No abstract

The study aim was to determine the association of a one United States dollar (USD) dollar incentive and tuberculosis (TB) treatment outcomes among people with TB receiving treatment at a rural hospital in Uganda under programmatic settings. We conducted a quasi-experiment in which people with TB were randomised (1:1 ratio) to receive either a one USD incentive at months 0, 2, 5 and 6 (Dollar arm) or routine care (Routine arm). A second control group (Retrospective controls) consisted of participants who had a treatment outcome in the preceding 6 months. Treatment outcomes were compared between the intervention and control groups using Pearson’s chi-square and Fisher’s exact tests. The association between the incentive and treatment outcomes was determined using Poisson regression analysis with robust variances. Between November 2018 and October 2019, we enrolled 180 participants (60 in the Dollar arm and 120 in the Control group). TB cure (33.3% vs. 20.8%, p = 0.068) and treatment success (70.0% vs. 59.2% p = 0.156) were higher in the Dollar arm than the Control group, while loss-to-follow-up was lower in the Dollar arm (10.0% vs. 20.8% p = 0.070). Participants in the Dollar arm were more likely to be cured (adjusted incidence rate ratio (aIRR): 1.59, 95% CI 1.04–2.44, p = 0.032) and less likely to be lost to follow-up (aIRR: 0.44, 95% CI 0.20–0.96, p = 0.040). A one-dollar incentive was associated with higher TB cure and lower loss-to-follow-up among people with TB in rural Uganda.

Individuals found at bars in slums have several risk factors for HIV and tuberculosis (TB). To determine the prevalence of HIV and TB among individuals found at bars in slums of Kampala, Uganda, we enrolled adults found at bars that provided written informed consent. Individuals with alcohol intoxication were excluded. We performed HIV testing using immunochromatographic antibody tests (Alere Determine HIV-1/2 and Chembio HIV 1/2 STAT-PAK). TB was confirmed using the Xpert MTB/ RIF Ultra assay, performed on single spot sputum samples. We enrolled 272 participants from 42 bars in 5 slums. The prevalence of HIV and TB was 11.4% (95% CI 8.1-15.8) and 15 (95% CI 6-39) per 1,000 population respectively. Predictors of HIV were female sex (aOR 5.87, 95% CI 2.05-16.83), current cigarette smoking (aOR 3.23, 95% CI 1.02-10.26), history of TB treatment (aOR 10.19, 95% CI 3.17-32.82) and CAGE scores of 2-3 (aOR 3.90, 95% CI 1.11-13.70) and 4 (aOR 4.77, 95% CI 1.07-21.35). The prevalence of HIV and TB was twice and four times the national averages respectively. These findings highlight the need for concurrent programmatic screening for both HIV and TB among high risk populations in slums. HIV and tuberculosis (TB) interact at an epidemiological, clinical, cellular, and molecular level to create a coepidemic 1. In 2018, HIV contributed 251,000 of the 1.2 million TB deaths while TB was the leading cause of death among HIV positive individuals 2,3. Notwithstanding, an estimated 3 million TB cases were missed in 2018 and only 79% of HIV-positive individuals knew their HIV status 2,3. To increase the detection of TB and HIV, it is important to target high risk and vulnerable populations through active community based screening strategies 4-6. Slum dwellers have a higher risk for HIV, TB and HIV/TB co-infection than the national averages 7,8. However, slum dwellers are less likely to utilise health services for HIV and TB diagnosis and have a low level of knowledge regarding prevention strategies for either disease 9,10. The low utilisation is partly attributed to the perceived poor quality of services at public facilities and thus high risk groups are not covered by facility based screening strategies 11,12. Within slum settlements, bars and social drinking places carry the highest risk for TB transmission than other social gathering places such as churches, clinics, hospitals, taxis, community halls, schools, and supermarkets 13-16. As such, bars and social alcohol drinking groups are avenues for TB transmission to bar customers, employees and neighbours, and they propagate outbreaks from an index case 17-21. Moreover, alcohol consumption is an established risk factor for tuberculosis in a dose dependent fashion, and exacerbates TB infection by blunting CD4 and CD8 T-lymphocyte cellular responses 22,23 .

Background Undernutrition is associated with unfavourable treatment outcomes among people with drug-resistant tuberculosis (DRTB). Factors influencing the treatment outcomes among undernourished people with DRTB are not well characterised. The aim of this study was to determine factors associated with treatment success among undernourished people with DRTB in Uganda. Methods We analysed data from a retrospective cohort of people with DRTB from 16 treatment sites in Uganda. We included participants with a pre-treatment body mass index (BMI) of <18.5 kilograms/meters 2 (kg/m 2 ). Participants were categorised as having mild (BMI of 18.5–17 kg/m 2 ), moderate (BMI of 16.9–16.0 kg/m 2 ) or severe (BMI of <16.0 kg/m 2 ) undernutrition. We performed logistic regression analysis to determine factors associated with treatment success. Results Among 473 people with DRTB, 276 (58.4%) were undernourished (BMI < 18.5 Kg/m 2 ) and were included in the study. Of these, 92 (33.3%) had mild, 69 (25.0%) had moderate and 115 (41.7%) had severe undernutrition. The overall treatment success rate (TSR) for the undernourished was 71.4% (n = 197). Although the TSR was similar among participants with mild (71.7%), moderate (78.3%) and severe (67.0%) undernutrition (p = 0.258), all treatment failure cases (n =6) were among participants with severe undernutrition (p = 0.010). Cigarette smoking (odds ratio (OR) = 0.19, 95% CI 0.07–0.47, p < 0.001), urban residence (OR = 0.31, 95% CI 0.14–0.70, p = 0.005) and moderate (OR = 0.14, 95% CI 0.06–0.35, p < 0.001) and severe anaemia (OR = 0.06, 95% CI 0.01–0.29, p = 0.001) were associated with lower odds of treatment success. Conclusion Most undernourished people with DRTB have severe undernutrition. Smoking and anaemia are modifiable factors which upon appropriate intervention could improve treatment success. The effect of urban residence on the TSR needs to be evaluated further.

There is limited information on microbiota dynamics in tuberculosis (TB) in Africa. Here, we investigated changes in microbiota composition, abundance, co-occurrence and community remodelling relative to clinical parameters, among treatment-naive pulmonary TB patients at Mulago National Referral Hospital in Kampala, Uganda. We sequenced 205 sputum samples from 120 patients before initiating anti-TB therapy (baseline) and during treatment follow-up (at months 2 and 5). A total of 8.6 million high quality sequences were generated, yielding 8,180 operational taxonomic units (OTUs), 18 phyla and 333 genera. A sputum sample on average generated 44,992 sequences, yielding 6,580 OTUs, 4 phyla and 36 genera. The sputum microbiota core comprised of 34 genera and it was remarkably stable during treatment. Month 2 was characterized by a significant mean reduction in core microbiota biomass, limited variance changes and general lack of entropy. However, variance and entropy recovered at month 5. Co-occurrence patterns were predominated by accessory genera at baseline but their abundance significantly reduced during treatment. Our findings reveal discernible sputum microbiota signals associated with first-line anti-TB therapy, with potential to inform treatment response monitoring in developing countries.

No abstract

Background There are few reports on lung cancer among people with HIV (PWH) in Sub-Saharan Africa. In this report, we describe a cohort of PWH and lung cancer at the Uganda Cancer Institute. Methods This retrospective cohort of PWH and lung cancer was managed at the Uganda Cancer Institute between 2008 and 2018. Sociodemographic and clinical data were abstracted from the patient charts. The median survival from diagnosis to death, loss-to-follow up or 31st December 2018, was estimated. Results There were 18 people with HIV and lung cancer. The median (interquartile range, IQR) age was 49.5 (38.8–56.0) years, 11 (61.1%) were women and 5 (27.8%) were smokers. Of the 18 PWH, 13 (72.2%) were on antiretroviral therapy and the median (IQR) CD4 count (n = 13) was 380 (243.5–595) cells per mm3. Difficulty in breathing (88.9%), chest pain (78.6%, n = 11), cough (76.5%, n = 17) and weight loss (72.2%) were the commonest symptoms while pleural effusions were observed in 12 (66.7%). In this cohort, 8 (44.4%) were presumptively treated for tuberculosis before the diagnosis of lung cancer. Seven (38.9%) had an Eastern Cooperative Oncology Group performance status of 3. Non-small cell lung cancer was the predominant histological type observed in 17 (94.4%) of whom 14 (82.4%) had adenocarcinoma. Majority of PWH had stage IV disease (88.9%). The median (IQR) survival was 3.3 (1.1–13.2) months and all were either dead (72.2%) or lost-to-follow up (27.8%) at five years from diagnosis. Conclusion People with HIV and lung cancer in Uganda report low rates of smoking, present with advanced disease and post very poor survival rates. There is need for biomarkers for early detection of lung cancer in HIV.

Information on microbiota dynamics in pulmonary tuberculosis (TB) in Africa is scarce. Here, we sequenced sputa from 120 treatment-naïve TB patients in Uganda, and investigated changes in microbiota of 30 patients with treatment-response follow-up samples. Overall, HIV-status and anti-TB treatment were associated with microbial structural and abundance changes. The predominant phyla were Bacteroidetes, Firmicutes, Proteobacteria, Fusobacteria and Actinobacteria, accounting for nearly 95% of the sputum microbiota composition; the predominant genera across time were Prevotella, Streptococcus, Veillonella, Haemophilus, Neisseria, Alloprevotella, Porphyromonas, Fusobacterium, Gemella, and Rothia. Treatment-response follow-up at month 2 was characterized by a reduction in abundance of Mycobacterium and Fretibacterium, and an increase in Ruminococcus and Peptococcus; month 5 was characterized by a reduction in Tannerella and Fusobacterium, and an increase in members of the family Neisseriaceae. The microbiota core comprised of 44 genera that were stable during treatment. Hierarchical clustering of this core’s abundance distinctly separated baseline (month 0) samples from treatment follow-up samples (months 2/5). We also observed a reduction in microbial diversity with 9.1% (CI 6–14%) of the structural variation attributed to HIV-status and anti-TB treatment. Our findings show discernible microbiota signals associated with treatment with potential to inform anti-TB treatment response monitoring.