Enteric pathogen infections are a leading cause of morbidity and mortality globally, with the highest disease burden in low-income countries. Hands act as intermediaries in enteric pathogen transmission, transferring enteric pathogens between people and the environment through contact with fomites, food, water, and soil. In this study, we conducted a systematic review of prevalence and concentrations of fecal indicator microorganisms (i.e., E. coli, fecal coliform) and enteric pathogens on hands. We identified 84 studies, reporting 35,440 observations of hand contamination of people in community or household settings. The studies investigated 44 unique microorganisms, of which the most commonly reported indicators were E. coli and fecal coliforms. Hand contamination with 12 unique enteric pathogens was reported, with adenovirus and norovirus as the most frequent. Mean E. coli prevalence on hands was 62% [95% CI 40%–82%] and mean fecal coliform prevalence was 66% [95% CI 22%–100%]. Hands were more likely to be contaminated with E. coli in low/lower-middle-income countries (prevalence: 69% [95% CI 48%–88%]) than in upper-middle/high-income countries (6% [95% CI 2%–12%]). The Review also highlights the importance of standardizing hand sampling methods, as hand rinsing was associated with greater fecal contamination compared to other sampling methods.@en

Human-associated microbial communities comprise not only complex mixtures of bacterial species, but also mixtures of conspecific strains, the implications of which are mostly unknown since strain level dynamics are underexplored due to the difficulties of studying them. We introduce the Strain Genome Explorer (StrainGE) toolkit, which deconvolves strain mixtures and characterizes component strains at the nucleotide level from short-read metagenomic sequencing with higher sensitivity and resolution than other tools. StrainGE is able to identify strains at 0.1x coverage and detect variants for multiple conspecific strains within a sample from coverages as low as 0.5x.

@en

Despite recent advances in robotic technology, sewer pipe inspection is still limited to conventional approaches that use cable-tethered robots. Such commercially available tethered robots lack autonomy, and their operation must be manually controlled via their tethered cables. Consequently, they can only travel to a certain distance in pipe, cannot access small-diameter pipes, and their deployment incurs high costs for highly skilled operators. In this paper, we introduce a miniaturised mobile robot for pipe inspection. We present an autonomous control strategy for this robot that is effective, stable, and requires only low-computational resources. The robots used here can access pipes as small as 75 mm in diameter. Due to their small size, low carrying capacity, and limited battery supply, our robots can only carry simple sensors, a small processor, and miniature wheel-legs for locomotion. Yet, our control method is able to compensate for these limitations. We demonstrate fully autonomous robot mobility in a sewer pipe network, without any visual aid or power-hungry image processing. The control algorithm allows the robot to correctly recognise each local network configuration, and to make appropriate decisions accordingly. The control strategy was tested using the physical micro robot in a laboratory pipe network. In both simulation and experiment, the robot autonomously and exhaustively explored an unknown pipe network without missing any pipe section while avoiding obstacles. This is a significant advance towards fully autonomous inspection robot systems for sewer pipe networks.

@en