Evolutionary epidemiology models to predict the dynamics of antibiotic resistance

Abstract

The evolution of resistance to antibiotics is a major public health problem and an example of rapid adaptation under natural selection by antibiotics. The dynamics of antibiotic resistance within and between hosts can be understood in the light of mathematical models that describe the epidemiology and evolution of the bacterial population. “Between‐host” models describe the spread of resistance in the host community, and in more specific settings such as hospitalized hosts (treated by antibiotics at a high rate), or farm animals. These models make predictions on the best strategies to limit the spread of resistance, such as reducing transmission or adapting the prescription of several antibiotics. Models can be fitted to epidemiological data in the context of intensive care units or hospitals to predict the impact of interventions on resistance. It has proven harder to explain the dynamics of resistance in the community at large, in particular because models often do not reproduce the observed coexistence of drug‐sensitive and drug‐resistant strains. “Within‐host” models describe the evolution of resistance within the treated host. They show that the risk of resistance emergence is maximal at an intermediate antibiotic dose, and some models successfully explain experimental data. New models that include the complex host population structure, the interaction between resistance‐determining loci and other loci, or integrating the within‐ and between‐host levels will allow better interpretation of epidemiological and genomic data from common pathogens and better prediction of the evolution of resistance.

Hygiene Hampers Competitive Release of Resistant Bacteria in the Commensal Microbiota

“…It is common to study the spread of antibiotic resistant bacteria using the epidemiological compartmental modelling framework (12), and to connect our results to this rich tradition, we here show the main result of our study within this framework. The within-host diversity of bacteria is modelled as a subdivision of the host population into compartments with different portions of different bacterial strains.…”

“…This sits most naturally within the theoretical framework of metacommunity ecology (10,11), and we will frame both informal discussion and mathematical analysis using this approach. However, since metacommunity theory is new to antibiotic resistance studies, we also reproduce the key result within the epidemiological compartmental modelling framework that is currently standard in the field (12). (See Supplement A for details.…”

Simulating the Influence of Conjugative Plasmids Kinetic Values on the Multilevel Dynamics of Antimicrobial Resistance in a Membrane Computing Model

“…The research involves a complex, multilevel, multiparametric, and interactive landscape, involving genes, cells, populations, communities, hosts, and factors that influence transmission and selection. However, this problem can be approached using novel computational models integrating within-host and between-host modeling (14,15). Multilevel membrane computing models can provide an ecosystem-like framework composed of discrete independent but interactive units mimicking biological ones in a multi-hierarchical landscape of nested entities (e.g., genes inside plasmids, plasmids inside bacteria, bacteria inside microbiota, microbiota inside hosts, hosts inside the hospital, and interacting with the community) (12).…”

Switching Logistic Maps to Design Cycling Approaches Against Antimicrobial Resistance

“…While theoretical approaches to mitigate drug resistance have been mainly developed at between-host level [37,8], too little has been directed to investigate within-host strategies against antimicrobial resistance [23]. However, previous within-host control strategies are only developed for switched linear systems [21].…”