Title: Global Health Research Unit on Genomics and enabling data for Surveillance of Antimicrobial Resistance
Funder: Department of Health and Social Care

Abstract: Whole genome sequencing when combined with surveillance data can enhance our ability to spot outbreaks, determine circulating high risk strains and produce information that can be used for decision making Rationally combining WGS within surveillance networks can inform on population and evolutionary dynamics and enhance our ability to mitigate spreads and understand the impact of interventions. Bringing this model to fruition requires a combination of infracstructure and capacity building and crucially, rapidly bringing the right data together in the right formats to deliver inferences to stakeholders at the very local level, and upwards through the information chain to national and international decision makers. Building on prior WGS capacity building we will implement data driven, WGS-enhanced surveillance in Nigeria, India, Colombia and The Philippines. We will deliver a rich network of data science, genomic technologies and surveillance reporting and build a public health legacy within countries. In Nigeria, we will deliver a national system from startup to drive down the time taken to implement informed WGS surveillance for control of AMR. Through formalising and enhancing information architecture, stakeholder reporting and strategic application to maximise value from WGS we will deliver surveillance data for routine decision making which will directly impact infection control policies locally and nationally and inform policy globally.

Lay abstract: AMR is a global threat to public health and new technologies and integrated understanding of information on a local and global scale are required. Enhancing local decision making by providing high resolution data that can enhance treatment strategies to the individual is key to improving infection control. Placing individuals and their data in the context of regional and national interpretation can aid understanding of transmission, pathogen population dynamics and public health risk. Ultimately, enhancing real time linkage of data at multiple geographic scales will provide us with a globally aware data landscape and enhance our ability to spot the emergence and spread of new threats and lead to intelligent deployment of interventions and the monitoring of their impact. Whole Genome Sequencing (WGS) is a technology increasingly embraced within translational public health communities and offers the ability to provide information at an individual level, as well as at a regional, national and international scale due to its digital nature. _x000D_ Barriers to uptake of WGS are broad, practical and political, eg technology rollout, implementation and embedding in current practice as well as supply chains and reagent availability. Much progress is being made in technical support for practical implementation. However, a remaining major bottleneck is the rapid and routine linkage of data and interpretation to provide the greatest value to data generators at a local level, as well as the routine combination of data aggregated at a regional, national and international level._x000D_ Here, we build upon work within the NIHR Global Health Research Unit on genomic surveillance of AMR focussed on technical support for practical rollout of WGS and expand and enhance through linkage with regional institutions such as WHO to deliver regional capacity building. In addition, we address the increasing emphasis and need for local data science and engineering to transform the data landscape within local and regional hubs for linking clinical and epidemiological data to genomics. We focus on operationalising methods and tools to deliver a data landscape for local and national, and ultimately international monitoring of genomic trends in AMR linked to relevant clinical and epidemiological data for enhancing infection control and taking decisive action to curb the threat of AMR;

Research activity codes: 2.4 SURVEILLANCE AND DISTRIBUTION;2.6 RESOURCES AND INFRASTRUCTURE (AETIOLOGY)
Health categories: INFECTION