Genomic epidemiology reveals geographical clustering of multidrug-resistant Escherichia coli ST131 associated with bacteraemia in Wales

Antibiotic resistance is a significant global public health concern. Uropathogenic Escherichia coli sequence type (ST)131, a widely prevalent multidrug-resistant clone, is frequently associated with bacteraemia. This study investigates third-generation cephalosporin resistance in bloodstream infections caused by E. coli ST131. From 2013-2014 blood culture surveillance in Wales, 142 E. coli ST131 genomes were studied alongside global data. All three major ST131 clades were represented across Wales, with clade C/H30 predominant (n = 102/142, 71.8%). Consistent with global findings, Welsh strains of clade C/H30 contain β-lactamase genes from the blaCTX-M-1 group (n = 65/102, 63.7%), which confer resistance to third-generation cephalosporins. Most Welsh clade C/H30 genomes belonged to sub-clade C2/H30Rx (58.3%). A Wales-specific sub-lineage, named GB-WLS.C2, diverged around 1996-2000. An introduction to North Wales around 2002 led to a localised cluster by 2009, depicting limited genomic diversity within North Wales. This investigation emphasises the value of genomic epidemiology, allowing the detection of genetically similar strains in local areas, enabling targeted and timely public health interventions.

COVID-19 surveillance robot: rapid innovation for public health pandemic management

Background

COVID-19 surveillance added a significant workload to the eight HSE-Departments of Public Health in Ireland. HSE-HPSC rapidly developed a fit-for-purpose robot to navigate the national infectious disease reporting system (CIDR) to automate three manual processes; laboratory records, notifications and contact-tracing data; which takes a surveillance scientist 26 minutes per case on average.

Methods

HSE-HPSC managed and delivered a multidisciplinary project team to develop the rapid solution. The robot was designed to operate the CIDR system using an agreed set of rules, developed through business process analyses of the ‘first wave', stakeholder engagement and technical collaboration. Development began in April 2020, and went live in August 2020 after phases of testing, piloting, and hyper-care.

Results

Successful integration: The robot aligned COVID-19 surveillance data across three national HSE information systems. Degree of automation: The robot processed greater than 80% of cases just like a human. The remaining 20% are flagged by the robot for data quality checks by the regional public health teams. Time-saving: The robot operates quicker than a human, 3.3minutes per case compared to 26minutes. Therefore for every 100 cases, the robot saves 38hours per day. Out-of-hours capacity: Robots currently operate for 22hours per day, resulting in overtime cost-savings for the HSE. Surge capacity: The automation was expanded to 42 robots for ‘third-wave' surge capacity. Sustainable change in surveillance system: Robots can be expanded for surveillance of other notifiable diseases.

Conclusions

The robot:

delivered a fit-for-purpose pandemic resource relieved the underfunded public health system of the administrative burden of COVID-19 surveillance delivered timely data for epidemiological reporting by the HSE-HPSC to the National Public Health Emergency Team.

Key messages

Through rapid collaboration, the robot successfully delivered a fit-for-purpose public health resource that aligned COVID-19 data across HSE information systems and achieved time/cost savings. The robot strengthened the public health surveillance response in Ireland.