One Health AMR Surveillance through Innovative Sampling (OASIS)
Project code: FLI-IMP-08-Je-0242
Contract period: 01.04.2020 - 31.03.2023
Purpose of research: Experimental development
The objective of OASIS is to develop a novel antimicrobial resistance (AMR) surveillance approach („Lot Quality Assurance Sampling - LQAS“) to guide empirical antimicrobial treatment strategies in human and animal populations in a One-Health context. LQAS does not determine exact AMR prevalences, but rather classifies a population as having either a high (don’t use) or a low (use) AMR prevalence, thereby contributing to the treatment choice, but requiring much smaller sample sizes. The aim of the two veterinary partners in the consortium, the Institute of Hygiene and Infectious Diseases of Animals (IHIT) of the Justus- Liebig-Universität Giessen and the Friedrich-Loeffler-Institut (FLI) in Jena, is to provide evidence that this novel and innovative surveillance approach can be transferred to veterinary medicine. To achieve this, FLI and IHIT (i) contribute to the design of the LQAS sampling strategy, (ii) conduct a conventional AMR prevalence survey for fattening pigs (FLI) and broiler chickens (IHIT), thereby (iii) generating the AMR data needed for biomathematical simulations to provide the evidence that the novel surveillance approach adequately identifies areas with high or low AMR prevalence for specific antibiotics, even at smaller regional and veterinarian-based levels, and (iv) after validation of LQAS as system for estimating AMR prevalence, build capacities for LQAS-based AMR surveillance in the veterinary domain in high-, middle and low-income countries (HIC, LMIC). This knowledge will be used to engage and interest domain-specific stakeholders to consider translating the results into policy. OASIS aims to fill the much required need for methods that allow high-quality, feasible and affordable AMR surveillance in both human and veterinary domains, in LMICs and HICs. It strengthens the knowledge and evidence-base on AMR and optimizes the use of antimicrobials in both human and animal health.