Integrating sewage and hospital-based surveillance data on antimicrobial resistance: resistance type affects community resistance patterns

Using waste water to detect and quantify abundances of antibiotic resistance genes has the potential to improve our understanding of resistance in the community and study the relationship with resistance in hospitals. By investigating similarities and differences in patterns and drivers of resistance in hospital and sewage surveillance data, and how this differs between resistance types, we can gain insights in this relationship.Here we use a multivariate regression model to investigate correlations between sewage and hospital data, and the effects of antimicrobial usage on hospital and community resistance levels. A Poisson model for resistance gene abundance in waste water (Global Sewage Surveillance Project) and a binomial model for clinical isolate resistance testing (EARS-Net, ECDC) are combined through country-level covariance between the datasets.Our results show that fluoroquinolone resistance was positively associated with antimicrobial consumption (ESAC-Net, ECDC) in both the hospital and the community, whereas carbapenem resistance was not. After taking antimicrobial consumption into account, resistance to fluoroquinolones in hospitals and waste water was not correlated, but carbapenem resistance was. This indicates that emergence and transmission of different types of resistance have different drivers in hospitals and the community, and highlights the need for flexible approaches to surveillance and prevention.