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10.3760/cma.j.cn112338-20200219-00121

http://scihub22266oqcxt.onion/10.3760/cma.j.cn112338-20200219-00121
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32162858!ä!32162858

suck abstract from ncbi


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pmid32162858      Zhonghua+Liu+Xing+Bing+Xue+Za+Zhi 2020 ; 41 (5): 648-652
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  • Epidemiological investigation on a cluster epidemic of COVID-19 in a collective workplace in Tianjin #MMPMID32162858
  • Zhang Y; Su X; Chen W; Fei CN; Guo LR; Wu XL; Zhou N; Guo YT; Dong XC; Zhao Y; Wang HW; Pan Y; Zuo LJ
  • Zhonghua Liu Xing Bing Xue Za Zhi 2020[May]; 41 (5): 648-652 PMID32162858show ga
  • Objective: To investigate and analysis the epidemiological characteristics of a cluster epidemic of COIVD-19 in a collective workplace in Tianjin, evduate the prevention and control measures based on limited evidence and experience in early period of COVID-19 epidemic. Methods: Descriptive research method was used to describe the distribution and other epidemiological characteristics of the cluster cases of COVID-19. Results: Since the onset of the first index case on January 15, ten confirmed COVID-19 cases had occurred in the workplace, and the epidemic had spread from the workplace to 4 families, infecting 7 family members. The median age of 17 cases was 55 (19-79) years. All the 10 employee cases were males, and in the family cases, 3 were males and 4 were females. Of the employee cases, 8 worked in CW workshop and 2 worked in administrative office building. The median exposure-onset interval of all the cases was 4 days, and the median exposure-onset interval was 4.5 days in the employee cases and 4 days in the family cases. The median onset-medical care seeking interval was 4 days in the non-isolated cases, 2.5 days in the cases with home isolation after onset, and 0.5 day in the cases with home isolation before onset. Conclusions: The clustering of COVID-19 cases was observed in this workplace in Tianjin, which affected 4 families. In the early stage of the epidemic, accurate and rapid blocking and control measures can completely prevent the large-scale spread of COVID-19.
  • |*Epidemics[MESH]
  • |*Workplace[MESH]
  • |Adult[MESH]
  • |Aged[MESH]
  • |COVID-19[MESH]
  • |China/epidemiology[MESH]
  • |Cluster Analysis[MESH]
  • |Coronavirus Infections/*epidemiology[MESH]
  • |Female[MESH]
  • |Humans[MESH]
  • |Male[MESH]
  • |Middle Aged[MESH]
  • |Pandemics[MESH]


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