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10.3760/cma.j.cn112338-20200608-00818 http://scihub22266oqcxt.onion/10.3760/cma.j.cn112338-20200608-00818 32654429!ä!32654429 Warning: Undefined variable $yww in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 538 Warning: Undefined variable $yww in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 538       Zhonghua+Liu+Xing+Bing+Xue+Za+Zhi 2020 ; 41 (10): 1611-1615 Nephropedia Template TP {{tp|p=32654429|t=2020. Application of healthcare big data in active case finding of COVID-19 in Yinzhou district of Ningbo |pdf=|usr=}}{{32654429}} gab.com Text Application of healthcare big data in active case finding of COVID-19 in Yinzhou district of Ningbo JO: Zhonghua Liu Xing Bing Xue Za Zhi http://www.kidney.de/pget.php?&tw=1&pmid=32654429 #FOAvip During the prevention and control of the COVID-19 epidemic, identifying and controlling the source of infection has become one of the most important prevention and control measures to curb the epidemic in the absence of vaccines and specific therapeutic drugs. While actively taking traditional and comprehensive "early detection" measures, Yinzhou district implemented inter-departmental data sharing through the joint prevention and control mechanism. Relying on a healthcare big data platform that integrates the data from medical, disease control and non-health sectors, Yinzhou district innovatively explored the big data-driven COVID-19 case finding pattern with online suspected case screening and offline verification and disposal. Such effort has laid a solid foundation and gathered experience to conduct the dynamic and continuous surveillance and early warning for infectious disease outbreaks more effectively and efficiently in the future. This article introduces the exploration of this pattern in Yinzhou district and discusses the role of big data-driven disease surveillance in the prevention and control of infectious diseases. Twit Text FOAVip Application of healthcare big data in active case finding of COVID-19 in Yinzhou district of Ningbo ????Zhonghua Liu Xing Bing Xue Za Zhi http://www.kidney.de/pget.php?&tw=1&pmid=32654429 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32654429 #FOAvip English Wikipedia <ref>{{Cite pmid|32654429}}</ref> Application of healthcare big data in active case finding of COVID-19 in Yinzhou district of Ningbo #MMPMID32654429 Sun YX; Lyu J; Shen P; Zhang JY; Lu P; Huang WZ; Lin HB; Shui LM; Li LM Zhonghua Liu Xing Bing Xue Za Zhi 2020[Oct]; 41 (10): 1611-1615 PMID32654429show ga During the prevention and control of the COVID-19 epidemic, identifying and controlling the source of infection has become one of the most important prevention and control measures to curb the epidemic in the absence of vaccines and specific therapeutic drugs. While actively taking traditional and comprehensive "early detection" measures, Yinzhou district implemented inter-departmental data sharing through the joint prevention and control mechanism. Relying on a healthcare big data platform that integrates the data from medical, disease control and non-health sectors, Yinzhou district innovatively explored the big data-driven COVID-19 case finding pattern with online suspected case screening and offline verification and disposal. Such effort has laid a solid foundation and gathered experience to conduct the dynamic and continuous surveillance and early warning for infectious disease outbreaks more effectively and efficiently in the future. This article introduces the exploration of this pattern in Yinzhou district and discusses the role of big data-driven disease surveillance in the prevention and control of infectious diseases. |*COVID-19[MESH] |Big Data[MESH] |China[MESH] |Delivery of Health Care[MESH] |Humans[MESH] |Pandemics[MESH] Application of healthcare big data in active case finding of COVID-19(epmc).pdf DeepDyve Pubget Overpricing