We analyse and mutually compare time series of COVID-19-related data and mobility data across Belgium's 43 arrondissements (NUTS 3). In this way, we reach three conclusions. First, we could detect a decrease in mobility during high-incidence stages of the pandemic. This is expressed as a significant change in the average amount of time spent outside one's home arrondissement, investigated over five distinct periods, and in more detail using an inter-arrondissement ``connectivity index'' (CI). Second, we analyse spatio-temporal COVID-19-related hospitalisation time series, after smoothing them using a generalise additive mixed model (GAMM). We confirm that some arrondissements are ahead of others and morphologically dissimilar to others, in terms of epidemiological progression. The tools used to quantify this are time-lagged cross-correlation (TLCC) and dynamic time warping (DTW), respectively. Third, we demonstrate that an arrondissement's CI with one of the three identified first-outbreak arrondissements is correlated to a significant local excess mortality some five to six weeks after the first outbreak. More generally, we couple results leading to the first and second conclusion, in order to demonstrate an overall correlation between CI values on the one hand, and TLCC and DTW values on the other. We conclude that there is a strong correlation between physical movement of people and viral spread in the early stage of the SARS-CoV-2 epidemic in Belgium, though its strength weakens as the virus spreads
翻译:我们分析并相互比较比利时43个地区(NUTS 3)与COVID-19有关的数据和流动数据的时间序列。 如此一来,我们得出了三个结论。 首先,我们可以发现,在流行病高发阶段,在这种流行病高发阶段中,在高发阶段中,我们可以看到流动性的下降。这表现为,在5个不同时期中,我们调查了在家庭偏转区外平均花费的时间数量发生了重大变化,并且使用一个时间错位的连接指数(CI)更详尽地分析了时间序列。 其次,我们分析了与COVID-19有关的住院时间序列,在使用一个通用添加混合模型(GAMM)来平息这些变化。 我们确认,在流行病高发阶段中,一些偏差在其它阶段中,在时间间隔期间的平均时间长度有显著变化。 用于量化这一变化的工具分别是时间滞后的交叉关系(TLCC)和动态时间扭曲(DTW)。 第三,我们证明,在首次确定的三阶段中,CI(CI)的直径)的直位化,在第一个阶段中, 直系直系直系直系直系直系直系直系直系直系直系直系直系直系至前六周后,而后, 。