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Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis

Jing Jia, Xiaowen Hu, Feng Yang, Xin Song, Liyan Dong, Jingfei Zhang, Fachun Jiang, Ruqin Gao

2020Disaster Medicine and Public Health Preparedness53 citationsDOIOpen Access PDF

Abstract

OBJECTIVES: As an emerging infectious disease, COVID-19 has involved many countries and regions. With the further development of the epidemic, the proportion of clusters has increased. METHODS: In our study, we collected information on COVID-19 clusters in Qingdao City. The epidemiological characteristics and clinical manifestations were analyzed. RESULTS: Eleven clusters of COVID-19 were reported in Qingdao City between January 29, and February 23, 2020, involving 44 confirmed cases, which accounted for 73.33% of all confirmed cases. From January 19 to February 2, 2020, the cases mainly concentrated in the district that had many designated hospitals. Patients aged 20-59 y old accounted for the largest proportion (68.18%) of cases; the male-to-female sex ratio was 0.52:1. Three cases were infected from exposure to confirmed cases. The average incubation period was 6.28 d. The median number of cases per cluster was 4, and the median duration time was 6 d. The median cumulative number of exposed persons was 53. CONCLUSION: More attention should be paid to the epidemic of clusters in prevention and control of COVID-19. In addition to isolating patients, it is essential to track, screen, and isolate those who have come in close contact with patients. Self-isolation is the key especially for healthy people in the epidemic area.

Topics & Concepts

EpidemiologyCoronavirus disease 2019 (COVID-19)Cluster (spacecraft)MedicineDemographySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Incubation periodIsolation (microbiology)Epidemic control2019-20 coronavirus outbreakInfectious disease (medical specialty)Environmental healthDiseaseOutbreakVirologyInternal medicineBiologyIncubationComputer scienceBiochemistryMicrobiologyProgramming languageSociologyCOVID-19 epidemiological studiesCOVID-19 Clinical Research StudiesCOVID-19 Impact on Reproduction
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