估算流感疫苗效力的数学模型:西班牙巴伦西亚社区案例研究。

IF 8.8 3区 医学 Q1 Medicine
Carlos Andreu-Vilarroig , Rafael J. Villanueva , Gilberto González-Parra
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引用次数: 0

摘要

疫苗效力及其量化是正确设计公共卫生疫苗接种政策的关键概念。在这项工作中,我们提出了一个数学模型,用于估算流感疫苗在真实情况下的效力。具体而言,我们的模型是一个 SEIR 型流行病学模型,它将接种疫苗和未接种疫苗的人群区分开来。在数学上,其动态受非线性常微分方程系统支配,其中的非线性来自易感者和感染者之间的有效接触。本研究的两个关键方面是,我们使用了基于巴伦西亚社区老年人真实数据的疫苗随时间变化的分布情况,并且校准过程考虑到了在一个流感季节中,特定比例的人口会感染流感。为了考虑疫苗的有效性,模型中加入了一个参数,即疫苗衰减系数,它与疫苗对流感病毒的有效性有关。在此框架下,为了校准模型参数并获得流感疫苗效力估计值,我们考虑了西班牙巴伦西亚社区 2016-2017 年流感季节的情况,使用了已接种疫苗和未接种疫苗的流感报告病例。为了确保模型的可识别性,我们选择对不同情况下的参数进行确定性校准,并找出误差最小的参数,以确定疫苗效力。校准结果表明,为 2016-2017 年流感季节开发的流感疫苗有效率约为 76.7%,未接种者的感染风险是接种者的五倍。这一估计与之前一些与流感疫苗相关的研究部分吻合。本研究提出了一种新的综合数学方法来研究流感疫苗的效力,并进一步深入探讨了这一重要的公共卫生课题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mathematical modeling for estimating influenza vaccine efficacy: A case study of the Valencian Community, Spain.

Vaccine efficacy and its quantification is a crucial concept for the proper design of public health vaccination policies. In this work we proposed a mathematical model to estimate the efficacy of the influenza vaccine in a real-word scenario. In particular, our model is a SEIR-type epidemiological model, which distinguishes vaccinated and unvaccinated populations. Mathematically, its dynamics is governed by a nonlinear system of ordinary differential equations, where the non-linearity arises from the effective contacts between susceptible and infected individuals. Two key aspects of this study is that we use a vaccine distribution over time that is based on real data specific to the elderly people in the Valencian Community and the calibration process takes into account that over one influenza season a specific proportion of the population becomes infected with influenza. To consider the effectiveness of the vaccine, the model incorporates a parameter, the vaccine attenuation factor, which is related with the vaccine efficacy against the influenza virus. With this framework, in order to calibrate the model parameters and to obtain an influenza vaccine efficacy estimation, we considered the 2016–2017 influenza season in the Valencian Community, Spain, using the influenza reported cases of vaccinated and unvaccinated. In order to ensure the model identifiability, we choose to deterministically calibrate the parameters for different scenarios and we find the one with the minimum error in order to determine the vaccine efficacy. The calibration results suggest that the influenza vaccine developed for 2016–2017 influenza season has an efficacy of approximately 76.7%, and that the risk of becoming infected is five times higher for an unvaccinated individual in comparison with a vaccinated one. This estimation partially agrees with some previous studies related to the influenza vaccine. This study presents a new integrated mathematical approach to study the influenza vaccine efficacy and gives further insight into this important public health topic.

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来源期刊
Infectious Disease Modelling
Infectious Disease Modelling Mathematics-Applied Mathematics
CiteScore
17.00
自引率
3.40%
发文量
73
审稿时长
17 weeks
期刊介绍: Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.
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