在2020年COVID-19大流行期间,探索塑造Streptococcus pneumoniae抗生素耐药性模式的因素
Aleksandra Kovacevic1,2, David R M Smith1,2,3,4, Eve Rahbé1,2
1Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE) unit, Paris, France.
随着COVID-19大流行,侵入性肺炎球菌病 (IPD) 减少了,但抗生素耐药性增加了. 数学建模确定了减少抗生素处方,减少呼吸道病毒和阿兹胺的使用是这些趋势的关键驱动因素.
科学领域:
- 流行病学 流行病学
- 数学建模的数学建模
- 传染病的动态传染病的动态.
背景情况:
- 针对SARS-CoV-2的非药物干预措施在全球范围内减少了侵入性肺炎球菌病 (IPD).
- 与此同时,尽管携带流行率稳定,但在欧洲Streptococcus pneumoniae的抗生素耐药性增加.
- COVID-19大流行对肺炎球菌流行病学的复杂影响需要解开.
研究的目的:
- 开发一个数学模型,模拟SARS-CoV-2和抗生素敏感/耐药S.肺炎的同时传播.
- 调查 пандемия期间影响肺炎球菌流行病学的五种潜在机制.
- 确定解释IPD,抗生素耐药性和携带观察到的趋势的流行病情景.
主要方法:
- 构建了一个数学模型来模拟同时传输动态.
- 纳入了五个关键机制:减少抗生素处方,封锁效应,减少病毒共感染,社区使用阿兹胺,以及改变运输时间.
- 模型模拟探讨了31种流行病情景,单独和组合,以匹配流行病学数据.
主要成果:
- 只有两种情景,包括减少抗生素处方,减少病毒共感染,以及社区使用阿兹胺,复制了观察到的趋势.
- 这些情景预测每年IPD减少50%左右,抗生素耐药性从20%上升到22%.
- 在这些模拟条件下,肺炎球菌携带流行率保持相对稳定.
结论:
- 减少抗生素处方,减少病毒共感染,以及在COVID-19患者中使用特定抗生素显著影响了肺炎球菌流行病学.
- 数学建模有效阐明了流行病反应和抗菌素耐药性 (AMR) 动态之间的复杂相互作用.
- 对SARS-CoV-2更高的传染性和病毒-细菌相互作用的进一步研究可能会解释抗生素耐药性的额外增加.
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