Seasonal influenza: Modelling approaches to capture immunity propagation
Seasonal influenza: Modelling approaches to capture immunity propagation
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DOI：
10.1371/journal.pcbi.1007096
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发表时间：
2019-10-01
影响因子：
4.3
通讯作者：
Keeling, Matt J.
中科院分区：
文献类型：
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作者：
Hill, Edward M.;Petrou, Stavros;Keeling, Matt J.
流感是一种传染性很强的呼吸道疾病，可导致严重的健康并发症。以季节性暴发为特征的政策制定者面临的一个关键挑战是实施措施，成功地减轻每年的公共卫生负担。季节性流感疫苗接种计划是提供具有成本效益的预防流感及其并发症的既定方法。传播模型一直是疫苗规划分析的基本组成部分，为有效利用有限的资源提供信息。然而，这些模型通常孤立地对待每个流感季节和该季节内传播的每一种毒株。通过建立一个明确包括多种免疫传播机制的数学模型，然后通过统计方法对英国流感相关疫苗和流行病学数据进行拟合，我们试图量化前一个流感季节的流行病学事件改变下一个季节开始时的易感性的程度。研究结果表明，下一个季节对某一特定流感毒株类型的易感性在最大程度上是通过当前季节该毒株类型的自然感染来调节的。疫苗残留免疫的作用较小。展望未来，采用带有免疫传播的流感传播模型框架将为评估季节性疫苗接种计划的影响提供一种全面的方式。季节性流感对全球公共卫生构成严重问题，是发病率和死亡率的重要贡献者。在英格兰，有一个长期的国家疫苗接种计划，为高危群体和儿童接种疫苗，提供部分保护，使其免受感染。传输模型一直是分析的基本组成部分，为有限资源的有效利用提供信息。然而，这些模型通常孤立地对待每个季节和在该季节内传播的每个毒株。在这里，我们合并了多个数据源，以校准季节性流感的易感-潜伏感染-恢复型传播模型，纳入了四个主要毒株和机制，将前一个季节的流行病学结果与下一个季节开始时的免疫联系起来。从2009/10年度开始的九个流感季节的相关数据为我们提供了皇家全科医生学会(RCGP)研究和监测中心报告的流行病学过程、病毒学样本阳性、疫苗接种和效力属性以及全科医生流感样疾病会诊的估计。我们通过近似贝叶斯计算进行参数推断，以评估毒株的传播性、当前季节流感免疫对先前预防的依赖性以及流感病例确定的跨季节变异性。这在年度应变组成的模型和数据之间产生了合理的一致性。参数拟合表明，与来自感染的自然免疫相比，疫苗从一个季节到下一个季节的免疫传播较弱。将动态向前预测表明，虽然历史免疫在确定年度毒株组成方面发挥了重要作用，但疫苗效力的可变性阻碍了我们进行长期预测的能力。
Author summary Influenza, the flu, is a highly infectious respiratory disease that can cause serious health complications. Characterised by seasonal outbreaks, a key challenge for policy-makers is implementing measures to successfully lessen the public health burden on an annual basis. Seasonal influenza vaccine programmes are an established method to deliver cost-effective prevention against influenza and its complications. Transmission models have been a fundamental component of vaccine programme analysis, informing the efficient use of limited resources. However, these models generally treat each influenza season and each strain circulating within that season in isolation. By developing a mathematical model explicitly including multiple immunity propagation mechanisms, then fit to influenza-related vaccine and epidemiological data from England via statistical methods, we sought to quantify the extent that epidemiological events in the previous influenza season alter susceptibility at the onset of the following season. The findings suggest that susceptibility in the next season to a given influenza strain type is modulated to the greatest extent through natural infection by that strain type in the current season. Residual vaccine immunity has a lesser role. Prospectively, the adoption of influenza transmission modelling frameworks with immunity propagation would provide a comprehensive manner to assess the impact of seasonal vaccination programmes.Seasonal influenza poses serious problems for global public health, being a significant contributor to morbidity and mortality. In England, there has been a long-standing national vaccination programme, with vaccination of at-risk groups and children offering partial protection against infection. Transmission models have been a fundamental component of analysis, informing the efficient use of limited resources. However, these models generally treat each season and each strain circulating within that season in isolation. Here, we amalgamate multiple data sources to calibrate a susceptible-latent-infected-recovered type transmission model for seasonal influenza, incorporating the four main strains and mechanisms linking prior season epidemiological outcomes to immunity at the beginning of the following season. Data pertaining to nine influenza seasons, starting with the 2009/10 season, informed our estimates for epidemiological processes, virological sample positivity, vaccine uptake and efficacy attributes, and general practitioner influenza-like-illness consultations as reported by the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC). We performed parameter inference via approximate Bayesian computation to assess strain transmissibility, dependence of present season influenza immunity on prior protection, and variability in the influenza case ascertainment across seasons. This produced reasonable agreement between model and data on the annual strain composition. Parameter fits indicated that the propagation of immunity from one season to the next is weaker if vaccine derived, compared to natural immunity from infection. Projecting the dynamics forward in time suggests that while historic immunity plays an important role in determining annual strain composition, the variability in vaccine efficacy hampers our ability to make long-term predictions.