Question to the Department of Health and Social Care:

To ask His Majesty's Government what assessment they have made of the use of artificial intelligence to support the early identification of hospital-acquired infections in NHS hospitals.

The UK Health Security Agency is currently exploring how artificial intelligence (AI) technologies may be used across a range of public health analyses and threat identification.

Hospital acquired infections (HAIs) are a major public health concern because bacteria in healthcare settings are often exposed to antibiotics, increasing the likelihood that they will develop resistance. These resistant infections are more difficult to treat and can lead to poorer patient outcomes. Through the Pathogen Risk Intelligence Modelling Project, we are generating metagenomic data from wastewater and air samples collected in hospitals and using AI and, in particular, supervised machine learning, to track the spread of antimicrobial resistance between different types of bacteria. Wastewater metagenomic surveillance is a cost-effective approach that provides a broad picture of microbial communities without targeting specific species. Our aim is to detect emerging resistance early, enabling healthcare professionals to take timely infection prevention and control measures. We are currently evaluating the performance of this approach to determine how effectively it can identify and monitor antibiotic resistance in realworld healthcare settings.