Antimicrobial Resistance Control through Adaptive healthcare NEtworks – ARCANE

The burden of healthcare-associated infections has increased over the last decades, especially due to the rising prevalence of antimicrobial resistance in opportunistic bacterial pathogens. The treatment of patients infected with antibiotic-resistant bacteria (ARB) is compromised due to the reduced effectiveness of therapy with standard antibiotics. Any ARB introduction into a hospital may be amplified by transmission among patients and staff, and later exported by discharged patients. Indeed, far from being isolated entities, hospitals form an important part of the ARB transmission pathway across all potential reservoirs.
Several studies have underlined the importance of shared patients for the spread of ARB between hospitals. By analysing flows of patients, they were able to reconstruct the healthcare network (HNet) connecting all hospitals within a country. Their results have led to recommendations that explicitly take this network into account for selecting hospitals for sentinel surveillance or targeted infection control measures.
However, current analyses use a static representation of the HNet based on aggregated numbers of patients over time. This simplification may bias our understanding of epidemiological dynamics and hinder our capacity to design efficient control and surveillance strategies, because temporal patterns in both individual patient care pathways and in the HNet may have different effects on the spread of ARB.
The purpose of the ARCANE project is to bring the HNet paradigm to a level enabling to grasp the complexity of patient care pathways. First, we will analyse how time aggregation and properties of patient care pathways may affect the shape and vulnerability of the HNet. Then, we will propose an integrative dynamic model of ARB spread along the HNet accounting for these complexities. Hence, we will be able to assess the impact of specific ARB introductions and the effectiveness of newly designed network-based control strategies.