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10.3760/cma.j.cn112338-20200313-00334

http://scihub22266oqcxt.onion/10.3760/cma.j.cn112338-20200313-00334
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suck abstract from ncbi


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pmid33076591      Zhonghua+Liu+Xing+Bing+Xue+Za+Zhi 2020 ; 41 (9): 1420-1423
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  • Analysis on transmission chain of a cluster epidemic of COVID-19, Nanchang #MMPMID33076591
  • Deng ZQ; Xia W; Fan YB; Wang R; Tu ZZ; Wang WK; Wu JW; Yang S; Chen HY
  • Zhonghua Liu Xing Bing Xue Za Zhi 2020[Sep]; 41 (9): 1420-1423 PMID33076591show ga
  • Objective: Based on an investigation of an outbreak of COVID-19 in Nanchang, to understand the transmission process, analyze the infectivity of the cases in incubation period and asymptomatic carrier, and evaluate the transmission risks in different exposures. Methods: Case investigation was based on the traditional epidemiological survey, combined with analysis based on big data about population movement trajectories. Transmission chain was identified to indicate transmission relationship. Results: A total of 27 cases were found in this cluster epidemic, including 25 confirmed cases, 1 suspected case (index case) and 1 asymptomatic carrier. A total of 347 close contacts were found. The secondary attack rate was 7.2% (25/347). The infection rates in close contacts of the first, second, third and fourth generation cases were 52.6% (10/19), 6.1% (13/213), 2.3% (2/88) and 0.0% (0/27), respectively. Asymptomatic carrier caused household transmission. The infection rates in close contacts after having meals, sharing rooms/beds, having work contacts, having neighbor contacts, having same time medical services or sharing wards and sharing vehicles with the patients were 10.6%(17/160), 10.0%(20/201), 5.3%(5/94), 0.0%(0/30), 0.0%(0/18) and 0.0%(0/17), respectively. Conclusions: The infection source of this cluster epidemic was a suspected case from Wuhan. Analysis based on big data about population movement trajectories can help to search the cases and close contacts accurately. The proposed epidemic prevention and control measures based on this investigation were effective.
  • |*Epidemics[MESH]
  • |COVID-19[MESH]
  • |China/epidemiology[MESH]
  • |Cluster Analysis[MESH]
  • |Coronavirus Infections/epidemiology/*transmission[MESH]
  • |Humans[MESH]
  • |Pandemics[MESH]


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