Local information is needed to guide targeted interventions for respiratory infections such as tuberculosis (TB). Case notification rates (CNRs) are readily available, but systematically underestimate true disease burden in neighbourhoods with high diagnostic access barriers. We explored a novel approach, adjusting CNRs for under-notification (P:N ratio) using neighbourhood-level predictors of TB prevalence-to-notification ratios. We analysed data from 1) a citywide routine TB surveillance system including geolocation, confirmatory mycobacteriology, and clinical and demographic characteristics of all registering TB patients in Blantyre, Malawi during 2015–19, and 2) an adult TB prevalence survey done in 2019. In the prevalence survey, consenting adults from randomly selected households in 72 neighbourhoods had symptom-plus-chest X-ray screening, confirmed with sputum smear microscopy, Xpert MTB/Rif and culture. Bayesian multilevel models were used to estimate adjusted neighbourhood prevalence-to-notification ratios, based on summarised posterior draws from fitted adult bacteriologically-confirmed TB CNRs and prevalence. From 2015–19, adult bacteriologically-confirmed CNRs were 131 (479/371,834), 134 (539/415,226), 114 (519/463,707), 56 (283/517,860) and 46 (258/578,377) per 100,000 adults per annum, and 2019 bacteriologically-confirmed prevalence was 215 (29/13,490) per 100,000 adults. Lower educational achievement by household head and neighbourhood distance to TB clinic was negatively associated with CNRs. The mean neighbourhood P:N ratio was 4.49 (95% credible interval [CrI]: 0.98–11.91), consistent with underdiagnosis of TB, and was most pronounced in informal peri-urban neighbourhoods. Here we have demonstrated a method for the identification of neighbourhoods with high levels of under-diagnosis of TB without the requirement for a prevalence survey; this is important since prevalence surveys are expensive and logistically challenging. If confirmed, this approach may support more efficient and effective targeting of intensified TB and HIV case-finding interventions aiming to accelerate elimination of urban TB.

Background The prevalence of diseases other than tuberculosis (TB) detected during chest X‐ray screening is poorly described in sub‐Saharan Africa. Computer‐assisted digital chest X‐ray technology is available for TB screening and has the potential to be a screening tool for non‐communicable diseases as well. Low‐ and middle‐income countries are in a transition period where the burden of non‐communicable diseases is increasing, but health systems are mainly focused on addressing infectious diseases. Methods Participants were adults undergoing computer‐assisted chest X‐ray screening for tuberculosis in a community‐wide tuberculosis prevalence survey in Blantyre, Malawi. Adults with abnormal radiographs by field radiographer interpretation were evaluated by a physician in a community‐based clinic. X‐ray classifications were compared to classifications of a random sample of normal chest X‐rays by radiographer interpretation. Radiographic features were classified using WHO Integrated Management for Adult Illnesses (IMAI) guidelines. All radiographs taken at the screening tent were analysed by the Qure.ai qXR v2.0 software. Results 5% (648/13,490) of adults who underwent chest radiography were identified to have an abnormal chest X‐ray by the radiographer. 387 (59.7%) of the participants attended the X‐ray clinic, and another 387 randomly sampled normal X‐rays were available for comparison. Participants who were referred to the community clinic had a significantly higher HIV prevalence than those who had been identified to have a normal CXR by the field radiographer (90 [23.3%] vs. 43 [11.1%] p‐value < 0.001). The commonest radiographic finding was cardiomegaly (20.7%, 95% CI 18.0–23.7). One in five (81/387) chest X‐rays were misclassified by the radiographer. The overall mean Qure.ai qXR v2.0 score for all reviewed X‐rays was 0.23 (SD 0.20). There was a high concordance of cardiomegaly classification between the physician and the computer‐assisted software (109/118, 92.4%). Conclusion There is a high burden of cardiomegaly on a chest X‐ray at a community level, much of which is in patients with diabetes, heart disease and high blood pressure. Cardiomegaly on chest X‐ray may be a potential tool for screening for cardiovascular NCDs at the primary care level as well as in the community.

Background TB is a leading cause of morbidity among HIV positive individuals. Accurate algorithms are needed to achieve early TB diagnosis and treatment. We investigated the use of Xpert MTB/RIF Ultra in combination with chest radiography for TB diagnosis in ambulatory HIV positive individuals. Methods This was a randomised controlled trial with a 2-by-2 factorial design. Outpatient HIV clinic attendees with cough were randomised to four arms: Arm 1—Standard Xpert/no chest radiography (CXR); Arm 2—Standard Xpert/CXR; Arm 3—Xpert Ultra/no CXR; and Arm 4—Xpert Ultra/CXR. Participants were followed up at days 28 and 56 to assess for TB treatment initiation. Results We randomised 640 participants. Bacteriologically confirmed TB treatment initiation at day 28 were: Arm 1 (8.4% [14/162]), Arm 2 (6.9% [11/159]), Arm 3 (8.2% [13/159]) and Arm 4 (5.6% [9/160]) and between Xpert Ultra group (Arms 3 and 4) (6.9% [22/319]) vs Standard Xpert group (Arms 1 and 2) (7.8% [25/321]), risk ratio 0.89 (95% CI 0.51 to 1.54). By day 56, there were also similar all-TB treatment initiations in the x-ray group (Arms 2 and 4) (16.0% [51/319]) compared with the no x-ray group (Arms 1 and 3) (13.1% [42/321]), risk ratio 1.22 (95% CI 0.84 to 1.78); however, the contribution of clinically diagnosed treatment initiations were higher in x-ray groups (50.9% vs 19.0%). Conclusions Xpert Ultra performed similarly to Xpert MTB/RIF. X-rays are useful for TB screening but further research should investigate how to mitigate false-positive treatment initiations.

Background People living with HIV (PLHIV) have a high risk of death if hospitalised in low-income countries. Tuberculosis has long been the leading cause of admission and death, in part due to suboptimal diagnostics. Two promising new diagnostic tools are digital chest Xray with computer-aided diagnosis (DCXR-CAD) and urine testing with Fujifilm SILVAMP LAM (FujiLAM). Neither test has been rigorously evaluated among inpatients. Test characteristics may be complementary, with FujiLAM especially sensitive for disseminated tuberculosis and DCXR-CAD especially sensitive for pulmonary tuberculosis, making combined interventions of interest. Design and methods An exploratory unblinded, single site, two-arm cluster randomised controlled trial, with day of admission as the unit of randomisation. A third, smaller, integrated cohort arm (4:4:1 random allocation) contributes to understanding case-mix, but not trial outcomes. Participants are adults living with HIV not currently on TB treatment. The intervention (DCXR-CAD plus urine FujiLAM plus usual care) is compared to usual care alone. The primary outcome is proportion of participants started on tuberculosis treatment by day 56, with secondary outcomes of mortality (time to event) measured to to 56 days from enrolment, proportions with undiagnosed tuberculosis at death or hospital discharge and comparing proportions with enrolment-day tuberculosis treatment initiation. Discussion Both DCXR-CAD and FujiLAM have potential clinical utility and may have complementary diagnostic performance. To our knowledge, this is the first randomised trial to evaluate these tests among hospitalised PLHIV.