Bongiorno Christian, Zino Lorenzo
CentraleSupélec, Mathématiques et Informatique pour la Complexité et les Systèmes, Université Paris-Saclay, 91190 Gif-sur-Yvette, France.
Faculty of Science and Engineering, University of Groningen, 9747 AG Groningen, The Netherlands.
Appl Netw Sci. 2022;7(1):12. doi: 10.1007/s41109-022-00449-z. Epub 2022 Mar 7.
We propose a multi-layer network model for the spread of an infectious disease that accounts for interactions within the family, between children in classes and schools, and casual contacts in the population. The proposed framework is designed to test several what-if scenarios on school openings during the vaccination campaigns, thereby assessing the safety of different policies, including testing practices in schools, diverse home-isolation policies, and targeted vaccination. We demonstrate the potentialities of our model by calibrating it on epidemiological and demographic data of the spring 2021 COVID-19 vaccination campaign in France. Specifically, we consider scenarios in which a fraction of the population is vaccinated, and we focus our analysis on the role of schools as drivers of the contagions and on the implementation of targeted intervention policies oriented to children and their families. We perform our analysis by means of a campaign of Monte Carlo simulations. Our findings suggest that transmission in schools may play a key role in the spreading of a disease. Interestingly, we show that children's testing might be an important tool to flatten the epidemic curve, in particular when combined with enacting temporary online education for classes in which infected students are detected. Finally, we test a vaccination strategy that prioritizes the members of large families and we demonstrate its good performance. We believe that our modeling framework and our findings could be of help for public health authorities for planning their current and future interventions, as well as to increase preparedness for future epidemic outbreaks.
我们提出了一种用于传染病传播的多层网络模型，该模型考虑了家庭内部、班级和学校中的儿童之间以及人群中的偶然接触。所提出的框架旨在测试疫苗接种运动期间学校开学的几种假设情景，从而评估不同政策的安全性，包括学校的检测措施、多样化的居家隔离政策以及有针对性的疫苗接种。我们通过根据2021年春季法国新冠疫苗接种运动的流行病学和人口统计学数据对模型进行校准，展示了我们模型的潜力。具体而言，我们考虑了部分人群接种疫苗的情景，并将分析重点放在学校作为传染驱动因素的作用以及针对儿童及其家庭的有针对性干预政策的实施上。我们通过蒙特卡洛模拟活动进行分析。我们的研究结果表明，学校中的传播可能在疾病传播中起关键作用。有趣的是，我们表明儿童检测可能是 flatten 疫情曲线的重要工具，特别是当与对检测出感染学生的班级实施临时在线教育相结合时。最后，我们测试了一种优先考虑大家庭成员的疫苗接种策略，并证明了其良好的效果。我们相信，我们的建模框架和研究结果可能有助于公共卫生当局规划其当前和未来的干预措施，以及提高对未来疫情爆发的准备程度。
