Department of Organismic & Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America.
PLoS Comput Biol. 2020 Jul 6;16(7):e1008010. doi: 10.1371/journal.pcbi.1008010. eCollection 2020 Jul.
Antibiotic-resistant infections are a growing threat to human health, but basic features of the eco-evolutionary dynamics remain unexplained. Most prominently, there is no clear mechanism for the long-term coexistence of both drug-sensitive and resistant strains at intermediate levels, a ubiquitous pattern seen in surveillance data. Here we show that accounting for structured or spatially-heterogeneous host populations and variability in antibiotic consumption can lead to persistent coexistence over a wide range of treatment coverages, drug efficacies, costs of resistance, and mixing patterns. Moreover, this mechanism can explain other puzzling spatiotemporal features of drug-resistance epidemiology that have received less attention, such as large differences in the prevalence of resistance between geographical regions with similar antibiotic consumption or that neighbor one another. We find that the same amount of antibiotic use can lead to very different levels of resistance depending on how treatment is distributed in a transmission network. We also identify parameter regimes in which population structure alone cannot support coexistence, suggesting the need for other mechanisms to explain the epidemiology of antibiotic resistance. Our analysis identifies key features of host population structure that can be used to assess resistance risk and highlights the need to include spatial or demographic heterogeneity in models to guide resistance management.
抗生素耐药性感染对人类健康构成了日益严重的威胁,但生态进化动力学的基本特征仍未得到解释。最突出的是,在中间水平上,没有明确的机制可以长期共存敏感和耐药菌株,这是监测数据中普遍存在的模式。在这里,我们表明,考虑到宿主群体的结构或空间异质性以及抗生素使用的可变性,可以在广泛的治疗覆盖率、药物疗效、耐药成本和混合模式下导致持续共存。此外,这种机制可以解释其他受到较少关注的耐药性流行病学令人困惑的时空特征,例如在抗生素使用相似的地理区域之间或彼此相邻的地区,耐药性的流行率存在很大差异。我们发现,相同数量的抗生素使用会导致耐药性水平非常不同,具体取决于治疗在传播网络中的分布方式。我们还确定了仅靠种群结构无法支持共存的参数范围,这表明需要其他机制来解释抗生素耐药性的流行病学。我们的分析确定了宿主种群结构的关键特征,可用于评估耐药风险,并强调需要在模型中包含空间或人口异质性,以指导耐药性管理。