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The impact of regular school closure on seasonal influenza epidemics: a data-driven spatial transmission model for Belgium

机译:常规学校关闭对季节性流感流行性流行的影响:比利时数据驱动空间传输模型

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School closure is often considered as an option to mitigate influenza epidemics because of its potential to reduce transmission in children and then in the community. The policy is still however highly debated because of controversial evidence. Moreover, the specific mechanisms leading to mitigation are not clearly identified. We introduced a stochastic spatial age-specific metapopulation model to assess the role of holiday-associated behavioral changes and how they affect seasonal influenza dynamics. The model is applied to Belgium, parameterized with country-specific data on social mixing and travel, and calibrated to the 2008/2009 influenza season. It includes behavioral changes occurring during weekend vs. weekday, and holiday vs. school-term. Several experimental scenarios are explored to identify the relevant social and behavioral mechanisms. Stochastic numerical simulations show that holidays considerably delay the peak of the season and mitigate its impact. Changes in mixing patterns are responsible for the observed effects, whereas changes in travel behavior do not alter the epidemic. Weekends are important in slowing down the season by periodically dampening transmission. Christmas holidays have the largest impact on the epidemic, however later school breaks may help in reducing the epidemic size, stressing the importance of considering the full calendar. An extension of the Christmas holiday of 1 week may further mitigate the epidemic. Changes in the way individuals establish contacts during holidays are the key ingredient explaining the mitigating effect of regular school closure. Our findings highlight the need to quantify these changes in different demographic and epidemic contexts in order to provide accurate and reliable evaluations of closure effectiveness. They also suggest strategic policies in the distribution of holiday periods to minimize the epidemic impact.
机译:学校关闭通常被认为是减轻流感流行病的选项,因为它可能降低在儿童中的传输,然后在社区中减少传播。然而,由于有争议的证据,政策仍然高度辩论。此外,没有明确识别导致缓解的具体机制。我们介绍了一个随机空间年龄特异性的核酸模型,以评估假日相关行为变化的作用以及它们如何影响季节性流感动态。该模型适用于比利时,参数化,参数化了关于社会混合和旅行的国家特定数据,并校准到2008/2009流感季节。它包括周末与平日期间发生的行为变化,以及假期与学术期间。探索了几种实验方案来确定相关的社会和行为机制。随机数值模拟表明,假期大大延迟了季节的高峰并减轻了它的影响。混合模式的变化负责观察到的效果,而行为行为的变化不会改变疫情。周末通过定期阻尼传输来减慢季节很重要。圣诞假期对该流行病的影响最大,但后来学校休息可能有助于降低疫情规模,强调考虑完整日历的重要性。圣诞节假期为1周的延伸可能进一步减轻流行病。个人在假期建立联系方式的方式是解释普通学校封闭效果的关键成分。我们的研究结果强调了在不同人口和流行环境中量化这些变化的需要,以便提供准确可靠的闭环效果评估。他们还建议在假期期间分配战略政策,以尽量减少流行影响。

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