Universidad Carlos III de Madrid, Computer Science Department, Leganes, Spain.
Ministerio de Sanidad, Madrid, Spain.
BMJ Open. 2022 Dec 9;12(12):e065937. doi: 10.1136/bmjopen-2022-065937.
We analyse the impact of different vaccination strategies on the propagation of COVID-19 within the Madrid metropolitan area, starting on 27 December 2020 and ending in Summer of 2021.
The predictions are based on simulation using EpiGraph, an agent-based COVID-19 simulator. We first summarise the different models implemented in the simulator, then provide a comprehensive description of the vaccination model and define different vaccination strategies. The simulator-including the vaccination model-is validated by comparing its results with real data from the metropolitan area of Madrid during the third COVID-19 wave. This work considers different COVID-19 propagation scenarios for a simulated population of about 5 million.
The main result shows that the best strategy is to vaccinate first the elderly with the two doses spaced 56 days apart; this approach reduces the final infection rate by an additional 6% and the number of deaths by an additional 3% with respect to vaccinating first the elderly at the interval recommended by the vaccine producer. The reason is the increase in the number of vaccinated individuals at any time during the simulation.
The existing level of detail and maturity of EpiGraph allowed us to evaluate complex scenarios and thus use it successfully to help guide the strategy for the COVID-19 vaccination campaign of the Spanish health authorities.
我们分析了从 2020 年 12 月 27 日开始至 2021 年夏季,马德里大都市区内不同疫苗接种策略对 COVID-19 传播的影响。
预测是基于使用 EpiGraph(一种基于代理的 COVID-19 模拟器)进行模拟的结果。我们首先总结了模拟器中实现的不同模型,然后全面描述了疫苗接种模型,并定义了不同的疫苗接种策略。通过将模拟器的结果与马德里大都市区第三次 COVID-19 浪潮期间的实际数据进行比较,对包括疫苗接种模型在内的模拟器进行了验证。这项工作考虑了大约 500 万模拟人口的不同 COVID-19 传播场景。
主要结果表明,最佳策略是先为老年人接种两剂疫苗,间隔 56 天;与按照疫苗生产商推荐的间隔时间先为老年人接种疫苗相比,这种方法使最终感染率额外降低 6%,死亡人数额外降低 3%。原因是在模拟过程中的任何时候,接种疫苗的人数都会增加。
EpiGraph 具有现有的详细程度和成熟度,使我们能够评估复杂的场景,并成功地将其用于帮助指导西班牙卫生当局 COVID-19 疫苗接种运动的策略。