Abstract
AbstractAntimicrobial resistance (AMR) poses an urgent public health challenge. To improve patient outcomes and design interventions we must identify patient characteristics which predict the presence of AMR pathogens. One potential and commonly collected patient characteristic is host age, consensus remains elusive regarding its impact on the probability of infecting pathogens being resistant to antimicrobials. Here, we employ a meta-analysis to consolidate and compare these previous studies and examine the relationship between antibiotic resistance and host age across bacteria and antibiotics. We show that although the probability that infecting bacteria are antimicrobial resistant increases with host age on average, diverse patterns exist across antibiotic classes and bacterial genera, including negative, humped, and U-shaped relationships. We further illustrate, using a compartmental epidemiological model, that this variation is likely driven by differences in antibiotic consumption or incidence of bacterial infection/carriage between age groups, combined with age assortative transmission. These findings imply that empirical antibiotic therapy could be improved by considering age-specific local resistance levels (compared with overall local resistance levels), resulting in improved treatment success and reduced spread of antibiotic resistance. They additionally display consequences of assuming population homogeneity in epidemiological models. Finally, they indicate that the landscape of the already severe resistance crisis is likely to change as the age distribution of the human population shifts.
Publisher
Cold Spring Harbor Laboratory