Cargando…
Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis
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 character...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7156571/ https://www.ncbi.nlm.nih.gov/pubmed/32228732 http://dx.doi.org/10.1017/dmp.2020.59 |
_version_ | 1783522237477814272 |
---|---|
author | Jia, Jing Hu, Xiaowen Yang, Feng Song, Xin Dong, Liyan Zhang, Jingfei Jiang, Fachun Gao, Ruqin |
author_facet | Jia, Jing Hu, Xiaowen Yang, Feng Song, Xin Dong, Liyan Zhang, Jingfei Jiang, Fachun Gao, Ruqin |
author_sort | Jia, Jing |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7156571 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-71565712020-04-15 Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis Jia, Jing Hu, Xiaowen Yang, Feng Song, Xin Dong, Liyan Zhang, Jingfei Jiang, Fachun Gao, Ruqin Disaster Med Public Health Prep Original Research 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. Cambridge University Press 2020-03-31 /pmc/articles/PMC7156571/ /pubmed/32228732 http://dx.doi.org/10.1017/dmp.2020.59 Text en © Society for Disaster Medicine and Public Health, Inc. 2020 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research Jia, Jing Hu, Xiaowen Yang, Feng Song, Xin Dong, Liyan Zhang, Jingfei Jiang, Fachun Gao, Ruqin Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis |
title | Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis |
title_full | Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis |
title_fullStr | Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis |
title_full_unstemmed | Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis |
title_short | Epidemiological Characteristics on the Clustering Nature of COVID-19 in Qingdao City, 2020: A Descriptive Analysis |
title_sort | epidemiological characteristics on the clustering nature of covid-19 in qingdao city, 2020: a descriptive analysis |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7156571/ https://www.ncbi.nlm.nih.gov/pubmed/32228732 http://dx.doi.org/10.1017/dmp.2020.59 |
work_keys_str_mv | AT jiajing epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis AT huxiaowen epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis AT yangfeng epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis AT songxin epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis AT dongliyan epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis AT zhangjingfei epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis AT jiangfachun epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis AT gaoruqin epidemiologicalcharacteristicsontheclusteringnatureofcovid19inqingdaocity2020adescriptiveanalysis |