How much is enough? Optimising sampling frames for genomic surveillance of Escherichia coli and Klebsiella spp. bloodstream infections - a retrospective study

Background: Optimising sampling frames for genomic surveillance of E. coli and Klebsiella may support interventions to mitigate bloodstream infections (BSIs), but approaches to estimating sample size and how these relate to bacterial population diversity at multiple genetic levels (strain/plasmid/antimicrobial resistance genes [ARGs]) are lacking. Methods: Using systematically collected, regionally-stratified, whole genome sequencing data from a 6-month genomic survey of English E. coli/Klebsiella BSI isolates (n=1,939; NEKSUS), we used Bayesian approaches to estimate the sample sizes required to capture genetic diversity at strain- (MLST, fastBAPS clusters), plasmid- and ARG-levels, using two diversity measures: 'coverage' (i.e. proportion of the bacterial population/plasmids/ARGs represented by features observed in the sample), and the number/proportion of unique features observed at varying surveillance sample sizes. Our method is available as a user-friendly R Shiny application, EpiSENTRY (https://01a0c3dd-90d2-e597-58a5-51391a468387.share.connect.posit.cloud/). Findings: Randomly sampling 1,400 E. coli/Klebsiella BSI isolates each achieved [≥]80% coverage of bacterial lineages and ARGs (i.e. capture features constituting [≥]80% of the population) at 95% certainty, but captured lower proportions of unique features (28% MLSTs, 59% fastBAPS clusters, 19% plasmid subcommunities, and 57% ARGs for E. coli; 49%, 87%, 50% and 83% for Klebsiella, respectively). Sample sizes required for 80% coverage of E. coli plasmid populations were higher than MLSTs (1,928 [95% CrI: 1,837-2,025] vs 1,351 [1,230-1,472]), while for Klebsiella, estimates were lower for plasmids (1,115 [1,052-1,181] vs 1,422 [1,331-1,515] for MLSTs). Lower sample sizes adequately captured 80% coverage of fastBAPS clusters and ARGs (649 [575-727] and 27 [23-30], respectively, for E. coli; 113 [84-145] and 83 [72-96] for Klebsiella), due to feature-specific frequency distributions. Klebsiella BSIs were more diverse than E. coli, with sampling 10.9% vs 3.2% of total annual BSIs in England needed to reach 80% MLST coverage. Plasmid populations and Klebsiella MLSTs were region-specific, emphasising the need for regionally-representative sampling. Interpretation: Bayesian analysis facilitates estimates of context-specific genomic surveillance sample sizes. Cost-effective targets for coverage require further optimisation.