Liu Yang, Gu Zhonglei, Liu Jiming
Department of Computer Science, Hong Kong Baptist University, Hong Kong Special Administrative Region, People's Republic of China.
EClinicalMedicine. 2021 Jun;36:100929. doi: 10.1016/j.eclinm.2021.100929. Epub 2021 Jun 6.
Given the dynamism and heterogeneity of COVID-19 transmission patterns, determining the most effective yet timely strategies for specific regions remains a severe challenge for public health decision-makers.
In this work, we proposed a spatiotemporal connectivity analysis method for discovering transmission patterns across geographic locations and age-groups throughout different COVID-19 outbreak phases. First, we constructed the transmission networks of the confirmed cases during different phases by considering the spatiotemporal connectivity of any two cases. Then, for each case and those cases immediately pointed from it, we characterized the corresponding cross-district/population transmission pattern by counting their district-to-district and age-to-age occurrences. By summating the cross-district/population transmission patterns of all cases during a given period, we obtained the aggregated cross-district and cross-population transmission patterns.
We conducted a region-wide comprehensive retrospective study in Hong Kong based on the complete data report of COVID-19 cases, covering all 18 districts between January 23, 2020, and January 8, 2021 (https://data.gov.hk/en-data/dataset/hk-dh-chpsebcddr-novel-infectious-agent). The spatiotemporal connectivity analysis clearly unveiled the quantitative differences among various outbreak waves in their transmission scales, durations, and patterns. Moreover, for the statistically similar waves, their cross-district/population transmission patterns could be quite different (e.g., the cross-district transmission of the fourth wave was more diverse than that of the third wave, while the transmission over age-groups of the fourth wave was more concentrated than that of the third wave). At an overall level, super-spreader individuals (highly connected cases in the transmission networks) were usually concentrated in only a few districts (2 out of 18 in our study) or age-groups (3 out of 11 in our study).
With the discovered cross-district or cross-population transmission patterns, all of the waves of COVID-19 outbreaks in Hong Kong can be systematically scrutinized. Among all districts, quite a few (e.g., the Yau Tsim Mong district) were instrumental in spreading the virus throughout the pandemic. Aside from being exceptionally densely populated, these districts were also social-economic centers. With a variety of situated public venues, such as restaurants and singing/dancing clubs, these districts played host to all kinds of social gathering events, thereby providing opportunities for widespread and rapid transmission of the virus. Thus, these districts should be given the highest priority when deploying district-specific social distancing or intervention strategies, such as lockdown and stringent mandatory coronavirus testing for identifying and obstructing the chain of transmission. We also observed that most of the reported cases and the highly connected cases were middle-aged and elderly people (40- to 69-year-olds). People in these age-groups were active in various public places and social activities, and thus had high chances of being infected by or infecting others.
General research fund of the Hong Kong research grants council.
鉴于新冠病毒传播模式的动态性和异质性,为特定地区确定最有效且及时的策略,对公共卫生决策者而言仍是一项严峻挑战。
在本研究中,我们提出了一种时空连通性分析方法,用于发现新冠疫情不同阶段跨地理位置和年龄组的传播模式。首先,通过考虑任意两例病例的时空连通性,构建不同阶段确诊病例的传播网络。然后,对于每例病例及其直接指向的病例,通过统计它们的区与区、年龄与年龄之间的出现情况,来刻画相应的跨区/人群传播模式。通过汇总给定时期内所有病例的跨区/人群传播模式,我们得到了汇总后的跨区和跨人群传播模式。
我们基于香港新冠病例的完整数据报告,开展了一项全地区范围的综合回顾性研究,涵盖了2020年1月23日至2021年1月8日期间的所有18个区(https://data.gov.hk/en-data/dataset/hk-dh-chpsebcddr-novel-infectious-agent)。时空连通性分析清晰揭示了不同疫情波次在传播规模、持续时间和模式上的定量差异。此外,对于统计上相似的波次,它们的跨区/人群传播模式可能大不相同(例如,第四波的跨区传播比第三波更多样化,而第四波的年龄组间传播比第三波更集中)。总体而言,超级传播者个体(传播网络中连接性高的病例)通常仅集中在少数几个区(我们研究中的18个区里有2个)或年龄组(我们研究中的11个年龄组里有3个)。
借助发现的跨区或跨人群传播模式,可以系统地审视香港新冠疫情的所有波次。在所有区中,有相当一部分区(例如油尖旺区)在整个疫情期间对病毒传播起到了推动作用。这些区除了人口极度密集外,还是社会经济中心。有各种公共活动场所,如餐馆和歌舞俱乐部,举办各类社交聚会活动,从而为病毒的广泛快速传播提供了机会。因此,在部署针对特定区的社交距离或干预策略(如封锁和严格的强制新冠病毒检测以识别和阻断传播链)时,这些区应被列为最高优先级。我们还观察到,报告的大多数病例和连接性高的病例是中年和老年人(40至69岁)。这些年龄组的人活跃于各种公共场所和社交活动中,因此感染他人或被他人感染的几率很高。
香港研究资助局一般研究基金