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Kenya has registered over 300,000 cases of COVID-19 and is a high-burden tuberculosis country. Tuberculosis diagnosis was significantly disrupted by the pandemic. Access to timely diagnosis, which is key to effective management of tuberculosis and COVID-19, can be expanded and made more efficient through integrated screening. Decentralized testing at community level further increases access, especially for underserved populations, and requires robust systems for data and process management. This study delivered integrated COVID-19 and tuberculosis testing to commercial motorbike (Bodaboda) riders, a population at increased risk of both diseases with limited access to services, in four counties: Nairobi, Kiambu, Machakos and Kajiado. Testing sheds were established where riders congregate, with demand creation carried out by the Bodaboda association. Integrated symptom screening for tuberculosis and COVID-19 was conducted through a digital questionnaire which automatically flagged participants who should be tested for either, or both, diseases. Rapid antigen-detecting tests (Ag-RDTs) for COVID-19 were conducted onsite, while sputum samples were collected and transported to laboratories for tuberculosis diagnosis. End-to-end patient data were captured using digital tools. 5663 participants enrolled in the study, 4946 of whom were tested for COVID-19. Ag-RDT positivity rate was 1% but fluctuated widely across counties in line with broader regional trends. Among a subset tested by PCR, positivity was greater in individuals flagged as high risk by the digital tool (8% compared with 4% overall). Of 355 participants tested for tuberculosis, 7 were positive, with the resulting prevalence rate higher than the national average. Over 40% of riders had elevated blood pressure or abnormal sugar levels. The digital tool successfully captured complete end-to-end data for 95% of all participants. This study revealed high rates of undetected disease among Bodaboda riders and demonstrated that integrated diagnosis can be delivered effectively in communities, with the support of digital tools, to maximize access.

Bacteria belonging to the SAR11 clade are among the most abundant prokaryotes in the pelagic zone of the ocean. 16S rRNA gene-based analyses indicate that they constitute up to 60% of the bacterioplankton community in the surface waters of the Red Sea. This extremely oligotrophic water body is further characterized by an epipelagic zone, which has a temperature above 24 °C throughout the year, and a remarkable uniform temperature (~22 °C) and salinity (~41 psu) from the mixed layer (~200 m) to the bottom at over 2000 m depth. Despite these conditions that set it apart from other marine environments, the microbiology of this ecosystem is still vastly understudied. Prompted by the limited phylogenetic resolution of the 16S rRNA gene, we extended our previous study by sequencing the internal transcribed spacer (ITS) region of SAR11 in different depths of the Red Sea's water column together with the respective 16S fragment. The overall diversity captured by the ITS loci was ten times higher than that of the corresponding 16S rRNA genes. Moreover, species estimates based on the ITS showed a highly diverse population of SAR11 in the mixed layer that became diminished in deep isothermal waters, which was in contrast to results of the related 16S rRNA genes. While the 16S rRNA gene-based sequences clustered into three phylogenetic subgroups, the related ITS fragments fell into several phylotypes that showed clear depth-dependent shifts in relative abundances. Blast-based analyses not only documented the observed vertical partitioning and universal co-occurrence of specific phylotypes in five other distinct oceanic provinces, but also highlighted the influence of ecosystem-specific traits (e.g., temperature, nutrient availability, and concentration of dissolved oxygen) on the population dynamics of this ubiquitous marine bacterium.