One Health AMR Surveillance through Innovative Sampling

Surveillance

Research Project: 2020-04-01 - 2024-06-30
Total sum awarded: €1 634 310

OASIS aims to develop an antimicrobial resistance (AMR) surveillance strategy in a One Health context, and applicable in high-, middle-, and low-income countries. The proposed strategy challenges the strong reliance on laboratory-based AMR surveillance for meeting objectives of the Global Action Plan on AMR. 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.

Read More
Read Less
  • Frank van Leth, Amsterdam Institute for Global Health and Development, Amsterdam UMC, Netherlands (Coordinator)
  • Francois-Xavier Babin, Fondation Mérieux, France (Partner)
  • Christian Menge, Friedrich-Loeffler-Institut, Germany (Partner)
  • Christa Ewers, Justu-Liebig University, Germany (Partner)
  • Mounerou Salou, University of Lomé, Togo (Partner)
  • Abdoul-Salam Ouedraogo, Higher National Institute of Health Sciences, Nazi Boni University, Burkina Faso (Partner)

Bacteria are increasingly resistant to antibiotics, which can hamper the treatment of even the simplest of infections. OASIS assesses a new way of measuring the extent of this resistance, as a way to identify places where action is required. To do so, OASIS changes the question “how much resistance is present?” to “is the resistance above a certain level?”. By doing so, information on the extent of the problem can be collected faster, cheaper, and becomes locally relevant. We hope to demonstrate that this approach can work for livestock and people. For livestock, we will collect samples of excrement from pigs transported in trucks to slaughterhouses. In addition, we will analyze peptone waters from the obligatory salmonella testing of broilers received from central laboratories of the poultry industry. Both strategies will provide accurate information on the presence of resistant bacteria. For humans, we collect urine samples from individuals who present with symptoms of a urinary tract infection at outpatient clinics in Togo and Burkina Faso. The urine is examined for the presence of resistant bacteria in a central laboratory. Using the new approach to estimate the extent of the resistance problem in human and livestock helps us to see what the differences and similarities are in quite different circumstances. Ultimately, we would like to take a similar approach for livestock and humans because this will enable information on antimicrobial resistance to be shared and interpreted simultaneously. We have designed a questionnaire for stakeholders to inform us on what they see as advantages and disadvantages of the new method. This information will guide the design of strategies of how to implement the new methods in the routine activities that are needed to prevent and curb antimicrobial resistance.

Call

2019 - Call on Diagnostics and Surveillance