Whole-genome sequencing, strain composition, and predicted antimicrobial resistance of Streptococcus pneumoniae causing invasive disease in England in 2017–20: a prospective national surveillance study

Surveillance of the invasive disease burden caused by Streptococcus pneumoniae in England is performed by the UK Health Security Agency (UKHSA). In 2017, UKHSA switched from phenotypic methods to whole-genome sequencing (WGS) approaches for pneumococcal surveillance. Here, we present the first results of national WGS surveillance, up to the start of the COVID-19 pandemic, with the aim of describing the population genomics of this important pathogen. We examined prospective national surveillance data from England, using bacterial isolates from cases of invasive pneumococcal disease (IPD) submitted to the national reference laboratory at UKHSA. A bioinformatic pipeline was developed to quality control WGS data and routinely report species and serotype. We assembled isolate data, assigned global pneumococcal sequencing clusters (GPSCs), and predicted antimicrobial resistance (AMR) profiles for isolates that passed further quality control. We collected additional data on patient outcomes and characteristics using enhanced surveillance questionnaires completed by patients' general practitioners. We used logistic regression analysis to assess the effects of various genomic and patient characteristics on the outcomes of IPD. In England, between July 1, 2017, and Feb 29, 2020, there were 15 400 cases of IPD. From these cases, 13 749 (89·3%) isolates were sequenced, passed quality control, and were included in analyses. Serotype diversity was high during the study period, with 2751 (20%) isolates serotyped as 13-valent pneumococcal conjugate vaccine (PCV13) types, whereas serotype 8 was the most prevalent serotype (n=3074 [22·4%]) overall. There were 157 GPSCs within the collection, with GSPC3 the most common, encompassing 98·7% (3033 of 3074) of serotype 8 isolates. Most isolates (n=10 198 [74·2%]) did not contain AMR-associated genes. Resistance to co-trimoxazole was the most frequently predicted resistance (n=2331 [17%]), followed by resistance to tetracycline (n=1199 [8·7%]) and β-lactams (n=1149 [8·4%]). Logistic regression analysis found the presence of AMR-associated genes significantly increased the odds of patient death (odds ratio 1·18, 95% CI 1·01-1·38). Some GPSCs were also associated with a significant increase in the odds of patient death, such as GPSC12 (1·88, 1·48-2·38). Isolates from 2018 were associated with a significant increase in the odds of patient death (1·12, 1·00-1·25), whereas younger patient age was significantly associated with a reduction in the odds of patient death compared with being aged 85 years or older. WGS-based surveillance has allowed us to interrogate country-wide population dynamics driving changes in pneumococcal serotype frequency. Here, we observe a stable but diverse population before the COVID-19 pandemic restrictions were enforced in England, with low rates of AMR. These findings will provide the baseline for pandemic and post-pandemic data, to collectively inform implementation and development of the vaccination programme within the country. None.