Epidemiological characteristics of COVID-19 monitoring cases in Yinzhou district based on health big data platform
10.3760/cma.j.cn112338-20200409-00540
- VernacularTitle:基于健康大数据平台的鄞州区新型冠状病毒肺炎监测病例流行病学特征分析
- Author:
Yexiang SUN
1
;
Peng SHEN
;
Jingyi ZHANG
;
Ping LU
;
Pengfei CHAI
;
Hai MOU
;
Wenzan HUANG
;
Hongbo LIN
;
Liming SHUI
Author Information
1. 宁波市鄞州区疾病预防控制中心数据中心 315100
- Keywords:
Health big data;
COVID-19;
Epidemiological characteristics;
Monitoring
- From:
Chinese Journal of Epidemiology
2020;41(8):1220-1224
- CountryChina
- Language:Chinese
-
Abstract:
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.
