| Title: |
Alarum:Active One Health surveillance in LMICs to monitor and predict Antimicrobial Resistance Using Metagenomics - a cross-sectional study protocol |
| Authors: |
van der Sande, Marianne A B; Valia,Daniel; Tigoi,Caroline; Stoesser,Nicole; Stamm,Linda; Marten,Andrea; Riems,Bram; Musyimi,Robert; Sibidou,Yougbare; Schurch, Anita C; Tiendrebeogo,Eric W; Mwaringa,Shalton; Kohns Vasconcelos,Malte; Ingelbeen,Brecht; Tinto,Halidou; Bielicki,Julia A; Cooper,Ben S; Berkley,James A; van Kleef, Esther; Global Health team 1; JC onderzoeksprogramma Cardiovascular Health; Global Health; MMB-bio; Infection & Immunity |
| Publication Year: |
2026 |
| Subject Terms: |
antimicrobial resistance; health demographic surveillance systems; mobile genetic elements; one health surveillance; pooled metagenomics; prediction; sub-Sahara Africa; General Medicine; Journal Article |
| Description: |
BACKGROUND: In rural sub-Saharan Africa (sSA), the burden of antimicrobial resistance (AMR) remains high. As AMR continues to rise, there is a strong need for practical, implementable surveillance to monitor and mitigate risks, as well as inform timely, evidence-based clinical decision-making. Emerging evidence points to possible community-level drivers, such as transmission between human, animal and environmental reservoirs as contributing factors, yet microbiological surveillance or opportunities for wastewater-based surveillance are often limited and insufficient in these settings. Therefore, alternative sustainable and affordable approaches are needed. We intend to build on the demonstrated potential of metagenomic profiling of pooled faecal material, which accurately predicted population-level AMR prevalence in invasive Enterobacterales infections. METHODS AND ANALYSIS: We aim to validate this metagenomic pooled approach on additional populations, and to evaluate whether AMR patterns could be similarly predicted from surveillance of community One Health reservoirs. We will assemble existing data from hospital-based microbiology diagnostic laboratories in rural Burkina Faso and Kenya, and determine to what extent community-level metagenomic data, and/or faecal material of patients on hospital admission, can predict AMR in clinical isolates. We will perform community-level surveys in eight clusters per country, randomly selecting 15 households per cluster. We will systematically sample suspected environmental AMR exposure sites in and around households (soil, drinking water, latrines, chicken faeces) and collect data on community-level antibiotic use, hygiene practices, contact with domestic animals and sanitary facilities. Samples and data will be collected twice: during the dry and during the rainy season.In addition to evaluating the accuracy of predicting resistance in clinical isolates, we will quantify community-level exposure risks. We will conduct metagenomic profiling on pooled DNA extracts from ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| ISSN: |
2044-6055 |
| Relation: |
https://dspace.library.uu.nl/handle/1874/469480 |
| Availability: |
https://dspace.library.uu.nl/handle/1874/469480 |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.4D1F49C |
| Database: |
BASE |