Simulation of antibiotic vs bacteria conflict

The ability to hydrolyse a lactam molecule is necessary for the survival of antibiotic resistant bacteria. Thus, bacteria have evolved to use beta-lactamase enzymes to hydrolyse lactam rings found in many antibiotics, rendering them ineffective. Resistance to antibiotics predates their use in medicine, as beta-lactamase function is believed to have first arisen more than two billion years ago, although it is the intensive use of antibiotics by the human population that has accelerated the recent well-publicised emergence of resistant strains.
The use of simulation in the study of disease and epidemiology is increasingly common. Often, the population is modelled down to the granularity of the individual. Approaches to the mathematical representation of disease transmission include network models, in which an individual has a probability of being infected by social contacts, group models where infection is via members of a group such as a household or workplace, distance based models where the spread of infection is a decreasing probabilistic function of spatial distance, and patch models where specific locations such as a town, school, or farm may become infected and then potentially transmit this to neighbouring patches.
We seek to understand the dynamics of the conflict between antibiotics and bacteria, and the factors which lead to faster and more dangerous evolution of antibiotic resistance. We will identify regions of model's parameter space that lead to more or less rapid evolution of resistance. In particular, we will compare different strategies for the deployment of classes of antibiotic, such as using all available drugs at once, giving different medicines to different groups of infected hosts, holding some back in reserve and so forth.
We will carry out simulations of sufficient granularity to capture the essential features of the conflict. These are likely to include approaches such as network models, genetic simulations, distance-based and group-based models, all of sufficient granularity to represent evolutionary and epidemiological processes underlying the behaviour, as well as representing aspects of the chemistry and biochemistry of antibiotic resistance.