Tuberculosis prevalence after 4 years of population-wide systematic TB symptom screening and universal testing and treatment for HIV in the HPTN 071 (PopART) community-randomised trial in Zambia and South Africa: A cross-sectional survey (TREATS).

BACKGROUND: Tuberculosis (TB) prevalence remains persistently high in many settings, with new or expanded interventions required to achieve substantial reductions. The HIV Prevention Trials Network (HPTN) 071 (PopART) community-randomised trial randomised 14 communities to receive the "PopART" intervention during 2014 to 2017 (7 arm A and 7 arm B communities) and 7 communities to receive standard-of-care (arm C). The intervention was delivered door-to-door by community HIV care providers (CHiPs) and included universal HIV testing, facilitated linkage to HIV care at government health clinics, and systematic TB symptom screening. The Tuberculosis Reduction through Expanded Anti-retroviral Treatment and Screening (TREATS) study aimed to measure the impact of delivering the PopART intervention on TB outcomes, in communities with high HIV and TB prevalence. METHODS AND FINDINGS: The study population of the HPTN 071 (PopART) trial included individuals aged ≥15 years living in 21 urban and peri-urban communities in Zambia and South Africa, with a total population of approximately 1 million and an adult HIV prevalence of around 15% at the time of the trial. Two sputum samples for TB testing were provided to CHiPs by individuals who reported ≥1 TB suggestive symptom (a cough for ≥2 weeks, unintentional weight loss ≥1.5 kg in the last month, or current night sweats) or that a household member was currently on TB treatment. Antiretroviral therapy (ART) was offered universally at clinics in arm A and according to local guidelines in arms B and C. The TREATS study was conducted in the same 21 communities as the HPTN 071 (PopART) trial between 2017 and 2022, and TB prevalence was a co-primary endpoint of the TREATS study. The primary comparison was between the PopART intervention (arms A and B combined) and the standard-of-care (arm C). During 2019 to 2021, a TB prevalence survey was conducted among randomly selected individuals aged ≥15 years (approximately 1,750 per community in arms A and B, approximately 3,500 in arm C). Participants were screened on TB symptoms and chest X-ray, with diagnostic testing using Xpert-Ultra followed by culture for individuals who screened positive. Sputum eligibility was determined by the presence of a cough for ≥2 weeks, or ≥2 of 5 "TB suggestive" symptoms (cough, weight loss for ≥4 weeks, night sweats, chest pain, and fever for ≥2 weeks), or chest X-ray CAD4TBv5 score ≥50, or no available X-ray results. TB prevalence was compared between trial arms using standard methods for cluster-randomised trials, with adjustment for age, sex, and HIV status, and multiple imputation was used for missing data on prevalent TB. Among 83,092 individuals who were eligible for the survey, 49,556 (59.6%) participated, 8,083 (16.3%) screened positive, 90.8% (7,336/8,083) provided 2 sputum samples for Xpert-Ultra testing, and 308 (4.2%) required culture confirmation. Overall, estimated TB prevalence was 0.92% (457/49,556). The geometric means of 7 community-level prevalence estimates were 0.91%, 0.70%, and 0.69% in arms A, B, and C, respectively, with no evidence of a difference comparing arms A and B combined with arm C (adjusted prevalence ratio 1.14, 95% confidence interval, CI [0.67, 1.95], p = 0.60). TB prevalence was higher among people living with HIV than HIV-negative individuals, with an age-sex-community adjusted odds ratio of 2.29 [95% CI 1.54, 3.41] in Zambian communities and 1.61 [95% CI 1.13, 2.30] in South African communities. The primary limitations are that the study was powered to detect only large reductions in TB prevalence in the intervention arm compared with standard-of-care, and the between-community variation in TB prevalence was larger than anticipated. CONCLUSIONS: There was no evidence that the PopART intervention reduced TB prevalence. Systematic screening for TB that is based on symptom screening alone may not be sufficient to achieve a large reduction in TB prevalence over a period of several years. Including chest X-ray screening alongside TB symptom screening could substantially increase the sensitivity of systematic screening for TB. TRIAL REGISTRATION: The TREATS study was registered with ClinicalTrials.gov Identifier: NCT03739736 on November 14, 2018. The HPTN 071 (PopART) trial was registered at ClinicalTrials.gov under number NCT01900977 on July 17, 2013.

Assessment of non-tuberculosis abnormalities on digital chest x-rays with high CAD4TB scores from a tuberculosis prevalence survey in Zambia and South Africa.

BACKGROUND: Chest X-rays (CXRs) have traditionally been used to aid the diagnosis of TB-suggestive abnormalities. Using Computer-Aided Detection (CAD) algorithms, TB risk is quantified to assist with diagnostics. However, CXRs capture all other structural abnormalities. Identification of non-TB abnormalities in individuals with CXRs that have high CAD scores but don't have bacteriologically confirmed TB is unknown. This presents a missed opportunity of extending novel CAD systems' potential to simultaneously provide information on other non-TB abnormalities alongside TB. This study aimed to characterize and estimate the prevalence of non-TB abnormalities on digital CXRs with high CAD4TB scores from a TB prevalence survey in Zambia and South Africa. METHODOLOGY: This was a cross-sectional analysis of clinical data of participants from the TREATS TB prevalence survey conducted in 21 communities in Zambia and South Africa. The study included individuals aged ≥ 15 years who had high CAD4TB scores (score ≥ 70), but had no bacteriologically confirmed TB in any of the samples submitted, were not on TB treatment, and had no history of TB. Two consultant radiologists reviewed the images for non-TB abnormalities. RESULTS: Of the 525 CXRs reviewed, 46.7% (245/525) images were reported to have non-TB abnormalities. About 11.43% (28/245) images had multiple non-TB abnormalities, while 88.67% (217/245) had a single non-TB abnormality. The readers had a fair inter-rater agreement (r = 0.40). Based on anatomical location, non-TB abnormalities in the lung parenchyma (19%) were the most prevalent, followed by Pleura (15.4%), then heart & great vessels (6.1%) abnormalities. Pleural effusion/thickening/calcification (8.8%) and cardiomegaly (5%) were the most prevalent non-TB abnormalities. Prevalence of (2.7%) for pneumonia not typical of pulmonary TB and (2.1%) mass/nodules (benign/ malignant) were also reported. CONCLUSION: A wide range of non-TB abnormalities can be identified on digital CXRs among individuals with high CAD4TB scores but don't have bacteriologically confirmed TB. Adaptation of AI systems like CAD4TB as a tool to simultaneously identify other causes of abnormal CXRs alongside TB can be interesting and useful in non-faculty-based screening programs to better link cases to appropriate care.

Community- and individual-level correlates of HIV incidence in HPTN 071 (PopART).

INTRODUCTION: Universal HIV testing and treatment aims to identify all people living with HIV and offer them treatment, decreasing the number of individuals with unsuppressed HIV and thus reducing HIV transmission. Longitudinal follow-up of individuals with and without HIV in a cluster-randomized trial of communities allowed for the examination of community- and individual-level measures of HIV risk and HIV incidence. METHODS: HPTN 071 (PopART) was a three-arm cluster-randomized trial conducted between 2013 and 2018 that evaluated the use of two combination HIV prevention strategies implemented at the community level to reduce HIV incidence compared to the standard of care. The trial, conducted in 21 communities in Zambia and South Africa, measured HIV incidence over 36 months in a population cohort of ∼2000 randomly selected adults per community aged 18-44. Multilevel models were used to assess the association between HIV incidence and community- and individual-level socio-demographic and behavioural risk factors, as well as prevalence of detectable virus (PDV) defined as the estimated proportion of the community with unsuppressed viral load. RESULTS: Overall HIV incidence was 1.49/100 person-years. Communities with less financial wealth and communities with more individuals reporting having sex partners outside of the community or two or more sexual partners had higher HIV incidence. PDV at 2 years of study was 6.8% and was strongly associated with HIV incidence: for every 50% relative reduction in community PDV, there was a 49% (95% confidence interval [CI]: 37%-58%, p < 0.001) relative decrease in HIV incidence. At the individual level; socio-economic status, AUDIT score, medical male circumcision and certain sexual behaviours were associated with HIV risk. CONCLUSIONS: Using data from the PopART randomized trial, we found several associations of HIV incidence with community-level measures reflecting the sexual behaviour and socio-economic make-up of each community. We also found a strong association between community PDV and HIV incidence supporting the use of PDV as a tool for monitoring progress in controlling the epidemic. Lastly, we found significant individual-level factors of HIV risk that are generally consistent with previous HIV epidemiological research. These results have the potential to identify high high-incidence communities, inform structural-level interventions, and optimize individual-level interventions for HIV prevention. CLINICAL TRIAL NUMBER: ClinicalTrials.gov number, NCT01900977, HPTN 071 [PopArt].

Creating access to SARS-CoV-2 screening and testing through community-based COVID-19 case-finding, observations from cross-sectional studies in Lesotho and Zambia.

BACKGROUND: The health impact of the COVID-19 pandemic largely depends on the ability of the healthcare systems to develop effective and adaptable preparedness and mitigation strategies. A collaborative initiative (BRCCH-EDCTP COVID-19 Initiative) was set up between Lesotho and Zambia early on in the pandemic, to jointly conduct a project to investigate creating access to SARS-CoV-2 screening and testing through community-based COVID-19 case-finding. METHODS: Two different community case-finding strategies were deployed. In Lesotho, an approach was implemented whereby a community (village) health worker screened community members at their home or during community gatherings for COVID-19 signs and symptoms. All community members who screened positive were then offered SARS-CoV-2 testing. In Zambia, so-called community hubs, staffed by community health care workers, were set up at different locations in the community for people to walk in and get tested for SARS-CoV-2. Hubs changed location from week-to-week and targeted transmission hotspots. All persons visiting the hubs were offered testing for SARS-CoV-2 irrespective of self-reported signs and symptoms of COVID-19 though information was collected on occurrence of these. Testing in both approaches was done using SARS-CoV-2 rapid antigen tests. RESULTS: Setting up testing in the community setting was feasible in both countries. In Lesotho in the village health worker approach, over a period of 46 weeks, 7221 persons were screened, and 49 (11.4%) SARS-COV-2 cases identified among 428 COVID-19 screen positive participants. In the community hubs among 3150 people tested, 166 (5.3%) SARS-CoV-2 cases were identified in a period of 26 weeks. From the community hubs approach, where all seen were offered COVID-19 testing it was learned that people screening positive for COVID-19 signs and symptoms were more likely to test SARS-COV-2 positive, especially those reporting classic COVID-19 symptoms like loss of sense/smell for a short period of time (1-3 days). CONCLUSIONS: In conclusion, in this project we learned that implementing COVID-19 screening and testing by lay health workers in the community is possible. Characteristics of the population screened, tested, and identified to have SARS-CoV-2 are described to help guide development of future testing strategies.

Impact of universal testing and treatment on sexual risk behaviour and herpes simplex virus type 2: a prespecified secondary outcomes analysis of the HPTN 071 (PopART) community-randomised trial.

BACKGROUND: Comprehensive HIV prevention strategies have raised concerns that knowledge of interventions to reduce risk of HIV infection might mitigate an individual's perception of risk, resulting in riskier sexual behaviour. We investigated the prespecified secondary outcomes of the HPTN 071 (PopART) trial to determine whether a combination HIV prevention strategy, including universal HIV testing and treatment, changed sexual behaviour; specifically, we investigated whether there was evidence of sexual risk compensation. METHODS: HPTN 071 (PopART) was a cluster-randomised trial conducted during 2013-18, in which we randomly assigned 21 communities with high HIV prevalence in Zambia and South Africa (total population, approximately 1 million) to combination prevention intervention with universal antiretroviral therapy (ART; arm A), prevention intervention with ART provided according to local guidelines (universal since 2016; arm B), or standard of care (arm C). The trial included a population cohort of approximately 2000 randomly selected adults (aged 18-44 years) in each community (N=38 474 at baseline) who were followed up for 36 months. A prespecified secondary objective was to evaluate the impact of the PopART intervention compared with standard of care on herpes simplex virus type 2 (HSV-2) and sexual behaviour (N=20 422 completed final visit). Secondary endpoints included differences in sexual risk behaviour measures at 36 months and were assessed using a two-stage method for matched cluster-randomised trials. This trial is registered with ClinicalTrials. gov, number NCT01900977. FINDINGS: The PopART intervention did not substantially change probability of self-reported multiple sex partners, sexual debut, or pregnancy in women at 36 months. Adjusted for baseline community prevalence, reported condomless sex was significantly lower in arm A versus arm C (adjusted prevalence ratio 0·80 [95% CI 0·64-0·99]; p=0·04) but not in arm B versus arm C (0·94 [0·76-1·17]; p=0·55). 3-year HSV-2 incidence was reduced in arm B versus arm C (adjusted risk ratio 0·76 [95% CI 0·63-0·92]; p=0·010); no significant change was shown between arm A versus arm C (0·89 [0·73-1·08]; p=0·199). INTERPRETATION: We found little evidence of any change in sexual behaviour owing to the PopART interventions, and reassuringly for public health, we saw no evidence of sexual risk compensation. The findings do not help to explain the differences between the two intervention groups of the HPTN 071 (PopART) trial. FUNDING: National Institute of Allergy and Infectious Diseases, the National Institutes of Health, the International Initiative for Impact Evaluation (3ie), the Bill & Melinda Gates Foundation, the US President's Emergency Plan for AIDS Relief, and the Medical Research Council UK.

Diagnosis of rifampicin-resistant tuberculosis: Discordant results by diagnostic methods.

The performance of the Xpert© MTB/RIF and MTBDRplus assays for the detection of rifampicin resistant Mycobacterium tuberculosis was compared to culture-based drug susceptibility testing in 30 specimens with rifampicin-resistant and rifampicin-indeterminate Xpert MTB/RIF results collected between March 2012 and March 2014. Xpert MTB/RIF and MTBDRplus were 100% sensitive and 100% concordant for rifampicin resistance detection, but 3 of 13 samples (23%) positive for rifampicin resistance on Xpert MTB/RIF and MTBDRplus were negative for rifampicin resistance on mycobacteria growth indicator tube drug susceptibility testing. Specificity was 72% for Xpert MTB/RIF and 80% for MTBDRplus. Positive predictive value for Xpert MTB/RIF for multidrug resistant tuberculosis was 47.8% for new patients and 77.8% for previously treated patients; negative predictive value was 100% for both new and previously treated patients. The discordant rifampicin resistance test results indicate a need to fully characterise circulating rifampicin resistant Mycobacterium tuberculosis strains in Zambia and to inform the development of guidelines for decision-making in relation to diagnosis of drug-resistant tuberculosis.

Digital CXR with computer aided diagnosis versus symptom screen to define presumptive tuberculosis among household contacts and impact on tuberculosis diagnosis.

BACKGROUND: Household (HH) contact tracing is a strategy that targets high risk groups for TB. Symptom based screening is the standard used to identify HH contacts at risk for TB during HH contact tracing for TB. However, this strategy may be limited due to poor performance in predicting TB. The objective of this study was to compare CXR with Computer Aided Diagnosis (CAD) against symptom screen for defining presumptive TB and how TB detection changes with each method. METHODS: Household contacts of consecutive index bacteriologically confirmed TB cases were visited by study teams and given TB/HIV education to raise awareness of the risk of TB following close contact with a TB patient. Contacts were encouraged to visit the health facility for screening; where symptoms history was obtained and opt out HIV testing was provided as part of the screening process. CXR was offered to all regardless of symptoms, followed by definitive sputum test with either Xpert MTB RIF or smear microscopy. RESULTS: Among 919 HH contacts that presented for screening, 865 were screened with CXR and 464 (53.6%) had an abnormal CXR and the rest had a normal CXR. Among 444 HH contacts with valid sputum results, 274 (61.7%) were symptom screen positive and 255 (57.4%) had an abnormal CXR. Overall, TB was diagnosed in 32/444 (7.2%); 13 bacteriologically unconfirmed and 19 bacteriologically confirmed. Of 19 bacteriologically confirmed TB 8 (42.1%) were symptom screen negative contacts with an abnormal CXR and these 6/8 (75.0%) were HIV positive. Among the 13 bacteriologically unconfirmed TB cases, 7 (53.8%) were HIV positive and all had an abnormal CXR. CONCLUSION: Symptom screen if used alone with follow on definitive TB testing only for symptom screen positive individuals would have missed eight of the 19 confirmed TB cases detected in this study. There is need to consider use of other screening strategies apart from symptom screen alone for optimal rule out of TB especially in HIV positive individuals that are at greatest risk of TB and present atypically.

Implementation Research to Inform the Use of Xpert MTB/RIF in Primary Health Care Facilities in High TB and HIV Settings in Resource Constrained Settings.

BACKGROUND: The current cost of Xpert MTB RIF (Xpert) consumables is such that algorithms are needed to select which patients to prioritise for testing with Xpert. OBJECTIVE: To evaluate two algorithms for prioritisation of Xpert in primary health care settings in a high TB and HIV burden setting. METHOD: Consecutive, presumptive TB patients with a cough of any duration were offered either Xpert or Fluorescence microscopy (FM) test depending on their CXR score or HIV status. In one facility, sputa from patients with an abnormal CXR were tested with Xpert and those with a normal CXR were tested with FM ("CXR algorithm"). CXR was scored automatically using a Computer Aided Diagnosis (CAD) program. In the other facility, patients who were HIV positive were tested using Xpert and those who were HIV negative were tested with FM ("HIV algorithm"). RESULTS: Of 9482 individuals pre-screened with CXR, Xpert detected TB in 2090/6568 (31.8%) with an abnormal CXR, and FM was AFB positive in 8/2455 (0.3%) with a normal CXR. Of 4444 pre-screened with HIV, Xpert detected TB in 508/2265 (22.4%) HIV positive and FM was AFB positive in 212/1920 (11.0%) in HIV negative individuals. The notification rate of new bacteriologically confirmed TB increased; from 366 to 620/ 100,000/yr and from 145 to 261/100,000/yr at the CXR and HIV algorithm sites respectively. The median time to starting TB treatment at the CXR site compared to the HIV algorithm site was; 1(IQR 1-3 days) and 3 (2-5 days) (p<0.0001) respectively. CONCLUSION: Use of Xpert in a resource-limited setting at primary care level in conjunction with pre-screening tests reduced the number of Xpert tests performed. The routine use of Xpert resulted in additional cases of confirmed TB patients starting treatment. However, there was no increase in absolute numbers of patients starting TB treatment. Same day diagnosis and treatment commencement was achieved for both bacteriologically confirmed and empirically diagnosed patients where Xpert was used in conjunction with CXR.

The sensitivity and specificity of using a computer aided diagnosis program for automatically scoring chest X-rays of presumptive TB patients compared with Xpert MTB/RIF in Lusaka Zambia.

OBJECTIVE: To determine the sensitivity and specificity of a Computer Aided Diagnosis (CAD) program for scoring chest x-rays (CXRs) of presumptive tuberculosis (TB) patients compared to Xpert MTB/RIF (Xpert). METHOD: Consecutive presumptive TB patients with a cough of any duration were offered digital CXR, and opt out HIV testing. CXRs were electronically scored as normal (CAD score ≤ 60) or abnormal (CAD score > 60) using a CAD program. All patients regardless of CAD score were requested to submit a spot sputum sample for testing with Xpert and a spot and morning sample for testing with LED Fluorescence Microscopy-(FM). RESULTS: Of 350 patients with evaluable data, 291 (83.1%) had an abnormal CXR score by CAD. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of CXR compared to Xpert were 100% (95%CI 96.2-100), 23.2% (95%CI 18.2-28.9), 33.0% (95%CI 27.6-38.7) and 100% (95% 93.9-100), respectively. The area under the receiver operator curve (AUC) for CAD was 0.71 (95%CI 0.66-0.77). CXR abnormality correlated with smear grade (r = 0.30, p<0.0001) and with Xpert CT(r = 0.37, p<0.0001). CONCLUSIONS: To our knowledge this is the first time that a CAD program for TB has been successfully tested in a real world setting. The study shows that the CAD program had high sensitivity but low specificity and PPV. The use of CAD with digital CXR has the potential to increase the use and availability of chest radiography in screening for TB where trained human resources are scarce.

Application of balanced scorecard in the evaluation of a complex health system intervention: 12 months post intervention findings from the BHOMA intervention: a cluster randomised trial in Zambia.

INTRODUCTION: In many low income countries, the delivery of quality health services is hampered by health system-wide barriers which are often interlinked, however empirical evidence on how to assess the level and scope of these barriers is scarce. A balanced scorecard is a tool that allows for wider analysis of domains that are deemed important in achieving the overall vision of the health system. We present the quantitative results of the 12 months follow-up study applying the balanced scorecard approach in the BHOMA intervention with the aim of demonstrating the utility of the balanced scorecard in evaluating multiple building blocks in a trial setting. METHODS: The BHOMA is a cluster randomised trial that aims to strengthen the health system in three rural districts in Zambia. The intervention aims to improve clinical care quality by implementing practical tools that establish clear clinical care standards through intensive clinic implementations. This paper reports the findings of the follow-up health facility survey that was conducted after 12 months of intervention implementation. Comparisons were made between those facilities in the intervention and control sites. STATA version 12 was used for analysis. RESULTS: The study found significant mean differences between intervention(I) and control (C) sites in the following domains: Training domain (Mean I:C; 87.5.vs 61.1, mean difference 23.3, p = 0.031), adult clinical observation domain (mean I:C; 73.3 vs.58.0, mean difference 10.9, p = 0.02 ) and health information domain (mean I:C; 63.6 vs.56.1, mean difference 6.8, p = 0.01. There was no gender differences in adult service satisfaction. Governance and motivation scores did not differ between control and intervention sites. CONCLUSION: This study demonstrates the utility of the balanced scorecard in assessing multiple elements of the health system. Using system wide approaches and triangulating data collection methods seems to be key to successful evaluation of such complex health intervention. TRIAL NUMBER: ClinicalTrials.gov NCT01942278.

Sensitivity, specificity, and reproducibility of the Capilia TB-Neo assay.

The performance of the Capilia TB-Neo assay, a new-generation assay, was assessed by determining its sensitivity, specificity, reproducibility, and cross-reaction with contaminating organisms. The sensitivity and specificity were 99.2 and 96.4% and 89.3 and 100% in pure and mixed-culture isolates, respectively. The kappa statistic was 95.0 and 77.9% in pure and mixed culture isolates, respectively. There was no cross-reaction with contaminating organisms.

Measuring health system strengthening: application of the balanced scorecard approach to rank the baseline performance of three rural districts in Zambia.

INTRODUCTION: There is growing interest in health system performance and recently WHO launched a report on health systems strengthening emphasising the need for close monitoring using system-wide approaches. One recent method is the balanced scorecard system. There is limited application of this method in middle- and low-income countries. This paper applies the concept of balanced scorecard to describe the baseline status of three intervention districts in Zambia. METHODOLOGY: The Better Health Outcome through Mentoring and Assessment (BHOMA) project is a randomised step-wedged community intervention that aims to strengthen the health system in three districts in the Republic of Zambia. To assess the baseline status of the participating districts we used a modified balanced scorecard approach following the domains highlighted in the MOH 2011 Strategic Plan. RESULTS: Differences in performance were noted by district and residence. Finance and service delivery domains performed poorly in all study districts. The proportion of the health workers receiving training in the past 12 months was lowest in Kafue (58%) and highest in Luangwa district (77%). Under service capacity, basic equipment and laboratory capacity scores showed major variation, with Kafue and Luangwa having lower scores when compared to Chongwe. The finance domain showed that Kafue and Chongwe had lower scores (44% and 47% respectively). Regression model showed that children's clinical observation scores were negatively correlated with drug availability (coeff -0.40, p = 0.02). Adult clinical observation scores were positively association with adult service satisfaction score (coeff 0.82, p = 0.04) and service readiness (coeff 0.54, p = 0.03). CONCLUSION: The study applied the balanced scorecard to describe the baseline status of 42 health facilities in three districts of Zambia. Differences in performance were noted by district and residence in most domains with finance and service delivery performing poorly in all study districts. This tool could be valuable in monitoring and evaluation of health systems.