The evolution of antibiotic resistance in a structured host population

Abstract

The evolution of antibiotic resistance in opportunistic pathogens such as Streptococcus pneumoniae, Escherichia coli or Staphylococcus aureus is a major public health problem, as infection with resistant strains leads to prolonged hospital stay and increased risk of death. Here, we develop a new model of the evolution of antibiotic resistance in a commensal bacterial population adapting to a heterogeneous host population composed of untreated and treated hosts, and structured in different host classes with different antibiotic use. Examples of host classes include age groups and geographic locations. Explicitly modelling the antibiotic treatment reveals that the emergence of a resistant strain is favoured by more frequent but shorter antibiotic courses, and by higher transmission rates. In addition, in a structured host population, localized transmission in host classes promotes both local adaptation of the bacterial population and the global maintenance of coexistence between sensitive and resistant strains. When transmission rates are heterogeneous across host classes, resistant strains evolve more readily in core groups of transmission. These findings have implications for the better management of antibiotic resistance: reducing the rate at which individuals receive antibiotics is more effective to reduce resistance than reducing the duration of treatment. Reducing the rate of treatment in a targeted class of the host population allows greater reduction in resistance, but determining which class to target is difficult in practice.

Duration of antibiotic treatment for common infections in English primary care: cross sectional analysis and comparison with guidelines

“… 14 Little attention has been given to the possibility of reducing antibiotic overuse in primary care by minimising unnecessarily prolonged treatment. 15 Historically, general practitioners have been taught that antibiotic courses should be long enough to prevent the development of antibiotic resistance in the infection that is being treated, based on evidence of the emergence of resistance frequently being related to suboptimal dosing of penicillins in the treatment of Streptococcus pneumoniae . 16 However, current concerns primarily relate to the development of resistance in common commensal bacteria, rather than in the ones causing the infections, where there is increasing evidence that the opposite is true—the longer the exposure to antibiotic the greater the development of antibiotic resistance, which then leads to a greater risk of resistance in subsequent infections.…”

Resistance diagnostics as a public health tool to combat antibiotic resistance: A model-based evaluation

“…Our focus on homogenous, closed populations ensures that R 0 maximization is always favored by selection, simplifying the evolutionary analysis (55). However, the basic idea underlying our analysis of modulating strain-fitness landscapes applies more broadly to models where R 0 is not a sufficient proxy for fitness, such as in cases of multiple carriage (55), host population structure (56), or an open population (28).…”

The role of “spillover” in antibiotic resistance

“…We adapted the WHN model to include multiple, interacting populations using a structured host population approach inspired by Blanquart et al (46). Interactions between populations are modulated by the proportion ε of a population’s contacts that are in other populations.…”