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Zhonghua Liu Xing Bing Xue Za Zhi ; 41(8): 1220-1224, 2020 Aug 10.
Article in Chinese | MEDLINE | ID: covidwho-739002


Objective: To understand the epidemiological characteristics of COVID-19 monitoring cases in Yinzhou district based on health big data platform to provide evidence for the construction of COVID-19 monitoring system. Methods: Data on Yinzhou COVID-19 daily surveillance were collected. Information on patients' population classification, epidemiological history, COVID-19 nucleic acid detection rate, positive detection rate and confirmed cases monitoring detection rate were analyzed. Results: Among the 1 595 COVID-19 monitoring cases, 79.94% were community population and 20.06% were key population. The verification rate of monitoring cases was 100.00%. The total percentage of epidemiological history related to Wuhan city or Hubei province was 6.27% in total, and was 2.12% in community population and 22.81% in key population (P<0.001). The total COVID-19 nucleic acid detection rate was 18.24% (291/1 595), and 53.00% in those with epidemiological history and 15.92% in those without (P<0.001).The total positive detection rate was 1.72% (5/291) and the confirmed cases monitoring detection rate was 0.31% (5/1 595). The time interval from the first visit to the first nucleic acid detection of the confirmed monitoring cases and other confirmed cases was statistically insignificant (P>0.05). Conclusions: The monitoring system of COVID-19 based on the health big data platform was working well but the confirmed cases monitoring detection rate need to be improved.

Betacoronavirus , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , Big Data , COVID-19 , China/epidemiology , Cities , Disease Outbreaks , Humans , Pandemics , Population Surveillance , RNA, Viral/genetics , RNA, Viral/isolation & purification , Real-Time Polymerase Chain Reaction , SARS-CoV-2