School of Science and Technology, Nottingham Trent University, Clifton Lane, Nottingham, United Kingdom.
Departamento de Física, Universidade Estadual de Maringá, Maringá, Brazil.
PLoS One. 2022 Mar 31;17(3):e0261725. doi: 10.1371/journal.pone.0261725. eCollection 2022.
We investigated daily COVID-19 cases and deaths in the 337 lower tier local authority regions in England and Wales to better understand how the disease propagated over a 15-month period. Population density scaling models revealed residual variance and skewness to be sensitive indicators of the dynamics of propagation. Lockdowns and schools reopening coincided with increased variance indicative of conditions with local impact and country scale heterogeneity. University reopening and December holidays reduced variance indicative of country scale homogenisation which reached a minimum in mid-January 2021. Homogeneous propagation was associated with better correspondence with normally distributed residuals while heterogeneous propagation was more consistent with skewed models. Skewness varied from strongly negative to strongly positive revealing an unappreciated feature of community propagation. Hot spots and super-spreading events are well understood descriptors of regional disease dynamics that would be expected to be associated with positively skewed distributions. Positively skewed behaviour was observed; however, negative skewness indicative of "cold-spots" and "super-isolation" dominated for approximately 8 months during the period of study. In contrast, death metrics showed near constant behaviour in scaling, variance, and skewness metrics over the full period with rural regions preferentially affected, an observation consistent with regional age demographics in England and Wales. Regional positions relative to density scaling laws were remarkably persistent after the first 5-9 days of the available data set. The determinants of this persistent behaviour probably precede the pandemic and remain unchanged.
我们调查了英格兰和威尔士 337 个低级别地方当局地区的每日 COVID-19 病例和死亡人数,以更好地了解这种疾病在 15 个月内的传播方式。人口密度比例模型揭示了残差方差和偏度是传播动态的敏感指标。封锁和学校重新开放恰逢方差增加,表明存在具有局部影响和国家规模异质性的条件。大学重新开放和 12 月假期减少了方差,表明国家规模同质化,这在 2021 年 1 月中旬达到最低水平。同质化传播与正常分布残差更好地吻合,而异质传播则更符合偏态模型。偏度从强烈负偏到强烈正偏不等,揭示了社区传播的一个未被重视的特征。热点和超级传播事件是理解区域疾病动态的很好的描述符,预计与正偏态分布相关。观察到正偏态行为;然而,在研究期间的大约 8 个月内,负偏态(指示“冷点”和“超级隔离”)占主导地位。相比之下,死亡指标在整个时期的比例、方差和偏度指标上的表现都非常稳定,农村地区受到的影响更大,这一观察结果与英格兰和威尔士的区域年龄人口统计学一致。在可用数据集的前 5-9 天之后,这些地区相对于密度比例法则的位置仍然非常稳定。这种持续行为的决定因素可能先于大流行发生且保持不变。