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

病原菌的抗生素耐药性在历史上与新抗生素的开发并行出现;这场竞赛在世界范围内构成了一个主要的健康问题，细菌似乎正在获胜[33]。一个典型的例子是耐甲氧西林金黄色葡萄球菌（MRSA），它可以引起血液和肺部的严重感染，并且在对青霉素产生耐药性后，也对第二种抗生素甲氧西林产生耐药性。抗生素耐药性的发展可能是由于抗生素的压力，其中不适当的处方政策发挥了根本作用。这是DRB在医疗机构中成为一个特别具有挑战性的问题的原因之一，以及其他原因，例如免疫系统较弱的老年人的存在。HCS中存在DRB的问题已经通过其在社区（非医疗环境）中的传播而迈出了下一步。这导致了能够在健康个体中引起严重感染的新菌株的出现。此外，这些新的社区相关菌株在HCS中的渗透也成为一个额外的挑战。为了避免HCS中DRB的出现和传播，通常采取不同的策略：适当的抗生素处方政策，人员配备水平的管理，感染患者的隔离，卫生程序的遵守等。然而，大多数HCS通常遵循这些程序的组合，而每一种药物的疗效都很难衡量。这种量化是重要的，不仅是因为这些临床环境中的资源稀缺，而且还因为这些政策中的一些涉及道德和伦理问题。事实证明，数学模型是一种强大的工具，可以解决这些单独策略的有效性，以及确定HCS中DRB出现和传播所涉及的因素。该奖学金的目的是为该领域的数学建模做出贡献，以回答一些悬而未决的问题。将在本奖学金中解决的特殊问题是：哪些是一些因素的重要性，如医疗环境（例如，设备）的污染，在医疗环境中耐药细菌的传播？这种传播在不同的医疗环境中是如何发生的（例如，在医院与疗养院）？HCS内个体间的现有异质性（健康个体，如HCW，与中度或重度疾病患者;成人与儿童;接受抗生素治疗的患者，.）造成的影响是什么？在这个奖学金中要解决的其他问题是有关使用临床数据来完善数学模型，并考虑新的数学模型，可以解释的过程中，DRB出现在一个特定的individual.The DRB的出现和蔓延是一个主要的问题世界各地。然而，由于经济原因（例如，一些新开发的抗生素仅有效几年，随后开发了新的DRB菌株），从事新抗生素开发的制药公司数量很少，通常需要政府的财政激励措施[24]。此外，值得注意的是，在欧洲，据估计，MDRB感染每年导致约25000人死亡[25]，估计额外花费1600万床日（转化为70亿欧元的直接医疗费用）[19]。因此，联合收割机的开发与控制干预措施相结合，是避免HCS中DRB发生和蔓延的必要措施，同时也是实施基于定量知识的干预策略的关键。

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.