Active One Health surveillance in LMICs to monitor and predict Antimicrobial Resistance Using Metagenomics

We will develop and validate approaches for sentinel One Health AMR surveillance in rural sub-Saharan Africa. Building on previous novel work showing that metagenomic profiling of pooled faecal material can accurately predict AMR prevalence in clinical isolates of Enterobacterales, we aim to extend this work to other bacterial species and One Health compartments. We will conduct metagenomic profiling on pooled DNA extracts from human stool samples (hospital and community-level) and from household environments in Burkina Faso and Kenya. We will assemble existing local data from hospital-based microbiology diagnostic laboratories. We will perform community-level surveys and use randomly selected households within village clusters. We will sample suspected environmental AMR exposure sites in and around households and collect data on community-level human and animal antibiotic use, hygiene practices, contact with domestic animals, and sanitary facilities. Data analysis will seek to quantify community-level exposure risks and evaluate the accuracy of predicting resistance in clinical isolates using metagenomic data. A cost-utility analysis will determine under what circumstances the use of pooled metagenomic data to inform empirical antibiotic policies would represent an efficient use of resources.The proposed work will establish how this approach could provide a viable, low-cost and convenient approach for AMR sentinel surveillance in settings which - like many in rural sub-Saharan Africa - lack systematic microbiological diagnostics and where sewage systems are non-existing.