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中国生物工程杂志

China Biotechnology
China Biotechnology
China Biotechnology  2020, Vol. 40 Issue (1-2): 109-115    DOI: 10.13523/j.cb.1906028
Orginal Article     
Platform Construction for the Early-Warning Forecast in Prevention and Control of Influenza Based on Multi-Source Heterogeneous Big-Data Mining
CHEN Cui-xia1,2,WANG Xiao-long3,JIANG Tai-jiao4,CAO Zong-fu1,2,LI Tian-jun1,2,YU Lei1,2,YU Yu-fei1,2,CAI Rui-kun1,2,GAO Hua-fang1,2,Ma Xu1,2,**()
1 National Research Institute for Family Planning,Beijing 100081,China
2 National Center of Human Genetic Resources,Beijing 102206,China
3 Institute of Electrics, Chinese Academy of Sciences,Beijing 100081,China
4 Institute of Biophysics,Chinese Academy of Sciences,Beijing 100730,China
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Abstract  

The control and prevention of the influenza virus is a challenging scientific question. The difficulty lies in its wide spread, variable antigen with high mutation rate, which enable it to escape the host’s immunity. The existing system for influenza surveillance is a hierarchical reporting system. Therefore, the influenza report was lagged behind 1-2 weeks. But influenza virus has a rapid mutation and transmission speed. So it is important to understand the influenza epidemic status in a real-time. The thesis focused on establishing a unified platform for influenza surveillance through the big-data minning of multi-source and the integration of a series of specific algorithm models.It includes three projects. The first one referred to the rapid estimation of influenza virus’s full-life monitoring in epidemic status, control, feedback, mutation and variation. Another project in the thesis was to systematically map the correlation between the dimension (such as time, geography and environment) and influenza virus through comprehensive analysis. Based the two project above, can gain an in-depth and comprehensive view of influenza forecasting warning system with characteristics of a safety, speediness, stability, accuration and real-time in mainland China.Systematic work has highlighted the challenge in its prevention and control, speaking to the necessity of extensive global influenza surveillance and local planning of the influenza.

Key words： Big-data of influenza virus      Influenza epidemic      Real-time surveillance      Geographic information map      Forecasting warning system     
Received: 21 June 2019      Published: 27 March 2020
ZTFLH:  Q813  
Corresponding Authors: Xu Ma     E-mail: 83555041@qq.com
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Cui-xia CHEN
Xiao-long WANG
Tai-jiao JIANG
Zong-fu CAO
Tian-jun LI
Lei YU
Yu-fei YU
Rui-kun CAI
Hua-fang GAO
Xu Ma
Cite this article:

CHEN Cui-xia,WANG Xiao-long,JIANG Tai-jiao,CAO Zong-fu,LI Tian-jun,YU Lei,YU Yu-fei,CAI Rui-kun,GAO Hua-fang,Ma Xu. Platform Construction for the Early-Warning Forecast in Prevention and Control of Influenza Based on Multi-Source Heterogeneous Big-Data Mining. China Biotechnology, 2020, 40(1-2): 109-115.

URL:

https://manu60.magtech.com.cn/biotech/10.13523/j.cb.1906028     OR     https://manu60.magtech.com.cn/biotech/Y2020/V40/I1-2/109

ID 基础数据表 存储内容 主题模型视图
1 暴发疫情信息表 存储暴发疫情模块的相关信息,如编号、事件名称、地理编码、机构编码、地址、型别、起数、时间编码、周次、用户ID等 暴发疫情主题模型
2 流病学信息表 存储ILI模块的样本信息,如地理编码、机构编码、送检单位、地理位置、时间编码、周、型别、哨点医院、诊室、年龄、批次、用户ID等 流病学监测主题模型
3 病原学信息表 存储病原学模块样本信息,如样本ID、患者姓名、送检医院、地理编码、机构编码、型别、时间编码、检测结果(分离、核酸鉴定、复核结果)周次、用户ID等 病原学监测主题模型
4 禽流感环境信息表 该表用于存储禽流感环境样本基本信息,如时间编码、地理位置、地理编码、机构编码、起数、型别、检测结果、周次、用户ID等 禽流感环境监测主题模型
5 禽流感血清信息表 该表主要用于存储禽流感血清样本信息,如地理编码、机构编码、时间编码,送检单位、检测结果、周次、用户ID等 禽流感血清监测主题模型
Table 1 Topic models were built on the basic database of influenza associated with meta-database
ID 中文名 描述
1 模块信息表 存储模块相关信息,如模块ID、模块名称、业务名称等
2 子模块信息表 存储一个模块下对应的子模块的相关信息,如子模块ID、子模块名称、子模块参数请求类型、获取数据时与sqlmap的映射ID、数据处理规则ID、返回数据类型等
3 图表模板信息表 存储图表的模板,每个图表都对应有相应的模板,当数据返回时会对模板进行替换,形成相应的需要的数据,存储的信息包括模块ID、模板、规则信息等
4 数据库缓存信息表 为了提高用户响应速度,存储用户对应条件请求下的数据库相应数据,存储的信息如模块ID、请求参数、请求返回的数据、最终模板替换后的数据等
5 规则映射表 为了配合规则引擎而设计的表,在对业务进行处理时,加入了相应的规则,在对业务进行处理时会根据相应的规则对业务进行相应的规则处理,该表就是用于存储规则替换的相关信息
Table 2 Specification table of database for bussiness diagrams
Fig.1 The home page of laboratory information management system
Fig.2 Week report of influenza automatically generated by Epiflu System
Fig.3 Statistical table of influenza strains typed weekly for a given year in Epiflu System
系统模块 指标体系 地图指征 表征信息阐述 图例
暴发疫情 指定时间段暴发疫情起数 散点数量
色差梯度		 疫情活动强度,打点越多或者颜色越深,表示暴发起数越多,打点位置是暴发疫情地点,精确到乡镇
病原学
监测		 毒株分型比 饼图 监测指定时间段各地区主导流行毒株(占比最大的型别)及各型别占比
流病学
监测		 就诊总数、流感疑似病例ILI绝对数、ILI百分比 热度色差
梯度		 监测指定时间段各地区流感样疑似病例分布情况,鼠标移入或点击地图上的具体地理位置,有详细数据展示(就诊总数、ILI绝对数、ILI%)。颜色越红,流感疑似病例数ILI数量越多
禽流感环
境样本和
血清样本
监测		 毒株分型比 饼图
色差梯度		 类似于流感病毒病原学监测地理图谱,目前禽流感环境样本及职业暴露人群血清样本检测出的型别主要是H5、H7、H9。颜色越深,表示数量越多
Table 3 The topical module content displayed in geographic information mapping system
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