Zhejiang Province Center for Disease Control and Prevention, Hangzhou, Zhejiang Province, China.
Key Laboratory for Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Hangzhou, Zhejiang Province, China.
PLoS One. 2021 Sep 17;16(9):e0257587. doi: 10.1371/journal.pone.0257587. eCollection 2021.
Zhejiang Province is one of the five provinces in China that had the highest incidence of novel coronavirus disease (COVID-19). Zhejiang, ranked fourth highest in COVID-19 incidence, is located in the Yangtze River Delta region of southeast China. This study was undertaken to identify the space-time characteristics of COVID-19 in Zhejiang.
Data on COVID-19 cases in Zhejiang Province from January to July 2020 were obtained from this network system. Individual information on cases and deaths was imported, and surveillance information, including demographic characteristics and geographic and temporal distributions, was computed by the system. The Knox test was used to identify possible space-time interactions to test whether cases that are close in distance were also close in time. Network analysis was performed to determine the relationship among the cases in a transmission community and to try to identify the key nodes.
In total, 1475 COVID-19 cases and 1 fatal case were reported from January to July 2020 in Zhejiang Province, China. Most of the cases occurred before February 15th, which accounted for 90.10%. The imported cases increased and became the main risk in Zhejiang Province after February 2020. The risk areas showed strong heterogeneity according to the Knox test. The areas at short distances within 1 kilometer and at brief periods within 5 days presented relatively high risk. The numbers of subcommunities for the four clusters were 12, 9, 6 and 4. There was obvious heterogeneity in the modularity of subcommunities. The maximum values of the node centrality for the four clusters were 2.9474, 4.3706, 4.1080 and 2.7500.
COVID-19 was brought under control over a short period in Zhejiang Province. Imported infections from outside of mainland China then became a new challenge. The effects of spatiotemporal interaction exhibited interval heterogeneity. The characteristics of transmission showed short range and short term risks. The importance to the cluster of each case was detected, and the key patients were identified. It is suggested that we should focus on key patients in complex conditions and in situations with limited control resources.
浙江省是中国五个新冠病毒病（COVID-19）发病率最高的省份之一。浙江省 COVID-19 发病率排名第四，位于中国东南部的长江三角洲地区。本研究旨在确定浙江省 COVID-19 的时空特征。
从网络系统中获取 2020 年 1 月至 7 月浙江省 COVID-19 病例数据。输入病例和死亡的个体信息，系统计算监测信息，包括人口统计学特征和地理与时间分布。采用 Knox 检验来识别可能的时空相互作用，以检验距离相近的病例是否也在时间上相近。进行网络分析以确定传播社区中病例之间的关系，并尝试确定关键节点。
2020 年 1 月至 7 月，中国浙江省共报告 1475 例 COVID-19 病例和 1 例死亡病例。大多数病例发生在 2 月 15 日之前，占 90.10%。2020 年 2 月以后，输入病例增加并成为浙江省的主要风险。根据 Knox 检验，风险区域表现出很强的异质性。在 1 公里以内的近距离和 5 天以内的短时间内，风险相对较高。四个聚类的亚社区数量分别为 12、9、6 和 4。亚社区的模块度具有明显的异质性。四个聚类的节点中心度最大值分别为 2.9474、4.3706、4.1080 和 2.7500。
浙江省 COVID-19 疫情在短时间内得到控制。随后，来自中国大陆以外地区的输入感染成为新的挑战。时空相互作用的影响表现出间隔异质性。传播特征显示出短距离和短期风险。检测到每个病例在聚类中的重要性，并确定了关键患者。建议我们应关注复杂情况下和资源有限的控制情况下的关键患者。
