Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China.
Collaborative Innovation Center for Western Ecological Safety, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China.
Environ Res. 2022 Oct;213:113604. doi: 10.1016/j.envres.2022.113604. Epub 2022 Jun 9.
Crowd gatherings are an important cause of COVID-19 outbreaks. However, how the scale, scene and other factors of gatherings affect the spread of the epidemic remains unclear. A total of 184 gathering events worldwide were collected to construct a database, and 99 of them with a clear gathering scale were used for statistical analysis of the impact of these factors on the disease incidence among the crowd in the study. The results showed that the impact of small-scale (less than 100 people) gathering events on the spread of COVID-19 in the city is also not to be underestimated due to their characteristics of more frequent occurrence and less detection and control. In our dataset, 22.22% of small-scale events have an incidence of more than 0.8. In contrast, the incidence of most large-scale events is less than 0.4. Gathering scenes such as "Meal" and "Family" occur in densely populated private or small public places have the highest incidence. We further designed a model of epidemic transmission triggered by crowd gathering events and simulated the impact of crowd gathering events on the overall epidemic situation in the city. The simulation results showed that the number of patients will be drastically reduced if the scale and the density of crowds gathering are halved. It indicated that crowd gatherings should be strictly controlled on a small scale. In addition, it showed that the model well reproduce the epidemic spread after crowd gathering events better than does the original SIER model and could be applied to epidemic prediction after sudden gathering events.
人群聚集是 COVID-19 爆发的一个重要原因。然而,聚集的规模、场景和其他因素如何影响疫情的传播仍不清楚。我们共收集了全球 184 次聚集事件,构建了一个数据库,其中 99 次有明确的聚集规模,用于统计分析这些因素对研究中人群疾病发病率的影响。结果表明,由于小规模(少于 100 人)聚集事件发生频率更高、检测和控制更少,因此对城市 COVID-19 传播的影响也不可低估。在我们的数据集,22.22%的小规模事件发病率超过 0.8。相比之下,大多数大规模事件的发病率低于 0.4。“用餐”和“家庭聚会”等聚集场景发生在人口密集的私人或小型公共场所,发病率最高。我们进一步设计了一个由人群聚集事件引发的传染病传播模型,并模拟了人群聚集事件对城市整体疫情的影响。模拟结果表明,如果人群聚集的规模和密度减半,患者数量将大幅减少。这表明应严格控制小规模的人群聚集。此外,结果表明该模型比原始 SIER 模型更好地再现了聚集事件后的疫情传播情况,可用于突发聚集事件后的疫情预测。