Institut Pasteur, Université Paris Cité, Epidemiology and Modelling of Antibiotic Evasion (EMAE) unit, Paris, France.
Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, Inserm U1018, CESP, Anti-infective evasion and pharmacoepidemiology team, Montigny-Le-Bretonneux, France.
Elife. 2024 Mar 7;13:e85701. doi: 10.7554/eLife.85701.
Non-pharmaceutical interventions implemented to block SARS-CoV-2 transmission in early 2020 led to global reductions in the incidence of invasive pneumococcal disease (IPD). By contrast, most European countries reported an increase in antibiotic resistance among invasive isolates from 2019 to 2020, while an increasing number of studies reported stable pneumococcal carriage prevalence over the same period. To disentangle the impacts of the COVID-19 pandemic on pneumococcal epidemiology in the community setting, we propose a mathematical model formalizing simultaneous transmission of SARS-CoV-2 and antibiotic-sensitive and -resistant strains of . To test hypotheses underlying these trends five mechanisms were built into the model and examined: (1) a population-wide reduction of antibiotic prescriptions in the community, (2) lockdown effect on pneumococcal transmission, (3) a reduced risk of developing an IPD due to the absence of common respiratory viruses, (4) community azithromycin use in COVID-19 infected individuals, (5) and a longer carriage duration of antibiotic-resistant pneumococcal strains. Among 31 possible pandemic scenarios involving mechanisms individually or in combination, model simulations surprisingly identified only two scenarios that reproduced the reported trends in the general population. They included factors (1), (3), and (4). These scenarios replicated a nearly 50% reduction in annual IPD, and an increase in antibiotic resistance from 20% to 22%, all while maintaining a relatively stable pneumococcal carriage. Exploring further, higher SARS-CoV-2 R values and synergistic within-host virus-bacteria interaction mechanisms could have additionally contributed to the observed antibiotic resistance increase. Our work demonstrates the utility of the mathematical modeling approach in unraveling the complex effects of the COVID-19 pandemic responses on AMR dynamics.
2020 年初实施的非药物干预措施阻断了 SARS-CoV-2 的传播，导致全球侵袭性肺炎球菌病 (IPD) 的发病率下降。相比之下，大多数欧洲国家报告称，2019 年至 2020 年期间，侵袭性分离株的抗生素耐药性增加，而同期越来越多的研究报告称肺炎球菌带菌率稳定。为了解 COVID-19 大流行对社区环境中肺炎球菌流行病学的影响，我们提出了一个数学模型，该模型将 SARS-CoV-2 以及抗生素敏感和耐药株的同时传播形式化。为了检验这些趋势背后的假设，我们将五种机制构建到模型中并进行了检验：(1) 社区范围内抗生素处方的普遍减少，(2) 封锁对肺炎球菌传播的影响，(3) 由于常见呼吸道病毒的缺失，IPD 发病风险降低，(4) COVID-19 感染者社区中阿奇霉素的使用，以及(5) 抗生素耐药性肺炎球菌株的携带时间延长。在涉及机制单独或组合的 31 种可能的大流行情景中，模型模拟令人惊讶地仅确定了两种情景可以复制一般人群中的报告趋势。它们包括因素(1)、(3) 和 (4)。这些情景再现了每年 IPD 减少近 50%，以及抗生素耐药性从 20%增加到 22%，同时保持相对稳定的肺炎球菌带菌率。进一步探索表明，更高的 SARS-CoV-2 R 值和宿主内病毒-细菌相互作用的协同机制可能进一步导致了观察到的抗生素耐药性增加。我们的工作证明了数学建模方法在揭示 COVID-19 大流行应对措施对 AMR 动态的复杂影响方面的效用。
