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The dissemination of Escherichia coli producing extended-spectrum beta-lactamase (ESBL-Ec) is evident in the community. A population-based spatial analysis is necessary to investigate community risk factors for ESBL-Ec occurrence. The study population was defined as individuals with ESBL-Ec isolated in Queensland, Australia, from 2010 to 2019. Choropleth maps, global Moran's index and Getis-Ord Gi* were used to describe ESBL-Ec distribution and identify hot spots. Multivariable Poisson regression models with or without spatially structured random effects were performed. A total of 12 786 individuals with ESBL-Ec isolate were identified. The crude incidence rate increased annually from 9.1 per 100 000 residents in 2010 to 49.8 per 100 000 residents in 2019. The geographical distribution of ESBL-Ec changed from random to clustered after 2014, suggesting presence of community-specific factors that can enhance occurrence. Hot spots were more frequently identified in Outback and Far North Queensland, future public health measures to reduce transmission should prioritise these communities. Communities with higher socioeconomic status (RR = 0.66, 95% CI 0.55–0.79, per 100 units increase) and higher proportion of residents employed in the agricultural industry (RR = 0.79, 95% CI 0.67–0.95, per 10% increase) had lower ESBL-Ec incidence. Risk factors for occurrence appear differential between remote and city settings and this should be further investigated.
Whole-genome sequencing (WGS) shotgun metagenomics (metagenomics) attempts to sequence the entire genetic content straight from the sample. Diagnostic advantages lie in the ability to detect unsuspected, uncultivatable, or very slow-growing organisms.
To evaluate the clinical and economic effects of using WGS and metagenomics for outbreak management in a large metropolitan hospital.
Cost-effectiveness study.
Intensive care unit and burn unit of large metropolitan hospital.
Simulated intensive care unit and burn unit patients.
We built a complex simulation model to estimate pathogen transmission, associated hospital costs, and quality-adjusted life years (QALYs) during a 32-month outbreak of carbapenem-resistant Acinetobacter baumannii (CRAB). Model parameters were determined using microbiology surveillance data, genome sequencing results, hospital admission databases, and local clinical knowledge. The model was calibrated to the actual pathogen spread within the intensive care unit and burn unit (scenario 1) and compared with early use of WGS (scenario 2) and early use of WGS and metagenomics (scenario 3) to determine their respective cost-effectiveness. Sensitivity analyses were performed to address model uncertainty.
On average compared with scenario 1, scenario 2 resulted in 14 fewer patients with CRAB, 59 additional QALYs, and $75,099 cost savings. Scenario 3, compared with scenario 1, resulted in 18 fewer patients with CRAB, 74 additional QALYs, and $93,822 in hospital cost savings. The likelihoods that scenario 2 and scenario 3 were cost-effective were 57% and 60%, respectively.
The use of WGS and metagenomics in infection control processes were predicted to produce favorable economic and clinical outcomes.
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