One Health AMR Surveillance through Innovative Sampling (OASIS)
Laboratory-based AMR surveillance is hampered by selection bias and unrepresentativeness for local settings, precluding guidance on empirical treatment decisions in the human or veterinary domains. Population-based AMR surveillance is preferred but is time-, labour- and cost intensive due to large sample sizes required. OASIS moves from estimating AMR prevalence to classifying populations/settings as having a high/low AMR prevalence, by applying a Lot Quality Assurance Sampling approach, which requires much smaller sample sizes and is uniquely positioned for population-based AMR surveillance.
OASIS optimises the LQAS approach as a rapid, domain-, and setting-appropriate AMR surveillance strategy, within a One Health context that appreciates the close interplay of drivers of AMR emergence and transmission in human and livestock populations. Surveillance strategies that use a similar methodology to assess AMR prevalence in multiple domains are highly desired, strengthen the knowledge and evidence base on AMR, and optimise the use of antimicrobials in both human and animal health. Oasis’ implementation research component engages domain-specific stakeholders throughout the project to optimise knowledge utilisation, and facilitate the translation of results into policy.
- Frank van Leth, Amsterdam Institute for Global Health and Development, Amsterdam UMC, Netherlands (Coordinator)
- Hubert Ph. Endtz, Foundation Merieux, France
- Christian Menge, Friedrich-Loeffler-Institut , Germany
- Christa Ewers, Institute of Hygiene and Infectious Diseases of Animals, Justus Liebig University, Germany
- Mounerou Salou, University of Lomé, Togo
- Abdoul-Salam Ouedraogo, Higher National Institute of Health Sciences, Nazi Boni University, Burkina Faso