%-38·0%) to 73·2% (60·4%-83·0%), and 75·0 (65·0%-82·9%) to 96·5 (92·1%-98·5%), respectively. Post-hoc exploratory analysis identified significant variability in the performance of the six FujiLAM lots used in this study. Lot variability limited interpretation of FujiLAM test performance. Although results with the current version of FujiLAM are too variable for clinical decision-making, the lipoarabinomannan biomarker still holds promise for tuberculosis diagnostics. The trial is registered at clinicaltrials.gov (NCT04089423).Item Diagnostic yield as an important metric for the evaluation of novel tuberculosis tests: rationale and guidance for future research.(2024-Jul) Broger T; Marx FM; Theron G; Marais BJ; Nicol MP; Kerkhoff AD; Nathavitharana R; Huerga H; Gupta-Wright A; Kohli M; Nichols BE; Muyoyeta M; Meintjes G; Ruhwald M; Peeling RW; Pai NP; Pollock NR; Pai M; Cattamanchi A; Dowdy DW; Dewan P; Denkinger CM; Centre for Infectious Diseases Research in Zambia, Lusaka, Zambia.; Boston Children's Hospital, Boston, MA, USA.; The University of Sydney Infectious Diseases Institute, Sydney, NSW, Australia; Children's Hospital at Westmead, Sydney, NSW, Australia.; Bill & Melinda Gates Foundation, Seattle, WA, USA.; Department of Epidemiology, Epicentre, Paris, France.; McGill International TB Centre, McGill University, Montreal, QC, Canada.; Center for Tuberculosis, University of California San Francisco, San Francisco, CA, USA; Department of Medicine, Division of Pulmonary Diseases and Critical Care Medicine, University of California Irvine, Irvine, CA, USA.; Department of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany; DSI-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Faculty of Science, Stellenbosch University, Stellenbosch, South Africa.; London School of Hygiene & Tropical Medicine, London, UK.; DSI-NRF Centre of Excellence for Biomedical Tuberculosis Research, South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.; Department of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany; German Center for Infection Research, Heidelberg University Hospital, Heidelberg, Germany. Electronic address: claudia.denkinger@uni-heidelberg.de.; Department of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany.; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.; Department of Medicine, University of Cape Town, Cape Town, South Africa; Wellcome Centre for Infectious Diseases Research in Africa (CIDRI-Africa), Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Division of HIV, Infectious Diseases, and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, USA; Center for Tuberculosis, University of California San Francisco, San Francisco, CA, USA.; Division of Infection and Immunity, School of Biomedical Sciences, University of Western Australia, Perth, WA, Australia.; Department of Medicine, Centre for Outcomes Research & Evaluation, McGill University, Montreal, QC, Canada.; FIND, Geneva, Switzerland.; Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA, USA.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)Better access to tuberculosis testing is a key priority for fighting tuberculosis, the leading cause of infectious disease deaths in people. Despite the roll-out of molecular WHO-recommended rapid diagnostics to replace sputum smear microscopy over the past decade, a large diagnostic gap remains. Of the estimated 10·6 million people who developed tuberculosis globally in 2022, more than 3·1 million were not diagnosed. An exclusive focus on improving tuberculosis test accuracy alone will not be sufficient to close the diagnostic gap for tuberculosis. Diagnostic yield, which we define as the proportion of people in whom a diagnostic test identifies tuberculosis among all people we attempt to test for tuberculosis, is an important metric not adequately explored. Diagnostic yield is particularly relevant for subpopulations unable to produce sputum such as young children, people living with HIV, and people with subclinical tuberculosis. As more accessible non-sputum specimens (eg, urine, oral swabs, saliva, capillary blood, and breath) are being explored for point-of-care tuberculosis testing, the concept of yield will be of growing importance. Using the example of urine lipoarabinomannan testing, we illustrate how even tests with limited sensitivity can diagnose more people with tuberculosis if they enable increased diagnostic yield. Using tongue swab-based molecular tuberculosis testing as another example, we provide definitions and guidance for the design and conduct of pragmatic studies that assess diagnostic yield. Lastly, we show how diagnostic yield and other important test characteristics, such as cost and implementation feasibility, are essential for increased effective population coverage, which is required for optimal clinical care and transmission impact. We are calling for diagnostic yield to be incorporated into tuberculosis test evaluation processes, including the WHO Grading of Recommendations, Assessment, Development, and Evaluations process, providing a crucial real-life implementation metric that complements traditional accuracy measures.Item Reaching for 90:90:90 in Correctional Facilities in South Africa and Zambia: Virtual Cross-Section of Coverage of HIV Testing and Antiretroviral Therapy During Universal Test and Treat Implementation.(2024-Aug-15) Hoffmann CJ; Herce ME; Chimoyi L; Smith HJ; Tlali M; Olivier CJ; Topp SM; Muyoyeta M; Reid SE; Hausler H; Charalambous S; Fielding K; Institute for Global Health and Infectious Diseases, School of Medicine, University of North Carolina, Chapel Hill, NC.; College of Public Health Medicine and Veterinary Sciences, James Cook University, Townsville, Australia.; Department of Medicine, Johns Hopkins University, Baltimore, MD.; Nossal Institute for Global Health, University of Melbourne, Melbourne, Australia.; Department of Family Medicine, School of Medicine, University of Pretoria, Pretoria, South Africa; and.; Department of Medicine, Division of Infectious Diseases, School of Medicine, University of Alabama at Birmingham, Birmingham, AL.; TB HIV Care, Cape Town, South Africa.; The Aurum Institute, Johannesburg, South Africa.; School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa.; Centre for Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.BACKGROUND: People in correctional settings are a key population for HIV epidemic control. We sought to demonstrate scale-up of universal test and treat in correctional facilities in South Africa and Zambia through a virtual cross-sectional analysis. METHODS: We used routine data on 2 dates: At the start of universal test and treat implementation (time 1, T1) and 1 year later (time 2, T2). We obtained correctional facility census lists for the selected dates and matched HIV testing and treatment data to generate virtual cross-sections of HIV care continuum indicators. RESULTS: In the South African site, there were 4193 and 3868 people in the facility at times T1 and T2; 43% and 36% were matched with HIV testing or treatment data, respectively. At T1 and T2, respectively, 1803 (43%) and 1386 (36%) had known HIV status, 804 (19%) and 845 (21%) were known to be living with HIV, and 60% and 56% of those with known HIV were receiving antiretroviral therapy (ART). In the Zambian site, there were 1467 and 1366 people in the facility at times T1 and T2; 58% and 92% were matched with HIV testing or treatment data, respectively. At T1 and T2, respectively, 857 (59%) and 1263 (92%) had known HIV status, 277 (19%) and 647 (47%) were known to be living with HIV, and 68% and 68% of those with known HIV were receiving ART. CONCLUSIONS: This virtual cross-sectional analysis identified gaps in HIV testing coverage, and ART initiation that was not clearly demonstrated by prior cohort-based studies.Item A Prospective Evaluation of the Diagnostic Accuracy of the Point-of-Care VISITECT CD4 Advanced Disease Test in 7 Countries.(2025-Feb-04) Gils T; Hella J; Jacobs BKM; Sossen B; Mukoka M; Muyoyeta M; Nakabugo E; Van Nguyen H; Ubolyam S; Macé A; Vermeulen M; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Denkinger CM; Nguyen NV; Avihingsanon A; Nakiyingi L; Székely R; Kerkhoff AD; MacPherson P; Meintjes G; Reither K; Ruhwald M; School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.; German Centre for Infection Research, Heidelberg University Hospital, Heidelberg, Germany.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; National Lung Hospital, Ha Noi, Viet Nam.; Taksin Hospital, Bangkok, Thailand.; Global Health Institute, University of Antwerp, Wilrijk, Belgium.; Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; University of Basel, Basel, Switzerland.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi.; Ifakara Health Institute, Dar es Salaam, Tanzania.; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California, San Francisco, San Francisco, California, USA.; Clinical Research Unit, Swiss Tropical and Public Health Institute, Allschwil, Switzerland.; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; HIV Netherlands Australia Thailand Research Collaboration, Thai Red Cross AIDS Research Centre and Center of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Foundation for Innovative New Diagnostics, the Global Alliance for Diagnostics, Geneva, Switzerland.; Clinical Research Department, London School of Hygiene and Tropical Medicine, London, United Kingdom.; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital and Faculty of Medicine, Heidelberg University, Heidelberg, Germany.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)BACKGROUND: CD4 measurement is pivotal in the management of advanced human immunodeficiency virus (HIV) disease. VISITECT CD4 Advanced Disease (VISITECT; AccuBio, Ltd) is an instrument-free, point-of-care, semiquantitative test allowing visual identification of CD4 ≤ 200 cells/µL or >200 cells/ µL from finger-prick or venous blood. METHODS: As part of a diagnostic accuracy study of FUJIFILM SILVAMP TB LAM, people with HIV ≥18 years old were prospectively recruited in 7 countries from outpatient departments if a tuberculosis symptom was present, and from inpatient departments. Participants provided venous blood for CD4 measurement using flow cytometry (reference standard) and finger-prick blood for VISITECT (index text), performed at point-of-care. Sensitivity, specificity, and positive and negative predictive values of VISITECT to determine CD4 ≤ 200 cells/ µL were evaluated. RESULTS: Among 1604 participants, the median flow cytometry CD4 was 367 cells/µL (interquartile range, 128-626 cells/µL) and 521 (32.5%) had CD4 ≤ 200 cells/µL. VISITECT sensitivity was 92.7% (483/521; 95% confidence interval [CI], 90.1%-94.7%) and specificity was 61.4% (665/1083; 95% CI, 58.4%-64.3%). For participants with CD4 0-100, 101-200, 201-300, 301-500, and >500 cells/µL, VISITECT misclassified 4.5% (95% CI, 2.5%-7.2%), 12.5 (95% CI, 8.0%-18.2%), 74.1% (95% CI, 67.0%-80.5%), 48.0% (95% CI, 42.5%-53.6%), and 22.6% (95% CI, 19.3%-26.3%), respectively. CONCLUSIONS: VISITECT's sensitivity, but not specificity, met the World Health Organization's minimal sensitivity and specificity threshold of 80% for point-of-care CD4 tests. VISITECT's quality needs to be assessed and its accuracy optimized. VISITECT's utility as CD4 triage test should be investigated. Clinical Trials Registration. NCT04089423.Item Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries.(2024) Codlin AJ; Vo LNQ; Garg T; Banu S; Ahmed S; John S; Abdulkarim S; Muyoyeta M; Sanjase N; Wingfield T; Iem V; Squire B; Creswell J; Stop TB Partnership, Geneva, Switzerland.; Liverpool School of Tropical Medicine, Liverpool, United Kingdom.; Karolinska Institutet, Stockholm, Sweden.; Liverpool University Hospitals NHS Foundation Trust, Liverpool, United Kingdom.; Janna Health Foundation, Yola, Nigeria.; icddr,b, Dhaka, Bangladesh.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; Friends for International TB Relief, Hanoi, Viet Nam.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)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.Item Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage.(2024-Oct) Geric C; Tavaziva G; Breuninger M; Dheda K; Esmail A; Scott A; Kagujje M; Muyoyeta M; Reither K; Khan AJ; Benedetti A; Ahmad Khan F; Tuberculosis Department, Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; IRD Global, Singapore.; Tuberculosis Department, Centre for Infectious Disease Research in Zambia, Lusaka, Zambia; Zambart, Lusaka, Zambia.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada. Electronic address: faiz.ahmadkhan@mcgill.ca.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada.; Centre for Lung Infection and Immunity Unit, Division of Pulmonology and UCT Lung Institute, University of Cape Town, Cape Town, South Africa.; Centre for Lung Infection and Immunity Unit, Division of Pulmonology and UCT Lung Institute, University of Cape Town, Cape Town, South Africa; Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.; Division of Infectious Diseases, Department I of Internal Medicine, University of Cologne, Cologne, Germany.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Canada.; Swiss Tropical and Public Health Institute, Allschwill, Switzerland; University of Basel, Basel, Switzerland.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)OBJECTIVES: Computer-aided detection (CAD) software packages quantify tuberculosis (TB)-compatible chest X-ray (CXR) abnormality as continuous scores. In practice, a threshold value is selected for binary CXR classification. We assessed the diagnostic accuracy of an alternative approach to applying CAD for TB triage: incorporating CAD scores in multivariable modeling. METHODS: We pooled individual patient data from four studies. Separately, for two commercial CAD, we used logistic regression to model microbiologically confirmed TB. Models included CAD score, study site, age, sex, human immunodeficiency virus status, and prior TB. We compared specificity at target sensitivities ≥90% between the multivariable model and the current threshold-based approach for CAD use. RESULTS: We included 4,733/5,640 (84%) participants with complete covariate data (median age 36 years; 45% female; 22% with prior TB; 22% people living with human immunodeficiency virus). A total of 805 (17%) had TB. Multivariable models demonstrated excellent performance (areas under the receiver operating characteristic curve [95% confidence interval]: software A, 0.91 [0.90-0.93]; software B, 0.92 [0.91-0.93]). Compared with threshold scores, multivariable models increased specificity (e.g., at 90% sensitivity, threshold vs model specificity [95% confidence interval]: software A, 71% [68-74%] vs 75% [74-77%]; software B, 69% [63-75%] vs 75% [74-77%]). CONCLUSION: Using CAD scores in multivariable models outperformed the current practice of CAD-threshold-based CXR classification for TB diagnosis.Item The accuracy of point-of-care C-Reactive Protein as a screening test for tuberculosis in children.(2024) Kagujje M; Nyangu S; Maimbolwa MM; Shuma B; Sanjase N; Chungu C; Kerkhoff AD; Creswell J; Muyoyeta M; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, California, United States of America.; Innovations and Grants, Stop TB Partnership, Geneva, Switzerland.; Tuberculosis Department, Centre of Infectious Disease Research in Zambia (CIDRZ), Lusaka, Zambia.; Zambia Paediatric Association, Lusaka, Zambia.Systematic screening for TB in children, especially among those at high risk of TB, can promote early diagnosis and treatment of TB. The World Health Organization (WHO) recently recommended C-Reactive Protein as a TB screening tool in adults and adolescents living with HIV (PLHIV). Thus, we aimed to assess the performance of point-of-care (POC) CRP as a screening tool for TB in children. A cross-sectional study was conducted at 2 primary health care facilities in Lusaka, Zambia between September 2020 -August 2021. Consecutive children (aged 5-14 years) presenting for TB services were enrolled irrespective of TB symptoms. All participants were screened for the presence of TB symptoms and signs, asked about TB contact history, and undertook a POC CRP test, chest X-ray, and sputum Xpert MTB/RIF Ultra test. The accuracy of CRP (≥10 mg/L cutoff) was determined using a microbiological reference standard (MRS) and a composite reference standard (CRS). Of 280 children enrolled and with complete results available, the median age was 10 years (IQR 7-12), 56 (20.0%) were HIV positive, 228 (81.4%) had a positive WHO symptom screen for TB, 62 (22.1%) had a close TB contact, and 79 (28.2%) had a positive CRP POC test. Five (1.8%) participants had confirmed TB, 71 (25.4%) had unconfirmed TB, and 204 (72.3%) had unlikely TB. When the MRS was used, the sensitivity of CRP was 80.0% (95%CI: 28.4-99.5%) and the specificity was 72.7% (95%CI: 67.1-77.9%). When the CRS was used, the sensitivity of CRP was 32.0% (95%CI: 23.3% - 42.5%), while the specificity was 74.0% (95%CI: 67.0% - 80.3%). Using the CRS, there were no statistically significant differences in sensitivity and specificity of CRP in the HIV positive and HIV negative individuals. Among children in Zambia, POC CRP had limited utility as a screening tool for TB. There remains a continued urgent need for better tools and strategies to improve TB detection in children.