Center for Epidemiological Data Sharing and Integration Research
About Center
This center aims to integrate existing epidemiological or clinical databases from multiple data sources, including omic data, population-based study, and ecological data, etc., and to study the methodology and standard processes of integrating these databases, and ultimately to conduct etiology studies using integrated datasets with regard to the major diseases in China.
Together with the National Institute of Health Data Science, the School of Public Health at Peking University, and the Chinese Journal of Epidemiology, the orientation of this center is a unique research platform for integrating cohort studies, training base for young scientists, and a practice base for the development of an advantage discipline branch of epidemiology.
Our Research
1. Integration of epidemiological data and clinical intervention research data resources: to develop standard processes for data release, data management, and data analysis, to provide professional data coordination and integration services, and to publish variable information to promote scientific research cooperation.
2. Integration of multi-omic data to conduct epidemiological etiology studies: based on data characteristics and research interests, to establish a series of working groups to conduct studies using environmental data, clinical data, multi-omic data, medical insurance data and regional platform databases, etc.
3. Methodology studies on epidemiological data integration, joint collaborative research and formulation of standard processes: to investigate cohort data integration methods in accordance with national conditions, to generate pathways of joint collaborative researches, and to develop standard processes for data sharing, data integration, and collaborative research, data security, etc.
Our People
Peking University School of Public Health is one of the leading institutes, whose research teams are mostly featured researchers in China, and they have conducted a series of researches in the fields of preventive medicine and public health. This center combines relevant disciplines from the School of Public Health with relevant disciplines such as systematic biology, information technology, and big data technology to formulate multidisciplinary innovations.
The center is established on the basis of the China Cohort Consortium, which was officially launched on October 13, 2017 with similar orientations as mentioned above. A three-level data sharing strategy was established, one data owner may decide to share their data in three dimensions: basic information, variable information and dataset hosting. The Consortium has formulated the "China Cohort Consortium Management Method" to explain the basic functions and composition of the platform, and to regulate and collect data collection and storage, data sharing and security. In addition, China Cohort Consortium has set up an independent website interface, and strives to establish a multi-level cooperation strategy and sharing mechanism, aiming to provide new cooperation channels and data sources for the development of public health and clinical research. By the end of 2018, the platform had included 36 cohorts, including 10 cohorts of Peking University School of Public Health, covering a number of research areas including chronic diseases, infectious diseases, maternal and child health, occupational diseases, etc. The data sources cover all provinces, municipalities, autonomous regions and municipalities across the country.
Leadership and Management
Prof. Siyan Zhan, deputy director of the Peking University Center for Evidence Based Medical and Clinical Research, director of the Department of Epidemiology and Biostatistics of the School of Public Health at Peking University, PhD tutor, director of the Evidence Based Medicine Committee of the Chinese Medical Doctor Association, and member of the Standing Committee of the Epidemiology Branch, deputy director of the Evidence Based Preventive Medicine Committee of the China Preventive Medicine Association.
