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2021年比利时各省新冠确诊病例、住院情况、疫苗接种及国际旅行的实证分析。

Empirical analysis of COVID-19 confirmed cases, hospitalizations, vaccination, and international travel across Belgian provinces in 2021.

作者信息

Natalia Yessika Adelwin, Molenberghs Geert, Neyens Thomas, Hens Niel, Faes Christel

机构信息

I-BioStat, Data Science Institute, Hasselt University, Hasselt, Belgium.

I-Biostat, Leuven Biostatistics and Statistical Bioinformatics Centre, KU Leuven, Leuven, Belgium.

出版信息

PLoS One. 2025 May 23;20(5):e0322017. doi: 10.1371/journal.pone.0322017. eCollection 2025.

Abstract

In the absence of definitive treatments or vaccines, the primary strategy to mitigate the COVID-19 pandemic relied on non-pharmaceutical interventions. By the end of 2020, COVID-19 vaccines had been developed and initiated for preventive purposes. To better understand the association between various mitigation measures and their impact on the pandemic, we analyzed the effect of vaccination coverage, international travel, traveler positivity rates, and the stringency of public health measures on the incidence of COVID-19 cases and hospitalizations at the provincial level in Belgium. We identified several important interactions among the covariates that influence the incidence of COVID-19 confirmed cases. Specifically, the best-fitting model (AIC = 965.658) revealed significant interactions between lagged vaccination coverage and the stringency index, as well as between incoming travel rates and positivity rates. Additionally, when modeling COVID-19 hospitalizations, a significant interaction was observed between the incoming travel rate and the stringency index. Model performance improved substantially when incorporating the incidence of confirmed cases as a covariate (AIC = 1061.516 vs. AIC = 432.708), while highlighting key interactions between confirmed cases and traveler positivity rates, as well as between lagged vaccination coverage and incoming travel rates. These findings underscore the intricate interplay between public health interventions, population immunity, and mobility patterns in shaping the course of the COVID-19 pandemic.

摘要

在缺乏确定性治疗方法或疫苗的情况下,减轻新冠疫情的主要策略依赖于非药物干预措施。到2020年底,新冠疫苗已研发出来并开始用于预防目的。为了更好地理解各种缓解措施及其对疫情的影响之间的关联,我们分析了疫苗接种覆盖率、国际旅行、旅行者阳性率以及公共卫生措施的严格程度对比利时省级层面新冠病例发病率和住院率的影响。我们确定了影响新冠确诊病例发病率的协变量之间的几个重要相互作用。具体而言,最佳拟合模型(AIC = 965.658)显示滞后疫苗接种覆盖率与严格指数之间以及入境旅行率与阳性率之间存在显著相互作用。此外,在对新冠住院情况进行建模时,观察到入境旅行率与严格指数之间存在显著相互作用。将确诊病例发病率作为协变量纳入模型时,模型性能有了显著提升(AIC = 1061.516对AIC = 432.708),同时突出了确诊病例与旅行者阳性率之间以及滞后疫苗接种覆盖率与入境旅行率之间的关键相互作用。这些发现强调了公共卫生干预措施、人群免疫力和流动模式在塑造新冠疫情发展过程中的复杂相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5439/12101632/56823d1e3097/pone.0322017.g001.jpg

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