Mathematical modelling of the emergence and spread of antibiotic resistant bacteria in healthcare settings: a stochastic approach

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See Case for Support for abbreviations and references.Antibiotic resistance of pathogenic bacteria has historically arisen in parallel with the development of new antibiotics; this race posing a major health problem worldwide where bacteria seem to be winning [33]. A paradigmatic example is methicillin-resistant Staphylococcus aureus (MRSA), which can cause severe infections in the bloodstream and the lung and that, after developing resistance against penicillin, has become resistant also against a second antibiotic, methicillin. Development of resistance against antibiotic can occur due to antibiotic pressure, where non adequate prescription policies play a fundamental role. This is one of the reasons for DRB being a particular challenging problem in healthcare facilities, together with other reasons such as the presence of aged individuals with weaken immune systems. The problem of the presence of DRB in HCSs has taken the next step by their spread in the community (non-healthcare environments). This has led to the appearance of new strains which are able to cause severe infections in healthy individuals. Moreover, the infiltration of these new community-related strains in HCSs has become an additional challenge.In order to avoid the emergence and spread of DRB in HCSs, different strategies are usually followed: appropriate antibiotic prescription policies, management of staffing levels, isolation of infected patients, compliance of hygiene procedures, etc. However, most of HCSs usually follow a combination of these procedures, and the individual efficacy of each of them is hard to measure. This quantification is important not only due to the scarcity of resources in these clinical environments, but also because some of these policies entail moral and ethical problems. Mathematical models have proven to be a robust tool for addressing the efficacy of these individual strategies, as well as for identifying the factors involved in the emergence and spread of DRB in HCSs. The aim of this fellowship is to contribute to the mathematical modelling in the area, in order to answer a number of open questions. Particular questions that will be addressed within this fellowship are: which is the importance of some factors, such as the contamination of the healthcare setting environment (for example, equipment), in the spread of resistant bacteria in healthcare settings? How does this spread occur in different healthcare settings (for example, in hospitals versus nursing homes)? What is the impact caused by the existing heterogeneities among individuals within the HCS (healthy individuals, such as HCWs, versus moderate or severe ill patients; adults versus children; patients under antibiotic treatment, ...)?. Additional questions to be addressed within this fellowship are related to the use of clinical data for refining the mathematical models, and the consideration of new mathematical models that can explain the process by which DRB arises within a particular individual.The emergence and spread of DRB is a major problem worldwide. However, due to financial reasons (for example, some antibiotics newly developed are only effective for a few years, with the subsequent development of new DRB strains) the number of pharmaceutical companies working in new antibiotics development is scarce, and governmental financial incentives are usually required [24]. Moreover, it is worth noting that, in Europe, it has been estimated that infections with MDRB cause around 25000 deaths per year [25], with an estimated cost of 16 million additional bed-days (translating into 7 billion Euros in direct medical costs) [19]. Thus, it is necessary to combine the development of new antibiotics with control intervention measures to avoid the emergence and the spread of DRB among HCSs, which is at the same time crucial to implement intervention strategies based in quantitative knowledge.