Tracking_Antimicrobial_Resistance_Across_Care_Settings_in_Liverpool_
Abstract*: Briefly describe the goals, purpose and scope of the study by typing in the grey box below. (For managed access studies, please bear in mind it's this text in the Abstract that will be publicly visible on the EGA website). Preventing the spread of antimicrobial resistant Enterobacterales bacteria is a global priority. This research study aims to find out how and where people catch these bacteria within the UK care setting, so we can develop ways to stop this happening. Previous research has shown that people who have been admitted to hospital or are resident in care homes may be at increased risk of infection with these bacteria, but the exact routes of transmission remain unknown. Drug-resistant Enterobacterales bacteria are thought to live harmlessly in the gut in many people before they go on to cause illness in some. This means that transmission between people needs one person to swallow bacteria from the gut of another. We aim to understand exactly how this happens in this research project. We will visit hospital wards and care homes and take samples at each place over a 2-week period. We will collect swabs from the environment (toilets, sinks, door handles, etc.) and stool samples or rectal swabs from residents, as well as swabs from the hands of staff. We will test all these samples for resistant Enterobacterales bacteria and, when we find them, we will use whole genome sequencing and statistical modelling to track where they may have come from. We will collect data from hospital and GP records (with people's permission) on antibiotics they have received and where they have been in the hospital. We aim to visit three hospital wards and three care homes in turn over a 12-week period and repeat this four times to see if there are any changes over time. This information will allow us to identify places where people catch resistant bacteria, and to design interventions to block transmission. Sanger's activities: Whole genome sequencing and collaboration on data analysis