Tuberculosis (TB) remains a significant public health challenge in many African communities, where underreporting and underdiagnosis are prevalent due to barriers in accessing care and inadequate diagnostic tools. This is particularly concerning in hard-to-reach areas with a high burden of TB/HIV co-infection, where missed or delayed diagnoses exacerbate disease transmission, increase mortality and lead to severe economic and health consequences. To address these challenges, it is crucial to evaluate innovative, cost-effective, community-based screening strategies that can improve early detection and linkage to care.

We conduct a prospective, community-based, diagnostic, pragmatic trial in communities of the Butha Buthe District in Lesotho and the Greater Edendale area of Msunduzi Municipality, KwaZulu-Natal in South Africa to compare two strategies for population-based TB screening: computer-aided detection (CAD) technology alone (CAD4TBv7 approach) versus CAD combined with point-of-care C reactive protein (CRP) testing (CAD4TBv7-CRP approach). Following a chest X-ray, CAD produces an abnormality score, which indicates the likelihood of TB. Score thresholds informing the screening logic for both approaches were determined based on the WHO’s target product profile for a TB screening test. CAD scores above a threshold prespecified for the CAD4TBv7 approach indicate confirmatory testing for TB (Xpert MTB/RIF Ultra). For the CAD4TBv7-CRP approach, a CAD score within a predefined window requires the conduct of the second screening test, CRP, while a score above the respective upper threshold is followed by Xpert MTB/RIF Ultra. A CRP result above the selected cut-off also requires a confirmatory TB test. Participants with CAD scores below the (lower) threshold and those with CRP levels below the cut-off are considered screen-negative. The trial aims to compare the yield of detected TB cases and cost-effectiveness between two screening approaches by applying a paired screen-positive design. 20 000 adult participants will be enrolled and will receive a posterior anterior digital chest X-ray which is analysed by CAD software.

The protocol was approved by National Health Research Ethics Committee in Lesotho (NH-REC, ID52-2022), the Human Sciences Research Council Research Ethics Committee (HSRC REC, REC 2/23/09/20) and the Provincial Health Research Committee of the Department of Health of KwaZulu-Natal (KZ_202209_022) in South Africa and from the Swiss Ethics Committee Northwest and Central Switzerland (EKNZ, AO_2022–00044). This manuscript is based on protocol V.4.0, 19 January 2024. Trial findings will be disseminated through peer-reviewed publications, conference presentations and through communication offices of the consortium partners and the project’s website (https://tbtriage.com/).

ClinicalTrials.gov (NCT05526885), South African National Clinical Trials Register (SANCTR; DOH-27-092022-8096).

Minority ethnic groups disproportionately experienced adverse COVID-19 outcomes, partly a consequence of disproportionate exposure to socioeconomic disadvantage and high-risk occupations. We examined whether minority ethnic groups were also disproportionately vulnerable to the consequences of socioeconomic disadvantage and high-risk occupations in Scotland.

We investigated effect modification and interaction between area deprivation, education and occupational risk and ethnicity (assessed as both a binary white vs non-white variable and a multi-category variable) in relation to severe COVID-19 (hospitalisation or death). We used electronic health records linked to the 2011 census and Cox proportional hazards models, adjusting for age, sex and health board. We were principally concerned with additive interactions as a measure of vulnerability, estimated as the relative excess risk due to interaction (RERI).

Analyses considered 3 730 837 individuals aged ≥16 years (with narrower age ranges for analyses focused on education and occupation). Severe COVID-19 risk was typically higher for minority ethnic groups and disadvantaged socioeconomic groups, but additive interactions were not consistent. For example, non-white ethnicity and highest deprivation level experienced elevated risk ((HR=2.7, 95% CI: 2.4, 3.2) compared with the white least deprived group. Additive interaction was not present (RERI=–0.1, 95% CI: –0.4, 0.2), this risk being less than the sum of risks of white ethnicity/highest deprivation level (HR=2.4, 95% CI: 2.3, 2.5) and non-white ethnicity/lowest deprivation level (1.4, 95% CI: 1.2, 1.7). Similarly, non-white ethnicity/no degree education (HR=2.5, 95% CI: 2.2, 2.7; RERI=–0.1, 95% CI: –0.4, 0.2) and non-white ethnicity/high-risk occupation (RERI=0.3, 95% CI: –0.2, 0.8) did not experience greater than additive risk. No clear evidence of effect modification was identified when using the multicategory ethnicity variable or on the multiplicative scale either.

We found no definitive evidence that minority ethnic groups were more vulnerable to the effect of social disadvantage on the risk of severe COVID-19.