In the past year, a team of researchers at the IAS has been working on a project on antimicrobial resistance (AMR) in close collaboration with the Amsterdam Institute for Global Health and Development (AIGHD). They laid the foundations for a new framework to study AMR at global and local scale from a complex systems’ perspective.
The spreading of antimicrobial resistance (AMR) is an extremely complex problem. The dynamics of AMR is the result of a complex adaptive system that spans across several spatio-temporal scales: for example the interplay between bacterial evolution and antimicrobial drug exposure at microscopic scale; access to healthcare and self-medication, and the likelihood of exposure to resistant bacteria at home or in hospitals at mesoscopic scale; various policies and strategies in different countries at macroscopic scale. It is well known that the use and abuse of antibiotics is driving the spread of AMR to the point that it will become a major challenge for healthcare in the coming years. However, data on the prevalence of resistant bacteria is still sparse, especially in Low and Middle Income countries (LMICs) and current models to inform policy makers are still unable to offer accurate predictions.
In the past year, a team of researchers at the UvA Institute for Advanced Study (IAS) has been working on a project on AMR in close collaboration with the Amsterdam Institute for Global Health and Development (AIGHD). Embedded in the IAS Health Systems Complexity programme this line of research laid the foundations for a new framework to study AMR at global and local scale from a complex systems’ perspective.
While national information on AMR prevalence is lacking for many countries, their socio-economic and demographic profile is more extensively characterized. Our framework uses data from the World Health Organization and World Bank on over 10,000+ standardized metrics covering a wide range of indicators across countries to identify key factors associated with AMR.
Once fully developed, this new comprehensive framework will be able to fill current gaps in global AMR surveillance networks and identify data-driven criteria to steer surveillance investments and inform policy makers. In particular this approach could provide a solution to the urgent need of estimating the prevalence of AMR in LMICs for which data collection on AMR is economically or politically not feasible.
For this collaboration, the IAS received a financial contribution from the Amsterdam University Fund (AUF) to support the stay of a highly talented researcher, Dr. Antonio Cappuccio, in Amsterdam for a period of 6 months. The outcome of the joint effort between the IAS and AIGHD is a conceptual framework for complexity analysis of AMR. It forms the basis of several new international project proposals currently under submission. Given the scientific novelty of this complex systems’ perspective on AMR, this first step was crucial for the team to increase its competitiveness for obtaining larger grants and scale-up the current research endeavour.