Objective: To understand the characteristics of clusters of COVID-19 cases in Tianjin, and provide epidemiological evidence for the prevention and control of COVID-19. Methods: The data of all the COVID-19 cluster cases in Tianjin, reported by 22 February 2020, were collected to analyze the characteristics of different types of the clusters. Results: A total of 115 COVID-19 cases were reported in 33 clusters in Tianjin included 28 family clusters (71 cases), 1 work place cluster (10 cases), 3 transport vehicle clusters (8 cases) and 1 public place cluster (26 cases). Family clusters were caused by the cases from the working place or public place clusters. Numbers of secondary cases of family clusters was between 1 to 7, the median number was 2. The interval from onset to diagnosis for the first case was longer than those of other cases in the familial clusters (Z=-2.406, P=0.016). The median of incubation period of the public place clusters was 2 days. The intervals from onset to diagnosis were significant different among the family, working place and public place clusters (H=8.843, P=0.012), and also significant differences in onset time among the secondary cases (H=16.607, P=0.000). Conclusions: In the surveillance of COVID-19 epidemic, special attention should be paid to places where clustering are prone to occur, and the epidemiological investigation should be carried out timely to confirm the cluster. To prevent the transmission of COVID-19, the close contacts of the patients should be transferred to an assigned observation place on time for single room isolation. The awareness of COVID-19 prevention is low in some rural areas, reflected by many mass gathering activities and delayed medical care seeking after onset. It is necessary to strengthen the health education and take control measures in early period of epidemic.
Objective: To understand the characteristics of clusters of COVID-19 cases in Tianjin, and provide epidemiological evidence for the prevention and control of COVID-19. Methods: The data of all the COVID-19 cluster cases in Tianjin, reported by 22 February 2020, were collected to analyze the characteristics of different types of the clusters. Results: A total of 115 COVID-19 cases were reported in 33 clusters in Tianjin included 28 family clusters (71 cases), 1 work place cluster (10 cases), 3 transport vehicle clusters (8 cases) and 1 public place cluster (26 cases). Family clusters were caused by the cases from the working place or public place clusters. Numbers of secondary cases of family clusters was between 1 to 7, the median number was 2. The interval from onset to diagnosis for the first case was longer than those of other cases in the familial clusters (Z=-2.406, P=0.016). The median of incubation period of the public place clusters was 2 days. The intervals from onset to diagnosis were significant different among the family, working place and public place clusters (H=8.843, P=0.012), and also significant differences in onset time among the secondary cases (H=16.607, P=0.000). Conclusions: In the surveillance of COVID-19 epidemic, special attention should be paid to places where clustering are prone to occur, and the epidemiological investigation should be carried out timely to confirm the cluster. To prevent the transmission of COVID-19, the close contacts of the patients should be transferred to an assigned observation place on time for single room isolation. The awareness of COVID-19 prevention is low in some rural areas, reflected by many mass gathering activities and delayed medical care seeking after onset. It is necessary to strengthen the health education and take control measures in early period of epidemic.
Authors: Wenning Li; Jianhua Gong; Jieping Zhou; Hongkui Fan; Cheng Qin; Yujiang Gong; Weidong Hu Journal: Int J Environ Res Public Health Date: 2022-04-17 Impact factor: 4.614
Authors: Moira A Mugglestone; Natasha V Ratnaraja; Aggie Bak; Jasmin Islam; Jennie A Wilson; Jennifer Bostock; Samuel E Moses; James R Price; Michael Weinbren; Heather P Loveday; Lucy Rivett; Simon M Stoneham; A Peter R Wilson Journal: BMC Infect Dis Date: 2022-05-12 Impact factor: 3.667