Moghadas Seyed M, Bowman Christopher S, Röst Gergely, Wu Jianhong
Institute for Biodiagnostics, National Research Council Canada, Winnipeg, Manitoba, Canada.
PLoS One. 2008 Mar 19;3(3):e1839. doi: 10.1371/journal.pone.0001839.
The emergence of neuraminidase inhibitor resistance has raised concerns about the prudent use of antiviral drugs in response to the next influenza pandemic. While resistant strains may initially emerge with compromised viral fitness, mutations that largely compensate for this impaired fitness can arise. Understanding the extent to which these mutations affect the spread of disease in the population can have important implications for developing pandemic plans.
METHODOLOGY/PRINCIPAL FINDINGS: By employing a deterministic mathematical model, we investigate possible scenarios for the emergence of population-wide resistance in the presence of antiviral drugs. The results show that if the treatment level (the fraction of clinical infections which receives treatment) is maintained constant during the course of the outbreak, there is an optimal level that minimizes the final size of the pandemic. However, aggressive treatment above the optimal level can substantially promote the spread of highly transmissible resistant mutants and increase the total number of infections. We demonstrate that resistant outbreaks can occur more readily when the spread of disease is further delayed by applying other curtailing measures, even if treatment levels are kept modest. However, by changing treatment levels over the course of the pandemic, it is possible to reduce the final size of the pandemic below the minimum achieved at the optimal constant level. This reduction can occur with low treatment levels during the early stages of the pandemic, followed by a sharp increase in drug-use before the virus becomes widely spread.
CONCLUSIONS/SIGNIFICANCE: Our findings suggest that an adaptive antiviral strategy with conservative initial treatment levels, followed by a timely increase in the scale of drug-use, can minimize the final size of a pandemic while preventing large outbreaks of resistant infections.
神经氨酸酶抑制剂耐药性的出现引发了人们对于在应对下一次流感大流行时谨慎使用抗病毒药物的担忧。虽然耐药菌株最初出现时病毒适应性可能受损,但能够在很大程度上弥补这种受损适应性的突变可能会产生。了解这些突变在多大程度上影响疾病在人群中的传播,对于制定大流行应对计划具有重要意义。
方法/主要发现:通过使用确定性数学模型,我们研究了在存在抗病毒药物的情况下人群范围内耐药性出现的可能情形。结果表明,如果在疫情爆发过程中治疗水平(接受治疗的临床感染比例)保持恒定,存在一个能使大流行最终规模最小化的最佳水平。然而,高于最佳水平的积极治疗会大幅促进高传播性耐药突变体的传播,并增加感染总数。我们证明,即使治疗水平保持适度,但当通过采取其他遏制措施进一步延迟疾病传播时,耐药性疫情更容易发生。不过,通过在大流行过程中改变治疗水平,有可能将大流行的最终规模降低到在最佳恒定水平下所能达到的最小值以下。这种降低可以在大流行早期阶段采用低治疗水平,随后在病毒广泛传播之前大幅增加药物使用量来实现。
结论/意义:我们的研究结果表明,一种采用保守初始治疗水平,随后及时扩大药物使用规模的适应性抗病毒策略,既能将大流行的最终规模最小化,又能防止耐药性感染的大规模爆发。