Researchers to build streamlined data landscape for infectious diseases with AI

Researchers from City St George’s, University of London have secured funding for a project that aims to streamline infectious disease data using artificial intelligence (AI) to help address key global health targets.

Antimicrobial resistance (AMR) is one of the top ten global threats, and which contributes to an estimated 4.95 million deaths worldwide every year. However, accurate estimates of deaths are extremely difficult to determine due to a multitude of public health and epidemiological challenges, including the scarcity of high-quality patient data, microbiology data, and data linked to clinical outcomes for each patient with an infectious disease.

Increased support for collating data

This data is limited in the UK and other high-income countries, but a major barrier to progress is that it is largely non-existent in many low- and middle- income countries, which AMR poses the biggest threat to. The data that does exist to diagnose and treat patients with infectious diseases is often not harmonised into useful datasets.

In 2024 alone, there has been increased support for national action plans to tackle AMR. This has brought the importance of collating surveillance data to inform local policies and minimise the threat of AMR to the forefront.

Awarded by the Infection Innovation Consortium (iiCON) and funded by UK Research and Innovation (UKRI), the project is led by Dr Catrin Moore at the University’s Institute for Infection and Immunity alongside Professor Eduardo Alonso, Director of the City St George's Artificial Intelligence Research Centre, which recently underwent a relaunch.

Together, they will build a data landscape by mapping where and what infectious disease data exists worldwide, understanding the structure of that data and identifying the data gaps that need to be addressed.

AI to build data pipeline

They will also use new machine learning and artificial intelligence tools to build a ‘pipeline’ to convert existing similar datasets, which will be in different formats, into a streamlined dataset to inform future treatment guidelines.

Dr Catrin Moore, study lead and Reader in Global Health and Infectious Diseases at City St George’s, said:

This is an exciting and very timely project working with fantastic partners. Through my work on estimating the global burden of antimicrobial resistance and leading the Microbiology Society’s Knocking Out AMR project, it’s become very apparent that AMR data is often siloed.

“It’s imperative that good quality research data is shared across the ‘One Health’ sector to inform evidence based decisions and to answer important policy questions, such as how we will reduce human deaths associated with AMR annually by 10% in 2030 - a target that world leaders committed to in September.

Combatting the transmission of infection is one of the most significant health challenges of our time, and its urgency continues to escalate. It is essential that we harness novel, disruptive technologies to advance our efforts in tackling the spread of infection.