Within-Host Mathematical Models of Antibiotic Resistance

Mathematical models have been used to study the spread of infectious diseases from person to person. More recently studies are developing within-host modeling which provides an understanding of how pathogens—bacteria, fungi, parasites, or viruses—develop, spread, and evolve inside a single individual and their interaction with the host’s immune system. Such models have the potential to provide a more detailed and complete description of the pathogenesis of diseases within-host and identify other influencing factors that may not be detected otherwise. Mathematical modelsMathematical models can be used to aid understanding of the global antibiotic resistanceAntibiotic resistance (ABR) crisis and identify new ways of combating this threat. ABR occurs when bacteria respond to random or selective pressures and adapt to new environments through the acquisition of new genetic traits. This is usually through the acquisition of a piece of DNADNA from other bacteria, a process called horizontal gene transfer (HGT)Horizontal gene transfer (HGT), the modification of a piece of DNA within a bacterium, or through. Bacteria have evolved mechanisms that enable them to respond to environmental threats by mutationMutations, and horizontal gene transfer (HGT)Horizontal gene transfer (HGT): conjugation; transduction; and transformationTransformation. A frequent mechanism of HGTHorizontal gene transfer (HGT) responsible for spreading antibiotic resistanceAntibiotic resistance on the global scale is conjugation, as it allows the direct transfer of mobile genetic elements (MGEs)Mobile genetic elements (MGEs). Although there are several MGEsMobile genetic elements (MGEs), the most important MGEsMobile genetic elements (MGEs) which promote the development and rapid spread of antimicrobial resistanceAntimicrobial resistance (AMR) genes in bacterial populations are plasmidsPlasmids and transposonsTransposons. Each of the resistance-spread-mechanisms mentioned above can be modeled allowing us to understand the process better and to define strategies to reduce resistance.