"Distance‐Driven" Versus "Density‐Driven": Understanding the Role of "Source‐Case" Distance and Gathering Places in the Localized Spatial Clustering of COVID‐19—A Case Study of the Xinfadi Market, Beijing (China). (23rd August 2021) - Zhang, Sui; Yang, Zhao; Wang, Minghao; Zhang, Baolei
Abstract: The frequent occurrence of local COVID‐19 today gives a strong necessity to better understand the effects of "source‐case" distance and gathering places, which are often considered to be the key factors of the localized spatial clustering of an epidemic. In this study, the localized spatial clustering of COVID‐19 cases, which originated in the Xinfadi market in Beijing from June–July 2020, was investigated by exploring the spatiotemporal characteristics of the clustering using descriptive statistics, point pattern analysis, and spatial autocorrelation calculation approaches. Spatial lag zero‐inflated negative binomial regression model and geographically weighted Poisson regression with spatial effects were also introduced to explore the factors which influenced the clustering of COVID‐19 cases at the micro spatial scale. It was found that the local epidemic can be significantly divided into two stages which are asymmetric in time. A significant spatial spillover effect of COVID‐19 was identified in both global and local modeling estimation. The dominant role of the "source‐case" distance effect, which was reflected in both global and local scales, was revealed. Relatively, the role of gathering places is not significant at the initial stage of the epidemic, but the upward trend of the significance of some places is obvious. The trend from "distance‐driven" to "density‐driven" of the localized spatial clustering of COVID‐19 was predicted. The effectiveness of blocking the transformation trend will be a key issue for the global response to the local COVID‐19. Plain Language Summary: The frequent occurrence of local COVID‐19 is becoming a global public health problem today. Most previous studies have focused on the influence of the "density" of socio‐economic and demographic factors on the spatial clustering of COVID‐19 (named "density‐driven" in this study) while ignoring the effect of the spatial distance between the source of the local COVID‐19 and the cases (named "distance‐driven" in this studies). Therefore, this manuscript took the local COVID‐19 cases which originated from the Xinfadi market from June–July 2020 as the study case. To obtain more accurate results, two improved quantitative research methods are adopted. It was found that the roles which the "source‐case" distance played were far more decisive than the scholars thought before. We also found that the local epidemic had a significant trend of changing from the "distance‐driven" diffusion mode to the "density‐driven" diffusion mode, and the critical point between these two driving modes will be one of the keys to prevent and control the clustering. Key Points: The spatiotemporal characteristics of localized spatial clustering of COVID‐19 were quantitively analyzed by multimethod The improved quantitative research methods were applied in the modeling of the spatial clustering factors at the micro scale The trend from "distance‐driven" to "density‐driven" of the localized spatial clustering of COVID‐19 was predicted