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Optimizing Tactics for Use of the U.S. Antiviral Strategic National Stockpile for Pandemic Influenza

机译:优化用于大流行性流感的美国抗病毒战略国家储备的使用策略

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摘要

In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.
机译:2009年,全球的公共卫生机构都在努力减轻源自猪的甲型流感(pH1N1)病毒的影响。这些努力包括加强监视,远离社会,采取卫生措施以及有针对性地使用抗病毒药物预防感染(预防)。此外,建议对某些患者亚组采用积极的抗病毒治疗,以减轻症状的严重程度和持续时间。为了协助各州和其他地方满足这些需求,美国政府在大流行开始后的几周内,将其四分之一的抗病毒药物分发到了国家战略储备中。但是,尚无定量模型来指导剩余库存与大流行传播或严重程度有关的地理时间分布。我们提出了一种战术优化模型,用于分配这种库存以在大流行早期(例如2009 pH1N1)的早期阶段(在广泛使用特定菌株疫苗之前)来处理感染病例。我们的优化方法有效地搜索了应用于美国城市内部和城市之间的大流行性流感传播随机网络模型的大量干预策略。最终的优化策略取决于病毒的传播能力以及假定的抗病毒吸收和浪费速率(通过分配不当或丢失)。我们的结果表明,积极的基于社区的抗病毒治疗策略涉及将抗病毒药早期,广泛,按比例分配给各州,可能有助于减缓pH1N1等轻度可传播菌株的传播。对于更易传播的毒株,抗病毒药物使用的结果受分配间隔,每批装运量以及与大流行传播相关的装运时间选择的影响更大。这项研究支持以前的建模结果,表明在未来流感大流行的早期阶段,适当的抗病毒治疗可能是一种有效的缓解策略,从而增加了对优化分配策略和为公共卫生政策制定者提供战术指导的系统性工作的需求。

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