SRA

This is a large scale project with the sequencing co-funded by collaborators at the University of Cape Town and WT Core (I2818). This is a project aimed at deepening our understanding of pneumococcal evolution and transmission dynamics through analysis of genomes from a large scale, deeply sampled pneumococcal population. It is based on a longitudinal carriage study conducted in the Drakenstein district near Cape Town, South Africa that has parallels with, and valuable differences from, the earlier longitudinal carriage study in the Maela refugee camp in North West Thailand. The primary aim of the “Drakenstein Child Health Study” (DCHS) is to longitudinally investigate aetiology, progression and risk factors for childhood pneumonia in a cohort of 1000 mother-infant pairs over a period of 5 years. A subset of 800 infants has been intensively sampled at fortnightly intervals during their first year of life. Nasopharyngeal (NP) swabs are collected every second week during the first year of life, during scheduled clinic visits at 6, 12, 18, 24 months of age and during any episode of pneumonia. The two-weekly sampling is a key difference from Maela where sampling was monthly and will enhance our ability to detect transmission events, particularly the early transmissions between mother and infant. Samples are linked to a very detailed set of metadata, including a range of relevant exposures (e.g., antimicrobial therapy, vaccination status, mode of delivery, socio-economic conditions, air quality, parental drug and alcohol abuse) and outcome (e.g., LRTI, wheezing illness, growth, lung function) variables. To date, more than 900 episodes of LRTI have been documented in this cohort. Detailed etiological investigation, including 33-plex qPCR for a range of respiratory pathogens has been completed on all samples collected at the time of pneumonia, and in a subset of NP samples over the 3-months preceding the LRTI event. Overall the study has collected 12,000 pneumococcal isolates. We would like to sequence all 12,000 available isolates to maximise the statistical power of analyses.